Merge branch 'develop' into hcc26

src/targets/gpu/include/migraphx/gpu/pow.hpp

+#ifndef MIGRAPHX_GUARD_RTGLIB_POW_HPP
+#define MIGRAPHX_GUARD_RTGLIB_POW_HPP
+
+#include <migraphx/gpu/oper.hpp>
+#include <migraphx/gpu/device/pow.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+struct hip_pow : binary_device<hip_pow, device::pow>
+{
+};
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/targets/gpu/include/migraphx/gpu/rsqrt.hpp

+#ifndef MIGRAPHX_GUARD_RTGLIB_RSQRT_HPP
+#define MIGRAPHX_GUARD_RTGLIB_RSQRT_HPP
+
+#include <migraphx/gpu/oper.hpp>
+#include <migraphx/gpu/device/rsqrt.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+struct hip_rsqrt : unary_device<hip_rsqrt, device::rsqrt>
+{
+};
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/targets/gpu/include/migraphx/gpu/sqdiff.hpp

+#ifndef MIGRAPHX_GUARD_RTGLIB_SQDIFF_HPP
+#define MIGRAPHX_GUARD_RTGLIB_SQDIFF_HPP
+
+#include <migraphx/gpu/oper.hpp>
+#include <migraphx/gpu/device/sqdiff.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+struct hip_sqdiff : binary_device<hip_sqdiff, device::sqdiff>
+{
+};
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/targets/gpu/include/migraphx/gpu/sqrt.hpp

+#ifndef MIGRAPHX_GUARD_RTGLIB_SQRT_HPP
+#define MIGRAPHX_GUARD_RTGLIB_SQRT_HPP
+
+#include <migraphx/gpu/oper.hpp>
+#include <migraphx/gpu/device/sqrt.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+struct hip_sqrt : unary_device<hip_sqrt, device::sqrt>
+{
+};
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/targets/gpu/lowering.cpp

@@ -26,6 +26,7 @@
 #include <migraphx/gpu/logsoftmax.hpp>
 #include <migraphx/gpu/add.hpp>
 #include <migraphx/gpu/sub.hpp>
+#include <migraphx/gpu/div.hpp>
 #include <migraphx/gpu/exp.hpp>
 #include <migraphx/gpu/erf.hpp>
 #include <migraphx/gpu/log.hpp>
@@ -51,7 +52,11 @@
 #include <migraphx/gpu/convert.hpp>
 #include <migraphx/gpu/clip.hpp>
 #include <migraphx/gpu/reduce_sum.hpp>
+#include <migraphx/gpu/rsqrt.hpp>
+#include <migraphx/gpu/sqrt.hpp>
 #include <migraphx/gpu/reduce_mean.hpp>
+#include <migraphx/gpu/pow.hpp>
+#include <migraphx/gpu/sqdiff.hpp>
 #include <utility>
 #include <functional>
 #include <algorithm>
@@ -98,9 +103,14 @@ struct miopen_apply
         add_generic_op<hip_asin>("asin");
         add_generic_op<hip_acos>("acos");
         add_generic_op<hip_atan>("atan");
+        add_generic_op<hip_sqrt>("sqrt");
         add_generic_op<hip_mul>("mul");
+        add_generic_op<hip_div>("div");
         add_generic_op<hip_max>("max");
         add_generic_op<hip_min>("min");
+        add_generic_op<hip_rsqrt>("rsqrt");
+        add_generic_op<hip_pow>("pow");
+        add_generic_op<hip_sqdiff>("sqdiff");
 
         add_extend_op<miopen_gemm, op::dot>("dot");
         add_extend_op<miopen_contiguous, op::contiguous>("contiguous");

src/tf/tf.cpp

@@ -79,7 +79,8 @@ struct tf_parser
         return result;
     }
 
-    std::vector<size_t> parse_axes(const attribute_map& attributes, const std::string& s) const
+    std::vector<size_t>
+    parse_axes(const attribute_map& attributes, const std::string& s, const size_t num_dims) const
     {
         auto attrs = attributes.at(s).list().i();
         std::vector<size_t> axes;
@@ -87,14 +88,14 @@ struct tf_parser
         if(is_nhwc)
         {
             std::transform(axes.begin(), axes.end(), axes.begin(), [&](size_t axis) {
-                return parse_axis(axis);
+                return parse_axis(axis, num_dims);
             });
         }
         return axes;
     }
 
     template <class T>
-    std::vector<T> parse_axes(std::vector<T> axes) const
+    std::vector<T> parse_axes(std::vector<T> axes, const size_t num_dims) const
     {
         if(is_nhwc)
         {
@@ -102,7 +103,7 @@ struct tf_parser
             std::transform(axes.begin(),
                            axes.end(),
                            std::back_inserter(new_axes),
-                           [&](size_t axis) { return parse_axis(axis); });
+                           [&](size_t axis) { return parse_axis(axis, num_dims); });
             return new_axes;
         }
         return axes;
@@ -117,17 +118,17 @@ struct tf_parser
         std::vector<T> new_data(prev_data.size());
         for(size_t i = 0; i < new_data.size(); i++)
         {
-            auto new_idx         = parse_axis(i);
+            auto new_idx         = parse_axis(i, new_data.size());
             new_data.at(new_idx) = prev_data.at(i);
         }
         prev_data = new_data;
     }
 
     template <class T>
-    T parse_axis(const T& dim) const
+    T parse_axis(const T& dim, const size_t num_dims) const
     {
         T new_dim = dim;
-        if(is_nhwc)
+        if(is_nhwc and num_dims >= 4)
         {
             switch(dim)
             {
@@ -153,10 +154,13 @@ struct tf_parser
         add_generic_op("Identity", op::identity{});
         add_generic_op("Relu", op::relu{});
         add_generic_op("Relu6", op::clip{6.0, 0.0});
+        add_generic_op("Rsqrt", op::rsqrt{});
         add_generic_op("Tanh", op::tanh{});
+        add_generic_op("StopGradient", op::identity{});
 
         add_binary_op("Add", op::add{});
         add_binary_op("Mul", op::mul{});
+        add_binary_op("SquaredDifference", op::sqdiff{});
         add_binary_op("Sub", op::sub{});
 
         add_mem_op("AvgPool", &tf_parser::parse_pooling);
@@ -165,6 +169,7 @@ struct tf_parser
         add_mem_op("Const", &tf_parser::parse_constant);
         add_mem_op("Conv2D", &tf_parser::parse_conv);
         add_mem_op("DepthwiseConv2dNative", &tf_parser::parse_depthwiseconv);
+        add_mem_op("ExpandDims", &tf_parser::parse_expanddims, false);
         add_mem_op("FusedBatchNorm", &tf_parser::parse_batchnorm);
         add_mem_op("MatMul", &tf_parser::parse_matmul, false);
         add_mem_op("MaxPool", &tf_parser::parse_pooling);
@@ -175,6 +180,7 @@ struct tf_parser
         add_mem_op("Softmax", &tf_parser::parse_softmax);
         add_mem_op("Squeeze", &tf_parser::parse_squeeze, false);
         add_mem_op("StridedSlice", &tf_parser::parse_stridedslice);
+        add_mem_op("Transpose", &tf_parser::parse_transpose, false);
     }
 
     template <class F>
@@ -490,6 +496,25 @@ struct tf_parser
         return prog.add_instruction(op, {l0, new_weights});
     }
 
+    instruction_ref
+    parse_expanddims(const std::string&, const attribute_map&, std::vector<instruction_ref> args)
+    {
+        std::vector<size_t> input_dims = args[0]->get_shape().lens();
+        std::vector<int64_t> new_dims(input_dims.begin(), input_dims.end());
+        size_t num_dims = input_dims.size();
+        int32_t dim     = args[1]->eval().at<int32_t>();
+
+        if(dim < 0)
+        {
+            new_dims.insert(new_dims.begin() + (num_dims + dim + 1), 1);
+        }
+        else
+        {
+            new_dims.insert(new_dims.begin() + dim, 1);
+        }
+        return prog.add_instruction(op::reshape{new_dims}, args[0]);
+    }
+
     instruction_ref
     parse_matmul(const std::string&, attribute_map attributes, std::vector<instruction_ref> args)
     {
@@ -519,11 +544,12 @@ struct tf_parser
     instruction_ref
     parse_mean(const std::string&, attribute_map attributes, std::vector<instruction_ref> args)
     {
-        auto axes      = parse_axes(args[1]->eval().get<int32_t>().to_vector());
         bool keep_dims = attributes.at("keep_dims").b();
         std::vector<int32_t> hw_axes{2, 3};
         // check if conditions for GlobalAvgPool are met
         auto lens = args[0]->get_shape().lens();
+        auto axes = parse_axes(args[1]->eval().get<int32_t>().to_vector(), lens.size());
+
         if(axes == hw_axes and lens.size() == 4)
         {
             op::pooling op{"average"};
@@ -694,14 +720,15 @@ struct tf_parser
                                   std::vector<instruction_ref> args)
     {
         op::squeeze op;
-        auto axes = attributes.at("squeeze_dims").list().i();
+        auto input_dims = args[0]->get_shape().lens();
+        auto axes       = attributes.at("squeeze_dims").list().i();
         copy(axes, std::back_inserter(op.axes));
-        auto args0_dims = args[0]->get_shape().lens();
+
         if(op.axes.empty()) // no squeeze_dims provided, remove any dim that equals 1
         {
-            for(size_t i = 0; i < args0_dims.size(); i++)
+            for(size_t i = 0; i < input_dims.size(); i++)
             {
-                if(args0_dims.at(i) == 1)
+                if(input_dims.at(i) == 1)
                 {
                     op.axes.push_back(i);
                 }
@@ -741,6 +768,16 @@ struct tf_parser
         return to_nhwc(prog.add_instruction(op::squeeze{squeeze_axes}, l0));
     }
 
+    instruction_ref
+    parse_transpose(const std::string&, const attribute_map&, std::vector<instruction_ref> args)
+    {
+        auto perm = args[1]->eval().get<int32_t>().to_vector();
+        op::transpose op;
+        op.dims = std::vector<int64_t>(perm.begin(), perm.end());
+
+        return prog.add_instruction(op, args.front());
+    }
+
     void parse_graph(const tensorflow::GraphDef& graph)
     {
         nodes = get_nodes(graph, input_nodes);

test/cpu_ops_test.cpp

@@ -542,6 +542,21 @@ TEST_CASE(erf_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(sqrt_test)
+{
+    migraphx::program p;
+    migraphx::shape s{migraphx::shape::float_type, {5}};
+    auto l = p.add_literal(
+        migraphx::literal{s, {1.02481645, 0.85643062, 0.03404123, 0.92791926, 0.10569184}});
+    p.add_instruction(migraphx::op::sqrt{}, l);
+    p.compile(migraphx::cpu::target{});
+    auto result = p.eval({});
+    std::vector<float> results_vector;
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = {1.01233218, 0.92543537, 0.18450265, 0.96328566, 0.32510282};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(log_test)
 {
     migraphx::program p;
@@ -556,6 +571,21 @@ TEST_CASE(log_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(pow_test)
+{
+    migraphx::program p;
+    migraphx::shape s{migraphx::shape::float_type, {3}};
+    auto b = p.add_literal(migraphx::literal{s, {1, 2, 3}});
+    auto e = p.add_literal(migraphx::literal{s, {1, 2, 3}});
+    p.add_instruction(migraphx::op::pow{}, b, e);
+    p.compile(migraphx::cpu::target{});
+    auto result = p.eval({});
+    std::vector<float> results_vector;
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = {1.0f, 4.0f, 27.0f};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(sin_test)
 {
     migraphx::program p;
@@ -1778,6 +1808,20 @@ TEST_CASE(reduce_sum_axis12)
     EXPECT(results_vector == gold);
 }
 
+TEST_CASE(rsqrt_test)
+{
+    migraphx::program p;
+    migraphx::shape s{migraphx::shape::float_type, {3}};
+    auto l = p.add_literal(migraphx::literal{s, {4.0, 16.0, 64.0}});
+    p.add_instruction(migraphx::op::rsqrt{}, l);
+    p.compile(migraphx::cpu::target{});
+    auto result = p.eval({});
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = {0.5, 0.25, 0.125};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(reduce_mean_axis1)
 {
     migraphx::program p;
@@ -1853,4 +1897,19 @@ TEST_CASE(reduce_mean_int)
     EXPECT(results_vector == gold);
 }
 
+TEST_CASE(sqdiff_test)
+{
+    migraphx::program p;
+    migraphx::shape s{migraphx::shape::float_type, {3}};
+    auto l1 = p.add_literal(migraphx::literal{s, {-1, 0, 1}});
+    auto l2 = p.add_literal(migraphx::literal{s, {1, 2, 3}});
+    p.add_instruction(migraphx::op::sqdiff{}, l1, l2);
+    p.compile(migraphx::cpu::target{});
+    auto result = p.eval({});
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = {4, 4, 4};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 int main(int argc, const char* argv[]) { test::run(argc, argv); }

test/gpu/miopen.cpp

@@ -255,6 +255,19 @@ struct test_erf : verify_program<test_erf>
     }
 };
 
+struct test_sqrt : verify_program<test_sqrt>
+{
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        migraphx::shape s{migraphx::shape::float_type, {2, 3, 4, 6}};
+        auto param     = p.add_parameter("x", s);
+        auto param_abs = p.add_instruction(migraphx::op::abs{}, param);
+        p.add_instruction(migraphx::op::sqrt{}, param_abs);
+        return p;
+    }
+};
+
 struct test_log : verify_program<test_log>
 {
     migraphx::program create_program() const
@@ -267,6 +280,20 @@ struct test_log : verify_program<test_log>
     }
 };
 
+struct test_pow : verify_program<test_pow>
+{
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        migraphx::shape s{migraphx::shape::float_type, {6}};
+        std::vector<float> vec_e(s.elements(), 2.0f);
+        auto b = p.add_parameter("x", s);
+        auto e = p.add_literal(migraphx::literal(s, vec_e));
+        p.add_instruction(migraphx::op::pow{}, b, e);
+        return p;
+    }
+};
+
 struct test_sin : verify_program<test_sin>
 {
     migraphx::program create_program() const
@@ -581,6 +608,38 @@ struct test_sub2 : verify_program<test_sub2>
     }
 };
 
+struct test_div : verify_program<test_div>
+{
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        migraphx::shape s{migraphx::shape::float_type, {3}};
+        auto x    = p.add_parameter("x", s);
+        auto y    = p.add_parameter("y", s);
+        auto z    = p.add_parameter("z", s);
+        auto diff = p.add_instruction(migraphx::op::div{}, x, y);
+        p.add_instruction(migraphx::op::div{}, diff, z);
+        return p;
+    }
+};
+
+struct test_div2 : verify_program<test_div2>
+{
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        migraphx::shape s{migraphx::shape::float_type, {2, 3}};
+        migraphx::shape b{migraphx::shape::float_type, {3}};
+        auto x    = p.add_parameter("x", s);
+        auto y    = p.add_parameter("y", s);
+        auto z    = p.add_parameter("z", b);
+        auto zb   = p.add_instruction(migraphx::op::broadcast{1, s.lens()}, z);
+        auto diff = p.add_instruction(migraphx::op::div{}, x, y);
+        p.add_instruction(migraphx::op::div{}, diff, zb);
+        return p;
+    }
+};
+
 struct test_softmax1 : verify_program<test_softmax1>
 {
     migraphx::program create_program() const
@@ -3511,6 +3570,19 @@ struct test_reduce_sum_half : verify_program<test_reduce_sum_half>
     };
 };
 
+struct test_rsqrt : verify_program<test_rsqrt>
+{
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        migraphx::shape s{migraphx::shape::float_type, {1, 3, 16, 16}};
+        auto x  = p.add_parameter("x", s);
+        auto l0 = p.add_instruction(migraphx::op::clip{std::numeric_limits<float>::max(), 1.0}, x);
+        p.add_instruction(migraphx::op::rsqrt{}, l0);
+        return p;
+    };
+};
+
 struct test_reduce_mean : verify_program<test_reduce_mean>
 {
     migraphx::program create_program() const

test/onnx/onnx_test.cpp

@@ -202,6 +202,16 @@ TEST_CASE(erf_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(sqrt_test)
+{
+    migraphx::program p;
+    auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10, 15}});
+    p.add_instruction(migraphx::op::sqrt{}, input);
+
+    auto prog = migraphx::parse_onnx("sqrt_test.onnx");
+    EXPECT(p == prog);
+}
+
 TEST_CASE(log_test)
 {
     migraphx::program p;
@@ -889,4 +899,30 @@ TEST_CASE(clip_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(implicit_pow_bcast_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
+    auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4, 1}});
+    auto l2 = p.add_instruction(migraphx::op::multibroadcast{{2, 3, 4, 5}}, l0);
+    auto l3 = p.add_instruction(migraphx::op::multibroadcast{{2, 3, 4, 5}}, l1);
+    p.add_instruction(migraphx::op::pow{}, l2, l3);
+
+    auto prog = migraphx::parse_onnx("pow_bcast_test.onnx");
+
+    EXPECT(p == prog);
+}
+
+TEST_CASE(pow_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
+    auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
+    p.add_instruction(migraphx::op::pow{}, l0, l1);
+
+    auto prog = migraphx::parse_onnx("pow_bcast_test1.onnx");
+
+    EXPECT(p == prog);
+}
+
 int main(int argc, const char* argv[]) { test::run(argc, argv); }

test/onnx/pow_bcast_test.onnx

+pow2:q
+
+
0
+
1out"Powpow_testZ
+
0
+

+
+
+
+Z
+
1
+

+
+
+
b
+out
+

+
+
+
+B

test/onnx/pow_bcast_test1.onnx

+pow2:u
+
+
0
+
1out"Powpow_testZ
+
0
+

+
+
+
+Z
+
1
+

+
+
+
+b
+out
+

+
+
+
+B

test/onnx/sqrt_test.onnx

+sqrt-example:C
+
+
x
y"Sqrt	test_sqrtZ
+
x
+

+
+
+b
+
y
+

+
+
+B

test/tf/rsqrt_test.pb

+
+:
+
0Placeholder*
+shape:
*
+dtype0

+
+rsqrtRsqrt
0*
+
T0
"
\ No newline at end of file

test/tf/sqdiff_test.pb

+
+:
+
0Placeholder*
+dtype0
*
+shape:

+:
+
1Placeholder*
+dtype0
*
+shape:

+*
+sqdiffSquaredDifference
0
1*
+
T0
"
\ No newline at end of file

test/tf/stopgradient_test.pb

+
+:
+
0Placeholder*
+dtype0
*
+shape:

+(
+stopgradientStopGradient
0*
+
T0
"
\ No newline at end of file

test/tf/tf_test.cpp

@@ -159,6 +159,31 @@ TEST_CASE(depthwiseconv_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(expanddims_test)
+{
+    migraphx::program p;
+
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4}});
+    p.add_literal(0);
+    p.add_instruction(migraphx::op::reshape{{1, 2, 3, 4}}, l0);
+    auto prog = optimize_tf("expanddims_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
+TEST_CASE(expanddims_test_neg_dims)
+{
+    // this check makes sure the pb parses negative dim value correctly
+    migraphx::program p;
+
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4}});
+    p.add_literal(-1);
+    p.add_instruction(migraphx::op::reshape{{2, 3, 4, 1}}, l0);
+    auto prog = optimize_tf("expanddims_neg_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(identity_test)
 {
     migraphx::program p;
@@ -326,6 +351,16 @@ TEST_CASE(reshape_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(rsqrt_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
+    p.add_instruction(migraphx::op::rsqrt{}, l0);
+    auto prog = optimize_tf("rsqrt_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(softmax_test)
 {
     migraphx::program p;
@@ -339,6 +374,17 @@ TEST_CASE(softmax_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(sqdiff_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 2, 2, 3}});
+    auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {1, 2, 2, 3}});
+    p.add_instruction(migraphx::op::sqdiff{}, l0, l1);
+    auto prog = optimize_tf("sqdiff_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(squeeze_test)
 {
     migraphx::program p;
@@ -349,6 +395,16 @@ TEST_CASE(squeeze_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(stopgradient_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
+    p.add_instruction(migraphx::op::identity{}, l0);
+    auto prog = optimize_tf("stopgradient_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(stridedslice_test)
 {
     migraphx::program p;
@@ -389,4 +445,16 @@ TEST_CASE(tanh_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(transpose_test)
+{
+    migraphx::program p;
+    auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {1, 3, 16, 16}});
+    migraphx::shape s0{migraphx::shape::int32_type, {4}};
+    p.add_literal(migraphx::literal{s0, {0, 2, 3, 1}});
+    p.add_instruction(migraphx::op::transpose{{0, 2, 3, 1}}, l0);
+    auto prog = optimize_tf("transpose_test.pb", false);
+
+    EXPECT(p == prog);
+}
+
 int main(int argc, const char* argv[]) { test::run(argc, argv); }