Merge branch 'develop' into qlinearmul

src/include/migraphx/matcher.hpp

@@ -591,6 +591,19 @@ MIGRAPHX_PRED_MATCHER(same_input_shapes, instruction_ref ins)
         ins->inputs().begin(), ins->inputs().end(), [&](auto x) { return x->get_shape() == s; });
 }
 
+MIGRAPHX_PRED_MATCHER(has_same_value, instruction_ref ins)
+{
+    if(ins->name() != "@literal")
+        return false;
+    bool all_same = false;
+    ins->get_literal().visit([&](auto s) {
+        all_same = std::all_of(s.begin() + 1, s.end(), [&](const auto& scale) {
+            return float_equal(scale, s.front());
+        });
+    });
+    return all_same;
+}
+
 MIGRAPHX_BASIC_MATCHER(output, const matcher_context&, instruction_ref ins)
 {
     if(ins->outputs().size() == 1)
@@ -844,6 +857,12 @@ auto skip_broadcasts_converts(Ms... ms)
     return skip(name("broadcast", "multibroadcast", "contiguous", "convert"))(ms...);
 }
 
+template <class... Ms>
+auto skip_broadcasts_transposes_contiguous(Ms... ms)
+{
+    return skip(name("broadcast", "multibroadcast", "contiguous", "transpose"))(ms...);
+}
+
 template <class T>
 inline auto has_value(T x, float tolerance = 1e-6)
 {

src/onnx/parse_lstm.cpp

@@ -116,6 +116,37 @@ void lstm_actv_functions(op::rnn_direction dirct, std::vector<std::string>& actv
     }
 }
 
+void lstm_transpose_inputs(onnx_parser::node_info& info, std::vector<instruction_ref>& args)
+{
+    std::vector<int64_t> perm{1, 0, 2};
+    args[0] = info.add_instruction(make_op("transpose", {{"permutation", perm}}), args[0]);
+
+    if(args.size() >= 6 and not args[5]->is_undefined())
+    {
+        args[5] = info.add_instruction(make_op("transpose", {{"permutation", perm}}), args[5]);
+    }
+
+    if(args.size() >= 7 and not args[6]->is_undefined())
+    {
+        args[6] = info.add_instruction(make_op("transpose", {{"permutation", perm}}), args[6]);
+    }
+}
+
+void lstm_transpose_outputs(onnx_parser::node_info& info,
+                            instruction_ref& hidden_states,
+                            instruction_ref& last_output,
+                            instruction_ref& last_cell_output)
+{
+    std::vector<int64_t> perm_hs{2, 0, 1, 3};
+    hidden_states =
+        info.add_instruction(make_op("transpose", {{"permutation", perm_hs}}), hidden_states);
+    std::vector<int64_t> perm_last{1, 0, 2};
+    last_output =
+        info.add_instruction(make_op("transpose", {{"permutation", perm_last}}), last_output);
+    last_cell_output =
+        info.add_instruction(make_op("transpose", {{"permutation", perm_last}}), last_cell_output);
+}
+
 struct parse_lstm : op_parser<parse_lstm>
 {
     std::vector<op_desc> operators() const { return {{"LSTM"}}; }
@@ -202,6 +233,12 @@ struct parse_lstm : op_parser<parse_lstm>
             input_forget = parser.parse_value(info.attributes.at("input_forget")).at<int>();
         }
 
+        int layout = 0;
+        if(contains(info.attributes, "layout"))
+        {
+            layout = parser.parse_value(info.attributes.at("layout")).at<int>();
+        }
+
         // append undefined opeator to make 6 arguments
         if(args.size() < 8)
         {
@@ -209,6 +246,11 @@ struct parse_lstm : op_parser<parse_lstm>
             args.insert(args.end(), 8 - args.size(), ins);
         }
 
+        if(layout != 0)
+        {
+            lstm_transpose_inputs(info, args);
+        }
+
         // first output for concatenation of hidden states
         auto hidden_states = info.add_instruction(make_op("lstm",
                                                           {{"hidden_size", hidden_size},
@@ -224,6 +266,11 @@ struct parse_lstm : op_parser<parse_lstm>
         auto last_cell_output =
             info.add_instruction(make_op("rnn_last_cell_output"), hidden_states);
 
+        if(layout != 0)
+        {
+            lstm_transpose_outputs(info, hidden_states, last_output, last_cell_output);
+        }
+
         return {hidden_states, last_output, last_cell_output};
     }
 };

src/simplify_qdq.cpp

@@ -45,77 +45,145 @@ std::unordered_set<std::string> get_quantizable_op_names()
     return s;
 }
 
-MIGRAPHX_PRED_MATCHER(has_same_value, instruction_ref ins)
+struct match_find_quantizable_ops
 {
-    if(ins->name() != "@literal")
-        return false;
-    bool all_same = false;
-    ins->get_literal().visit([&](auto s) {
-        all_same = std::all_of(s.begin() + 1, s.end(), [&](const auto& scale) {
-            return float_equal(scale, s.front());
+    static bool
+    is_valid_scale(instruction_ref scale, std::vector<std::size_t> lens, std::size_t axis)
+    {
+        return scale->get_shape().scalar() or scale->get_shape().elements() == lens.at(axis);
+    }
+
+    static bool is_valid_zero_point(instruction_ref zp)
+    {
+        if(not zp->can_eval())
+            return false;
+
+        bool all_zeros = false;
+        zp->eval().visit([&](auto z) {
+            all_zeros =
+                std::all_of(z.begin(), z.end(), [&](auto val) { return float_equal(val, 0); });
         });
-    });
-    return all_same;
-}
+        return all_zeros;
+    }
 
-struct match_find_quantizable_ops
-{
+    static auto
+    scale_broadcast_op(instruction_ref scale, std::vector<std::size_t> lens, std::size_t axis)
+    {
+        if(scale->get_shape().scalar())
+        {
+            return migraphx::make_op("multibroadcast", {{"out_lens", lens}});
+        }
+        else
+        {
+            return migraphx::make_op("broadcast", {{"out_lens", lens}, {"axis", axis}});
+        }
+    }
 
-    static auto dequantizelinear_op(const std::string& name, const std::string& scale)
+    // Helper function to insert quantized versions of any broadcasts and transpose ops that
+    // occur between dequantizelinear and the quantized op
+    static auto
+    propagate_quantized_ins(module& m, const instruction_ref dqins, const instruction_ref qop)
+    {
+        auto qinp     = dqins->inputs().front();
+        auto next_ins = dqins;
+
+        while(next_ins != qop)
+        {
+            if(next_ins->name() != "dequantizelinear")
+            {
+                qinp = m.insert_instruction(qop, next_ins->get_operator(), qinp);
+            }
+            next_ins = next_ins->outputs().front();
+        }
+        return qinp;
+    }
+
+    static auto dequantizelinear_op(const std::string& scale, const std::string& zp)
     {
         return match::name("dequantizelinear")(
-            match::arg(0)(match::skip(match::name("quantizelinear"))(match::any().bind(name))),
-            match::arg(1)(match::skip_broadcasts(has_same_value().bind(scale))),
-            match::arg(2)(match::skip_broadcasts(match::all_of(match::has_value(0)))));
+            match::arg(0)(match::skip(match::name("quantizelinear"))(match::any())),
+            match::arg(1)(match::skip_broadcasts(match::is_constant().bind(scale))),
+            match::arg(2)(match::skip_broadcasts(match::is_constant().bind(zp))));
     }
 
     auto matcher() const
     {
         return match::name(get_quantizable_op_names())(
-            match::arg(0)(dequantizelinear_op("x1", "scale1")),
-            match::arg(1)(dequantizelinear_op("x2", "scale2")));
+            match::arg(0)(match::skip_broadcasts_transposes_contiguous(
+                dequantizelinear_op("scale1", "zp1").bind("dq1"))),
+            match::arg(1)(match::skip_broadcasts_transposes_contiguous(
+                dequantizelinear_op("scale2", "zp2").bind("dq2"))));
     }
 
     void apply(module& m, const match::matcher_result& r) const
     {
         auto qop    = r.result;
-        auto q1     = r.instructions["x1"];
-        auto q2     = r.instructions["x2"];
+        auto dq1    = r.instructions["dq1"];
+        auto dq2    = r.instructions["dq2"];
         auto scale1 = r.instructions["scale1"];
         auto scale2 = r.instructions["scale2"];
+        auto zp1    = r.instructions["zp1"];
+        auto zp2    = r.instructions["zp2"];
 
         // Only INT8 type currently supported
-        if(q1->get_shape().type() != migraphx::shape::int8_type or
-           q2->get_shape().type() != migraphx::shape::int8_type)
+        if(dq1->inputs().front()->get_shape().type() != migraphx::shape::int8_type or
+           dq2->inputs().front()->get_shape().type() != migraphx::shape::int8_type)
             return;
 
-        double scale;
-        visit_all(scale1->get_literal(), scale2->get_literal())(
-            [&](const auto s1, const auto s2) { scale = s1.front() * s2.front(); });
+        // Only symmetric quantization supported (ie. non-zero zero_points not allowed)
+        if(not(is_valid_zero_point(zp1) and is_valid_zero_point(zp2)))
+            return;
 
+        // Only support scalar and 1D scales
+        if(scale1->get_shape().lens().size() != 1 or scale2->get_shape().lens().size() != 1)
+            return;
+
+        // Propagate q1 and q2 through any broadcasts and transposes before qop
         auto qop_args  = qop->inputs();
-        qop_args.at(0) = q1;
-        qop_args.at(1) = q2;
+        qop_args.at(0) = propagate_quantized_ins(m, dq1, qop);
+        qop_args.at(1) = propagate_quantized_ins(m, dq2, qop);
         instruction_ref dq;
-        instruction_ref dq_scale;
+        instruction_ref out_scale;
         instruction_ref zero_point;
         if(qop->name() == "convolution")
         {
             auto conv_val = qop->get_operator().to_value();
             dq            = m.insert_instruction(
                 qop, migraphx::make_op("quant_convolution", conv_val), qop_args);
+            auto out_lens = dq->get_shape().lens();
+
+            // Input scale should always be scalar and weight scale can be scalar or 1D of the
+            // same lens as the output channel dim (dim 1 in the output)
+            if(not(is_valid_scale(scale1, out_lens, 1) and is_valid_scale(scale2, out_lens, 1)))
+                return;
+
+            auto s1_bcast =
+                m.insert_instruction(qop, scale_broadcast_op(scale1, out_lens, 1), scale1);
+            auto s2_bcast =
+                m.insert_instruction(qop, scale_broadcast_op(scale2, out_lens, 1), scale2);
+
+            out_scale = m.insert_instruction(qop, migraphx::make_op("mul"), s1_bcast, s2_bcast);
         }
         else if(qop->name() == "dot")
         {
-            dq = m.insert_instruction(qop, migraphx::make_op("quant_dot"), qop_args);
+            dq            = m.insert_instruction(qop, migraphx::make_op("quant_dot"), qop_args);
+            auto out_lens = dq->get_shape().lens();
+
+            // For (..., M, N) x (..., N, K) dot, only support cases where quantization axis is M
+            // for input1 and K for input 2
+            if(not(is_valid_scale(scale1, out_lens, out_lens.size() - 2) and
+                   is_valid_scale(scale2, out_lens, out_lens.size() - 1)))
+                return;
+
+            auto s1_bcast = m.insert_instruction(
+                qop, scale_broadcast_op(scale1, out_lens, out_lens.size() - 2), scale1);
+            auto s2_bcast = m.insert_instruction(
+                qop, scale_broadcast_op(scale2, out_lens, out_lens.size() - 1), scale2);
+
+            out_scale = m.insert_instruction(qop, migraphx::make_op("mul"), s1_bcast, s2_bcast);
         }
-        auto ins_type = qop->get_shape().type();
-        dq_scale      = m.add_literal(literal({ins_type}, {scale}));
 
-        auto lens = dq->get_shape().lens();
-        auto scale_mb =
-            m.insert_instruction(qop, make_op("multibroadcast", {{"out_lens", lens}}), dq_scale);
-        dq = m.insert_instruction(qop, make_op("dequantizelinear"), dq, scale_mb);
+        dq = m.insert_instruction(qop, make_op("dequantizelinear"), dq, out_scale);
         m.replace_instruction(qop, dq);
     }
 };

test/onnx/gen_onnx.py

@@ -4484,6 +4484,177 @@ def lrn_test():
     return ([node], [x], [y])
 
 
+@onnx_test()
+def lstm_bi_layout_cell_test():
+    seq = helper.make_tensor_value_info('seq', TensorProto.FLOAT, [3, 5, 10])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [2, 80, 10])
+    r = helper.make_tensor_value_info('r', TensorProto.FLOAT, [2, 80, 20])
+    bias = helper.make_tensor_value_info('bias', TensorProto.FLOAT, [2, 160])
+    seq_len = helper.make_tensor_value_info('seq_len', TensorProto.INT32, [3])
+    h0 = helper.make_tensor_value_info('h0', TensorProto.FLOAT, [3, 2, 20])
+    c0 = helper.make_tensor_value_info('c0', TensorProto.FLOAT, [3, 2, 20])
+    pph = helper.make_tensor_value_info('pph', TensorProto.FLOAT, [2, 60])
+
+    cellout = helper.make_tensor_value_info('cellout', TensorProto.FLOAT,
+                                            [3, 2, 20])
+
+    node = onnx.helper.make_node(
+        'LSTM',
+        inputs=['seq', 'w', 'r', 'bias', 'seq_len', 'h0', 'c0', 'pph'],
+        outputs=['', '', 'cellout'],
+        activations=['sigmoid', 'tanh', 'tanh'],
+        clip=0,
+        direction='bidirectional',
+        hidden_size=20,
+        input_forget=1,
+        layout=1)
+
+    return ([node], [seq, w, r, bias, seq_len, h0, c0, pph], [cellout])
+
+
+@onnx_test()
+def lstm_bi_layout_last_test():
+    seq = helper.make_tensor_value_info('seq', TensorProto.FLOAT, [3, 5, 10])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [2, 80, 10])
+    r = helper.make_tensor_value_info('r', TensorProto.FLOAT, [2, 80, 20])
+    bias = helper.make_tensor_value_info('bias', TensorProto.FLOAT, [2, 160])
+    seq_len = helper.make_tensor_value_info('seq_len', TensorProto.INT32, [3])
+    h0 = helper.make_tensor_value_info('h0', TensorProto.FLOAT, [3, 2, 20])
+    c0 = helper.make_tensor_value_info('c0', TensorProto.FLOAT, [3, 2, 20])
+    pph = helper.make_tensor_value_info('pph', TensorProto.FLOAT, [2, 60])
+
+    hs = helper.make_tensor_value_info('hs', TensorProto.FLOAT, [3, 5, 2, 20])
+    output = helper.make_tensor_value_info('output', TensorProto.FLOAT,
+                                           [3, 2, 20])
+
+    node = onnx.helper.make_node(
+        'LSTM',
+        inputs=['seq', 'w', 'r', 'bias', 'seq_len', 'h0', 'c0', 'pph'],
+        outputs=['hs', 'output'],
+        activations=['sigmoid', 'tanh', 'tanh'],
+        clip=0,
+        direction='bidirectional',
+        hidden_size=20,
+        input_forget=1,
+        layout=1)
+
+    return ([node], [seq, w, r, bias, seq_len, h0, c0, pph], [hs, output])
+
+
+@onnx_test()
+def lstm_f_layout_hs_test():
+    seq = helper.make_tensor_value_info('seq', TensorProto.FLOAT, [3, 5, 10])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 80, 10])
+    r = helper.make_tensor_value_info('r', TensorProto.FLOAT, [1, 80, 20])
+    bias = helper.make_tensor_value_info('bias', TensorProto.FLOAT, [1, 160])
+    seq_len = helper.make_tensor_value_info('seq_len', TensorProto.INT32, [3])
+    h0 = helper.make_tensor_value_info('h0', TensorProto.FLOAT, [3, 1, 20])
+    c0 = helper.make_tensor_value_info('c0', TensorProto.FLOAT, [3, 1, 20])
+    pph = helper.make_tensor_value_info('pph', TensorProto.FLOAT, [1, 60])
+
+    hs = helper.make_tensor_value_info('hs', TensorProto.FLOAT, [3, 5, 1, 20])
+    output = helper.make_tensor_value_info('output', TensorProto.FLOAT,
+                                           [3, 1, 20])
+
+    node = onnx.helper.make_node(
+        'LSTM',
+        inputs=['seq', 'w', 'r', 'bias', 'seq_len', 'h0', 'c0', 'pph'],
+        outputs=['hs', 'output'],
+        activations=['sigmoid', 'tanh', 'tanh'],
+        clip=0,
+        direction='forward',
+        hidden_size=20,
+        input_forget=1,
+        layout=1)
+
+    return ([node], [seq, w, r, bias, seq_len, h0, c0, pph], [hs, output])
+
+
+@onnx_test()
+def lstm_f_layout_cell_test():
+    seq = helper.make_tensor_value_info('seq', TensorProto.FLOAT, [3, 5, 10])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 80, 10])
+    r = helper.make_tensor_value_info('r', TensorProto.FLOAT, [1, 80, 20])
+    bias = helper.make_tensor_value_info('bias', TensorProto.FLOAT, [1, 160])
+    seq_len = helper.make_tensor_value_info('seq_len', TensorProto.INT32, [3])
+    h0 = helper.make_tensor_value_info('h0', TensorProto.FLOAT, [3, 1, 20])
+    c0 = helper.make_tensor_value_info('c0', TensorProto.FLOAT, [3, 1, 20])
+    pph = helper.make_tensor_value_info('pph', TensorProto.FLOAT, [1, 60])
+
+    cellout = helper.make_tensor_value_info('cellout', TensorProto.FLOAT,
+                                            [3, 1, 20])
+
+    node = onnx.helper.make_node(
+        'LSTM',
+        inputs=['seq', 'w', 'r', 'bias', 'seq_len', 'h0', 'c0', 'pph'],
+        outputs=['', '', 'cellout'],
+        activations=['sigmoid', 'tanh', 'tanh'],
+        clip=0,
+        direction='forward',
+        hidden_size=20,
+        input_forget=1,
+        layout=1)
+
+    return ([node], [seq, w, r, bias, seq_len, h0, c0, pph], [cellout])
+
+
+@onnx_test()
+def lstm_r_layout_test():
+    seq = helper.make_tensor_value_info('seq', TensorProto.FLOAT, [3, 5, 10])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 80, 10])
+    r = helper.make_tensor_value_info('r', TensorProto.FLOAT, [1, 80, 20])
+    bias = helper.make_tensor_value_info('bias', TensorProto.FLOAT, [1, 160])
+    seq_len = helper.make_tensor_value_info('seq_len', TensorProto.INT32, [3])
+    h0 = helper.make_tensor_value_info('h0', TensorProto.FLOAT, [3, 1, 20])
+    c0 = helper.make_tensor_value_info('c0', TensorProto.FLOAT, [3, 1, 20])
+    pph = helper.make_tensor_value_info('pph', TensorProto.FLOAT, [1, 60])
+
+    hs = helper.make_tensor_value_info('hs', TensorProto.FLOAT, [3, 5, 1, 20])
+
+    node = onnx.helper.make_node(
+        'LSTM',
+        inputs=['seq', 'w', 'r', 'bias', 'seq_len', 'h0', 'c0', 'pph'],
+        outputs=['hs'],
+        activations=['sigmoid', 'tanh', 'tanh'],
+        clip=0,
+        direction='reverse',
+        hidden_size=20,
+        input_forget=1,
+        layout=1)
+
+    return ([node], [seq, w, r, bias, seq_len, h0, c0, pph], [hs])
+
+
+@onnx_test()
+def lstm_r_layout_hs_cell_test():
+    seq = helper.make_tensor_value_info('seq', TensorProto.FLOAT, [3, 5, 10])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 80, 10])
+    r = helper.make_tensor_value_info('r', TensorProto.FLOAT, [1, 80, 20])
+    bias = helper.make_tensor_value_info('bias', TensorProto.FLOAT, [1, 160])
+    seq_len = helper.make_tensor_value_info('seq_len', TensorProto.INT32, [3])
+    h0 = helper.make_tensor_value_info('h0', TensorProto.FLOAT, [3, 1, 20])
+    c0 = helper.make_tensor_value_info('c0', TensorProto.FLOAT, [3, 1, 20])
+    pph = helper.make_tensor_value_info('pph', TensorProto.FLOAT, [1, 60])
+
+    output = helper.make_tensor_value_info('output', TensorProto.FLOAT,
+                                           [3, 1, 20])
+    cellout = helper.make_tensor_value_info('cellout', TensorProto.FLOAT,
+                                            [3, 1, 20])
+
+    node = onnx.helper.make_node(
+        'LSTM',
+        inputs=['seq', 'w', 'r', 'bias', 'seq_len', 'h0', 'c0', 'pph'],
+        outputs=['', 'output', 'cellout'],
+        activations=['sigmoid', 'tanh', 'tanh'],
+        clip=0,
+        direction='reverse',
+        hidden_size=20,
+        input_forget=1,
+        layout=1)
+
+    return ([node], [seq, w, r, bias, seq_len, h0, c0, pph], [output, cellout])
+
+
 @onnx_test()
 def matmul_bmbm_test():
     m1 = helper.make_tensor_value_info('1', TensorProto.FLOAT, [3, 6, 7])

test/onnx/onnx_rnn_test.cpp

@@ -1092,6 +1092,115 @@ TEST_CASE(lstm_forward)
     }
 }
 
+TEST_CASE(lstm_forward_layout)
+{
+    std::size_t sl   = 5;  // sequence len
+    std::size_t bs   = 3;  // batch size
+    std::size_t hs   = 20; // hidden size
+    std::size_t is   = 10; // input size
+    std::size_t nd   = 1;  // num directions
+    float clip       = 0.0f;
+    int input_forget = 1;
+    migraphx::shape seq_shape{migraphx::shape::float_type, {bs, sl, is}};
+    migraphx::shape w_shape{migraphx::shape::float_type, {nd, 4 * hs, is}};
+    migraphx::shape r_shape{migraphx::shape::float_type, {nd, 4 * hs, hs}};
+    migraphx::shape bias_shape{migraphx::shape::float_type, {nd, 8 * hs}};
+    migraphx::shape sl_shape{migraphx::shape::int32_type, {bs}};
+    migraphx::shape ih_shape{migraphx::shape::float_type, {bs, nd, hs}};
+    migraphx::shape pph_shape{migraphx::shape::float_type, {nd, 3 * hs}};
+
+    // 8 args, hs and last output
+    {
+        migraphx::program p;
+        auto* mm     = p.get_main_module();
+        auto seq     = mm->add_parameter("seq", seq_shape);
+        auto w       = mm->add_parameter("w", w_shape);
+        auto r       = mm->add_parameter("r", r_shape);
+        auto bias    = mm->add_parameter("bias", bias_shape);
+        auto seq_len = mm->add_parameter("seq_len", sl_shape);
+        auto ih      = mm->add_parameter("h0", ih_shape);
+        auto ic      = mm->add_parameter("c0", ih_shape);
+        auto pph     = mm->add_parameter("pph", pph_shape);
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto out_hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hs},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip},
+                 {"input_forget", input_forget}}),
+            seq,
+            w,
+            r,
+            bias,
+            seq_len,
+            ih,
+            ic,
+            pph);
+        auto last_output = mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), out_hs);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        out_hs = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}),
+                                     out_hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_output);
+
+        auto prog = optimize_onnx("lstm_f_layout_hs_test.onnx");
+
+        EXPECT(p == prog);
+    }
+    // 8 args, cell output
+    {
+        migraphx::program p;
+        auto* mm     = p.get_main_module();
+        auto seq     = mm->add_parameter("seq", seq_shape);
+        auto w       = mm->add_parameter("w", w_shape);
+        auto r       = mm->add_parameter("r", r_shape);
+        auto bias    = mm->add_parameter("bias", bias_shape);
+        auto seq_len = mm->add_parameter("seq_len", sl_shape);
+        auto ih      = mm->add_parameter("h0", ih_shape);
+        auto ic      = mm->add_parameter("c0", ih_shape);
+        auto pph     = mm->add_parameter("pph", pph_shape);
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto out_hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hs},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip},
+                 {"input_forget", input_forget}}),
+            seq,
+            w,
+            r,
+            bias,
+            seq_len,
+            ih,
+            ic,
+            pph);
+        auto last_cell = mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), out_hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_cell);
+        auto prog = optimize_onnx("lstm_f_layout_cell_test.onnx");
+
+        EXPECT(p == prog);
+    }
+}
+
 // activation functions
 TEST_CASE(lstm_forward_actv_func)
 {
@@ -1342,6 +1451,117 @@ TEST_CASE(lstm_reverse)
     }
 }
 
+TEST_CASE(lstm_reverse_layout)
+{
+    std::size_t sl   = 5;  // sequence len
+    std::size_t bs   = 3;  // batch size
+    std::size_t hs   = 20; // hidden size
+    std::size_t is   = 10; // input size
+    std::size_t nd   = 1;  // num directions
+    float clip       = 0.0f;
+    int input_forget = 1;
+    migraphx::shape seq_shape{migraphx::shape::float_type, {bs, sl, is}};
+    migraphx::shape w_shape{migraphx::shape::float_type, {nd, 4 * hs, is}};
+    migraphx::shape r_shape{migraphx::shape::float_type, {nd, 4 * hs, hs}};
+    migraphx::shape bias_shape{migraphx::shape::float_type, {nd, 8 * hs}};
+    migraphx::shape sl_shape{migraphx::shape::int32_type, {bs}};
+    migraphx::shape ih_shape{migraphx::shape::float_type, {bs, nd, hs}};
+    migraphx::shape pph_shape{migraphx::shape::float_type, {nd, 3 * hs}};
+
+    // 8 args, hs output
+    {
+        migraphx::program p;
+        auto* mm     = p.get_main_module();
+        auto seq     = mm->add_parameter("seq", seq_shape);
+        auto w       = mm->add_parameter("w", w_shape);
+        auto r       = mm->add_parameter("r", r_shape);
+        auto bias    = mm->add_parameter("bias", bias_shape);
+        auto seq_len = mm->add_parameter("seq_len", sl_shape);
+        auto ih      = mm->add_parameter("h0", ih_shape);
+        auto ic      = mm->add_parameter("c0", ih_shape);
+        auto pph     = mm->add_parameter("pph", pph_shape);
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto out_hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hs},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                 {"clip", clip},
+                 {"input_forget", input_forget}}),
+            seq,
+            w,
+            r,
+            bias,
+            seq_len,
+            ih,
+            ic,
+            pph);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        out_hs    = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}),
+                                     out_hs);
+        auto prog = optimize_onnx("lstm_r_layout_test.onnx");
+
+        EXPECT(p == prog);
+    }
+
+    // 8 args, last and cell output
+    {
+        migraphx::program p;
+        auto* mm     = p.get_main_module();
+        auto seq     = mm->add_parameter("seq", seq_shape);
+        auto w       = mm->add_parameter("w", w_shape);
+        auto r       = mm->add_parameter("r", r_shape);
+        auto bias    = mm->add_parameter("bias", bias_shape);
+        auto seq_len = mm->add_parameter("seq_len", sl_shape);
+        auto ih      = mm->add_parameter("h0", ih_shape);
+        auto ic      = mm->add_parameter("c0", ih_shape);
+        auto pph     = mm->add_parameter("pph", pph_shape);
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto out_hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hs},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                 {"clip", clip},
+                 {"input_forget", input_forget}}),
+            seq,
+            w,
+            r,
+            bias,
+            seq_len,
+            ih,
+            ic,
+            pph);
+        auto last_output = mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), out_hs);
+        auto last_cell   = mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), out_hs);
+        last_output = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}),
+                                          last_output);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_cell);
+
+        auto prog = optimize_onnx("lstm_r_layout_hs_cell_test.onnx");
+
+        EXPECT(p == prog);
+    }
+}
+
 TEST_CASE(lstm_bidirectional)
 {
     std::size_t sl   = 5;  // sequence len
@@ -1594,6 +1814,118 @@ TEST_CASE(lstm_bidirectional)
     }
 }
 
+TEST_CASE(lstm_bidirectional_layout)
+{
+    std::size_t sl   = 5;  // sequence len
+    std::size_t bs   = 3;  // batch size
+    std::size_t hs   = 20; // hidden size
+    std::size_t is   = 10; // input size
+    std::size_t nd   = 2;  // num directions
+    float clip       = 0.0f;
+    int input_forget = 1;
+    migraphx::shape seq_shape{migraphx::shape::float_type, {bs, sl, is}};
+    migraphx::shape w_shape{migraphx::shape::float_type, {nd, 4 * hs, is}};
+    migraphx::shape r_shape{migraphx::shape::float_type, {nd, 4 * hs, hs}};
+    migraphx::shape bias_shape{migraphx::shape::float_type, {nd, 8 * hs}};
+    migraphx::shape sl_shape{migraphx::shape::int32_type, {bs}};
+    migraphx::shape ih_shape{migraphx::shape::float_type, {bs, nd, hs}};
+    migraphx::shape pph_shape{migraphx::shape::float_type, {nd, 3 * hs}};
+    // 0 activation function
+    {
+        migraphx::program p;
+        auto* mm     = p.get_main_module();
+        auto seq     = mm->add_parameter("seq", seq_shape);
+        auto w       = mm->add_parameter("w", w_shape);
+        auto r       = mm->add_parameter("r", r_shape);
+        auto bias    = mm->add_parameter("bias", bias_shape);
+        auto seq_len = mm->add_parameter("seq_len", sl_shape);
+        auto ih      = mm->add_parameter("h0", ih_shape);
+        auto ic      = mm->add_parameter("c0", ih_shape);
+        auto pph     = mm->add_parameter("pph", pph_shape);
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto out_hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hs},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
+                 {"clip", clip},
+                 {"input_forget", input_forget}}),
+            seq,
+            w,
+            r,
+            bias,
+            seq_len,
+            ih,
+            ic,
+            pph);
+        auto last_output = mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), out_hs);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        out_hs = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}),
+                                     out_hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_output);
+        auto prog = optimize_onnx("lstm_bi_layout_last_test.onnx");
+
+        EXPECT(p == prog);
+    }
+    {
+        migraphx::program p;
+        auto* mm     = p.get_main_module();
+        auto seq     = mm->add_parameter("seq", seq_shape);
+        auto w       = mm->add_parameter("w", w_shape);
+        auto r       = mm->add_parameter("r", r_shape);
+        auto bias    = mm->add_parameter("bias", bias_shape);
+        auto seq_len = mm->add_parameter("seq_len", sl_shape);
+        auto ih      = mm->add_parameter("h0", ih_shape);
+        auto ic      = mm->add_parameter("c0", ih_shape);
+        auto pph     = mm->add_parameter("pph", pph_shape);
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto out_hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hs},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
+                 {"clip", clip},
+                 {"input_forget", input_forget}}),
+            seq,
+            w,
+            r,
+            bias,
+            seq_len,
+            ih,
+            ic,
+            pph);
+        auto last_cell = mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), out_hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_cell);
+        auto prog = optimize_onnx("lstm_bi_layout_cell_test.onnx");
+
+        EXPECT(p == prog);
+    }
+}
+
 TEST_CASE(lstm_bi_actv_funcs)
 {
     std::size_t sl   = 5;  // sequence len

test/py/onnx_backend_test.py

@@ -574,7 +574,6 @@ def disabled_tests_onnx_1_9_0(backend_test):
     # fails
     # from OnnxBackendNodeModelTest
     backend_test.exclude(r'test_gru_batchwise_cpu')
-    backend_test.exclude(r'test_lstm_batchwise_cpu')
     backend_test.exclude(r'test_simple_rnn_batchwise_cpu')
     # from OnnxBackendPyTorchConvertedModelTest
     backend_test.exclude(r'test_MaxPool1d_stride_padding_dilation_cpu')

test/quantization.cpp

@@ -636,13 +636,12 @@ TEST_CASE(dot_float)
             migraphx::make_op("multibroadcast", {{"out_lens", sb.lens()}}), scale);
         auto zp_b =
             mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", sb.lens()}}), zp);
-        auto quant_b = mm->add_instruction(migraphx::make_op("quantizelinear"), pb, scale_b, zp_b);
-        auto quant   = mm->add_instruction(migraphx::make_op("quant_dot"), quant_a, quant_b);
-        std::vector<float> vec(sc.elements(), 100.0f);
-        auto dc = mm->add_literal(100.0f);
-        auto mdc =
-            mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", sc.lens()}}), dc);
-        auto r = mm->add_instruction(migraphx::make_op("dequantizelinear"), quant, mdc);
+        auto quant_b  = mm->add_instruction(migraphx::make_op("quantizelinear"), pb, scale_b, zp_b);
+        auto quant    = mm->add_instruction(migraphx::make_op("quant_dot"), quant_a, quant_b);
+        auto scale_mb = mm->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", quant->get_shape().lens()}}), scale);
+        auto out_scale = mm->add_instruction(migraphx::make_op("mul"), scale_mb, scale_mb);
+        auto r = mm->add_instruction(migraphx::make_op("dequantizelinear"), quant, out_scale);
         mm->add_return({r});
 
         return p;
@@ -717,24 +716,28 @@ TEST_CASE(dot_double_2args)
         auto pa = mm->add_parameter("a", sa);
         auto pb = mm->add_parameter("b", sb);
 
-        auto scale_a = mm->add_literal(10.0);
-        auto zp      = mm->add_literal(static_cast<int8_t>(0));
-        scale_a      = mm->add_instruction(
-            migraphx::make_op("multibroadcast", {{"out_lens", sa.lens()}}), scale_a);
+        auto scale_a_lit = mm->add_literal(10.0);
+        auto zp          = mm->add_literal(static_cast<int8_t>(0));
+        auto scale_a     = mm->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", sa.lens()}}), scale_a_lit);
         auto zp_a =
             mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", sa.lens()}}), zp);
-        auto qa      = mm->add_instruction(migraphx::make_op("quantizelinear"), pa, scale_a, zp_a);
-        auto scale_b = mm->add_literal(5.0);
-        scale_b      = mm->add_instruction(
-            migraphx::make_op("multibroadcast", {{"out_lens", sb.lens()}}), scale_b);
+        auto qa = mm->add_instruction(migraphx::make_op("quantizelinear"), pa, scale_a, zp_a);
+        auto scale_b_lit = mm->add_literal(5.0);
+        auto scale_b     = mm->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", sb.lens()}}), scale_b_lit);
         auto zp_b =
             mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", sb.lens()}}), zp);
-        auto qb    = mm->add_instruction(migraphx::make_op("quantizelinear"), pb, scale_b, zp_b);
-        auto qdot  = mm->add_instruction(migraphx::make_op("quant_dot"), qa, qb);
-        auto scale = mm->add_literal(50.0);
-        scale      = mm->add_instruction(
-            migraphx::make_op("multibroadcast", {{"out_lens", qdot->get_shape().lens()}}), scale);
-        auto r = mm->add_instruction(migraphx::make_op("dequantizelinear"), qdot, scale);
+        auto qb   = mm->add_instruction(migraphx::make_op("quantizelinear"), pb, scale_b, zp_b);
+        auto qdot = mm->add_instruction(migraphx::make_op("quant_dot"), qa, qb);
+        auto scale_a_mb = mm->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", qdot->get_shape().lens()}}),
+            scale_a_lit);
+        auto scale_b_mb = mm->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", qdot->get_shape().lens()}}),
+            scale_b_lit);
+        auto out_scale = mm->add_instruction(migraphx::make_op("mul"), scale_a_mb, scale_b_mb);
+        auto r = mm->add_instruction(migraphx::make_op("dequantizelinear"), qdot, out_scale);
         mm->add_return({r});
         return p;
     };
@@ -798,19 +801,16 @@ TEST_CASE(dot_half_1arg)
         migraphx::shape sa{migraphx::shape::half_type, {9, 9}};
         auto x = mm->add_parameter("x", sa);
 
-        auto zp    = mm->add_literal(static_cast<int8_t>(0));
-        auto scale = mm->add_literal(migraphx::literal({sa.type()}, {10.0}));
-        scale = mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", sa.lens()}}),
-                                    scale);
+        auto zp        = mm->add_literal(static_cast<int8_t>(0));
+        auto scale_lit = mm->add_literal(migraphx::literal({sa.type()}, {10.0}));
+        auto scale     = mm->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", sa.lens()}}), scale_lit);
         zp =
             mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", sa.lens()}}), zp);
-        auto qx       = mm->add_instruction(migraphx::make_op("quantizelinear"), x, scale, zp);
-        auto qdot     = mm->add_instruction(migraphx::make_op("quant_dot"), qx, qx);
-        auto dq_scale = mm->add_literal(migraphx::literal({sa.type()}, {100.0}));
-        dq_scale      = mm->add_instruction(
-            migraphx::make_op("multibroadcast", {{"out_lens", qdot->get_shape().lens()}}),
-            dq_scale);
-        auto r = mm->add_instruction(migraphx::make_op("dequantizelinear"), qdot, dq_scale);
+        auto qx        = mm->add_instruction(migraphx::make_op("quantizelinear"), x, scale, zp);
+        auto qdot      = mm->add_instruction(migraphx::make_op("quant_dot"), qx, qx);
+        auto out_scale = mm->add_instruction(migraphx::make_op("mul"), scale, scale);
+        auto r = mm->add_instruction(migraphx::make_op("dequantizelinear"), qdot, out_scale);
         mm->add_return({r});
         return p;
     };
@@ -851,10 +851,10 @@ TEST_CASE(conv_float)
         auto px = mm->add_parameter("x", sx);
         auto pw = mm->add_parameter("w", sw);
 
-        auto zp    = mm->add_literal(static_cast<int8_t>(0));
-        auto scale = mm->add_literal(10.0f);
-        scale = mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", sx.lens()}}),
-                                    scale);
+        auto zp        = mm->add_literal(static_cast<int8_t>(0));
+        auto scale_lit = mm->add_literal(10.0f);
+        auto scale     = mm->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", sx.lens()}}), scale_lit);
         zp =
             mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", sx.lens()}}), zp);
         auto quant_x = mm->add_instruction(migraphx::make_op("quantizelinear"), px, scale, zp);
@@ -862,13 +862,11 @@ TEST_CASE(conv_float)
 
         auto quant = mm->add_instruction(migraphx::make_op("quant_convolution"), quant_x, quant_w);
 
-        migraphx::shape sc{migraphx::shape::float_type, {4, 4, 1, 1}};
-        std::vector<float> vec(sc.elements(), 100.0f);
-        migraphx::shape s_scale{migraphx::shape::float_type, sc.lens()};
-        auto d_scale = mm->add_literal(100.0f);
-        d_scale      = mm->add_instruction(
-            migraphx::make_op("multibroadcast", {{"out_lens", {4, 4, 1, 1}}}), d_scale);
-        auto r = mm->add_instruction(migraphx::make_op("dequantizelinear"), quant, d_scale);
+        auto scale_mb = mm->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", quant->get_shape().lens()}}),
+            scale_lit);
+        auto out_scale = mm->add_instruction(migraphx::make_op("mul"), scale_mb, scale_mb);
+        auto r = mm->add_instruction(migraphx::make_op("dequantizelinear"), quant, out_scale);
         mm->add_return({r});
 
         return p;
@@ -930,20 +928,21 @@ TEST_CASE(conv_half)
         auto px = mm->add_parameter("x", sx);
         auto pw = mm->add_parameter("w", sw);
 
-        auto zp    = mm->add_literal(static_cast<int8_t>(0));
-        auto scale = mm->add_literal(migraphx::literal({sx.type()}, {10.0}));
-        scale = mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", sx.lens()}}),
-                                    scale);
+        auto zp        = mm->add_literal(static_cast<int8_t>(0));
+        auto scale_lit = mm->add_literal(migraphx::literal({sx.type()}, {10.0}));
+        auto scale     = mm->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", sx.lens()}}), scale_lit);
         zp =
             mm->add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", sx.lens()}}), zp);
         auto quant_x = mm->add_instruction(migraphx::make_op("quantizelinear"), px, scale, zp);
         auto quant_w = mm->add_instruction(migraphx::make_op("quantizelinear"), pw, scale, zp);
 
         auto quant = mm->add_instruction(migraphx::make_op("quant_convolution"), quant_x, quant_w);
-        auto d_scale = mm->add_literal(migraphx::literal({sx.type()}, {100.0}));
-        d_scale      = mm->add_instruction(
-            migraphx::make_op("multibroadcast", {{"out_lens", {4, 4, 1, 1}}}), d_scale);
-        auto r = mm->add_instruction(migraphx::make_op("dequantizelinear"), quant, d_scale);
+        auto scale_mb = mm->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", quant->get_shape().lens()}}),
+            scale_lit);
+        auto out_scale = mm->add_instruction(migraphx::make_op("mul"), scale_mb, scale_mb);
+        auto r = mm->add_instruction(migraphx::make_op("dequantizelinear"), quant, out_scale);
         mm->add_return({r});
 
         return p;
@@ -1185,12 +1184,12 @@ TEST_CASE(int8_subgraph)
             migraphx::make_op("multibroadcast", {{"out_lens", sy.lens()}}), s1);
         auto zpb = then_mod->add_instruction(
             migraphx::make_op("multibroadcast", {{"out_lens", sy.lens()}}), zp1);
-        auto qb   = then_mod->add_instruction(migraphx::make_op("quantizelinear"), b, sb, zpb);
-        auto qdot = then_mod->add_instruction(migraphx::make_op("quant_dot"), qa, qb);
-        auto so   = then_mod->add_literal(100.0f);
-        so        = then_mod->add_instruction(
-            migraphx::make_op("multibroadcast", {{"out_lens", sout.lens()}}), so);
-        auto r = then_mod->add_instruction(migraphx::make_op("dequantizelinear"), qdot, so);
+        auto qb    = then_mod->add_instruction(migraphx::make_op("quantizelinear"), b, sb, zpb);
+        auto qdot  = then_mod->add_instruction(migraphx::make_op("quant_dot"), qa, qb);
+        auto s1_mb = then_mod->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", qdot->get_shape().lens()}}), s1);
+        auto so = then_mod->add_instruction(migraphx::make_op("mul"), s1_mb, s1_mb);
+        auto r  = then_mod->add_instruction(migraphx::make_op("dequantizelinear"), qdot, so);
         then_mod->add_return({r});
 
         migraphx::shape sd{migraphx::shape::float_type, {2, 2, 4, 6}};
@@ -1199,24 +1198,25 @@ TEST_CASE(int8_subgraph)
         auto w = mm->add_parameter("w", sw);
         // else submod
         auto* else_mod = p.create_module("If_6_else");
-        auto sax       = else_mod->add_literal(2.0f);
+        auto sax_lit   = else_mod->add_literal(2.0f);
         auto zp        = else_mod->add_literal(static_cast<int8_t>(0));
-        sax            = else_mod->add_instruction(
-            migraphx::make_op("multibroadcast", {{"out_lens", sd.lens()}}), sax);
+        auto sax       = else_mod->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", sd.lens()}}), sax_lit);
         auto zpx = else_mod->add_instruction(
             migraphx::make_op("multibroadcast", {{"out_lens", sd.lens()}}), zp);
-        auto qx  = else_mod->add_instruction(migraphx::make_op("quantizelinear"), x, sax, zpx);
-        auto ssw = else_mod->add_literal(1.66667f);
-        ssw      = else_mod->add_instruction(
-            migraphx::make_op("multibroadcast", {{"out_lens", sw.lens()}}), ssw);
+        auto qx      = else_mod->add_instruction(migraphx::make_op("quantizelinear"), x, sax, zpx);
+        auto ssw_lit = else_mod->add_literal(1.66667f);
+        auto ssw     = else_mod->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", sw.lens()}}), ssw_lit);
         auto zpw = else_mod->add_instruction(
             migraphx::make_op("multibroadcast", {{"out_lens", sw.lens()}}), zp);
-        auto qw    = else_mod->add_instruction(migraphx::make_op("quantizelinear"), w, ssw, zpw);
-        auto qconv = else_mod->add_instruction(migraphx::make_op("quant_convolution"), qx, qw);
-        auto so1   = else_mod->add_literal(3.33333f);
-        so1        = else_mod->add_instruction(
-            migraphx::make_op("multibroadcast", {{"out_lens", sout.lens()}}), so1);
-        auto r1 = else_mod->add_instruction(migraphx::make_op("dequantizelinear"), qconv, so1);
+        auto qw     = else_mod->add_instruction(migraphx::make_op("quantizelinear"), w, ssw, zpw);
+        auto qconv  = else_mod->add_instruction(migraphx::make_op("quant_convolution"), qx, qw);
+        auto ssw_mb = else_mod->add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", qconv->get_shape().lens()}}),
+            ssw_lit);
+        auto so1 = else_mod->add_instruction(migraphx::make_op("mul"), sax, ssw_mb);
+        auto r1  = else_mod->add_instruction(migraphx::make_op("dequantizelinear"), qconv, so1);
         else_mod->add_return({r1});
 
         auto ret = mm->add_instruction(migraphx::make_op("if"), {cond}, {then_mod, else_mod});

test/ref/rnn_ops.cpp

@@ -3228,6 +3228,264 @@ TEST_CASE(lstm_forward)
     }
 }
 
+TEST_CASE(lstm_forward_layout)
+{
+    std::size_t batch_size  = 3;
+    std::size_t seq_len     = 4;
+    std::size_t hidden_size = 4;
+    std::size_t input_size  = 3;
+    std::size_t num_dirct   = 1;
+
+    std::vector<float> w_data{
+        0.1236,  -0.3942, 0.4149,  0.0795,  0.4934,  -0.2858, 0.2602,  -0.3098, 0.0567,  0.3344,
+        0.3607,  -0.0551, 0.4952,  0.3799,  0.0630,  -0.3532, 0.0023,  -0.0592, 0.4267,  0.2382,
+        -0.0784, -0.0032, -0.2476, -0.0206, -0.4963, 0.4837,  0.0827,  0.0123,  -0.1203, -0.0279,
+        -0.0049, 0.4721,  -0.3564, -0.1286, 0.4090,  -0.0504, 0.0575,  -0.2138, 0.1071,  0.1976,
+        -0.0758, 0.0139,  -0.0761, 0.3991,  -0.2965, -0.4845, -0.1496, 0.3285};
+
+    std::vector<float> r_data{
+        0.1237,  0.1229,  -0.0766, -0.1144, -0.1186, 0.2922,  0.2478,  0.3159,  -0.0522, 0.1685,
+        -0.4621, 0.1728,  0.0670,  -0.2458, -0.3835, -0.4589, -0.3109, 0.4908,  -0.0133, -0.1858,
+        -0.0590, -0.0347, -0.2353, -0.0671, -0.3812, -0.0004, -0.1432, 0.2406,  0.1033,  -0.0265,
+        -0.3902, 0.0755,  0.3733,  0.4383,  -0.3140, 0.2537,  -0.1818, -0.4127, 0.3506,  0.2562,
+        0.2926,  0.1620,  -0.4849, -0.4861, 0.4426,  0.2106,  -0.0005, 0.4418,  -0.2926, -0.3100,
+        0.1500,  -0.0362, -0.3801, -0.0065, -0.0631, 0.1277,  0.2315,  0.4087,  -0.3963, -0.4161,
+        -0.2169, -0.1344, 0.3468,  -0.2260};
+
+    std::vector<float> bias_data{0.0088,  0.1183,  0.1642,  -0.2631, -0.1330, -0.4008, 0.3881,
+                                 -0.4407, -0.2760, 0.1274,  -0.0083, -0.2885, 0.3949,  -0.0182,
+                                 0.4445,  0.3477,  0.2266,  0.3423,  -0.0674, -0.4067, 0.0807,
+                                 0.1109,  -0.2036, 0.1782,  -0.2467, -0.0730, -0.4216, 0.0316,
+                                 -0.3025, 0.3637,  -0.3181, -0.4655};
+
+    std::vector<float> input_data{
+        -0.5516, 0.2391, -1.6951, -0.0910, 1.2122,  -0.1952, 0.3577,  1.3508,  -0.5366,
+        0.4583,  2.3794, 1.0372,  -0.4313, -0.9730, -0.2005, 0.4661,  0.6494,  2.1332,
+        1.7449,  0.5483, -0.0701, -0.8887, 0.7892,  -0.4012, 2.3930,  -0.5221, -0.1331,
+        -1.0972, 0.9816, 0.1122,  -0.4100, -2.2344, 0.3685,  -0.2818, -2.3374, 1.5310};
+
+    std::vector<float> ih_data{1.9104,
+                               -1.9004,
+                               0.3337,
+                               0.5741,
+                               0.5671,
+                               0.0458,
+                               0.4514,
+                               -0.8968,
+                               -0.9201,
+                               0.1962,
+                               0.5771,
+                               -0.5332};
+
+    std::vector<float> ic_data{0.9569,
+                               -0.5981,
+                               1.1312,
+                               1.0945,
+                               1.1055,
+                               -0.1212,
+                               -0.9097,
+                               0.7831,
+                               -1.6991,
+                               -1.9498,
+                               -1.2567,
+                               -0.4114};
+
+    std::vector<float> pph_data{1.84369764,
+                                0.68413646,
+                                -0.44892886,
+                                -1.50904413,
+                                0.3860796,
+                                -0.52186625,
+                                1.08474445,
+                                -1.80867321,
+                                1.32594529,
+                                0.4336262,
+                                -0.83699064,
+                                0.49162736};
+
+    float clip = 0.0f;
+    migraphx::shape in_shape{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
+    migraphx::shape ih_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+    migraphx::shape ic_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+    migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, input_size}};
+    migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, hidden_size}};
+    migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 8 * hidden_size}};
+    migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
+
+    // forward, hidden state concatenation as output
+    {
+        migraphx::program p;
+        auto* mm  = p.get_main_module();
+        auto seq  = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            und);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
+        p.compile(migraphx::make_target("ref"));
+
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> hs_data;
+        hs_concat.visit([&](auto output) { hs_data.assign(output.begin(), output.end()); });
+
+        std::vector<float> hs_data_gold{
+            0.0417273,  -0.272355,   0.206765,  0.223879,   0.0742487,  -0.0800085, 0.259897,
+            0.0670196,  -0.00532985, 0.0440265, 0.29654,    -0.0463156, -0.0847427, 0.0874114,
+            0.304256,   -0.0585745,  0.138193,  -0.0322939, -0.0891815, 0.15773,    0.184266,
+            0.0610048,  -0.138041,   0.0963885, 0.0498799,  0.125772,   0.0533032,  -0.131413,
+            -0.0223018, 0.131113,    0.135643,  -0.056620,  0.19139,    -0.127708,  -0.409371,
+            -0.136186,  0.0213755,   -0.146027, -0.0324509, -0.0620429, 0.0988431,  -0.018085,
+            -0.159434,  0.030266,    0.142701,  0.0342236,  -0.198664,  0.0702607};
+        EXPECT(migraphx::verify::verify_rms_range(hs_data, hs_data_gold));
+    }
+
+    // forward, last_output as program output
+    {
+        migraphx::program p;
+        auto* mm  = p.get_main_module();
+        auto seq  = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            und);
+        auto last_output = mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_output);
+        p.compile(migraphx::make_target("ref"));
+
+        auto last_hs = p.eval({}).back();
+        std::vector<float> output_data;
+        last_hs.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+
+        std::vector<float> output_data_gold{-0.0847427,
+                                            0.0874114,
+                                            0.304256,
+                                            -0.0585745,
+                                            -0.0223018,
+                                            0.131113,
+                                            0.135643,
+                                            -0.0566208,
+                                            0.142701,
+                                            0.0342236,
+                                            -0.198664,
+                                            0.0702607};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // forward, last_cell_output as program output
+    {
+        migraphx::program p;
+        auto* mm  = p.get_main_module();
+        auto seq  = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            und);
+        auto cell_output = mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), cell_output);
+        p.compile(migraphx::make_target("ref"));
+
+        auto last_hs = p.eval({}).back();
+        std::vector<float> output_data;
+        last_hs.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+
+        std::vector<float> output_data_gold{-0.111454,
+                                            0.247794,
+                                            0.471087,
+                                            -0.220574,
+                                            -0.048196,
+                                            0.263184,
+                                            0.283258,
+                                            -0.14882,
+                                            0.605585,
+                                            0.078598,
+                                            -0.64457,
+                                            0.119811};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+}
+
 TEST_CASE(lstm_forward_more)
 {
     std::size_t batch_size  = 3;
@@ -3519,7 +3777,7 @@ TEST_CASE(lstm_forward_more)
     }
 }
 
-TEST_CASE(lstm_reverse)
+TEST_CASE(lstm_forward_more_layout)
 {
     std::size_t batch_size  = 3;
     std::size_t seq_len     = 4;
@@ -3527,32 +3785,668 @@ TEST_CASE(lstm_reverse)
     std::size_t input_size  = 3;
     std::size_t num_dirct   = 1;
     std::vector<float> w_data{
-        -0.2763, -0.4715, -0.3010, -0.2306, -0.2283, -0.2656, 0.2035,  0.3570,  -0.1499, 0.4390,
-        -0.1843, 0.2351,  0.3357,  0.1217,  0.1401,  0.3300,  -0.0429, 0.3266,  0.4834,  -0.3914,
-        -0.1480, 0.3734,  -0.0372, -0.1746, 0.0550,  0.4177,  -0.1332, 0.4391,  -0.3287, -0.4401,
-        0.1486,  0.1346,  0.1048,  -0.4361, 0.0886,  -0.3840, -0.2730, -0.1710, 0.3274,  0.0169,
-        -0.4462, 0.0729,  0.3983,  -0.0669, 0.0756,  0.4150,  -0.4684, -0.2522};
+        0.1236,  -0.3942, 0.4149,  0.0795,  0.4934,  -0.2858, 0.2602,  -0.3098, 0.0567,  0.3344,
+        0.3607,  -0.0551, 0.4952,  0.3799,  0.0630,  -0.3532, 0.0023,  -0.0592, 0.4267,  0.2382,
+        -0.0784, -0.0032, -0.2476, -0.0206, -0.4963, 0.4837,  0.0827,  0.0123,  -0.1203, -0.0279,
+        -0.0049, 0.4721,  -0.3564, -0.1286, 0.4090,  -0.0504, 0.0575,  -0.2138, 0.1071,  0.1976,
+        -0.0758, 0.0139,  -0.0761, 0.3991,  -0.2965, -0.4845, -0.1496, 0.3285};
 
     std::vector<float> r_data{
-        -0.4564, -0.4432, 0.1605,  0.4387,  0.0034,  0.4116,  0.2824,  0.4775,  -0.2729, -0.4707,
-        0.1363,  0.2218,  0.0559,  0.2828,  0.2093,  0.4687,  0.3794,  -0.1069, -0.3049, 0.1430,
-        -0.2506, 0.4644,  0.2755,  -0.3645, -0.3155, 0.1425,  0.2891,  0.1786,  -0.3274, 0.2365,
-        0.2522,  -0.4312, -0.0562, -0.2748, 0.0776,  -0.3154, 0.2851,  -0.3930, -0.1174, 0.4360,
-        0.2436,  0.0164,  -0.0680, 0.3403,  -0.2857, -0.0459, -0.2991, -0.2624, 0.4194,  -0.3291,
-        -0.4659, 0.3300,  0.0454,  0.4981,  -0.4706, -0.4584, 0.2596,  0.2871,  -0.3509, -0.1910,
-        0.3987,  -0.1687, -0.0032, -0.1038};
-
-    std::vector<float> bias_data{-0.0258, 0.0073,  -0.4780, -0.4101, -0.3556, -0.1017, 0.3632,
-                                 -0.1823, 0.1479,  0.1677,  -0.2603, 0.0381,  0.1575,  0.1896,
-                                 0.4755,  -0.4794, 0.2167,  -0.4474, -0.3139, 0.1018,  0.4470,
-                                 -0.4232, 0.3247,  -0.1636, -0.1582, -0.1703, 0.3920,  0.2055,
-                                 -0.4386, 0.4208,  0.0717,  0.3789};
+        0.1237,  0.1229,  -0.0766, -0.1144, -0.1186, 0.2922,  0.2478,  0.3159,  -0.0522, 0.1685,
+        -0.4621, 0.1728,  0.0670,  -0.2458, -0.3835, -0.4589, -0.3109, 0.4908,  -0.0133, -0.1858,
+        -0.0590, -0.0347, -0.2353, -0.0671, -0.3812, -0.0004, -0.1432, 0.2406,  0.1033,  -0.0265,
+        -0.3902, 0.0755,  0.3733,  0.4383,  -0.3140, 0.2537,  -0.1818, -0.4127, 0.3506,  0.2562,
+        0.2926,  0.1620,  -0.4849, -0.4861, 0.4426,  0.2106,  -0.0005, 0.4418,  -0.2926, -0.3100,
+        0.1500,  -0.0362, -0.3801, -0.0065, -0.0631, 0.1277,  0.2315,  0.4087,  -0.3963, -0.4161,
+        -0.2169, -0.1344, 0.3468,  -0.2260};
+
+    std::vector<float> bias_data{0.0088,  0.1183,  0.1642,  -0.2631, -0.1330, -0.4008, 0.3881,
+                                 -0.4407, -0.2760, 0.1274,  -0.0083, -0.2885, 0.3949,  -0.0182,
+                                 0.4445,  0.3477,  0.2266,  0.3423,  -0.0674, -0.4067, 0.0807,
+                                 0.1109,  -0.2036, 0.1782,  -0.2467, -0.0730, -0.4216, 0.0316,
+                                 -0.3025, 0.3637,  -0.3181, -0.4655};
+
+    std::vector<float> input_data{
+        -0.5516, 0.2391, -1.6951, -0.0910, 1.2122,  -0.1952, 0.3577,  1.3508,  -0.5366,
+        0.4583,  2.3794, 1.0372,  -0.4313, -0.9730, -0.2005, 0.4661,  0.6494,  2.1332,
+        1.7449,  0.5483, -0.0701, -0.8887, 0.7892,  -0.4012, 2.3930,  -0.5221, -0.1331,
+        -1.0972, 0.9816, 0.1122,  -0.4100, -2.2344, 0.3685,  -0.2818, -2.3374, 1.5310};
+
+    std::vector<float> ih_data{1.9104,
+                               -1.9004,
+                               0.3337,
+                               0.5741,
+                               0.5671,
+                               0.0458,
+                               0.4514,
+                               -0.8968,
+                               -0.9201,
+                               0.1962,
+                               0.5771,
+                               -0.5332};
+
+    std::vector<float> ic_data{0.9569,
+                               -0.5981,
+                               1.1312,
+                               1.0945,
+                               1.1055,
+                               -0.1212,
+                               -0.9097,
+                               0.7831,
+                               -1.6991,
+                               -1.9498,
+                               -1.2567,
+                               -0.4114};
+
+    std::vector<float> pph_data{1.84369764,
+                                0.68413646,
+                                -0.44892886,
+                                -1.50904413,
+                                0.3860796,
+                                -0.52186625,
+                                1.08474445,
+                                -1.80867321,
+                                1.32594529,
+                                0.4336262,
+                                -0.83699064,
+                                0.49162736};
+
+    float clip = 0.0f;
+    migraphx::shape in_shape{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
+    migraphx::shape ih_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+    migraphx::shape ic_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+    migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, input_size}};
+    migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, hidden_size}};
+    migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 8 * hidden_size}};
+    migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
+
+    // forward, 3 args
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto w   = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r   = mm->add_literal(migraphx::literal{r_shape, r_data});
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
+        p.compile(migraphx::make_target("ref"));
+
+        auto last_hs = p.eval({}).back();
+        std::vector<float> output_data;
+        last_hs.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+
+        std::vector<float> output_data_gold{
+            -0.0327039, -0.0543852,  0.114378,   -0.0768855,  -0.0786602, -0.0613048, 0.179592,
+            -0.071286,  -0.102509,   -0.0372696, 0.252296,    -0.144544,  -0.165194,  -0.0372928,
+            0.273786,   -0.100877,   0.0319021,  -0.00298698, -0.0623361, 0.0598866,  0.074206,
+            0.0124086,  -0.139544,   0.108016,   0.00496085,  0.0662588,  -0.048577,  -0.187329,
+            -0.0458544, -0.0401315,  0.0737483,  -0.064505,   0.101585,   0.0687269,  -0.161725,
+            -0.25617,   -0.00973633, -0.0552699, 0.0252681,   -0.0562072, 0.0855831,  -0.0171894,
+            -0.140202,  0.0828391,   0.136898,   0.00160891,  -0.184812,  0.147774};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // forward, 8 args
+    {
+        migraphx::program p;
+        auto* mm  = p.get_main_module();
+        auto seq  = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            pph);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
+        p.compile(migraphx::make_target("ref"));
+
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> hs_data;
+        hs_concat.visit([&](auto output) { hs_data.assign(output.begin(), output.end()); });
+
+        std::vector<float> hs_data_gold{
+            0.079753,  -0.289854,  0.160043,   0.115056,   0.186991,   -0.0624168, 0.205513,
+            0.0836373, 0.0459033,  0.0414126,  0.272303,   0.0393149,  -0.058052,  0.0795391,
+            0.266617,  -0.0128746, 0.294074,   -0.0319677, -0.0955337, 0.104168,   0.421857,
+            0.0459771, -0.144955,  0.0720673,  0.218258,   0.0944405,  0.0431211,  -0.132394,
+            0.0309878, 0.0971544,  0.149294,   -0.0492549, 0.022618,   -0.121195,  -0.4065,
+            -0.252054, -0.0300906, -0.0890598, -0.135266,  -0.0413375, 0.103489,   0.0142918,
+            -0.123408, 0.0401075,  0.187761,   0.0501726,  -0.121584,  0.0606723};
+
+        EXPECT(migraphx::verify::verify_rms_range(hs_data, hs_data_gold));
+    }
+
+    // forward, last_output as program output, sequence length shorter
+    // than max_seq_len
+    {
+        migraphx::program p;
+        auto* mm      = p.get_main_module();
+        auto seq_orig = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto w        = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r        = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias     = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto ih       = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic       = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        migraphx::shape pad_seq_s{migraphx::shape::float_type, {batch_size, 2, input_size}};
+        std::vector<float> pad_data(pad_seq_s.elements(), 0.0f);
+        auto seq_p = mm->add_literal(migraphx::literal{pad_seq_s, pad_data});
+        auto seq = mm->add_instruction(migraphx::make_op("concat", {{"axis", 1}}), seq_orig, seq_p);
+        migraphx::shape seq_len_s{migraphx::shape::int32_type, {batch_size}};
+        std::vector<int32_t> len_data(batch_size, static_cast<int32_t>(seq_len));
+        auto sql = mm->add_literal(seq_len_s, len_data);
+
+        auto und = mm->add_instruction(migraphx::make_op("undefined"));
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            sql,
+            ih,
+            ic,
+            und);
+        auto last_output = mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_output);
+        p.compile(migraphx::make_target("ref"));
+
+        auto last_hs = p.eval({}).back();
+        std::vector<float> output_data;
+        last_hs.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+
+        std::vector<float> output_data_gold{-0.0847427,
+                                            0.0874114,
+                                            0.304256,
+                                            -0.0585745,
+                                            -0.0223018,
+                                            0.131113,
+                                            0.135643,
+                                            -0.0566208,
+                                            0.142701,
+                                            0.0342236,
+                                            -0.198664,
+                                            0.0702607};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // seq_len = 1
+    {
+        seq_len = 1;
+        migraphx::shape in_shape1{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
+        std::vector<float> input_data1{
+            -0.5516, 0.2391, -1.6951, -0.4313, -0.9730, -0.2005, 2.3930, -0.5221, -0.1331};
+        migraphx::program p;
+        auto* mm  = p.get_main_module();
+        auto seq  = mm->add_literal(migraphx::literal{in_shape1, input_data1});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            pph);
+        auto last_output = mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_output);
+        p.compile(migraphx::make_target("ref"));
+
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> hs_data;
+        hs_concat.visit([&](auto output) { hs_data.assign(output.begin(), output.end()); });
+
+        std::vector<float> hs_data_gold{0.079753,
+                                        -0.289854,
+                                        0.160043,
+                                        0.115056,
+                                        0.294074,
+                                        -0.0319677,
+                                        -0.0955337,
+                                        0.104168,
+                                        0.022618,
+                                        -0.121195,
+                                        -0.4065,
+                                        -0.252054};
+        EXPECT(migraphx::verify::verify_rms_range(hs_data, hs_data_gold));
+    }
+}
+
+TEST_CASE(lstm_reverse)
+{
+    std::size_t batch_size  = 3;
+    std::size_t seq_len     = 4;
+    std::size_t hidden_size = 4;
+    std::size_t input_size  = 3;
+    std::size_t num_dirct   = 1;
+    std::vector<float> w_data{
+        -0.2763, -0.4715, -0.3010, -0.2306, -0.2283, -0.2656, 0.2035,  0.3570,  -0.1499, 0.4390,
+        -0.1843, 0.2351,  0.3357,  0.1217,  0.1401,  0.3300,  -0.0429, 0.3266,  0.4834,  -0.3914,
+        -0.1480, 0.3734,  -0.0372, -0.1746, 0.0550,  0.4177,  -0.1332, 0.4391,  -0.3287, -0.4401,
+        0.1486,  0.1346,  0.1048,  -0.4361, 0.0886,  -0.3840, -0.2730, -0.1710, 0.3274,  0.0169,
+        -0.4462, 0.0729,  0.3983,  -0.0669, 0.0756,  0.4150,  -0.4684, -0.2522};
+
+    std::vector<float> r_data{
+        -0.4564, -0.4432, 0.1605,  0.4387,  0.0034,  0.4116,  0.2824,  0.4775,  -0.2729, -0.4707,
+        0.1363,  0.2218,  0.0559,  0.2828,  0.2093,  0.4687,  0.3794,  -0.1069, -0.3049, 0.1430,
+        -0.2506, 0.4644,  0.2755,  -0.3645, -0.3155, 0.1425,  0.2891,  0.1786,  -0.3274, 0.2365,
+        0.2522,  -0.4312, -0.0562, -0.2748, 0.0776,  -0.3154, 0.2851,  -0.3930, -0.1174, 0.4360,
+        0.2436,  0.0164,  -0.0680, 0.3403,  -0.2857, -0.0459, -0.2991, -0.2624, 0.4194,  -0.3291,
+        -0.4659, 0.3300,  0.0454,  0.4981,  -0.4706, -0.4584, 0.2596,  0.2871,  -0.3509, -0.1910,
+        0.3987,  -0.1687, -0.0032, -0.1038};
+
+    std::vector<float> bias_data{-0.0258, 0.0073,  -0.4780, -0.4101, -0.3556, -0.1017, 0.3632,
+                                 -0.1823, 0.1479,  0.1677,  -0.2603, 0.0381,  0.1575,  0.1896,
+                                 0.4755,  -0.4794, 0.2167,  -0.4474, -0.3139, 0.1018,  0.4470,
+                                 -0.4232, 0.3247,  -0.1636, -0.1582, -0.1703, 0.3920,  0.2055,
+                                 -0.4386, 0.4208,  0.0717,  0.3789};
+
+    std::vector<float> input_data{
+        -0.5516, 0.2391, -1.6951, -0.4313, -0.9730, -0.2005, 2.3930,  -0.5221, -0.1331,
+        -0.0910, 1.2122, -0.1952, 0.4661,  0.6494,  2.1332,  -1.0972, 0.9816,  0.1122,
+        0.3577,  1.3508, -0.5366, 1.7449,  0.5483,  -0.0701, -0.4100, -2.2344, 0.3685,
+        0.4583,  2.3794, 1.0372,  -0.8887, 0.7892,  -0.4012, -0.2818, -2.3374, 1.5310};
+
+    std::vector<float> ih_data{1.5289,
+                               1.0986,
+                               0.6091,
+                               1.6462,
+                               0.8720,
+                               0.5349,
+                               -0.1962,
+                               -1.7416,
+                               -0.9912,
+                               1.2831,
+                               1.0896,
+                               -0.6959};
+
+    std::vector<float> ic_data{-0.8323,
+                               0.3998,
+                               0.1831,
+                               0.5938,
+                               2.7096,
+                               -0.1790,
+                               0.0022,
+                               -0.8040,
+                               0.1578,
+                               0.0567,
+                               0.8069,
+                               -0.5141};
+
+    std::vector<float> pph_data{-0.8271,
+                                -0.5683,
+                                0.4562,
+                                -1.2545,
+                                1.2729,
+                                -0.4082,
+                                -0.4392,
+                                -0.9406,
+                                0.7794,
+                                1.8194,
+                                -0.5811,
+                                0.2166};
+
+    migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
+    migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, input_size}};
+    migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, hidden_size}};
+    migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 8 * hidden_size}};
+    migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
+    migraphx::shape ic_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
+    migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
+    float clip = 0.0f;
+    // reverse, concatenation of hidden states as program output
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
+
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+        mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            pph);
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        std::vector<float> output_data_gold{
+            -0.120174, 0.043157,  0.117138,   -0.222188, 0.789732,   0.128538,   0.20909,
+            0.0553812, -0.224905, 0.32421,    0.344048,  0.271694,   -0.175114,  -0.00543549,
+            0.178681,  -0.266999, 0.928866,   0.113685,  0.220626,   -0.0432316, -0.063456,
+            0.148524,  0.05108,   -0.0234895, -0.182201, -0.0232277, 0.235501,   -0.213485,
+            0.960938,  0.133565,  0.269741,   0.130438,  -0.0252804, 0.267356,   0.146353,
+            0.0789186, -0.185038, -0.026845,  0.177273,  -0.0774616, 0.946669,   0.0868676,
+            0.044508,  -0.373961, -0.0681467, 0.382748,  0.230211,   -0.161537};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // reverse, sequence lengths are the same, but less than max_seq_lens
+    {
+        migraphx::program p;
+        auto* mm      = p.get_main_module();
+        auto seq_orig = mm->add_literal(migraphx::literal{in_shape, input_data});
+
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
+
+        migraphx::shape pad_seq_s{migraphx::shape::float_type, {2, batch_size, input_size}};
+        std::vector<float> pad_data(pad_seq_s.elements(), 0.0f);
+        auto seq_p = mm->add_literal(migraphx::literal{pad_seq_s, pad_data});
+        auto seq = mm->add_instruction(migraphx::make_op("concat", {{"axis", 0}}), seq_orig, seq_p);
+        migraphx::shape seq_len_s{migraphx::shape::int32_type, {batch_size}};
+        std::vector<int32_t> len_data(batch_size, static_cast<int32_t>(seq_len));
+        auto sql = mm->add_literal(seq_len_s, len_data);
+        mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            sql,
+            ih,
+            ic,
+            pph);
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        std::vector<float> output_data_gold{
+            -0.120174, 0.043157,  0.117138,   -0.222188, 0.789732,   0.128538,   0.20909,
+            0.0553812, -0.224905, 0.32421,    0.344048,  0.271694,   -0.175114,  -0.00543549,
+            0.178681,  -0.266999, 0.928866,   0.113685,  0.220626,   -0.0432316, -0.063456,
+            0.148524,  0.05108,   -0.0234895, -0.182201, -0.0232277, 0.235501,   -0.213485,
+            0.960938,  0.133565,  0.269741,   0.130438,  -0.0252804, 0.267356,   0.146353,
+            0.0789186, -0.185038, -0.026845,  0.177273,  -0.0774616, 0.946669,   0.0868676,
+            0.044508,  -0.373961, -0.0681467, 0.382748,  0.230211,   -0.161537,  0.0,
+            0.0,       0.0,       0.0,        0.0,       0.0,        0.0,        0.0,
+            0.0,       0.0,       0.0,        0.0,       0.0,        0.0,        0.0,
+            0.0,       0.0,       0.0,        0.0,       0.0,        0.0,        0.0,
+            0.0,       0.0};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // variable sequence lengths
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
+
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
+
+        migraphx::shape seq_len_s{migraphx::shape::int32_type, {batch_size}};
+        std::vector<int32_t> len_data{3, 2, 1};
+        auto sql = mm->add_literal(seq_len_s, len_data);
+        mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            sql,
+            ih,
+            ic,
+            pph);
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        std::vector<float> output_data_gold{
+            -0.126517, 0.0359124,  0.107453, -0.0617278, 0.911307,  0.11468,   0.114449,
+            0.0196755, -0.102969,  0.295872, 0.515859,   0.246501,  -0.168327, 0.00023761,
+            0.167567,  -0.0621982, 0.96657,  0.0755112,  0.0620917, -0.264845, 0,
+            0,         0,          0,        -0.204545,  0.0146403, 0.210057,  0.0296268,
+            0,         0,          0,        0,          0,         0,         0,
+            0,         0,          0,        0,          0,         0,         0,
+            0,         0,          0,        0,          0,         0};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // reverse, 3 args, last cell output as program output
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto w   = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r   = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto hs  = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                  {"actv_func",
+                   migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                       migraphx::make_op("tanh"),
+                                                                       migraphx::make_op("tanh")})},
+                  {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                  {"clip", clip},
+                  {"input_forget", 0}}),
+            seq,
+            w,
+            r);
+        mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
+
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        std::vector<float> output_data_gold{-0.443077,
+                                            -0.325425,
+                                            -0.249367,
+                                            -0.270812,
+                                            0.122913,
+                                            0.118537,
+                                            0.0370199,
+                                            -0.0164687,
+                                            -0.00754759,
+                                            0.141613,
+                                            0.348002,
+                                            0.667298};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // reverse, 3 args, 0 actv function
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto w   = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r   = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto hs  = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                  {"actv_func", {}},
+                  {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                  {"clip", clip},
+                  {"input_forget", 0}}),
+            seq,
+            w,
+            r);
+        mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
+
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        std::vector<float> output_data_gold{-0.443077,
+                                            -0.325425,
+                                            -0.249367,
+                                            -0.270812,
+                                            0.122913,
+                                            0.118537,
+                                            0.0370199,
+                                            -0.0164687,
+                                            -0.00754759,
+                                            0.141613,
+                                            0.348002,
+                                            0.667298};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+}
+
+TEST_CASE(lstm_reverse_layout)
+{
+    std::size_t batch_size  = 3;
+    std::size_t seq_len     = 4;
+    std::size_t hidden_size = 4;
+    std::size_t input_size  = 3;
+    std::size_t num_dirct   = 1;
+    std::vector<float> w_data{
+        -0.2763, -0.4715, -0.3010, -0.2306, -0.2283, -0.2656, 0.2035,  0.3570,  -0.1499, 0.4390,
+        -0.1843, 0.2351,  0.3357,  0.1217,  0.1401,  0.3300,  -0.0429, 0.3266,  0.4834,  -0.3914,
+        -0.1480, 0.3734,  -0.0372, -0.1746, 0.0550,  0.4177,  -0.1332, 0.4391,  -0.3287, -0.4401,
+        0.1486,  0.1346,  0.1048,  -0.4361, 0.0886,  -0.3840, -0.2730, -0.1710, 0.3274,  0.0169,
+        -0.4462, 0.0729,  0.3983,  -0.0669, 0.0756,  0.4150,  -0.4684, -0.2522};
+
+    std::vector<float> r_data{
+        -0.4564, -0.4432, 0.1605,  0.4387,  0.0034,  0.4116,  0.2824,  0.4775,  -0.2729, -0.4707,
+        0.1363,  0.2218,  0.0559,  0.2828,  0.2093,  0.4687,  0.3794,  -0.1069, -0.3049, 0.1430,
+        -0.2506, 0.4644,  0.2755,  -0.3645, -0.3155, 0.1425,  0.2891,  0.1786,  -0.3274, 0.2365,
+        0.2522,  -0.4312, -0.0562, -0.2748, 0.0776,  -0.3154, 0.2851,  -0.3930, -0.1174, 0.4360,
+        0.2436,  0.0164,  -0.0680, 0.3403,  -0.2857, -0.0459, -0.2991, -0.2624, 0.4194,  -0.3291,
+        -0.4659, 0.3300,  0.0454,  0.4981,  -0.4706, -0.4584, 0.2596,  0.2871,  -0.3509, -0.1910,
+        0.3987,  -0.1687, -0.0032, -0.1038};
+
+    std::vector<float> bias_data{-0.0258, 0.0073,  -0.4780, -0.4101, -0.3556, -0.1017, 0.3632,
+                                 -0.1823, 0.1479,  0.1677,  -0.2603, 0.0381,  0.1575,  0.1896,
+                                 0.4755,  -0.4794, 0.2167,  -0.4474, -0.3139, 0.1018,  0.4470,
+                                 -0.4232, 0.3247,  -0.1636, -0.1582, -0.1703, 0.3920,  0.2055,
+                                 -0.4386, 0.4208,  0.0717,  0.3789};
 
     std::vector<float> input_data{
-        -0.5516, 0.2391, -1.6951, -0.4313, -0.9730, -0.2005, 2.3930,  -0.5221, -0.1331,
-        -0.0910, 1.2122, -0.1952, 0.4661,  0.6494,  2.1332,  -1.0972, 0.9816,  0.1122,
-        0.3577,  1.3508, -0.5366, 1.7449,  0.5483,  -0.0701, -0.4100, -2.2344, 0.3685,
-        0.4583,  2.3794, 1.0372,  -0.8887, 0.7892,  -0.4012, -0.2818, -2.3374, 1.5310};
+        -0.5516, 0.2391, -1.6951, -0.0910, 1.2122,  -0.1952, 0.3577,  1.3508,  -0.5366,
+        0.4583,  2.3794, 1.0372,  -0.4313, -0.9730, -0.2005, 0.4661,  0.6494,  2.1332,
+        1.7449,  0.5483, -0.0701, -0.8887, 0.7892,  -0.4012, 2.3930,  -0.5221, -0.1331,
+        -1.0972, 0.9816, 0.1122,  -0.4100, -2.2344, 0.3685,  -0.2818, -2.3374, 1.5310};
 
     std::vector<float> ih_data{1.5289,
                                1.0986,
@@ -3593,14 +4487,15 @@ TEST_CASE(lstm_reverse)
                                 -0.5811,
                                 0.2166};
 
-    migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
+    migraphx::shape in_shape{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
     migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, input_size}};
     migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, hidden_size}};
     migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 8 * hidden_size}};
-    migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
-    migraphx::shape ic_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
+    migraphx::shape ih_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+    migraphx::shape ic_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
     migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
     float clip = 0.0f;
+
     // reverse, concatenation of hidden states as program output
     {
         migraphx::program p;
@@ -3614,7 +4509,13 @@ TEST_CASE(lstm_reverse)
         auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
         auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
         auto und  = mm->add_instruction(migraphx::make_op("undefined"));
-        mm->add_instruction(
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
             migraphx::make_op(
                 "lstm",
                 {{"hidden_size", hidden_size},
@@ -3633,18 +4534,21 @@ TEST_CASE(lstm_reverse)
             ih,
             ic,
             pph);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
         p.compile(migraphx::make_target("ref"));
         auto hs_concat = p.eval({}).back();
         std::vector<float> output_data;
         hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
         std::vector<float> output_data_gold{
-            -0.120174, 0.043157,  0.117138,   -0.222188, 0.789732,   0.128538,   0.20909,
-            0.0553812, -0.224905, 0.32421,    0.344048,  0.271694,   -0.175114,  -0.00543549,
-            0.178681,  -0.266999, 0.928866,   0.113685,  0.220626,   -0.0432316, -0.063456,
-            0.148524,  0.05108,   -0.0234895, -0.182201, -0.0232277, 0.235501,   -0.213485,
-            0.960938,  0.133565,  0.269741,   0.130438,  -0.0252804, 0.267356,   0.146353,
-            0.0789186, -0.185038, -0.026845,  0.177273,  -0.0774616, 0.946669,   0.0868676,
-            0.044508,  -0.373961, -0.0681467, 0.382748,  0.230211,   -0.161537};
+            -0.120174, 0.043157,   0.117138,   -0.222188, -0.175114,  -0.00543549, 0.178681,
+            -0.266999, -0.182201,  -0.0232277, 0.235501,  -0.213485,  -0.185038,   -0.026845,
+            0.177273,  -0.0774616, 0.789732,   0.128538,  0.20909,    0.0553812,   0.928866,
+            0.113685,  0.220626,   -0.0432316, 0.960938,  0.133565,   0.269741,    0.130438,
+            0.946669,  0.0868676,  0.044508,   -0.373961, -0.224905,  0.32421,     0.344048,
+            0.271694,  -0.063456,  0.148524,   0.05108,   -0.0234895, -0.0252804,  0.267356,
+            0.146353,  0.0789186,  -0.0681467, 0.382748,  0.230211,   -0.161537};
+
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 
@@ -3661,14 +4565,20 @@ TEST_CASE(lstm_reverse)
         auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
         auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
 
-        migraphx::shape pad_seq_s{migraphx::shape::float_type, {2, batch_size, input_size}};
+        migraphx::shape pad_seq_s{migraphx::shape::float_type, {batch_size, 2, input_size}};
         std::vector<float> pad_data(pad_seq_s.elements(), 0.0f);
         auto seq_p = mm->add_literal(migraphx::literal{pad_seq_s, pad_data});
-        auto seq = mm->add_instruction(migraphx::make_op("concat", {{"axis", 0}}), seq_orig, seq_p);
+        auto seq = mm->add_instruction(migraphx::make_op("concat", {{"axis", 1}}), seq_orig, seq_p);
         migraphx::shape seq_len_s{migraphx::shape::int32_type, {batch_size}};
         std::vector<int32_t> len_data(batch_size, static_cast<int32_t>(seq_len));
         auto sql = mm->add_literal(seq_len_s, len_data);
-        mm->add_instruction(
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
             migraphx::make_op(
                 "lstm",
                 {{"hidden_size", hidden_size},
@@ -3687,22 +4597,26 @@ TEST_CASE(lstm_reverse)
             ih,
             ic,
             pph);
-        p.compile(migraphx::make_target("ref"));
-        auto hs_concat = p.eval({}).back();
-        std::vector<float> output_data;
-        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
-        std::vector<float> output_data_gold{
-            -0.120174, 0.043157,  0.117138,   -0.222188, 0.789732,   0.128538,   0.20909,
-            0.0553812, -0.224905, 0.32421,    0.344048,  0.271694,   -0.175114,  -0.00543549,
-            0.178681,  -0.266999, 0.928866,   0.113685,  0.220626,   -0.0432316, -0.063456,
-            0.148524,  0.05108,   -0.0234895, -0.182201, -0.0232277, 0.235501,   -0.213485,
-            0.960938,  0.133565,  0.269741,   0.130438,  -0.0252804, 0.267356,   0.146353,
-            0.0789186, -0.185038, -0.026845,  0.177273,  -0.0774616, 0.946669,   0.0868676,
-            0.044508,  -0.373961, -0.0681467, 0.382748,  0.230211,   -0.161537,  0.0,
-            0.0,       0.0,       0.0,        0.0,       0.0,        0.0,        0.0,
-            0.0,       0.0,       0.0,        0.0,       0.0,        0.0,        0.0,
-            0.0,       0.0,       0.0,        0.0,       0.0,        0.0,        0.0,
-            0.0,       0.0};
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+
+        std::vector<float> output_data_gold{
+            -0.120174,  0.043157,   0.117138,   -0.222188,  -0.175114,  -0.00543549, 0.178681,
+            -0.266999,  -0.182201,  -0.0232277, 0.235501,   -0.213485,  -0.185038,   -0.026845,
+            0.177273,   -0.0774616, 0.0,        0.0,        0.0,        0.0,         0.0,
+            0.0,        0.0,        0.0,        0.789732,   0.128538,   0.20909,     0.0553812,
+            0.928866,   0.113685,   0.220626,   -0.0432316, 0.960938,   0.133565,    0.269741,
+            0.130438,   0.946669,   0.0868676,  0.044508,   -0.373961,  0.0,         0.0,
+            0.0,        0.0,        0.0,        0.0,        0.0,        0.0,         -0.224905,
+            0.32421,    0.344048,   0.271694,   -0.063456,  0.148524,   0.05108,     -0.0234895,
+            -0.0252804, 0.267356,   0.146353,   0.0789186,  -0.0681467, 0.382748,    0.230211,
+            -0.161537,  0.0,        0.0,        0.0,        0.0,        0.0,         0.0,
+            0.0,        0.0};
+
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 
@@ -3722,7 +4636,13 @@ TEST_CASE(lstm_reverse)
         migraphx::shape seq_len_s{migraphx::shape::int32_type, {batch_size}};
         std::vector<int32_t> len_data{3, 2, 1};
         auto sql = mm->add_literal(seq_len_s, len_data);
-        mm->add_instruction(
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
             migraphx::make_op(
                 "lstm",
                 {{"hidden_size", hidden_size},
@@ -3741,18 +4661,22 @@ TEST_CASE(lstm_reverse)
             ih,
             ic,
             pph);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
         p.compile(migraphx::make_target("ref"));
         auto hs_concat = p.eval({}).back();
         std::vector<float> output_data;
         hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+
         std::vector<float> output_data_gold{
-            -0.126517, 0.0359124,  0.107453, -0.0617278, 0.911307,  0.11468,   0.114449,
-            0.0196755, -0.102969,  0.295872, 0.515859,   0.246501,  -0.168327, 0.00023761,
-            0.167567,  -0.0621982, 0.96657,  0.0755112,  0.0620917, -0.264845, 0,
-            0,         0,          0,        -0.204545,  0.0146403, 0.210057,  0.0296268,
-            0,         0,          0,        0,          0,         0,         0,
-            0,         0,          0,        0,          0,         0,         0,
-            0,         0,          0,        0,          0,         0};
+            -0.126517,  0.0359124, 0.107453,  -0.0617278, -0.168327, 0.00023761, 0.167567,
+            -0.0621982, -0.204545, 0.0146403, 0.210057,   0.0296268, 0,          0,
+            0,          0,         0.911307,  0.11468,    0.114449,  0.0196755,  0.96657,
+            0.0755112,  0.0620917, -0.264845, 0,          0,         0,          0,
+            0,          0,         0,         0,          -0.102969, 0.295872,   0.515859,
+            0.246501,   0,         0,         0,          0,         0,          0,
+            0,          0,         0,         0,          0,         0};
+
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 
@@ -3763,6 +4687,10 @@ TEST_CASE(lstm_reverse)
         auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
         auto w   = mm->add_literal(migraphx::literal{w_shape, w_data});
         auto r   = mm->add_literal(migraphx::literal{r_shape, r_data});
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+
         auto hs  = mm->add_instruction(
             migraphx::make_op(
                 "lstm",
@@ -3777,46 +4705,8 @@ TEST_CASE(lstm_reverse)
             seq,
             w,
             r);
-        mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
-
-        p.compile(migraphx::make_target("ref"));
-        auto hs_concat = p.eval({}).back();
-        std::vector<float> output_data;
-        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
-        std::vector<float> output_data_gold{-0.443077,
-                                            -0.325425,
-                                            -0.249367,
-                                            -0.270812,
-                                            0.122913,
-                                            0.118537,
-                                            0.0370199,
-                                            -0.0164687,
-                                            -0.00754759,
-                                            0.141613,
-                                            0.348002,
-                                            0.667298};
-        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
-    }
-
-    // reverse, 3 args, 0 actv function
-    {
-        migraphx::program p;
-        auto* mm = p.get_main_module();
-        auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
-        auto w   = mm->add_literal(migraphx::literal{w_shape, w_data});
-        auto r   = mm->add_literal(migraphx::literal{r_shape, r_data});
-        auto hs  = mm->add_instruction(
-            migraphx::make_op(
-                "lstm",
-                {{"hidden_size", hidden_size},
-                  {"actv_func", {}},
-                  {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
-                  {"clip", clip},
-                  {"input_forget", 0}}),
-            seq,
-            w,
-            r);
-        mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
+        auto cell_output = mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), cell_output);
 
         p.compile(migraphx::make_target("ref"));
         auto hs_concat = p.eval({}).back();
@@ -3900,19 +4790,214 @@ TEST_CASE(lstm_reverse_actv)
                                0.8069,
                                -0.5141};
 
-    std::vector<float> pph_data{-0.8271,
-                                -0.5683,
-                                0.4562,
-                                -1.2545,
-                                1.2729,
-                                -0.4082,
-                                -0.4392,
-                                -0.9406,
-                                0.7794,
-                                1.8194,
-                                -0.5811,
-                                0.2166};
+    std::vector<float> pph_data{-0.8271,
+                                -0.5683,
+                                0.4562,
+                                -1.2545,
+                                1.2729,
+                                -0.4082,
+                                -0.4392,
+                                -0.9406,
+                                0.7794,
+                                1.8194,
+                                -0.5811,
+                                0.2166};
+
+    migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
+    migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, input_size}};
+    migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, hidden_size}};
+    migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 8 * hidden_size}};
+    migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
+    migraphx::shape ic_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
+    migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
+    float clip = 0.0f;
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
+
+        auto w = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r = mm->add_literal(migraphx::literal{r_shape, r_data});
+        mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(
+                      std::vector<migraphx::operation>{migraphx::make_op("sigmoid")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r);
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        std::vector<float> output_data_gold{
+            0.246078, 0.199709, 0.303753, 0.301178, 0.264634, 0.304661, 0.349371, 0.288934,
+            0.405483, 0.445586, 0.515814, 0.473186, 0.301937, 0.264893, 0.254353, 0.269231,
+            0.359258, 0.400097, 0.288884, 0.247329, 0.276519, 0.264249, 0.1769,   0.23213,
+            0.310306, 0.262902, 0.276964, 0.295002, 0.373802, 0.366785, 0.419791, 0.393216,
+            0.262827, 0.371441, 0.369022, 0.298262, 0.334143, 0.309444, 0.174822, 0.251634,
+            0.244564, 0.214386, 0.185994, 0.226699, 0.28445,  0.376092, 0.338326, 0.259502};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // reverse, 3 args, 2 actv functions
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
+
+        auto w  = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r  = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{
+                      migraphx::make_op("tanh"), migraphx::make_op("sigmoid")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r);
+        mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), hs);
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        std::vector<float> output_data_gold{-0.132123,
+                                            -0.37531,
+                                            -0.12943,
+                                            -0.00798307,
+                                            -0.133882,
+                                            -0.0251383,
+                                            0.0486486,
+                                            -0.0220606,
+                                            0.292495,
+                                            0.233866,
+                                            0.48646,
+                                            0.481844};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // reverse, 3 args, seq_len = 1, concatenation of hidden states as program output
+    {
+        seq_len = 1;
+        std::vector<float> input_data1{
+            -0.5516, 0.2391, -1.6951, -0.4313, -0.9730, -0.2005, 2.3930, -0.5221, -0.1331};
+        migraphx::shape in_shape1{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
+
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        auto seq = mm->add_literal(migraphx::literal{in_shape1, input_data1});
+
+        auto w = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r = mm->add_literal(migraphx::literal{r_shape, r_data});
+        mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r);
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        std::vector<float> output_data_gold{-0.104351,
+                                            -0.0471426,
+                                            -0.0905753,
+                                            0.01506,
+                                            0.059797,
+                                            0.104239,
+                                            -0.0266768,
+                                            0.0727547,
+                                            -0.146298,
+                                            0.070535,
+                                            0.327809,
+                                            0.407388};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+}
+
+TEST_CASE(lstm_bidirectional)
+{
+    std::size_t batch_size  = 3;
+    std::size_t seq_len     = 4;
+    std::size_t hidden_size = 4;
+    std::size_t input_size  = 3;
+    std::size_t num_dirct   = 2;
+    std::vector<float> w_data{
+        0.1236,  -0.3942, 0.4149,  0.0795,  0.4934,  -0.2858, 0.2602,  -0.3098, 0.0567,  0.3344,
+        0.3607,  -0.0551, 0.4952,  0.3799,  0.0630,  -0.3532, 0.0023,  -0.0592, 0.4267,  0.2382,
+        -0.0784, -0.0032, -0.2476, -0.0206, -0.4963, 0.4837,  0.0827,  0.0123,  -0.1203, -0.0279,
+        -0.0049, 0.4721,  -0.3564, -0.1286, 0.4090,  -0.0504, 0.0575,  -0.2138, 0.1071,  0.1976,
+        -0.0758, 0.0139,  -0.0761, 0.3991,  -0.2965, -0.4845, -0.1496, 0.3285,  -0.2763, -0.4715,
+        -0.3010, -0.2306, -0.2283, -0.2656, 0.2035,  0.3570,  -0.1499, 0.4390,  -0.1843, 0.2351,
+        0.3357,  0.1217,  0.1401,  0.3300,  -0.0429, 0.3266,  0.4834,  -0.3914, -0.1480, 0.3734,
+        -0.0372, -0.1746, 0.0550,  0.4177,  -0.1332, 0.4391,  -0.3287, -0.4401, 0.1486,  0.1346,
+        0.1048,  -0.4361, 0.0886,  -0.3840, -0.2730, -0.1710, 0.3274,  0.0169,  -0.4462, 0.0729,
+        0.3983,  -0.0669, 0.0756,  0.4150,  -0.4684, -0.2522};
+
+    std::vector<float> r_data{
+        0.1237,  0.1229,  -0.0766, -0.1144, -0.1186, 0.2922,  0.2478,  0.3159,  -0.0522, 0.1685,
+        -0.4621, 0.1728,  0.0670,  -0.2458, -0.3835, -0.4589, -0.3109, 0.4908,  -0.0133, -0.1858,
+        -0.0590, -0.0347, -0.2353, -0.0671, -0.3812, -0.0004, -0.1432, 0.2406,  0.1033,  -0.0265,
+        -0.3902, 0.0755,  0.3733,  0.4383,  -0.3140, 0.2537,  -0.1818, -0.4127, 0.3506,  0.2562,
+        0.2926,  0.1620,  -0.4849, -0.4861, 0.4426,  0.2106,  -0.0005, 0.4418,  -0.2926, -0.3100,
+        0.1500,  -0.0362, -0.3801, -0.0065, -0.0631, 0.1277,  0.2315,  0.4087,  -0.3963, -0.4161,
+        -0.2169, -0.1344, 0.3468,  -0.2260, -0.4564, -0.4432, 0.1605,  0.4387,  0.0034,  0.4116,
+        0.2824,  0.4775,  -0.2729, -0.4707, 0.1363,  0.2218,  0.0559,  0.2828,  0.2093,  0.4687,
+        0.3794,  -0.1069, -0.3049, 0.1430,  -0.2506, 0.4644,  0.2755,  -0.3645, -0.3155, 0.1425,
+        0.2891,  0.1786,  -0.3274, 0.2365,  0.2522,  -0.4312, -0.0562, -0.2748, 0.0776,  -0.3154,
+        0.2851,  -0.3930, -0.1174, 0.4360,  0.2436,  0.0164,  -0.0680, 0.3403,  -0.2857, -0.0459,
+        -0.2991, -0.2624, 0.4194,  -0.3291, -0.4659, 0.3300,  0.0454,  0.4981,  -0.4706, -0.4584,
+        0.2596,  0.2871,  -0.3509, -0.1910, 0.3987,  -0.1687, -0.0032, -0.1038};
+
+    std::vector<float> bias_data{
+        0.0088,  0.1183,  0.1642,  -0.2631, -0.1330, -0.4008, 0.3881,  -0.4407, -0.2760, 0.1274,
+        -0.0083, -0.2885, 0.3949,  -0.0182, 0.4445,  0.3477,  0.2266,  0.3423,  -0.0674, -0.4067,
+        0.0807,  0.1109,  -0.2036, 0.1782,  -0.2467, -0.0730, -0.4216, 0.0316,  -0.3025, 0.3637,
+        -0.3181, -0.4655, -0.0258, 0.0073,  -0.4780, -0.4101, -0.3556, -0.1017, 0.3632,  -0.1823,
+        0.1479,  0.1677,  -0.2603, 0.0381,  0.1575,  0.1896,  0.4755,  -0.4794, 0.2167,  -0.4474,
+        -0.3139, 0.1018,  0.4470,  -0.4232, 0.3247,  -0.1636, -0.1582, -0.1703, 0.3920,  0.2055,
+        -0.4386, 0.4208,  0.0717,  0.3789};
+
+    std::vector<float> input_data{
+        -0.5516, 0.2391, -1.6951, -0.4313, -0.9730, -0.2005, 2.3930,  -0.5221, -0.1331,
+        -0.0910, 1.2122, -0.1952, 0.4661,  0.6494,  2.1332,  -1.0972, 0.9816,  0.1122,
+        0.3577,  1.3508, -0.5366, 1.7449,  0.5483,  -0.0701, -0.4100, -2.2344, 0.3685,
+        0.4583,  2.3794, 1.0372,  -0.8887, 0.7892,  -0.4012, -0.2818, -2.3374, 1.5310};
+
+    std::vector<float> ih_data{1.9104,  -1.9004, 0.3337,  0.5741, 0.5671, 0.0458,
+                               0.4514,  -0.8968, -0.9201, 0.1962, 0.5771, -0.5332,
+                               1.5289,  1.0986,  0.6091,  1.6462, 0.8720, 0.5349,
+                               -0.1962, -1.7416, -0.9912, 1.2831, 1.0896, -0.6959};
+
+    std::vector<float> ic_data{0.9569,  -0.5981, 1.1312,  1.0945,  1.1055,  -0.1212,
+                               -0.9097, 0.7831,  -1.6991, -1.9498, -1.2567, -0.4114,
+                               -0.8323, 0.3998,  0.1831,  0.5938,  2.7096,  -0.1790,
+                               0.0022,  -0.8040, 0.1578,  0.0567,  0.8069,  -0.5141};
 
+    std::vector<float> pph_data{1.84369764,  0.68413646, -0.44892886, -1.50904413, 0.3860796,
+                                -0.52186625, 1.08474445, -1.80867321, 1.32594529,  0.4336262,
+                                -0.83699064, 0.49162736, -0.8271,     -0.5683,     0.4562,
+                                -1.2545,     1.2729,     -0.4082,     -0.4392,     -0.9406,
+                                0.7794,      1.8194,     -0.5811,     0.2166};
+    float clip = 0.0f;
     migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
     migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, input_size}};
     migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, hidden_size}};
@@ -3920,95 +5005,200 @@ TEST_CASE(lstm_reverse_actv)
     migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
     migraphx::shape ic_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
     migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
-    float clip = 0.0f;
+
+    // concatenation of hidden states as program output
     {
         migraphx::program p;
-        auto* mm = p.get_main_module();
-        auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
-
-        auto w = mm->add_literal(migraphx::literal{w_shape, w_data});
-        auto r = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto* mm  = p.get_main_module();
+        auto seq  = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
         mm->add_instruction(
             migraphx::make_op(
                 "lstm",
                 {{"hidden_size", hidden_size},
                  {"actv_func",
-                  migraphx::to_value(
-                      std::vector<migraphx::operation>{migraphx::make_op("sigmoid")})},
-                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
                  {"clip", clip},
                  {"input_forget", 0}}),
             seq,
             w,
-            r);
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            pph);
         p.compile(migraphx::make_target("ref"));
         auto hs_concat = p.eval({}).back();
         std::vector<float> output_data;
         hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
         std::vector<float> output_data_gold{
-            0.246078, 0.199709, 0.303753, 0.301178, 0.264634, 0.304661, 0.349371, 0.288934,
-            0.405483, 0.445586, 0.515814, 0.473186, 0.301937, 0.264893, 0.254353, 0.269231,
-            0.359258, 0.400097, 0.288884, 0.247329, 0.276519, 0.264249, 0.1769,   0.23213,
-            0.310306, 0.262902, 0.276964, 0.295002, 0.373802, 0.366785, 0.419791, 0.393216,
-            0.262827, 0.371441, 0.369022, 0.298262, 0.334143, 0.309444, 0.174822, 0.251634,
-            0.244564, 0.214386, 0.185994, 0.226699, 0.28445,  0.376092, 0.338326, 0.259502};
+            0.079753,   -0.289854,  0.160043,    0.115056,   0.294074,   -0.0319677, -0.0955337,
+            0.104168,   0.022618,   -0.121195,   -0.4065,    -0.252054,  -0.120174,  0.043157,
+            0.117138,   -0.222188,  0.789732,    0.128538,   0.20909,    0.0553812,  -0.224905,
+            0.32421,    0.344048,   0.271694,    0.186991,   -0.0624168, 0.205513,   0.0836373,
+            0.421857,   0.0459771,  -0.144955,   0.0720673,  -0.0300906, -0.0890598, -0.135266,
+            -0.0413375, -0.175114,  -0.00543549, 0.178681,   -0.266999,  0.928866,   0.113685,
+            0.220626,   -0.0432316, -0.063456,   0.148524,   0.05108,    -0.0234895, 0.0459032,
+            0.0414126,  0.272303,   0.0393149,   0.218258,   0.0944405,  0.0431211,  -0.132394,
+            0.103489,   0.0142918,  -0.123408,   0.0401075,  -0.182201,  -0.0232277, 0.235501,
+            -0.213485,  0.960938,   0.133565,    0.269741,   0.130438,   -0.0252804, 0.267356,
+            0.146353,   0.0789186,  -0.058052,   0.0795391,  0.266617,   -0.0128746, 0.0309878,
+            0.0971544,  0.149294,   -0.0492549,  0.187761,   0.0501726,  -0.121584,  0.0606723,
+            -0.185038,  -0.026845,  0.177273,    -0.0774616, 0.946669,   0.0868676,  0.044508,
+            -0.373961,  -0.0681467, 0.382748,    0.230211,   -0.161537};
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 
-    // reverse, 3 args, 2 actv functions
+    // last hidden state as program output
+    {
+        migraphx::program p;
+        auto* mm  = p.get_main_module();
+        auto seq  = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+        auto hs   = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                   {"actv_func",
+                    migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                        migraphx::make_op("tanh"),
+                                                                        migraphx::make_op("tanh")})},
+                   {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
+                   {"clip", clip},
+                   {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            pph);
+        mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), hs);
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        std::vector<float> output_data_gold{
+            -0.058052, 0.0795391, 0.266617,  -0.0128746, 0.0309878, 0.0971544, 0.149294, -0.0492549,
+            0.187761,  0.0501726, -0.121584, 0.0606723,  -0.120174, 0.043157,  0.117138, -0.222188,
+            0.789732,  0.128538,  0.20909,   0.0553812,  -0.224905, 0.32421,   0.344048, 0.271694};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // last cell output as program output
+    {
+        migraphx::program p;
+        auto* mm  = p.get_main_module();
+        auto seq  = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+        auto hs   = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                   {"actv_func",
+                    migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                        migraphx::make_op("tanh"),
+                                                                        migraphx::make_op("tanh")})},
+                   {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
+                   {"clip", clip},
+                   {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            pph);
+        mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
+        p.compile(migraphx::make_target("ref"));
+        auto hs_concat = p.eval({}).back();
+        std::vector<float> output_data;
+        hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        std::vector<float> output_data_gold{
+            -0.077353, 0.245616, 0.361023,  -0.0443759, 0.0685243, 0.20465,  0.277867, -0.112934,
+            0.67312,   0.120508, -0.726968, 0.113845,   -0.889294, 0.182463, 0.186512, -0.402334,
+            1.48161,   0.524116, 0.347113,  0.181813,   -0.434265, 0.747833, 0.416053, 0.558713};
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+    }
+
+    // 3 args, concatenation of hidden states as program output
     {
         migraphx::program p;
         auto* mm = p.get_main_module();
         auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
-
-        auto w  = mm->add_literal(migraphx::literal{w_shape, w_data});
-        auto r  = mm->add_literal(migraphx::literal{r_shape, r_data});
-        auto hs = mm->add_instruction(
+        auto w   = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r   = mm->add_literal(migraphx::literal{r_shape, r_data});
+        mm->add_instruction(
             migraphx::make_op(
                 "lstm",
                 {{"hidden_size", hidden_size},
                  {"actv_func",
-                  migraphx::to_value(std::vector<migraphx::operation>{
-                      migraphx::make_op("tanh"), migraphx::make_op("sigmoid")})},
-                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
                  {"clip", clip},
                  {"input_forget", 0}}),
             seq,
             w,
             r);
-        mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), hs);
         p.compile(migraphx::make_target("ref"));
         auto hs_concat = p.eval({}).back();
         std::vector<float> output_data;
         hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
-        std::vector<float> output_data_gold{-0.132123,
-                                            -0.37531,
-                                            -0.12943,
-                                            -0.00798307,
-                                            -0.133882,
-                                            -0.0251383,
-                                            0.0486486,
-                                            -0.0220606,
-                                            0.292495,
-                                            0.233866,
-                                            0.48646,
-                                            0.481844};
+        std::vector<float> output_data_gold{
+            -0.0327039, -0.0543852, 0.114378,  -0.0768855, 0.0319021,   -0.00298698, -0.0623361,
+            0.0598866,  0.101585,   0.0687269, -0.161725,  -0.25617,    -0.162851,   -0.102647,
+            -0.113827,  -0.142818,  0.0513685, 0.0547876,  0.0201981,   -0.00808453, -0.00520328,
+            0.0945081,  0.264123,   0.410805,  -0.0786602, -0.0613048,  0.179592,    -0.071286,
+            0.074206,   0.0124086,  -0.139544, 0.108016,   -0.00973633, -0.0552699,  0.0252681,
+            -0.0562072, -0.123496,  -0.153616, -0.032874,  -0.195349,   0.0192675,   -0.108636,
+            0.098927,   -0.140733,  0.162602,  0.0143099,  -0.0455534,  0.0151574,   -0.102509,
+            -0.0372696, 0.252296,   -0.144544, 0.00496085, 0.0662588,   -0.048577,   -0.187329,
+            0.0855831,  -0.0171894, -0.140202, 0.0828391,  -0.1073,     -0.150145,   0.015065,
+            -0.192699,  -0.112764,  -0.120496, 0.155754,   0.148256,    0.208491,    0.348432,
+            0.0291103,  0.230275,   -0.165194, -0.0372928, 0.273786,    -0.100877,   -0.0458544,
+            -0.0401315, 0.0737483,  -0.064505, 0.136898,   0.00160891,  -0.184812,   0.147774,
+            -0.021205,  -0.125423,  0.0206439, -0.187097,  -0.0051453,  -0.0767618,  -0.0735348,
+            -0.0826436, 0.214159,   0.262295,  0.0247127,  0.14472};
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 
-    // reverse, 3 args, seq_len = 1, concatenation of hidden states as program output
+    // sequence length is 1, contenation of hidden state as program output
     {
-        seq_len = 1;
-        std::vector<float> input_data1{
-            -0.5516, 0.2391, -1.6951, -0.4313, -0.9730, -0.2005, 2.3930, -0.5221, -0.1331};
-        migraphx::shape in_shape1{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
-
         migraphx::program p;
         auto* mm = p.get_main_module();
+        seq_len  = 1;
+        migraphx::shape in_shape1{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
+        std::vector<float> input_data1{
+            -0.5516, 0.2391, -1.6951, -0.4313, -0.9730, -0.2005, 2.3930, -0.5221, -0.1331};
         auto seq = mm->add_literal(migraphx::literal{in_shape1, input_data1});
-
-        auto w = mm->add_literal(migraphx::literal{w_shape, w_data});
-        auto r = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto w   = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r   = mm->add_literal(migraphx::literal{r_shape, r_data});
         mm->add_instruction(
             migraphx::make_op(
                 "lstm",
@@ -4017,7 +5207,7 @@ TEST_CASE(lstm_reverse_actv)
                   migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
                                                                       migraphx::make_op("tanh"),
                                                                       migraphx::make_op("tanh")})},
-                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
                  {"clip", clip},
                  {"input_forget", 0}}),
             seq,
@@ -4027,23 +5217,16 @@ TEST_CASE(lstm_reverse_actv)
         auto hs_concat = p.eval({}).back();
         std::vector<float> output_data;
         hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
-        std::vector<float> output_data_gold{-0.104351,
-                                            -0.0471426,
-                                            -0.0905753,
-                                            0.01506,
-                                            0.059797,
-                                            0.104239,
-                                            -0.0266768,
-                                            0.0727547,
-                                            -0.146298,
-                                            0.070535,
-                                            0.327809,
-                                            0.407388};
+        std::vector<float> output_data_gold{
+            -0.0327039, -0.0543852, 0.114378,   -0.0768855, 0.0319021, -0.00298698,
+            -0.0623361, 0.0598866,  0.101585,   0.0687269,  -0.161725, -0.25617,
+            -0.104351,  -0.0471426, -0.0905753, 0.01506,    0.059797,  0.104239,
+            -0.0266768, 0.0727547,  -0.146298,  0.070535,   0.327809,  0.407388};
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 }
 
-TEST_CASE(lstm_bidirectional)
+TEST_CASE(lstm_bidirectional_layout)
 {
     std::size_t batch_size  = 3;
     std::size_t seq_len     = 4;
@@ -4087,20 +5270,20 @@ TEST_CASE(lstm_bidirectional)
         -0.4386, 0.4208,  0.0717,  0.3789};
 
     std::vector<float> input_data{
-        -0.5516, 0.2391, -1.6951, -0.4313, -0.9730, -0.2005, 2.3930,  -0.5221, -0.1331,
-        -0.0910, 1.2122, -0.1952, 0.4661,  0.6494,  2.1332,  -1.0972, 0.9816,  0.1122,
-        0.3577,  1.3508, -0.5366, 1.7449,  0.5483,  -0.0701, -0.4100, -2.2344, 0.3685,
-        0.4583,  2.3794, 1.0372,  -0.8887, 0.7892,  -0.4012, -0.2818, -2.3374, 1.5310};
-
-    std::vector<float> ih_data{1.9104,  -1.9004, 0.3337,  0.5741, 0.5671, 0.0458,
-                               0.4514,  -0.8968, -0.9201, 0.1962, 0.5771, -0.5332,
-                               1.5289,  1.0986,  0.6091,  1.6462, 0.8720, 0.5349,
-                               -0.1962, -1.7416, -0.9912, 1.2831, 1.0896, -0.6959};
-
-    std::vector<float> ic_data{0.9569,  -0.5981, 1.1312,  1.0945,  1.1055,  -0.1212,
-                               -0.9097, 0.7831,  -1.6991, -1.9498, -1.2567, -0.4114,
-                               -0.8323, 0.3998,  0.1831,  0.5938,  2.7096,  -0.1790,
-                               0.0022,  -0.8040, 0.1578,  0.0567,  0.8069,  -0.5141};
+        -0.5516, 0.2391, -1.6951, -0.0910, 1.2122,  -0.1952, 0.3577,  1.3508,  -0.5366,
+        0.4583,  2.3794, 1.0372,  -0.4313, -0.9730, -0.2005, 0.4661,  0.6494,  2.1332,
+        1.7449,  0.5483, -0.0701, -0.8887, 0.7892,  -0.4012, 2.3930,  -0.5221, -0.1331,
+        -1.0972, 0.9816, 0.1122,  -0.4100, -2.2344, 0.3685,  -0.2818, -2.3374, 1.5310};
+
+    std::vector<float> ih_data{1.9104, -1.9004, 0.3337,  0.5741,  1.5289,  1.0986,
+                               0.6091, 1.6462,  0.5671,  0.0458,  0.4514,  -0.8968,
+                               0.8720, 0.5349,  -0.1962, -1.7416, -0.9201, 0.1962,
+                               0.5771, -0.5332, -0.9912, 1.2831,  1.0896,  -0.6959};
+
+    std::vector<float> ic_data{0.9569,  -0.5981, 1.1312, 1.0945,  -0.8323, 0.3998,
+                               0.1831,  0.5938,  1.1055, -0.1212, -0.9097, 0.7831,
+                               2.7096,  -0.1790, 0.0022, -0.8040, -1.6991, -1.9498,
+                               -1.2567, -0.4114, 0.1578, 0.0567,  0.8069,  -0.5141};
 
     std::vector<float> pph_data{1.84369764,  0.68413646, -0.44892886, -1.50904413, 0.3860796,
                                 -0.52186625, 1.08474445, -1.80867321, 1.32594529,  0.4336262,
@@ -4108,12 +5291,12 @@ TEST_CASE(lstm_bidirectional)
                                 -1.2545,     1.2729,     -0.4082,     -0.4392,     -0.9406,
                                 0.7794,      1.8194,     -0.5811,     0.2166};
     float clip = 0.0f;
-    migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
+    migraphx::shape in_shape{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
     migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, input_size}};
     migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, hidden_size}};
     migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 8 * hidden_size}};
-    migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
-    migraphx::shape ic_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
+    migraphx::shape ih_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+    migraphx::shape ic_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
     migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
 
     // concatenation of hidden states as program output
@@ -4128,7 +5311,13 @@ TEST_CASE(lstm_bidirectional)
         auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
         auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
         auto und  = mm->add_instruction(migraphx::make_op("undefined"));
-        mm->add_instruction(
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
             migraphx::make_op(
                 "lstm",
                 {{"hidden_size", hidden_size},
@@ -4147,25 +5336,29 @@ TEST_CASE(lstm_bidirectional)
             ih,
             ic,
             pph);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
         p.compile(migraphx::make_target("ref"));
         auto hs_concat = p.eval({}).back();
         std::vector<float> output_data;
         hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+
         std::vector<float> output_data_gold{
-            0.079753,   -0.289854,  0.160043,    0.115056,   0.294074,   -0.0319677, -0.0955337,
-            0.104168,   0.022618,   -0.121195,   -0.4065,    -0.252054,  -0.120174,  0.043157,
-            0.117138,   -0.222188,  0.789732,    0.128538,   0.20909,    0.0553812,  -0.224905,
-            0.32421,    0.344048,   0.271694,    0.186991,   -0.0624168, 0.205513,   0.0836373,
-            0.421857,   0.0459771,  -0.144955,   0.0720673,  -0.0300906, -0.0890598, -0.135266,
-            -0.0413375, -0.175114,  -0.00543549, 0.178681,   -0.266999,  0.928866,   0.113685,
-            0.220626,   -0.0432316, -0.063456,   0.148524,   0.05108,    -0.0234895, 0.0459032,
-            0.0414126,  0.272303,   0.0393149,   0.218258,   0.0944405,  0.0431211,  -0.132394,
-            0.103489,   0.0142918,  -0.123408,   0.0401075,  -0.182201,  -0.0232277, 0.235501,
-            -0.213485,  0.960938,   0.133565,    0.269741,   0.130438,   -0.0252804, 0.267356,
-            0.146353,   0.0789186,  -0.058052,   0.0795391,  0.266617,   -0.0128746, 0.0309878,
-            0.0971544,  0.149294,   -0.0492549,  0.187761,   0.0501726,  -0.121584,  0.0606723,
-            -0.185038,  -0.026845,  0.177273,    -0.0774616, 0.946669,   0.0868676,  0.044508,
-            -0.373961,  -0.0681467, 0.382748,    0.230211,   -0.161537};
+            0.079753,   -0.289854,  0.160043,   0.115056,   -0.120174, 0.043157,   0.117138,
+            -0.222188,  0.186991,   -0.0624168, 0.205513,   0.0836373, -0.175114,  -0.00543549,
+            0.178681,   -0.266999,  0.0459032,  0.0414126,  0.272303,  0.0393149,  -0.182201,
+            -0.0232277, 0.235501,   -0.213485,  -0.058052,  0.0795391, 0.266617,   -0.0128746,
+            -0.185038,  -0.026845,  0.177273,   -0.0774616, 0.294074,  -0.0319677, -0.0955337,
+            0.104168,   0.789732,   0.128538,   0.20909,    0.0553812, 0.421857,   0.0459771,
+            -0.144955,  0.0720673,  0.928866,   0.113685,   0.220626,  -0.0432316, 0.218258,
+            0.0944405,  0.0431211,  -0.132394,  0.960938,   0.133565,  0.269741,   0.130438,
+            0.0309878,  0.0971544,  0.149294,   -0.0492549, 0.946669,  0.0868676,  0.044508,
+            -0.373961,  0.022618,   -0.121195,  -0.4065,    -0.252054, -0.224905,  0.32421,
+            0.344048,   0.271694,   -0.0300906, -0.0890598, -0.135266, -0.0413375, -0.063456,
+            0.148524,   0.05108,    -0.0234895, 0.103489,   0.0142918, -0.123408,  0.0401075,
+            -0.0252804, 0.267356,   0.146353,   0.0789186,  0.187761,  0.0501726,  -0.121584,
+            0.0606723,  -0.0681467, 0.382748,   0.230211,   -0.161537};
+
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 
@@ -4181,6 +5374,12 @@ TEST_CASE(lstm_bidirectional)
         auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
         auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
         auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
         auto hs   = mm->add_instruction(
             migraphx::make_op(
                 "lstm",
@@ -4200,15 +5399,17 @@ TEST_CASE(lstm_bidirectional)
             ih,
             ic,
             pph);
-        mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), hs);
+        auto last_output = mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_output);
         p.compile(migraphx::make_target("ref"));
         auto hs_concat = p.eval({}).back();
         std::vector<float> output_data;
         hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
         std::vector<float> output_data_gold{
-            -0.058052, 0.0795391, 0.266617,  -0.0128746, 0.0309878, 0.0971544, 0.149294, -0.0492549,
-            0.187761,  0.0501726, -0.121584, 0.0606723,  -0.120174, 0.043157,  0.117138, -0.222188,
-            0.789732,  0.128538,  0.20909,   0.0553812,  -0.224905, 0.32421,   0.344048, 0.271694};
+            -0.058052, 0.0795391, 0.266617,  -0.0128746, -0.120174, 0.043157, 0.117138, -0.222188,
+            0.0309878, 0.0971544, 0.149294,  -0.0492549, 0.789732,  0.128538, 0.20909,  0.0553812,
+            0.187761,  0.0501726, -0.121584, 0.0606723,  -0.224905, 0.32421,  0.344048, 0.271694};
+
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 
@@ -4224,6 +5425,12 @@ TEST_CASE(lstm_bidirectional)
         auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
         auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
         auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
         auto hs   = mm->add_instruction(
             migraphx::make_op(
                 "lstm",
@@ -4243,15 +5450,17 @@ TEST_CASE(lstm_bidirectional)
             ih,
             ic,
             pph);
-        mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
+        auto cell_output = mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), cell_output);
         p.compile(migraphx::make_target("ref"));
         auto hs_concat = p.eval({}).back();
         std::vector<float> output_data;
         hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
         std::vector<float> output_data_gold{
-            -0.077353, 0.245616, 0.361023,  -0.0443759, 0.0685243, 0.20465,  0.277867, -0.112934,
-            0.67312,   0.120508, -0.726968, 0.113845,   -0.889294, 0.182463, 0.186512, -0.402334,
-            1.48161,   0.524116, 0.347113,  0.181813,   -0.434265, 0.747833, 0.416053, 0.558713};
+            -0.077353, 0.245616, 0.361023,  -0.0443759, -0.889294, 0.182463, 0.186512, -0.402334,
+            0.0685243, 0.20465,  0.277867,  -0.112934,  1.48161,   0.524116, 0.347113, 0.181813,
+            0.67312,   0.120508, -0.726968, 0.113845,   -0.434265, 0.747833, 0.416053, 0.558713};
+
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 
@@ -4262,7 +5471,11 @@ TEST_CASE(lstm_bidirectional)
         auto seq = mm->add_literal(migraphx::literal{in_shape, input_data});
         auto w   = mm->add_literal(migraphx::literal{w_shape, w_data});
         auto r   = mm->add_literal(migraphx::literal{r_shape, r_data});
-        mm->add_instruction(
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+
+        auto hs = mm->add_instruction(
             migraphx::make_op(
                 "lstm",
                 {{"hidden_size", hidden_size},
@@ -4276,25 +5489,28 @@ TEST_CASE(lstm_bidirectional)
             seq,
             w,
             r);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
         p.compile(migraphx::make_target("ref"));
         auto hs_concat = p.eval({}).back();
         std::vector<float> output_data;
         hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+
         std::vector<float> output_data_gold{
-            -0.0327039, -0.0543852, 0.114378,  -0.0768855, 0.0319021,   -0.00298698, -0.0623361,
-            0.0598866,  0.101585,   0.0687269, -0.161725,  -0.25617,    -0.162851,   -0.102647,
-            -0.113827,  -0.142818,  0.0513685, 0.0547876,  0.0201981,   -0.00808453, -0.00520328,
-            0.0945081,  0.264123,   0.410805,  -0.0786602, -0.0613048,  0.179592,    -0.071286,
-            0.074206,   0.0124086,  -0.139544, 0.108016,   -0.00973633, -0.0552699,  0.0252681,
-            -0.0562072, -0.123496,  -0.153616, -0.032874,  -0.195349,   0.0192675,   -0.108636,
-            0.098927,   -0.140733,  0.162602,  0.0143099,  -0.0455534,  0.0151574,   -0.102509,
-            -0.0372696, 0.252296,   -0.144544, 0.00496085, 0.0662588,   -0.048577,   -0.187329,
-            0.0855831,  -0.0171894, -0.140202, 0.0828391,  -0.1073,     -0.150145,   0.015065,
-            -0.192699,  -0.112764,  -0.120496, 0.155754,   0.148256,    0.208491,    0.348432,
-            0.0291103,  0.230275,   -0.165194, -0.0372928, 0.273786,    -0.100877,   -0.0458544,
-            -0.0401315, 0.0737483,  -0.064505, 0.136898,   0.00160891,  -0.184812,   0.147774,
-            -0.021205,  -0.125423,  0.0206439, -0.187097,  -0.0051453,  -0.0767618,  -0.0735348,
-            -0.0826436, 0.214159,   0.262295,  0.0247127,  0.14472};
+            -0.0327039, -0.0543852, 0.114378,    -0.0768855, -0.162851,   -0.102647,   -0.113827,
+            -0.142818,  -0.0786602, -0.0613048,  0.179592,   -0.071286,   -0.123496,   -0.153616,
+            -0.032874,  -0.195349,  -0.102509,   -0.0372696, 0.252296,    -0.144544,   -0.1073,
+            -0.150145,  0.015065,   -0.192699,   -0.165194,  -0.0372928,  0.273786,    -0.100877,
+            -0.021205,  -0.125423,  0.0206439,   -0.187097,  0.0319021,   -0.00298698, -0.0623361,
+            0.0598866,  0.0513685,  0.0547876,   0.0201981,  -0.00808453, 0.074206,    0.0124086,
+            -0.139544,  0.108016,   0.0192675,   -0.108636,  0.098927,    -0.140733,   0.00496085,
+            0.0662588,  -0.048577,  -0.187329,   -0.112764,  -0.120496,   0.155754,    0.148256,
+            -0.0458544, -0.0401315, 0.0737483,   -0.064505,  -0.0051453,  -0.0767618,  -0.0735348,
+            -0.0826436, 0.101585,   0.0687269,   -0.161725,  -0.25617,    -0.00520328, 0.0945081,
+            0.264123,   0.410805,   -0.00973633, -0.0552699, 0.0252681,   -0.0562072,  0.162602,
+            0.0143099,  -0.0455534, 0.0151574,   0.0855831,  -0.0171894,  -0.140202,   0.0828391,
+            0.208491,   0.348432,   0.0291103,   0.230275,   0.136898,    0.00160891,  -0.184812,
+            0.147774,   0.214159,   0.262295,    0.0247127,  0.14472};
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 
@@ -4303,13 +5519,17 @@ TEST_CASE(lstm_bidirectional)
         migraphx::program p;
         auto* mm = p.get_main_module();
         seq_len  = 1;
-        migraphx::shape in_shape1{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
+        migraphx::shape in_shape1{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
         std::vector<float> input_data1{
             -0.5516, 0.2391, -1.6951, -0.4313, -0.9730, -0.2005, 2.3930, -0.5221, -0.1331};
         auto seq = mm->add_literal(migraphx::literal{in_shape1, input_data1});
         auto w   = mm->add_literal(migraphx::literal{w_shape, w_data});
         auto r   = mm->add_literal(migraphx::literal{r_shape, r_data});
-        mm->add_instruction(
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+
+        auto hs = mm->add_instruction(
             migraphx::make_op(
                 "lstm",
                 {{"hidden_size", hidden_size},
@@ -4323,15 +5543,19 @@ TEST_CASE(lstm_bidirectional)
             seq,
             w,
             r);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
         p.compile(migraphx::make_target("ref"));
         auto hs_concat = p.eval({}).back();
         std::vector<float> output_data;
         hs_concat.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+
         std::vector<float> output_data_gold{
-            -0.0327039, -0.0543852, 0.114378,   -0.0768855, 0.0319021, -0.00298698,
-            -0.0623361, 0.0598866,  0.101585,   0.0687269,  -0.161725, -0.25617,
-            -0.104351,  -0.0471426, -0.0905753, 0.01506,    0.059797,  0.104239,
-            -0.0266768, 0.0727547,  -0.146298,  0.070535,   0.327809,  0.407388};
+            -0.0327039, -0.0543852, 0.114378,   -0.0768855,  -0.104351,  -0.0471426,
+            -0.0905753, 0.01506,    0.0319021,  -0.00298698, -0.0623361, 0.0598866,
+            0.059797,   0.104239,   -0.0266768, 0.0727547,   0.101585,   0.0687269,
+            -0.161725,  -0.25617,   -0.146298,  0.070535,    0.327809,   0.407388};
+
         EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
     }
 }
@@ -4577,6 +5801,275 @@ TEST_CASE(lstm_bidirectional_var_seq_lens)
     }
 }
 
+TEST_CASE(lstm_bidirectional_var_seq_lens_layout)
+{
+    std::size_t batch_size  = 3;
+    std::size_t seq_len     = 4;
+    std::size_t hidden_size = 4;
+    std::size_t input_size  = 3;
+    std::size_t num_dirct   = 2;
+    std::vector<float> w_data{
+        0.1236,  -0.3942, 0.4149,  0.0795,  0.4934,  -0.2858, 0.2602,  -0.3098, 0.0567,  0.3344,
+        0.3607,  -0.0551, 0.4952,  0.3799,  0.0630,  -0.3532, 0.0023,  -0.0592, 0.4267,  0.2382,
+        -0.0784, -0.0032, -0.2476, -0.0206, -0.4963, 0.4837,  0.0827,  0.0123,  -0.1203, -0.0279,
+        -0.0049, 0.4721,  -0.3564, -0.1286, 0.4090,  -0.0504, 0.0575,  -0.2138, 0.1071,  0.1976,
+        -0.0758, 0.0139,  -0.0761, 0.3991,  -0.2965, -0.4845, -0.1496, 0.3285,  -0.2763, -0.4715,
+        -0.3010, -0.2306, -0.2283, -0.2656, 0.2035,  0.3570,  -0.1499, 0.4390,  -0.1843, 0.2351,
+        0.3357,  0.1217,  0.1401,  0.3300,  -0.0429, 0.3266,  0.4834,  -0.3914, -0.1480, 0.3734,
+        -0.0372, -0.1746, 0.0550,  0.4177,  -0.1332, 0.4391,  -0.3287, -0.4401, 0.1486,  0.1346,
+        0.1048,  -0.4361, 0.0886,  -0.3840, -0.2730, -0.1710, 0.3274,  0.0169,  -0.4462, 0.0729,
+        0.3983,  -0.0669, 0.0756,  0.4150,  -0.4684, -0.2522};
+
+    std::vector<float> r_data{
+        0.1237,  0.1229,  -0.0766, -0.1144, -0.1186, 0.2922,  0.2478,  0.3159,  -0.0522, 0.1685,
+        -0.4621, 0.1728,  0.0670,  -0.2458, -0.3835, -0.4589, -0.3109, 0.4908,  -0.0133, -0.1858,
+        -0.0590, -0.0347, -0.2353, -0.0671, -0.3812, -0.0004, -0.1432, 0.2406,  0.1033,  -0.0265,
+        -0.3902, 0.0755,  0.3733,  0.4383,  -0.3140, 0.2537,  -0.1818, -0.4127, 0.3506,  0.2562,
+        0.2926,  0.1620,  -0.4849, -0.4861, 0.4426,  0.2106,  -0.0005, 0.4418,  -0.2926, -0.3100,
+        0.1500,  -0.0362, -0.3801, -0.0065, -0.0631, 0.1277,  0.2315,  0.4087,  -0.3963, -0.4161,
+        -0.2169, -0.1344, 0.3468,  -0.2260, -0.4564, -0.4432, 0.1605,  0.4387,  0.0034,  0.4116,
+        0.2824,  0.4775,  -0.2729, -0.4707, 0.1363,  0.2218,  0.0559,  0.2828,  0.2093,  0.4687,
+        0.3794,  -0.1069, -0.3049, 0.1430,  -0.2506, 0.4644,  0.2755,  -0.3645, -0.3155, 0.1425,
+        0.2891,  0.1786,  -0.3274, 0.2365,  0.2522,  -0.4312, -0.0562, -0.2748, 0.0776,  -0.3154,
+        0.2851,  -0.3930, -0.1174, 0.4360,  0.2436,  0.0164,  -0.0680, 0.3403,  -0.2857, -0.0459,
+        -0.2991, -0.2624, 0.4194,  -0.3291, -0.4659, 0.3300,  0.0454,  0.4981,  -0.4706, -0.4584,
+        0.2596,  0.2871,  -0.3509, -0.1910, 0.3987,  -0.1687, -0.0032, -0.1038};
+
+    std::vector<float> bias_data{
+        0.0088,  0.1183,  0.1642,  -0.2631, -0.1330, -0.4008, 0.3881,  -0.4407, -0.2760, 0.1274,
+        -0.0083, -0.2885, 0.3949,  -0.0182, 0.4445,  0.3477,  0.2266,  0.3423,  -0.0674, -0.4067,
+        0.0807,  0.1109,  -0.2036, 0.1782,  -0.2467, -0.0730, -0.4216, 0.0316,  -0.3025, 0.3637,
+        -0.3181, -0.4655, -0.0258, 0.0073,  -0.4780, -0.4101, -0.3556, -0.1017, 0.3632,  -0.1823,
+        0.1479,  0.1677,  -0.2603, 0.0381,  0.1575,  0.1896,  0.4755,  -0.4794, 0.2167,  -0.4474,
+        -0.3139, 0.1018,  0.4470,  -0.4232, 0.3247,  -0.1636, -0.1582, -0.1703, 0.3920,  0.2055,
+        -0.4386, 0.4208,  0.0717,  0.3789};
+
+    std::vector<float> input_data{
+        -0.5516, 0.2391, -1.6951, -0.0910, 1.2122,  -0.1952, 0.3577,  1.3508,  -0.5366,
+        0.4583,  2.3794, 1.0372,  -0.4313, -0.9730, -0.2005, 0.4661,  0.6494,  2.1332,
+        1.7449,  0.5483, -0.0701, -0.8887, 0.7892,  -0.4012, 2.3930,  -0.5221, -0.1331,
+        -1.0972, 0.9816, 0.1122,  -0.4100, -2.2344, 0.3685,  -0.2818, -2.3374, 1.5310};
+
+    std::vector<float> ih_data{1.9104, -1.9004, 0.3337,  0.5741,  1.5289,  1.0986,
+                               0.6091, 1.6462,  0.5671,  0.0458,  0.4514,  -0.8968,
+                               0.8720, 0.5349,  -0.1962, -1.7416, -0.9201, 0.1962,
+                               0.5771, -0.5332, -0.9912, 1.2831,  1.0896,  -0.6959};
+
+    std::vector<float> ic_data{0.9569,  -0.5981, 1.1312, 1.0945,  -0.8323, 0.3998,
+                               0.1831,  0.5938,  1.1055, -0.1212, -0.9097, 0.7831,
+                               2.7096,  -0.1790, 0.0022, -0.8040, -1.6991, -1.9498,
+                               -1.2567, -0.4114, 0.1578, 0.0567,  0.8069,  -0.5141};
+
+    std::vector<float> pph_data{1.84369764,  0.68413646, -0.44892886, -1.50904413, 0.3860796,
+                                -0.52186625, 1.08474445, -1.80867321, 1.32594529,  0.4336262,
+                                -0.83699064, 0.49162736, -0.8271,     -0.5683,     0.4562,
+                                -1.2545,     1.2729,     -0.4082,     -0.4392,     -0.9406,
+                                0.7794,      1.8194,     -0.5811,     0.2166};
+
+    float clip = 0.0f;
+    migraphx::shape in_shape{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
+    migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, input_size}};
+    migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, 4 * hidden_size, hidden_size}};
+    migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 8 * hidden_size}};
+    migraphx::shape ih_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+    migraphx::shape ic_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+    migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
+
+    // concatenation of hidden states as program output
+    {
+        std::vector<int> sl_data{1, 2, 3};
+        migraphx::shape sl_shape{migraphx::shape::int32_type, {batch_size}};
+        migraphx::program p;
+        auto* mm  = p.get_main_module();
+        auto seq  = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto ih   = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic   = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto w    = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r    = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto pph  = mm->add_literal(migraphx::literal{pph_shape, pph_data});
+        auto sql  = mm->add_literal(migraphx::literal{sl_shape, sl_data});
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto out_hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            sql,
+            ih,
+            ic,
+            pph);
+        auto lho = mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), out_hs);
+        auto lco = mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), out_hs);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        out_hs = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}),
+                                     out_hs);
+        lho    = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), lho);
+        lco    = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), lco);
+        mm->add_return({out_hs, lho, lco});
+        p.compile(migraphx::make_target("ref"));
+
+        auto outputs = p.eval({});
+        auto arg_hs  = outputs.front();
+        auto arg_lho = outputs.at(1);
+        auto arg_lco = outputs.at(2);
+
+        std::vector<float> output_data;
+        std::vector<float> last_output_data;
+        std::vector<float> last_cell_data;
+
+        arg_hs.visit([&](auto output) { output_data.assign(output.begin(), output.end()); });
+        arg_lho.visit([&](auto output) { last_output_data.assign(output.begin(), output.end()); });
+        arg_lco.visit([&](auto output) { last_cell_data.assign(output.begin(), output.end()); });
+
+        std::vector<float> output_data_gold{
+            0.079753,   -0.289854, 0.160043,   0.115056,   -0.141643, 0.0451978,  0.140804,
+            0.0745128,  0,         0,          0,          0,         0,          0,
+            0,          0,         0,          0,          0,         0,          0,
+            0,          0,         0,          0,          0,         0,          0,
+            0,          0,         0,          0,          0.294074,  -0.0319677, -0.0955337,
+            0.104168,   0.911307,  0.11468,    0.114449,   0.0196755, 0.421857,   0.0459771,
+            -0.144955,  0.0720673, 0.96657,    0.0755112,  0.0620917, -0.264845,  0,
+            0,          0,         0,          0,          0,         0,          0,
+            0,          0,         0,          0,          0,         0,          0,
+            0,          0.022618,  -0.121195,  -0.4065,    -0.252054, -0.262807,  0.275286,
+            0.358395,   0.266267,  -0.0300906, -0.0890598, -0.135266, -0.0413375, -0.128254,
+            0.125398,   0.0665142, -0.163651,  0.103489,   0.0142918, -0.123408,  0.0401075,
+            -0.0644683, 0.371512,  0.212431,   -0.116131,  0,         0,          0,
+            0,          0,         0,          0,          0};
+
+        std::vector<float> last_output_data_gold{
+            0.079753, -0.289854, 0.160043,  0.115056,  -0.141643, 0.0451978, 0.140804, 0.0745128,
+            0.421857, 0.0459771, -0.144955, 0.0720673, 0.911307,  0.11468,   0.114449, 0.0196755,
+            0.103489, 0.0142918, -0.123408, 0.0401075, -0.262807, 0.275286,  0.358395, 0.266267};
+
+        std::vector<float> last_cell_data_gold{
+            0.600582, -0.601197, 0.353558,  0.789097,  -0.326822, 0.301121, 0.219523, 0.415242,
+            0.737121, 0.134902,  -0.303595, 0.241948,  2.08242,   0.442513, 0.187127, 0.0577626,
+            0.391174, 0.0308845, -0.561745, 0.0730323, -0.611307, 0.55454,  0.4364,   0.509436};
+
+        EXPECT(migraphx::verify::verify_rms_range(output_data, output_data_gold));
+        EXPECT(migraphx::verify::verify_rms_range(last_output_data, last_output_data_gold));
+        EXPECT(migraphx::verify::verify_rms_range(last_cell_data, last_cell_data_gold));
+    }
+
+    // last cell output as program output
+    {
+        migraphx::program p;
+        auto* mm      = p.get_main_module();
+        auto seq_orig = mm->add_literal(migraphx::literal{in_shape, input_data});
+        auto ih       = mm->add_literal(migraphx::literal{ih_shape, ih_data});
+        auto ic       = mm->add_literal(migraphx::literal{ic_shape, ic_data});
+        auto w        = mm->add_literal(migraphx::literal{w_shape, w_data});
+        auto r        = mm->add_literal(migraphx::literal{r_shape, r_data});
+        auto bias     = mm->add_literal(migraphx::literal{b_shape, bias_data});
+        auto pph      = mm->add_literal(migraphx::literal{pph_shape, pph_data});
+        migraphx::shape pad_seq_s{migraphx::shape::float_type, {batch_size, 2, input_size}};
+        std::vector<float> pad_data(pad_seq_s.elements(), 0.0f);
+        auto seq_p = mm->add_literal(migraphx::literal{pad_seq_s, pad_data});
+        auto seq = mm->add_instruction(migraphx::make_op("concat", {{"axis", 1}}), seq_orig, seq_p);
+        migraphx::shape seq_len_s{migraphx::shape::int32_type, {batch_size}};
+        std::vector<int32_t> len_data(batch_size, static_cast<int32_t>(seq_len));
+        auto sql = mm->add_literal(seq_len_s, len_data);
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
+                 {"clip", clip},
+                 {"input_forget", 0}}),
+            seq,
+            w,
+            r,
+            bias,
+            sql,
+            ih,
+            ic,
+            pph);
+        auto lho = mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), hs);
+        auto lco = mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        hs  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
+        lho = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), lho);
+        lco = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), lco);
+        mm->add_return({hs, lho, lco});
+        p.compile(migraphx::make_target("ref"));
+
+        auto outputs = p.eval({});
+        auto res_hs  = outputs.at(0);
+        auto res_lho = outputs.at(1);
+        auto res_lco = outputs.at(2);
+        std::vector<float> hs_data;
+        std::vector<float> lho_data;
+        std::vector<float> lco_data;
+        res_hs.visit([&](auto output) { hs_data.assign(output.begin(), output.end()); });
+        res_lho.visit([&](auto output) { lho_data.assign(output.begin(), output.end()); });
+        res_lco.visit([&](auto output) { lco_data.assign(output.begin(), output.end()); });
+
+        std::vector<float> hs_data_gold{
+            0.079753,   -0.289854,  0.160043,   0.115056,   -0.120174,  0.043157,   0.117138,
+            -0.222188,  0.186991,   -0.0624168, 0.205513,   0.0836373,  -0.175114,  -0.00543549,
+            0.178681,   -0.266999,  0.0459033,  0.0414126,  0.272303,   0.0393149,  -0.182201,
+            -0.0232277, 0.235501,   -0.213485,  -0.058052,  0.0795391,  0.266617,   -0.0128746,
+            -0.185038,  -0.026845,  0.177273,   -0.0774616, 0,          0,          0,
+            0,          0,          0,          0,          0,          0,          0,
+            0,          0,          0,          0,          0,          0,          0.294074,
+            -0.0319677, -0.0955337, 0.104168,   0.789732,   0.128538,   0.20909,    0.0553812,
+            0.421857,   0.0459771,  -0.144955,  0.0720673,  0.928866,   0.113685,   0.220626,
+            -0.0432316, 0.218258,   0.0944405,  0.0431211,  -0.132394,  0.960938,   0.133565,
+            0.269741,   0.130438,   0.0309878,  0.0971544,  0.149294,   -0.0492549, 0.946669,
+            0.0868676,  0.044508,   -0.373961,  0,          0,          0,          0,
+            0,          0,          0,          0,          0,          0,          0,
+            0,          0,          0,          0,          0,          0.022618,   -0.121195,
+            -0.4065,    -0.252054,  -0.224905,  0.32421,    0.344048,   0.271694,   -0.0300906,
+            -0.0890598, -0.135266,  -0.0413375, -0.063456,  0.148524,   0.05108,    -0.0234895,
+            0.103489,   0.0142918,  -0.123408,  0.0401075,  -0.0252804, 0.267356,   0.146353,
+            0.0789186,  0.187761,   0.0501726,  -0.121584,  0.0606723,  -0.0681467, 0.382748,
+            0.230211,   -0.161537,  0,          0,          0,          0,          0,
+            0,          0,          0,          0,          0,          0,          0,
+            0,          0,          0,          0};
+
+        std::vector<float> lho_data_gold{
+            -0.058052, 0.0795391, 0.266617,  -0.0128746, -0.120174, 0.043157, 0.117138, -0.222188,
+            0.0309878, 0.0971544, 0.149294,  -0.0492549, 0.789732,  0.128538, 0.20909,  0.0553812,
+            0.187761,  0.0501726, -0.121584, 0.0606723,  -0.224905, 0.32421,  0.344048, 0.271694};
+
+        std::vector<float> lco_data_gold{
+            -0.077353, 0.245616, 0.361023,  -0.0443759, -0.889294, 0.182463, 0.186512, -0.402334,
+            0.0685243, 0.20465,  0.277867,  -0.112934,  1.48161,   0.524116, 0.347113, 0.181813,
+            0.67312,   0.120508, -0.726968, 0.113845,   -0.434265, 0.747833, 0.416053, 0.558713};
+
+        EXPECT(migraphx::verify::verify_rms_range(hs_data, hs_data_gold));
+        EXPECT(migraphx::verify::verify_rms_range(lho_data, lho_data_gold));
+        EXPECT(migraphx::verify::verify_rms_range(lco_data, lco_data_gold));
+    }
+}
+
 TEST_CASE(lstm_bidirectional_actv_func)
 {
     std::size_t batch_size  = 3;

test/simplify_qdq_test.cpp

@@ -44,20 +44,34 @@ void run_pass(migraphx::module& m)
     sqdq.apply(m);
 }
 
-migraphx::instruction_ref add_quantize_op(migraphx::module& m,
-                                          const std::string& name,
-                                          migraphx::instruction_ref x,
+migraphx::instruction_ref broadcast_scale(migraphx::module& m,
                                           migraphx::instruction_ref scale,
-                                          migraphx::instruction_ref shift)
+                                          const std::vector<std::size_t>& out_lens,
+                                          std::size_t axis)
 {
-    auto lens = x->get_shape().lens();
+    if(scale->get_shape().lens() == out_lens)
+        return scale;
+
     migraphx::instruction_ref scale_mb;
-    if(scale->get_shape().lens().front() == 1)
+    auto scale_lens = scale->get_shape().lens();
+    if(scale_lens.front() == 1 and scale_lens.size() == 1)
         scale_mb =
-            m.add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", lens}}), scale);
+            m.add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", out_lens}}), scale);
     else
         scale_mb = m.add_instruction(
-            migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", lens}}), scale);
+            migraphx::make_op("broadcast", {{"axis", axis}, {"out_lens", out_lens}}), scale);
+    return scale_mb;
+}
+
+migraphx::instruction_ref add_quantize_op(migraphx::module& m,
+                                          const std::string& name,
+                                          migraphx::instruction_ref x,
+                                          migraphx::instruction_ref scale,
+                                          migraphx::instruction_ref shift,
+                                          std::size_t q_axis = 1)
+{
+    auto lens     = x->get_shape().lens();
+    auto scale_mb = broadcast_scale(m, scale, lens, q_axis);
     auto shift_mb =
         m.add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", lens}}), shift);
     return m.add_instruction(migraphx::make_op(name), x, scale_mb, shift_mb);
@@ -66,19 +80,26 @@ migraphx::instruction_ref add_quantize_op(migraphx::module& m,
 migraphx::instruction_ref add_quantize_op(migraphx::module& m,
                                           const std::string& name,
                                           migraphx::instruction_ref x,
-                                          migraphx::instruction_ref scale)
+                                          migraphx::instruction_ref scale,
+                                          std::size_t q_axis = 1)
 {
-    auto lens = x->get_shape().lens();
-    migraphx::instruction_ref scale_mb;
-    if(scale->get_shape().lens().front() == 1)
-        scale_mb =
-            m.add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", lens}}), scale);
-    else
-        scale_mb = m.add_instruction(
-            migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", lens}}), scale);
+    auto lens     = x->get_shape().lens();
+    auto scale_mb = broadcast_scale(m, scale, lens, q_axis);
     return m.add_instruction(migraphx::make_op(name), x, scale_mb);
 }
 
+migraphx::instruction_ref add_scale_mul(migraphx::module& m,
+                                        migraphx::instruction_ref scale1,
+                                        migraphx::instruction_ref scale2,
+                                        std::size_t axis1,
+                                        std::size_t axis2,
+                                        const std::vector<std::size_t>& out_lens)
+{
+    auto scale1_mb = broadcast_scale(m, scale1, out_lens, axis1);
+    auto scale2_mb = broadcast_scale(m, scale2, out_lens, axis2);
+    return m.add_instruction(migraphx::make_op("mul"), scale1_mb, scale2_mb);
+}
+
 TEST_CASE(remove_qdq)
 {
     migraphx::shape sh1{migraphx::shape::float_type, {100, 100}};
@@ -159,18 +180,62 @@ TEST_CASE(dot)
         m1.add_return({dot});
     }
 
+    migraphx::module m2;
+    {
+        auto t1    = m2.add_parameter("t1", sh1);
+        auto t2    = m2.add_parameter("t2", sh2);
+        auto scale = m2.add_literal(0.5f);
+        auto zero  = m2.add_literal(std::int8_t{0});
+
+        auto q1 = add_quantize_op(m2, "quantizelinear", t1, scale, zero);
+        auto q2 = add_quantize_op(m2, "quantizelinear", t2, scale, zero);
+
+        auto dot       = m2.add_instruction(migraphx::make_op("quant_dot"), q1, q2);
+        auto out_scale = add_scale_mul(m2, scale, scale, 1, 1, dot->get_shape().lens());
+        auto d3        = add_quantize_op(m2, "dequantizelinear", dot, out_scale);
+        m2.add_return({d3});
+    }
+
+    run_pass(m1);
+    EXPECT(m1 == m2);
+}
+
+TEST_CASE(dot_multi_scale)
+{
+    migraphx::shape sh1{migraphx::shape::float_type, {1280, 1000}};
+    migraphx::shape sh2{migraphx::shape::float_type, {1000, 1024}};
+    migraphx::shape sh3{migraphx::shape::float_type, {1280}};
+
+    migraphx::module m1;
+    {
+        auto t1     = m1.add_parameter("t1", sh1);
+        auto t2     = m1.add_parameter("t2", sh2);
+        auto scale1 = m1.add_literal(migraphx::generate_literal(sh3, 0));
+        auto scale2 = m1.add_literal(0.4f);
+        auto zero   = m1.add_literal(std::int8_t{0});
+
+        auto q1  = add_quantize_op(m1, "quantizelinear", t1, scale1, zero, 0);
+        auto d1  = add_quantize_op(m1, "dequantizelinear", q1, scale1, zero, 0);
+        auto q2  = add_quantize_op(m1, "quantizelinear", t2, scale2, zero, 1);
+        auto d2  = add_quantize_op(m1, "dequantizelinear", q2, scale2, zero, 1);
+        auto dot = m1.add_instruction(migraphx::make_op("dot"), d1, d2);
+        m1.add_return({dot});
+    }
+
     migraphx::module m2;
     {
         auto t1     = m2.add_parameter("t1", sh1);
         auto t2     = m2.add_parameter("t2", sh2);
-        auto scale  = m2.add_literal(0.5f);
+        auto scale1 = m2.add_literal(migraphx::generate_literal(sh3, 0));
+        auto scale2 = m2.add_literal(0.4f);
         auto zero   = m2.add_literal(std::int8_t{0});
-        auto scale1 = m2.add_literal(0.25f);
 
-        auto q1  = add_quantize_op(m2, "quantizelinear", t1, scale, zero);
-        auto q2  = add_quantize_op(m2, "quantizelinear", t2, scale, zero);
-        auto dot = m2.add_instruction(migraphx::make_op("quant_dot"), q1, q2);
-        auto d3  = add_quantize_op(m2, "dequantizelinear", dot, scale1);
+        auto q1 = add_quantize_op(m2, "quantizelinear", t1, scale1, zero, 0);
+        auto q2 = add_quantize_op(m2, "quantizelinear", t2, scale2, zero, 1);
+
+        auto dot       = m2.add_instruction(migraphx::make_op("quant_dot"), q1, q2);
+        auto out_scale = add_scale_mul(m2, scale1, scale2, 0, 1, dot->get_shape().lens());
+        auto d3        = add_quantize_op(m2, "dequantizelinear", dot, out_scale);
         m2.add_return({d3});
     }
 
@@ -178,6 +243,180 @@ TEST_CASE(dot)
     EXPECT(m1 == m2);
 }
 
+TEST_CASE(dot_broadcasted)
+{
+    migraphx::shape sh1{migraphx::shape::float_type, {2, 1280, 1000}};
+    migraphx::shape sh2{migraphx::shape::float_type, {1000, 1024}};
+
+    migraphx::module m1;
+    {
+        auto t1    = m1.add_parameter("t1", sh1);
+        auto t2    = m1.add_parameter("t2", sh2);
+        auto scale = m1.add_literal(0.5f);
+        auto zero  = m1.add_literal(std::int8_t{0});
+
+        auto q1    = add_quantize_op(m1, "quantizelinear", t1, scale, zero);
+        auto d1    = add_quantize_op(m1, "dequantizelinear", q1, scale, zero);
+        auto q2    = add_quantize_op(m1, "quantizelinear", t2, scale, zero);
+        auto d2    = add_quantize_op(m1, "dequantizelinear", q2, scale, zero);
+        auto d2_mb = m1.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", {2, 1000, 1024}}}), d2);
+        auto dot = m1.add_instruction(migraphx::make_op("dot"), d1, d2_mb);
+        m1.add_return({dot});
+    }
+
+    migraphx::module m2;
+    {
+        auto t1    = m2.add_parameter("t1", sh1);
+        auto t2    = m2.add_parameter("t2", sh2);
+        auto scale = m2.add_literal(0.5f);
+        auto zero  = m2.add_literal(std::int8_t{0});
+
+        auto q1    = add_quantize_op(m2, "quantizelinear", t1, scale, zero);
+        auto q2    = add_quantize_op(m2, "quantizelinear", t2, scale, zero);
+        auto q2_mb = m2.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", {2, 1000, 1024}}}), q2);
+
+        auto dot       = m2.add_instruction(migraphx::make_op("quant_dot"), q1, q2_mb);
+        auto out_scale = add_scale_mul(m2, scale, scale, 1, 1, dot->get_shape().lens());
+        auto d3        = add_quantize_op(m2, "dequantizelinear", dot, out_scale);
+        m2.add_return({d3});
+    }
+
+    run_pass(m1);
+    EXPECT(m1 == m2);
+}
+
+TEST_CASE(dot_transposed)
+{
+    migraphx::shape sh1{migraphx::shape::float_type, {1280, 1000}};
+    migraphx::shape sh2{migraphx::shape::float_type, {1024, 1000}};
+
+    migraphx::module m1;
+    {
+        auto t1    = m1.add_parameter("t1", sh1);
+        auto t2    = m1.add_parameter("t2", sh2);
+        auto scale = m1.add_literal(0.5f);
+        auto zero  = m1.add_literal(std::int8_t{0});
+
+        auto q1 = add_quantize_op(m1, "quantizelinear", t1, scale, zero);
+        auto d1 = add_quantize_op(m1, "dequantizelinear", q1, scale, zero);
+        auto q2 = add_quantize_op(m1, "quantizelinear", t2, scale, zero);
+        auto d2 = add_quantize_op(m1, "dequantizelinear", q2, scale, zero);
+        auto d2_t =
+            m1.add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), d2);
+        auto dot = m1.add_instruction(migraphx::make_op("dot"), d1, d2_t);
+        m1.add_return({dot});
+    }
+
+    migraphx::module m2;
+    {
+        auto t1    = m2.add_parameter("t1", sh1);
+        auto t2    = m2.add_parameter("t2", sh2);
+        auto scale = m2.add_literal(0.5f);
+        auto zero  = m2.add_literal(std::int8_t{0});
+
+        auto q1 = add_quantize_op(m2, "quantizelinear", t1, scale, zero);
+        auto q2 = add_quantize_op(m2, "quantizelinear", t2, scale, zero);
+        auto q2_t =
+            m2.add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), q2);
+
+        auto dot       = m2.add_instruction(migraphx::make_op("quant_dot"), q1, q2_t);
+        auto out_scale = add_scale_mul(m2, scale, scale, 1, 1, dot->get_shape().lens());
+        auto d3        = add_quantize_op(m2, "dequantizelinear", dot, out_scale);
+        m2.add_return({d3});
+    }
+
+    run_pass(m1);
+    EXPECT(m1 == m2);
+}
+
+TEST_CASE(dot_multi_scale_transposed_broadcasted)
+{
+    migraphx::shape sh1{migraphx::shape::float_type, {2, 3, 1280, 1000}};
+    migraphx::shape sh2{migraphx::shape::float_type, {1024, 1000}};
+    migraphx::shape sh3{migraphx::shape::float_type, {1280}};
+    migraphx::shape sh4{migraphx::shape::float_type, {1024}};
+
+    migraphx::module m1;
+    {
+        auto t1     = m1.add_parameter("t1", sh1);
+        auto t2     = m1.add_parameter("t2", sh2);
+        auto scale1 = m1.add_literal(migraphx::generate_literal(sh3, 0));
+        auto scale2 = m1.add_literal(migraphx::generate_literal(sh4, 0));
+        auto zero   = m1.add_literal(std::int8_t{0});
+
+        auto q1 = add_quantize_op(m1, "quantizelinear", t1, scale1, zero, 2);
+        auto d1 = add_quantize_op(m1, "dequantizelinear", q1, scale1, zero, 2);
+        auto q2 = add_quantize_op(m1, "quantizelinear", t2, scale2, zero, 0);
+        auto d2 = add_quantize_op(m1, "dequantizelinear", q2, scale2, zero, 0);
+        auto d2_t =
+            m1.add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), d2);
+        auto d2_mb = m1.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", {2, 3, 1000, 1024}}}), d2_t);
+        auto dot = m1.add_instruction(migraphx::make_op("dot"), d1, d2_mb);
+        m1.add_return({dot});
+    }
+
+    migraphx::module m2;
+    {
+        auto t1     = m2.add_parameter("t1", sh1);
+        auto t2     = m2.add_parameter("t2", sh2);
+        auto scale1 = m2.add_literal(migraphx::generate_literal(sh3, 0));
+        auto scale2 = m2.add_literal(migraphx::generate_literal(sh4, 0));
+        auto zero   = m2.add_literal(std::int8_t{0});
+
+        auto q1 = add_quantize_op(m2, "quantizelinear", t1, scale1, zero, 2);
+        auto q2 = add_quantize_op(m2, "quantizelinear", t2, scale2, zero, 0);
+        auto q2_t =
+            m2.add_instruction(migraphx::make_op("transpose", {{"permutation", {1, 0}}}), q2);
+        auto q2_mb = m2.add_instruction(
+            migraphx::make_op("multibroadcast", {{"out_lens", {2, 3, 1000, 1024}}}), q2_t);
+
+        auto dot       = m2.add_instruction(migraphx::make_op("quant_dot"), q1, q2_mb);
+        auto out_scale = add_scale_mul(m2, scale1, scale2, 2, 3, dot->get_shape().lens());
+        auto d3        = add_quantize_op(m2, "dequantizelinear", dot, out_scale);
+        m2.add_return({d3});
+    }
+
+    run_pass(m1);
+    EXPECT(m1 == m2);
+}
+
+TEST_CASE(dot_multi_scale_unsupported_axis)
+{
+    migraphx::shape sh1{migraphx::shape::float_type, {1280, 1000}};
+    migraphx::shape sh2{migraphx::shape::float_type, {1000, 1024}};
+    migraphx::shape sh3{migraphx::shape::float_type, {1000}};
+
+    migraphx::module m1;
+    {
+        auto t1     = m1.add_parameter("t1", sh1);
+        auto t2     = m1.add_parameter("t2", sh2);
+        auto scale1 = m1.add_literal(migraphx::generate_literal(sh3, 0));
+        auto scale2 = m1.add_literal(0.4f);
+        auto zero   = m1.add_literal(std::int8_t{0});
+
+        auto q1  = add_quantize_op(m1, "quantizelinear", t1, scale1, zero, 1);
+        auto d1  = add_quantize_op(m1, "dequantizelinear", q1, scale1, zero, 1);
+        auto q2  = add_quantize_op(m1, "quantizelinear", t2, scale2, zero, 1);
+        auto d2  = add_quantize_op(m1, "dequantizelinear", q2, scale2, zero, 1);
+        auto dot = m1.add_instruction(migraphx::make_op("dot"), d1, d2);
+        m1.add_return({dot});
+    }
+
+    migraphx::module m2;
+    {
+        auto t1  = m2.add_parameter("t1", sh1);
+        auto t2  = m2.add_parameter("t2", sh2);
+        auto dot = m2.add_instruction(migraphx::make_op("dot"), t1, t2);
+        m2.add_return({dot});
+    }
+
+    run_pass(m1);
+    EXPECT(m1 == m2);
+}
+
 TEST_CASE(dot_non_zero_point)
 {
     migraphx::shape sh1{migraphx::shape::float_type, {1280, 1000}};
@@ -269,18 +508,18 @@ TEST_CASE(dot_add)
 
     migraphx::module m2;
     {
-        auto t1     = m2.add_parameter("t1", sh1);
-        auto t2     = m2.add_parameter("t2", sh2);
-        auto ab     = m2.add_parameter("ab", sh3);
-        auto scale  = m2.add_literal(0.5f);
-        auto zero   = m2.add_literal(std::int8_t{0});
-        auto scale1 = m2.add_literal(0.25f);
-
-        auto q1  = add_quantize_op(m2, "quantizelinear", t1, scale, zero);
-        auto q2  = add_quantize_op(m2, "quantizelinear", t2, scale, zero);
-        auto dot = m2.add_instruction(migraphx::make_op("quant_dot"), q1, q2);
-        auto d3  = add_quantize_op(m2, "dequantizelinear", dot, scale1);
-        auto add = m2.add_instruction(migraphx::make_op("add"), d3, ab);
+        auto t1    = m2.add_parameter("t1", sh1);
+        auto t2    = m2.add_parameter("t2", sh2);
+        auto ab    = m2.add_parameter("ab", sh3);
+        auto scale = m2.add_literal(0.5f);
+        auto zero  = m2.add_literal(std::int8_t{0});
+
+        auto q1        = add_quantize_op(m2, "quantizelinear", t1, scale, zero);
+        auto q2        = add_quantize_op(m2, "quantizelinear", t2, scale, zero);
+        auto dot       = m2.add_instruction(migraphx::make_op("quant_dot"), q1, q2);
+        auto out_scale = add_scale_mul(m2, scale, scale, 1, 1, dot->get_shape().lens());
+        auto d3        = add_quantize_op(m2, "dequantizelinear", dot, out_scale);
+        auto add       = m2.add_instruction(migraphx::make_op("add"), d3, ab);
         m2.add_return({add});
     }
 
@@ -320,26 +559,80 @@ TEST_CASE(conv)
         auto weights = m2.add_parameter("weights", s4);
         auto scale   = m2.add_literal(0.5f);
         auto zero    = m2.add_literal(std::int8_t{0});
-        auto scale1  = m2.add_literal(0.25f);
 
-        auto q1 = add_quantize_op(m2, "quantizelinear", input, scale, zero);
-        auto c1 = m2.add_instruction(migraphx::make_op("quant_convolution",
+        auto q1        = add_quantize_op(m2, "quantizelinear", input, scale, zero);
+        auto c1        = m2.add_instruction(migraphx::make_op("quant_convolution",
+                                                              {{"padding", {0, 0, 0, 0}},
+                                                               {"stride", {1, 1}},
+                                                               {"dilation", {1, 1}},
+                                                               {"group", 1},
+                                                               {"padding_mode", 0}}),
+                                     q1,
+                                     weights);
+        auto out_scale = add_scale_mul(m2, scale, scale, 1, 1, c1->get_shape().lens());
+        auto d6        = add_quantize_op(m2, "dequantizelinear", c1, out_scale);
+        m2.add_return({d6});
+    }
+
+    run_pass(m1);
+    EXPECT(m1 == m2);
+}
+
+TEST_CASE(conv_multi_scale)
+{
+    migraphx::shape s4{migraphx::shape::int8_type, {1280, 320, 1, 1}};
+    migraphx::shape s7{migraphx::shape::float_type, {1, 320, 7, 7}};
+    migraphx::shape s8{migraphx::shape::float_type, {1280}};
+
+    migraphx::module m1;
+    {
+        auto input     = m1.add_parameter("input", s7);
+        auto weights   = m1.add_parameter("weights", s4);
+        auto w_scale   = m1.add_literal(migraphx::generate_literal(s8, 0));
+        auto inp_scale = m1.add_literal(0.5f);
+        auto zero      = m1.add_literal(std::int8_t{0});
+
+        auto d1 = add_quantize_op(m1, "dequantizelinear", weights, w_scale, zero, 0);
+        auto q1 = add_quantize_op(m1, "quantizelinear", input, inp_scale, zero);
+        auto d5 = add_quantize_op(m1, "dequantizelinear", q1, inp_scale, zero);
+        auto c1 = m1.add_instruction(migraphx::make_op("convolution",
                                                        {{"padding", {0, 0, 0, 0}},
                                                         {"stride", {1, 1}},
                                                         {"dilation", {1, 1}},
                                                         {"group", 1},
                                                         {"padding_mode", 0}}),
-                                     q1,
+                                     d5,
+                                     d1);
+        m1.add_return({c1});
+    }
+
+    migraphx::module m2;
+    {
+        auto input     = m2.add_parameter("input", s7);
+        auto weights   = m2.add_parameter("weights", s4);
+        auto w_scale   = m2.add_literal(migraphx::generate_literal(s8, 0));
+        auto inp_scale = m2.add_literal(0.5f);
+        auto zero      = m2.add_literal(std::int8_t{0});
+
+        auto q_inp     = add_quantize_op(m2, "quantizelinear", input, inp_scale, zero);
+        auto c1        = m2.add_instruction(migraphx::make_op("quant_convolution",
+                                                              {{"padding", {0, 0, 0, 0}},
+                                                               {"stride", {1, 1}},
+                                                               {"dilation", {1, 1}},
+                                                               {"group", 1},
+                                                               {"padding_mode", 0}}),
+                                     q_inp,
                                      weights);
-        auto d6 = add_quantize_op(m2, "dequantizelinear", c1, scale1);
-        m2.add_return({d6});
+        auto out_scale = add_scale_mul(m2, inp_scale, w_scale, 1, 1, c1->get_shape().lens());
+        auto d1        = add_quantize_op(m2, "dequantizelinear", c1, out_scale);
+        m2.add_return({d1});
     }
 
     run_pass(m1);
     EXPECT(m1 == m2);
 }
 
-TEST_CASE(conv_multi_scale)
+TEST_CASE(conv_multi_scale_unsupported_axis)
 {
     migraphx::shape s4{migraphx::shape::int8_type, {1280, 320, 1, 1}};
     migraphx::shape s7{migraphx::shape::float_type, {1, 320, 7, 7}};
@@ -430,20 +723,20 @@ TEST_CASE(conv_bias_add)
         auto scale   = m2.add_literal(0.5f);
         auto zero    = m2.add_literal(std::int8_t{0});
         auto zero32  = m2.add_literal(std::int32_t{0});
-        auto scale1  = m2.add_literal(0.25f);
 
-        auto d2 = add_quantize_op(m2, "dequantizelinear", bias, scale, zero32);
-        auto q1 = add_quantize_op(m2, "quantizelinear", input, scale, zero);
-        auto c1 = m2.add_instruction(migraphx::make_op("quant_convolution",
-                                                       {{"padding", {0, 0, 0, 0}},
-                                                        {"stride", {1, 1}},
-                                                        {"dilation", {1, 1}},
-                                                        {"group", 1},
-                                                        {"padding_mode", 0}}),
+        auto d2        = add_quantize_op(m2, "dequantizelinear", bias, scale, zero32);
+        auto q1        = add_quantize_op(m2, "quantizelinear", input, scale, zero);
+        auto c1        = m2.add_instruction(migraphx::make_op("quant_convolution",
+                                                              {{"padding", {0, 0, 0, 0}},
+                                                               {"stride", {1, 1}},
+                                                               {"dilation", {1, 1}},
+                                                               {"group", 1},
+                                                               {"padding_mode", 0}}),
                                      q1,
                                      weights);
-        auto d6 = add_quantize_op(m2, "dequantizelinear", c1, scale1);
-        auto b1 = m2.add_instruction(
+        auto out_scale = add_scale_mul(m2, scale, scale, 1, 1, c1->get_shape().lens());
+        auto d6        = add_quantize_op(m2, "dequantizelinear", c1, out_scale);
+        auto b1        = m2.add_instruction(
             migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", {1, 1280, 7, 7}}}), d2);
         auto a1 = m2.add_instruction(migraphx::make_op("add"), d6, b1);
         m2.add_return({a1});
@@ -519,22 +812,21 @@ TEST_CASE(conv_pooling_dot)
         auto scale   = m2.add_literal(0.5f);
         auto zero    = m2.add_literal(std::int8_t{0});
         auto zero32  = m2.add_literal(std::int32_t{0});
-        auto scale1  = m2.add_literal(0.25f);
-        auto scale2  = m2.add_literal(0.25f);
 
-        auto d2  = add_quantize_op(m2, "dequantizelinear", bias, scale, zero32);
-        auto d3  = add_quantize_op(m2, "dequantizelinear", ab, scale, zero);
-        auto q1  = add_quantize_op(m2, "quantizelinear", input, scale, zero);
-        auto c1  = m2.add_instruction(migraphx::make_op("quant_convolution",
-                                                        {{"padding", {0, 0, 0, 0}},
-                                                         {"stride", {1, 1}},
-                                                         {"dilation", {1, 1}},
-                                                         {"group", 1},
-                                                         {"padding_mode", 0}}),
+        auto d2         = add_quantize_op(m2, "dequantizelinear", bias, scale, zero32);
+        auto d3         = add_quantize_op(m2, "dequantizelinear", ab, scale, zero);
+        auto q1         = add_quantize_op(m2, "quantizelinear", input, scale, zero);
+        auto c1         = m2.add_instruction(migraphx::make_op("quant_convolution",
+                                                               {{"padding", {0, 0, 0, 0}},
+                                                                {"stride", {1, 1}},
+                                                                {"dilation", {1, 1}},
+                                                                {"group", 1},
+                                                                {"padding_mode", 0}}),
                                      q1,
                                      weights);
-        auto d5  = add_quantize_op(m2, "dequantizelinear", c1, scale1);
-        auto bc1 = m2.add_instruction(
+        auto out_scale1 = add_scale_mul(m2, scale, scale, 1, 1, c1->get_shape().lens());
+        auto d5         = add_quantize_op(m2, "dequantizelinear", c1, out_scale1);
+        auto bc1        = m2.add_instruction(
             migraphx::make_op("broadcast", {{"axis", 1}, {"out_lens", {1, 1280, 7, 7}}}), d2);
         auto a1 = m2.add_instruction(migraphx::make_op("add"), d5, bc1);
         auto ap =
@@ -545,10 +837,11 @@ TEST_CASE(conv_pooling_dot)
                                                   {"lengths", {7, 7}},
                                                   {"ceil_mode", 0}}),
                                a1);
-        auto fl  = m2.add_instruction(migraphx::make_op("flatten", {{"axis", 1}}), ap);
-        auto q4  = add_quantize_op(m2, "quantizelinear", fl, scale, zero);
-        auto dot = m2.add_instruction(migraphx::make_op("quant_dot"), q4, db);
-        auto d9  = add_quantize_op(m2, "dequantizelinear", dot, scale2);
+        auto fl         = m2.add_instruction(migraphx::make_op("flatten", {{"axis", 1}}), ap);
+        auto q4         = add_quantize_op(m2, "quantizelinear", fl, scale, zero);
+        auto dot        = m2.add_instruction(migraphx::make_op("quant_dot"), q4, db);
+        auto out_scale2 = add_scale_mul(m2, scale, scale, 1, 0, dot->get_shape().lens());
+        auto d9         = add_quantize_op(m2, "dequantizelinear", dot, out_scale2);
         auto mb1 =
             m2.add_instruction(migraphx::make_op("multibroadcast", {{"out_lens", {1, 1000}}}), d3);
         auto a2 = m2.add_instruction(migraphx::make_op("add"), d9, mb1);

test/verify/test_lstm_bidirct_3args_layout.cpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include "verify_program.hpp"
+#include <migraphx/program.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/serialize.hpp>
+
+#include <migraphx/make_op.hpp>
+
+#include <migraphx/op/common.hpp>
+
+struct test_lstm_bidirct_3args_layout : verify_program<test_lstm_bidirct_3args_layout>
+{
+    migraphx::program create_program() const
+    {
+        std::size_t batch_size  = 2;
+        std::size_t seq_len     = 3;
+        std::size_t hidden_size = 5;
+        std::size_t input_size  = 8;
+        std::size_t num_dirct   = 2;
+        float clip              = 0.0f;
+
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        migraphx::shape in_shape{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
+        migraphx::shape w_shape{migraphx::shape::float_type,
+                                {num_dirct, 4 * hidden_size, input_size}};
+        migraphx::shape r_shape{migraphx::shape::float_type,
+                                {num_dirct, 4 * hidden_size, hidden_size}};
+        auto seq = mm->add_parameter("seq", in_shape);
+        auto w   = mm->add_parameter("w", w_shape);
+        auto r   = mm->add_parameter("r", r_shape);
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
+                 {"clip", clip}}),
+            seq,
+            w,
+            r);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
+
+        return p;
+    }
+    std::string section() const { return "rnn"; }
+};

test/verify/test_lstm_bidirct_last_layout.cpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include "verify_program.hpp"
+#include <migraphx/program.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/make_op.hpp>
+
+#include <migraphx/serialize.hpp>
+
+#include <migraphx/op/common.hpp>
+
+struct test_lstm_bidirct_last_layout : verify_program<test_lstm_bidirct_last_layout>
+{
+    migraphx::program create_program() const
+    {
+        std::size_t batch_size  = 2;
+        std::size_t seq_len     = 3;
+        std::size_t hidden_size = 5;
+        std::size_t input_size  = 8;
+        std::size_t num_dirct   = 2;
+        float clip              = 0.0f;
+
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        migraphx::shape in_shape{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
+        migraphx::shape w_shape{migraphx::shape::float_type,
+                                {num_dirct, 4 * hidden_size, input_size}};
+        migraphx::shape r_shape{migraphx::shape::float_type,
+                                {num_dirct, 4 * hidden_size, hidden_size}};
+        migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 8 * hidden_size}};
+        migraphx::shape ih_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+        migraphx::shape ic_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+        migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
+
+        auto seq  = mm->add_parameter("seq", in_shape);
+        auto w    = mm->add_parameter("w", w_shape);
+        auto r    = mm->add_parameter("r", r_shape);
+        auto bias = mm->add_parameter("bias", b_shape);
+        auto ih   = mm->add_parameter("ih", ih_shape);
+        auto ic   = mm->add_parameter("ic", ic_shape);
+        auto pph  = mm->add_parameter("pph", pph_shape);
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto output = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::bidirectional)},
+                 {"clip", clip}}),
+            seq,
+            w,
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            pph);
+        auto last_output = mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), output);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_output);
+
+        return p;
+    }
+    std::string section() const { return "rnn"; }
+};

test/verify/test_lstm_forward_hs_layout.cpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include "verify_program.hpp"
+#include <migraphx/program.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/make_op.hpp>
+
+#include <migraphx/serialize.hpp>
+
+#include <migraphx/op/common.hpp>
+
+struct test_lstm_forward_hs_layout : verify_program<test_lstm_forward_hs_layout>
+{
+    migraphx::program create_program() const
+    {
+        std::size_t batch_size  = 2;
+        std::size_t seq_len     = 3;
+        std::size_t hidden_size = 5;
+        std::size_t input_size  = 8;
+        std::size_t num_dirct   = 1;
+        float clip              = 0.0f;
+
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        migraphx::shape in_shape{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
+        migraphx::shape w_shape{migraphx::shape::float_type,
+                                {num_dirct, 4 * hidden_size, input_size}};
+        migraphx::shape r_shape{migraphx::shape::float_type,
+                                {num_dirct, 4 * hidden_size, hidden_size}};
+        migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 8 * hidden_size}};
+        migraphx::shape ih_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+        migraphx::shape ic_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+        migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
+
+        auto seq  = mm->add_parameter("seq", in_shape);
+        auto w    = mm->add_parameter("w", w_shape);
+        auto r    = mm->add_parameter("r", r_shape);
+        auto bias = mm->add_parameter("bias", b_shape);
+        auto ih   = mm->add_parameter("ih", ih_shape);
+        auto ic   = mm->add_parameter("ic", ic_shape);
+        auto pph  = mm->add_parameter("pph", pph_shape);
+        auto und  = mm->add_instruction(migraphx::make_op("undefined"));
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip}}),
+            seq,
+            w,
+            r,
+            bias,
+            und,
+            ih,
+            ic,
+            pph);
+        std::vector<int64_t> perm_hid{2, 0, 1, 3};
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm_hid}}), hs);
+
+        return p;
+    }
+    std::string section() const { return "rnn"; }
+};

test/verify/test_lstm_forward_last_layout.cpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include "verify_program.hpp"
+#include <migraphx/program.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/serialize.hpp>
+
+#include <migraphx/make_op.hpp>
+
+#include <migraphx/op/common.hpp>
+
+struct test_lstm_forward_last_layout : verify_program<test_lstm_forward_last_layout>
+{
+    migraphx::program create_program() const
+    {
+        std::size_t batch_size  = 2;
+        std::size_t seq_len     = 3;
+        std::size_t hidden_size = 5;
+        std::size_t input_size  = 8;
+        std::size_t num_dirct   = 1;
+        float clip              = 0.0f;
+
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        migraphx::shape in_shape{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
+        migraphx::shape w_shape{migraphx::shape::float_type,
+                                {num_dirct, 4 * hidden_size, input_size}};
+        migraphx::shape r_shape{migraphx::shape::float_type,
+                                {num_dirct, 4 * hidden_size, hidden_size}};
+        migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 8 * hidden_size}};
+        migraphx::shape ih_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+        migraphx::shape l_shape{migraphx::shape::int32_type, {batch_size}};
+        migraphx::shape ic_shape{migraphx::shape::float_type, {batch_size, num_dirct, hidden_size}};
+        migraphx::shape pph_shape{migraphx::shape::float_type, {num_dirct, 3 * hidden_size}};
+
+        auto seq  = mm->add_parameter("seq", in_shape);
+        auto w    = mm->add_parameter("w", w_shape);
+        auto r    = mm->add_parameter("r", r_shape);
+        auto bias = mm->add_parameter("bias", b_shape);
+        auto ih   = mm->add_parameter("ih", ih_shape);
+        auto len  = mm->add_literal(migraphx::literal(l_shape, {1, 2}));
+        auto ic   = mm->add_parameter("ic", ic_shape);
+        auto pph  = mm->add_parameter("pph", pph_shape);
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+        ih  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ih);
+        ic  = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), ic);
+
+        auto output = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::forward)},
+                 {"clip", clip}}),
+            seq,
+            w,
+            r,
+            bias,
+            len,
+            ih,
+            ic,
+            pph);
+        auto last_output =
+            mm->add_instruction(migraphx::make_op("rnn_last_hs_output"), output, len);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), last_output);
+
+        return p;
+    }
+    std::string section() const { return "rnn"; }
+};

test/verify/test_lstm_reverse_3args_cell_output_layout.cpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+
+#include "verify_program.hpp"
+#include <migraphx/program.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/serialize.hpp>
+
+#include <migraphx/make_op.hpp>
+
+#include <migraphx/op/common.hpp>
+
+struct test_lstm_reverse_3args_cell_layout : verify_program<test_lstm_reverse_3args_cell_layout>
+{
+    migraphx::program create_program() const
+    {
+        std::size_t batch_size  = 2;
+        std::size_t seq_len     = 3;
+        std::size_t hidden_size = 5;
+        std::size_t input_size  = 8;
+        std::size_t num_dirct   = 1;
+        float clip              = 0.0f;
+
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        migraphx::shape in_shape{migraphx::shape::float_type, {batch_size, seq_len, input_size}};
+        migraphx::shape w_shape{migraphx::shape::float_type,
+                                {num_dirct, 4 * hidden_size, input_size}};
+        migraphx::shape r_shape{migraphx::shape::float_type,
+                                {num_dirct, 4 * hidden_size, hidden_size}};
+        auto seq = mm->add_parameter("seq", in_shape);
+        auto w   = mm->add_parameter("w", w_shape);
+        auto r   = mm->add_parameter("r", r_shape);
+
+        std::vector<int64_t> perm{1, 0, 2};
+        seq = mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), seq);
+
+        auto hs = mm->add_instruction(
+            migraphx::make_op(
+                "lstm",
+                {{"hidden_size", hidden_size},
+                 {"actv_func",
+                  migraphx::to_value(std::vector<migraphx::operation>{migraphx::make_op("sigmoid"),
+                                                                      migraphx::make_op("tanh"),
+                                                                      migraphx::make_op("tanh")})},
+                 {"direction", migraphx::to_value(migraphx::op::rnn_direction::reverse)},
+                 {"clip", clip}}),
+            seq,
+            w,
+            r);
+        auto cell_output = mm->add_instruction(migraphx::make_op("rnn_last_cell_output"), hs);
+        mm->add_instruction(migraphx::make_op("transpose", {{"permutation", perm}}), cell_output);
+
+        return p;
+    }
+    std::string section() const { return "rnn"; }
+};