merge changes from int8_miopen_call

CMakeLists.txt

@@ -32,7 +32,9 @@ if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
     endif()
 endif()
 
-if(CMAKE_CXX_COMPILER MATCHES ".*hcc")
+include(CheckCXXCompilerFlag)
+check_cxx_compiler_flag("--cuda-host-only -x hip" HAS_HIP)
+if(HAS_HIP)
     message(STATUS "Enable miopen backend")
     set(MIGRAPHX_ENABLE_GPU On CACHE BOOL "")
 else()

src/targets/gpu/CMakeLists.txt

@@ -37,7 +37,7 @@ add_library(migraphx_device
     device/pad.cpp
     device/gather.cpp
     device/sub.cpp
-    device/pack.cpp
+    device/int8_gemm_pack.cpp
     device/div.cpp
     device/clip.cpp
     device/reduce_sum.cpp
@@ -85,9 +85,12 @@ add_library(migraphx_gpu
     lrn.cpp
     schedule_model.cpp
     adjust_allocation.cpp
+    pack_int8_args.cpp
     clip.cpp
     reduce_sum.cpp
     reduce_mean.cpp
+    int8_gemm_pack.cpp
+    int8_conv_pack.cpp
 )
 set_target_properties(migraphx_gpu PROPERTIES EXPORT_NAME gpu)
 rocm_clang_tidy_check(migraphx_gpu)

src/targets/gpu/device/pack.cpp → src/targets/gpu/device/int8_gemm_pack.cpp

 #include <migraphx/shape.hpp>
 #include <migraphx/argument.hpp>
-#include <migraphx/gpu/device/pack.hpp>
-#include <migraphx/gpu/device/tensor.hpp>
+#include <migraphx/gpu/device/int8_gemm_pack.hpp>
 #include <migraphx/gpu/device/launch.hpp>
 #include <migraphx/gpu/device/types.hpp>
+#include <migraphx/gpu/device/tensor.hpp>
 #include <migraphx/gpu/hip.hpp>
 
 namespace migraphx {
@@ -11,7 +11,7 @@ inline namespace MIGRAPHX_INLINE_NS {
 namespace gpu {
 namespace device {
 
-void pack_a(hipStream_t stream, const argument& result, const argument& arg)
+void int8_gemm_pack_a(hipStream_t stream, const argument& result, const argument& arg)
 {
     auto comp_shape    = arg.get_shape();
     auto out_lens      = comp_shape.lens();
@@ -38,7 +38,7 @@ void pack_a(hipStream_t stream, const argument& result, const argument& arg)
     });
 }
 
-void pack_b(hipStream_t stream, const argument& result, const argument& arg)
+void int8_gemm_pack_b(hipStream_t stream, const argument& result, const argument& arg)
 {
     auto trans_shape = arg.get_shape();
     auto out_lens    = trans_shape.lens();

src/targets/gpu/include/migraphx/gpu/device/pack.hpp → src/targets/gpu/include/migraphx/gpu/device/int8_gemm_pack.hpp

-#ifndef MIGRAPHX_GUARD_RTGLIB_DEVICE_PACK_HPP
-#define MIGRAPHX_GUARD_RTGLIB_DEVICE_PACK_HPP
+#ifndef MIGRAPHX_GUARD_RTGLIB_DEVICE_INT8_GEMM_PACK_HPP
+#define MIGRAPHX_GUARD_RTGLIB_DEVICE_INT8_GEMM_PACK_HPP
 
 #include <migraphx/argument.hpp>
 #include <migraphx/config.hpp>
@@ -10,11 +10,9 @@ inline namespace MIGRAPHX_INLINE_NS {
 namespace gpu {
 namespace device {
 
-void pack_a(hipStream_t stream, const argument& result, const argument& arg);
+void int8_gemm_pack_a(hipStream_t stream, const argument& result, const argument& arg);
 
-void pack_b(hipStream_t stream, const argument& result, const argument& arg);
-
-void sync_stream(hipStream_t stream);
+void int8_gemm_pack_b(hipStream_t stream, const argument& result, const argument& arg);
 
 } // namespace device
 } // namespace gpu

src/targets/gpu/include/migraphx/gpu/int8_conv_pack.hpp

+#ifndef MIGRAPHX_GUARD_RTGLIB_INT8_CONV_PACK_HPP
+#define MIGRAPHX_GUARD_RTGLIB_INT8_CONV_PACK_HPP
+
+#include <migraphx/op/quant_dot.hpp>
+#include <migraphx/config.hpp>
+#include <utility>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+struct context;
+
+struct miopen_int8_conv_pack
+{
+    std::string name() const { return "gpu::int8_conv_pack"; }
+    shape compute_shape(const std::vector<shape>& inputs) const;
+    argument compute(context& ctx, const shape&, const std::vector<argument>& args) const;
+    std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
+    {
+        return shapes.size() - 1;
+    }
+};
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/targets/gpu/include/migraphx/gpu/int8_gemm_pack.hpp

+#ifndef MIGRAPHX_GUARD_RTGLIB_INT8_GEMM_PACK_HPP
+#define MIGRAPHX_GUARD_RTGLIB_INT8_GEMM_PACK_HPP
+
+#include <migraphx/op/quant_dot.hpp>
+#include <migraphx/config.hpp>
+#include <utility>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+struct context;
+
+struct hip_int8_gemm_pack_a
+{
+    std::string name() const { return "gpu::int8_gemm_pack_a"; }
+    shape compute_shape(const std::vector<shape>& inputs) const;
+    argument compute(context& ctx, const shape&, const std::vector<argument>& args) const;
+    std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
+    {
+        return shapes.size() - 1;
+    }
+};
+
+struct hip_int8_gemm_pack_b
+{
+    std::string name() const { return "gpu::int8_gemm_pack_b"; }
+    shape compute_shape(const std::vector<shape>& inputs) const;
+    argument compute(context& ctx, const shape&, const std::vector<argument>& args) const;
+    std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
+    {
+        return shapes.size() - 1;
+    }
+};
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/targets/gpu/include/migraphx/gpu/pack_int8_args.hpp

+#ifndef MIGRAPHX_GUARD_RTGLIB_PACK_INT8_ARGS_HPP
+#define MIGRAPHX_GUARD_RTGLIB_PACK_INT8_ARGS_HPP
+
+#include <migraphx/program.hpp>
+#include <migraphx/config.hpp>
+#include <migraphx/gpu/context.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+
+namespace gpu {
+
+struct pack_int8_args
+{
+    std::string name() const { return "gpu::pack_int8_args"; }
+    void apply(program& p) const;
+    shape pack_int8_shape(const shape& s) const;
+};
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

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

@@ -17,8 +17,6 @@ struct miopen_quant_convolution
     shared<convolution_descriptor> cd;
     miopenConvFwdAlgorithm_t algo{};
     miopenHandle_t handle = nullptr;
-    argument arg_vec4_x{};
-    argument arg_vec4_w{};
 
     template <class Self, class F>
     static auto reflect(Self& self, F f)
@@ -39,7 +37,7 @@ struct miopen_quant_convolution
     }
 
     private:
-    shape pack_int8_shape(shape& s);
+    shape pack_int8_shape(const shape& s) const;
 };
 
 } // namespace gpu

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

@@ -10,7 +10,7 @@ namespace gpu {
 
 struct context;
 
-struct miopen_quant_gemm
+struct rocblas_quant_gemm
 {
     op::quant_dot op;
 
@@ -24,6 +24,7 @@ struct miopen_quant_gemm
     shape compute_shape(const std::vector<shape>& inputs) const;
     argument
     compute(context& ctx, const shape& output_shape, const std::vector<argument>& args) const;
+    void batch_not_transposed(const std::vector<std::size_t>& strides) const;
     std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
     {
         return shapes.size() - 1;

src/targets/gpu/int8_conv_pack.cpp

+#include <migraphx/gpu/int8_conv_pack.hpp>
+#include <migraphx/gpu/context.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+shape miopen_int8_conv_pack::compute_shape(const std::vector<shape>& inputs) const
+{
+    check_shapes{{inputs.at(0)}, *this}.has(1).standard();
+    return inputs.at(0);
+}
+
+argument
+miopen_int8_conv_pack::compute(context& ctx, const shape&, const std::vector<argument>& args) const
+{
+    auto arg_desc      = make_tensor(args[0].get_shape());
+    auto arg_desc_vec4 = make_tensor(args[0].get_shape(), true);
+
+    float alpha = 1;
+    float beta  = 0;
+    // pack input to vec4 format
+    auto status = miopenTransformTensor(ctx.get_stream().get_miopen(),
+                                        &alpha,
+                                        arg_desc.get(),
+                                        args[0].implicit(),
+                                        &beta,
+                                        arg_desc_vec4.get(),
+                                        args[1].implicit());
+    if(status != miopenStatusSuccess)
+    {
+        MIGRAPHX_THROW("INT8_CONV_PACK: transform input tensor failed");
+    }
+
+    return args[1];
+}
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/targets/gpu/int8_gemm_pack.cpp

+#include <migraphx/gpu/int8_gemm_pack.hpp>
+#include <migraphx/gpu/device/int8_gemm_pack.hpp>
+#include <migraphx/gpu/context.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+shape hip_int8_gemm_pack_a::compute_shape(const std::vector<shape>& inputs) const
+{
+    check_shapes{{inputs.at(0)}, *this}.has(1).not_broadcasted().packed();
+    return inputs.at(0);
+}
+
+argument
+hip_int8_gemm_pack_a::compute(context& ctx, const shape&, const std::vector<argument>& args) const
+{
+    device::int8_gemm_pack_a(ctx.get_stream().get(), args[1], args[0]);
+    return args[1];
+}
+
+shape hip_int8_gemm_pack_b::compute_shape(const std::vector<shape>& inputs) const
+{
+    check_shapes{{inputs.at(0)}, *this}.has(1).not_broadcasted().packed();
+    return inputs.at(0);
+}
+
+argument
+hip_int8_gemm_pack_b::compute(context& ctx, const shape&, const std::vector<argument>& args) const
+{
+    device::int8_gemm_pack_b(ctx.get_stream().get(), args[1], args[0]);
+    return args[1];
+}
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/targets/gpu/lowering.cpp

@@ -59,6 +59,7 @@
 #include <migraphx/gpu/reduce_mean.hpp>
 #include <migraphx/gpu/pow.hpp>
 #include <migraphx/gpu/sqdiff.hpp>
+#include <migraphx/gpu/int8_conv_pack.hpp>
 #include <utility>
 #include <functional>
 #include <algorithm>
@@ -115,6 +116,7 @@ struct miopen_apply
         add_generic_op<hip_sqdiff>("sqdiff");
 
         add_extend_op<miopen_gemm, op::dot>("dot");
+        add_extend_op<rocblas_quant_gemm, op::quant_dot>("quant_dot");
         add_extend_op<miopen_contiguous, op::contiguous>("contiguous");
         add_extend_op<hip_concat, op::concat>("concat");
         add_extend_op<hip_softmax, op::softmax>("softmax");
@@ -131,7 +133,7 @@ struct miopen_apply
         add_lrn_op();
         add_convolution_op();
         add_quant_convolution_op();
-        add_quant_dot_op();
+        // add_quant_dot_op();
         add_pooling_op();
         add_batch_norm_inference_op();
     }
@@ -182,32 +184,14 @@ struct miopen_apply
     {
         apply_map.emplace("quant_convolution", [=](instruction_ref ins) {
             auto&& op = any_cast<op::quant_convolution>(ins->get_operator());
-
             auto conv = miopen_quant_convolution{op, make_conv(op)};
             auto ws   = conv.compile(ctx, ins->get_shape(), to_shapes(ins->inputs()));
 
+            auto args      = ins->inputs();
             auto workspace = insert_allocation(ins, ws, "workspace");
             auto output    = insert_allocation(ins, ins->get_shape());
 
-            return prog->replace_instruction(
-                ins, conv, ins->inputs().at(0), ins->inputs().at(1), workspace, output);
-        });
-    }
-
-    void add_quant_dot_op()
-    {
-        apply_map.emplace("quant_dot", [=](instruction_ref ins) {
-            auto&& op      = any_cast<op::quant_dot>(ins->get_operator());
-            auto inputs    = ins->inputs();
-            auto in_shapes = to_shapes(inputs);
-            auto pack_a    = insert_allocation(ins, in_shapes[0], "pack_a");
-            auto pack_b    = insert_allocation(ins, in_shapes[1], "pack_b");
-            auto output    = insert_allocation(ins, ins->get_shape());
-            inputs.push_back(pack_a);
-            inputs.push_back(pack_b);
-            inputs.push_back(output);
-
-            return prog->replace_instruction(ins, miopen_quant_gemm{op}, inputs);
+            return prog->replace_instruction(ins, conv, args[0], args[1], workspace, output);
         });
     }
 

src/targets/gpu/pack_int8_args.cpp

+#include <migraphx/gpu/pack_int8_args.hpp>
+#include <migraphx/gpu/int8_gemm_pack.hpp>
+#include <migraphx/gpu/int8_conv_pack.hpp>
+#include <migraphx/gpu/hip.hpp>
+#include <migraphx/instruction.hpp>
+#include <migraphx/program.hpp>
+#include <migraphx/iterator_for.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+void pack_int8_args::apply(program& p) const
+{
+    for(auto ins : iterator_for(p))
+    {
+        if(ins->name() == "gpu::quant_gemm")
+        {
+            auto inputs = ins->inputs();
+            bool transa = inputs[0]->get_shape().transposed();
+            bool transb = inputs[1]->get_shape().transposed();
+
+            if(!transb)
+            {
+                auto packed_b = p.insert_instruction(ins, hip_allocate{inputs[1]->get_shape()});
+                auto output_b =
+                    p.insert_instruction(ins, hip_int8_gemm_pack_a{}, {inputs[1], packed_b});
+                instruction::replace_argument(ins, inputs[1], output_b);
+            }
+
+            if(transa)
+            {
+                auto packed_a = p.insert_instruction(ins, hip_allocate{inputs[0]->get_shape()});
+                auto output_a =
+                    p.insert_instruction(ins, hip_int8_gemm_pack_b{}, {inputs[0], packed_a});
+                instruction::replace_argument(ins, inputs[0], output_a);
+            }
+        }
+        else if(ins->name() == "gpu::quant_convolution")
+        {
+            auto inputs = ins->inputs();
+            auto packed_x =
+                p.insert_instruction(ins, hip_allocate{pack_int8_shape(inputs[0]->get_shape())});
+            auto output_x =
+                p.insert_instruction(ins, miopen_int8_conv_pack{}, {inputs[0], packed_x});
+            instruction::replace_argument(ins, inputs[0], output_x);
+
+            auto packed_w =
+                p.insert_instruction(ins, hip_allocate{pack_int8_shape(inputs[1]->get_shape())});
+            auto output_w =
+                p.insert_instruction(ins, miopen_int8_conv_pack{}, {inputs[1], packed_w});
+            instruction::replace_argument(ins, inputs[1], output_w);
+        }
+    }
+}
+
+shape pack_int8_args::pack_int8_shape(const shape& s) const
+{
+    if(s.type() != shape::int8_type)
+    {
+        MIGRAPHX_THROW("PACK_INT8_ARGS: only process int8_type");
+    }
+
+    auto lens    = s.lens();
+    auto strides = s.strides();
+    lens[1]      = (lens[1] + 3) / 4 * 4;
+    strides[0]   = strides[1] * lens[1];
+
+    return {s.type(), lens, strides};
+}
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/targets/gpu/quant_convolution.cpp

@@ -16,54 +16,26 @@ argument miopen_quant_convolution::compute(context& ctx,
                                            const shape& output_shape,
                                            const std::vector<argument>& args) const
 {
-    auto x_desc      = make_tensor(args[0].get_shape());
-    auto x_desc_vec4 = make_tensor(args[0].get_shape(), true);
-    auto w_desc      = make_tensor(args[1].get_shape());
-    auto w_desc_vec4 = make_tensor(args[1].get_shape(), true);
-    auto y_desc      = make_tensor(output_shape);
+    auto x_desc = make_tensor(args[0].get_shape(), true);
+    auto w_desc = make_tensor(args[1].get_shape(), true);
+    auto y_desc = make_tensor(output_shape);
 
     float alpha = 1;
     float beta  = 0;
 
-    // pack input to vec4 format
-    auto status = miopenTransformTensor(ctx.get_stream().get_miopen(),
-                                        &alpha,
-                                        x_desc.get(),
-                                        args[0].implicit(),
-                                        &beta,
-                                        x_desc_vec4.get(),
-                                        arg_vec4_x.implicit());
-    if(status != miopenStatusSuccess)
-    {
-        MIGRAPHX_THROW("QUANT_CONVOLUTION: transform input tensor failed");
-    }
-
-    // pack input to vec4 format
-    status = miopenTransformTensor(ctx.get_stream().get_miopen(),
-                                   &alpha,
-                                   w_desc.get(),
-                                   args[1].implicit(),
-                                   &beta,
-                                   w_desc_vec4.get(),
-                                   arg_vec4_w.implicit());
-    if(status != miopenStatusSuccess)
-    {
-        MIGRAPHX_THROW("QUANT_CONVOLUTION: transform weight tensor failed");
-    }
-
-    status = miopenConvolutionForward(ctx.get_stream().get_miopen(),
-                                      &alpha,
-                                      x_desc_vec4.get(),
-                                      arg_vec4_x.implicit(),
-                                      w_desc_vec4.get(),
-                                      arg_vec4_w.implicit(),
-                                      cd.get(),
-                                      algo,
-                                      &beta,
-                                      y_desc.get(),
-                                      args[3].implicit(),
-                                      args[2].implicit(),
-                                      args[2].get_shape().bytes());
+    auto status = miopenConvolutionForward(ctx.get_stream().get_miopen(),
+                                           &alpha,
+                                           x_desc.get(),
+                                           args[0].implicit(),
+                                           w_desc.get(),
+                                           args[1].implicit(),
+                                           cd.get(),
+                                           algo,
+                                           &beta,
+                                           y_desc.get(),
+                                           args[3].implicit(),
+                                           args[2].implicit(),
+                                           args[2].get_shape().bytes());
     if(status != miopenStatusSuccess)
     {
         MIGRAPHX_THROW("QUANT_CONVOLUTION: run convolution forward failed");
@@ -90,10 +62,10 @@ shape miopen_quant_convolution::compile(context& ctx,
                                              &workspace_size);
     workspace_shape = shape{shape::int8_type, {workspace_size}};
 
-    arg_vec4_x     = to_gpu(generate_argument(pack_int8_shape(inputs[0])));
-    arg_vec4_w     = to_gpu(generate_argument(pack_int8_shape(inputs[1])));
-    auto y         = allocate_gpu(output_shape);
-    auto workspace = allocate_gpu(workspace_shape);
+    auto arg_vec4_x = to_gpu(generate_argument(pack_int8_shape(inputs[0])));
+    auto arg_vec4_w = to_gpu(generate_argument(pack_int8_shape(inputs[1])));
+    auto y          = allocate_gpu(output_shape);
+    auto workspace  = allocate_gpu(workspace_shape);
 
     int algo_count = 1;
     miopenConvAlgoPerf_t perf;
@@ -133,7 +105,7 @@ void miopen_quant_convolution::finalize(context& ctx,
         MIGRAPHX_THROW("Workspace has changed during finalization.");
 }
 
-shape miopen_quant_convolution::pack_int8_shape(shape& s)
+shape miopen_quant_convolution::pack_int8_shape(const shape& s) const
 {
     if(s.type() != shape::int8_type)
     {

src/targets/gpu/quant_gemm.cpp

 #include <migraphx/gpu/quant_gemm.hpp>
-#include <migraphx/gpu/device/pack.hpp>
 #include <migraphx/gpu/context.hpp>
 #include <migraphx/generate.hpp>
 #include <fstream>
@@ -54,43 +53,46 @@ rb_type<T>* to_rocblas_type(T* x)
     return reinterpret_cast<rb_type<T>*>(x);
 }
 
-shape miopen_quant_gemm::compute_shape(const std::vector<shape>& inputs) const
+shape rocblas_quant_gemm::compute_shape(const std::vector<shape>& inputs) const
 {
     std::vector<shape> in_shapes(inputs);
-    in_shapes.erase(in_shapes.begin() + in_shapes.size() - 3, in_shapes.end());
+    in_shapes.pop_back();
     check_shapes{in_shapes}.not_broadcasted();
+    batch_not_transposed(inputs[0].strides());
+    batch_not_transposed(inputs[1].strides());
 
     return op.compute_shape(in_shapes);
 }
 
-argument miopen_quant_gemm::compute(context& ctx,
-                                    const shape& output_shape,
-                                    const std::vector<argument>& args) const
+void rocblas_quant_gemm::batch_not_transposed(const std::vector<std::size_t>& strides) const
+{
+    if(strides.size() <= 2)
+        return;
+    auto dim_0       = strides.size() - 2;
+    auto matrix_size = std::max(strides[dim_0], strides[dim_0 + 1]);
+    std::vector<std::size_t> batch(strides.begin(), strides.begin() + dim_0);
+    if(std::adjacent_find(batch.begin(), batch.end(), [&](auto i, auto j) {
+           return (i < j or i < matrix_size or j < matrix_size);
+       }) != batch.end())
+    {
+        MIGRAPHX_THROW("QUANT_DOT: batch size {" + to_string_range(strides) + "} is transposed!");
+    }
+}
+
+argument rocblas_quant_gemm::compute(context& ctx,
+                                     const shape& output_shape,
+                                     const std::vector<argument>& args) const
 {
     bool transa     = args[0].get_shape().transposed();
     bool transb     = args[1].get_shape().transposed();
     auto n_dim      = output_shape.lens().size();
     auto dim_1      = n_dim - 1;
     auto dim_0      = n_dim - 2;
-    auto arg_num    = args.size();
     rocblas_int lda = args[0].get_shape().strides()[transa ? dim_1 : dim_0];
     rocblas_int ldb = args[1].get_shape().strides()[transb ? dim_1 : dim_0];
-    rocblas_int ldc = args[arg_num - 1].get_shape().strides()[dim_0];
-
-    if(!transb)
-    {
-        device::pack_a(ctx.get_stream().get(), args[arg_num - 2], args[1]);
-    }
-
-    // need to pack A in this scenario, use the algorithm to pack B in the
-    // comment of the API
-    if(transa)
-    {
-        device::pack_b(ctx.get_stream().get(), args[arg_num - 3], args[0]);
-    }
-    device::sync_stream(ctx.get_stream().get());
+    rocblas_int ldc = args[2].get_shape().strides()[dim_0];
 
-    bool is_3inputs = (arg_num == 6);
+    bool is_3inputs = (args.size() == 4);
     int32_t beta    = 0;
     if(is_3inputs)
     {
@@ -124,18 +126,17 @@ argument miopen_quant_gemm::compute(context& ctx,
                                     m,
                                     k,
                                     &alpha_r,
-                                    (!transb) ? to_pointer(args[arg_num - 2])
-                                              : to_pointer(args.at(1)),
+                                    to_pointer(args.at(1)),
                                     rocblas_datatype_i8_r,
                                     ldb,
-                                    transa ? to_pointer(args[arg_num - 3]) : to_pointer(args.at(0)),
+                                    to_pointer(args.at(0)),
                                     rocblas_datatype_i8_r,
                                     lda,
                                     &beta_r,
                                     to_pointer(args[2]),
                                     rocblas_datatype_i32_r,
                                     ldc,
-                                    to_pointer(args[arg_num - 1]),
+                                    is_3inputs ? to_pointer(args[3]) : to_pointer(args[2]),
                                     rocblas_datatype_i32_r,
                                     ldc,
                                     rocblas_datatype_i32_r,
@@ -155,11 +156,11 @@ argument miopen_quant_gemm::compute(context& ctx,
                 m,
                 k,
                 &alpha_r,
-                (!transb) ? to_pointer(args[arg_num - 2]) : to_pointer(args.at(1)),
+                to_pointer(args.at(1)),
                 rocblas_datatype_i8_r,
                 ldb,
                 k * n,
-                transa ? to_pointer(args[arg_num - 3]) : to_pointer(args.at(0)),
+                to_pointer(args.at(0)),
                 rocblas_datatype_i8_r,
                 lda,
                 m * k,
@@ -168,7 +169,7 @@ argument miopen_quant_gemm::compute(context& ctx,
                 rocblas_datatype_i32_r,
                 ldc,
                 m * n,
-                to_pointer(args[arg_num - 1]),
+                is_3inputs ? to_pointer(args[3]) : to_pointer(args[2]),
                 rocblas_datatype_i32_r,
                 ldc,
                 m * n,
@@ -182,7 +183,7 @@ argument miopen_quant_gemm::compute(context& ctx,
         }
     });
 
-    return args[arg_num - 1];
+    return is_3inputs ? args[3] : args[2];
 }
 
 } // namespace gpu

src/targets/gpu/target.cpp

@@ -21,6 +21,7 @@
 #include <migraphx/gpu/concat_gpu_opt.hpp>
 #include <migraphx/gpu/schedule_model.hpp>
 #include <migraphx/gpu/adjust_allocation.hpp>
+#include <migraphx/gpu/pack_int8_args.hpp>
 #include <migraphx/eliminate_pad.hpp>
 #include <migraphx/schedule.hpp>
 
@@ -62,6 +63,8 @@ std::vector<pass> target::get_passes(migraphx::context& gctx) const
         dead_code_elimination{},
         adjust_allocation{},
         dead_code_elimination{},
+        pack_int8_args{},
+        dead_code_elimination{},
         fuse_ops{&ctx},
         dead_code_elimination{},
         write_literals{&ctx},

test/gpu/miopen.cpp

@@ -663,13 +663,13 @@ struct test_softmax2 : verify_program<test_softmax2>
     }
 };
 
-template <int Axis>
-struct test_softmax : verify_program<test_softmax<Axis>>
+template <int Axis, migraphx::shape::type_t T>
+struct test_softmax : verify_program<test_softmax<Axis, T>>
 {
     migraphx::program create_program() const
     {
         migraphx::program p;
-        migraphx::shape s{migraphx::shape::float_type, {3, 4, 5, 6}};
+        migraphx::shape s{T, {512, 4, 1067, 6}};
         auto param = p.add_parameter("0", s);
         p.add_instruction(migraphx::op::softmax{Axis}, param);
 
@@ -677,10 +677,38 @@ struct test_softmax : verify_program<test_softmax<Axis>>
     }
 };
 
-template struct test_softmax<0>;
-template struct test_softmax<1>;
-template struct test_softmax<2>;
-template struct test_softmax<3>;
+template struct test_softmax<0, migraphx::shape::float_type>;
+template struct test_softmax<2, migraphx::shape::float_type>;
+template struct test_softmax<1, migraphx::shape::double_type>;
+template struct test_softmax<3, migraphx::shape::double_type>;
+template struct test_softmax<0, migraphx::shape::half_type>;
+template struct test_softmax<1, migraphx::shape::half_type>;
+template struct test_softmax<2, migraphx::shape::half_type>;
+template struct test_softmax<3, migraphx::shape::half_type>;
+
+template <class T, int Axis>
+struct test_arg_ops : verify_program<test_arg_ops<T, Axis>>
+{
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        migraphx::shape s{migraphx::shape::float_type, {2, 3, 4, 1025}};
+        auto param = p.add_parameter("data", s);
+        p.add_instruction(T{Axis}, param);
+
+        return p;
+    }
+};
+
+template struct test_arg_ops<migraphx::op::argmax, 0>;
+template struct test_arg_ops<migraphx::op::argmax, 1>;
+template struct test_arg_ops<migraphx::op::argmax, 2>;
+template struct test_arg_ops<migraphx::op::argmax, 3>;
+
+template struct test_arg_ops<migraphx::op::argmin, 0>;
+template struct test_arg_ops<migraphx::op::argmin, 1>;
+template struct test_arg_ops<migraphx::op::argmin, 2>;
+template struct test_arg_ops<migraphx::op::argmin, 3>;
 
 struct test_conv : verify_program<test_conv>
 {
@@ -3601,32 +3629,13 @@ struct test_lstm_bidirct_default_actv2 : verify_program<test_lstm_bidirct_defaul
     }
 };
 
-template <int Axis>
-struct test_logsoftmax : verify_program<test_logsoftmax<Axis>>
-{
-    migraphx::program create_program() const
-    {
-        migraphx::program p;
-        migraphx::shape s{migraphx::shape::float_type, {3, 4, 5, 6}};
-        auto param = p.add_parameter("0", s);
-        p.add_instruction(migraphx::op::logsoftmax{Axis}, param);
-
-        return p;
-    }
-};
-
-template struct test_logsoftmax<0>;
-template struct test_logsoftmax<1>;
-template struct test_logsoftmax<2>;
-template struct test_logsoftmax<3>;
-
-template <int Axis>
-struct test_logsoftmax_1 : verify_program<test_logsoftmax_1<Axis>>
+template <int Axis, migraphx::shape::type_t T>
+struct test_logsoftmax : verify_program<test_logsoftmax<Axis, T>>
 {
     migraphx::program create_program() const
     {
         migraphx::program p;
-        migraphx::shape s{migraphx::shape::float_type, {3}};
+        migraphx::shape s{T, {10, 4, 2080, 6}};
         auto param = p.add_parameter("0", s);
         p.add_instruction(migraphx::op::logsoftmax{Axis}, param);
 
@@ -3634,7 +3643,16 @@ struct test_logsoftmax_1 : verify_program<test_logsoftmax_1<Axis>>
     }
 };
 
-template struct test_logsoftmax_1<0>;
+template struct test_logsoftmax<0, migraphx::shape::float_type>;
+template struct test_logsoftmax<1, migraphx::shape::float_type>;
+template struct test_logsoftmax<2, migraphx::shape::float_type>;
+template struct test_logsoftmax<3, migraphx::shape::float_type>;
+template struct test_logsoftmax<1, migraphx::shape::double_type>;
+template struct test_logsoftmax<3, migraphx::shape::double_type>;
+template struct test_logsoftmax<1, migraphx::shape::half_type>;
+template struct test_logsoftmax<0, migraphx::shape::half_type>;
+template struct test_logsoftmax<2, migraphx::shape::half_type>;
+template struct test_logsoftmax<3, migraphx::shape::half_type>;
 
 struct test_fp32_fp16_lall : verify_program<test_fp32_fp16_lall>
 {