Merge remote-tracking branch 'origin/develop' into ck-gsg

src/include/migraphx/pass_config.hpp → test/verify/test_select_module_add.cpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * Copyright (c) 2015-2023 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
@@ -22,17 +22,56 @@
  * THE SOFTWARE.
  */
 
-#ifndef MIGRAPHX_GUARD_PASS_CONFIG_HPP
-#define MIGRAPHX_GUARD_PASS_CONFIG_HPP
+#include "verify_program.hpp"
+#include <migraphx/program.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/make_op.hpp>
 
-#include <migraphx/env.hpp>
-#include <migraphx/config.hpp>
+struct test_select_module_add : verify_program<test_select_module_add>
+{
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+        migraphx::shape lit_s{migraphx::shape{migraphx::shape::float_type, {1}}};
+        auto literal_ins = mm->add_literal(migraphx::literal{lit_s, {6}});
 
-namespace migraphx {
-inline namespace MIGRAPHX_INLINE_NS {
+        // create batch submodules
+        auto create_submodule = [&](std::size_t batch_size, const std::string& module_name) {
+            auto* submod = p.create_module(module_name);
+            migraphx::shape sm_shape{migraphx::shape::float_type, {batch_size, 4}};
+            auto sm_input = submod->add_parameter("data", sm_shape);
+            auto broadcast_lit =
+                submod->add_instruction(migraphx::make_op("multibroadcast"), literal_ins, sm_input);
+            auto add_ins0 =
+                submod->add_instruction(migraphx::make_op("add"), sm_input, broadcast_lit);
+            auto add_ins1 =
+                submod->add_instruction(migraphx::make_op("add"), add_ins0, broadcast_lit);
+            submod->add_return({add_ins0, add_ins1});
+            return submod;
+        };
+        auto* batch1 = create_submodule(1, "batch_1");
+        auto* batch2 = create_submodule(2, "batch_2");
+        auto* batch3 = create_submodule(3, "batch_3");
+        auto* batch4 = create_submodule(4, "batch_4");
 
-MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_DISABLE_MEMORY_COLORING)
+        migraphx::shape s{migraphx::shape::float_type, {{1, 4}, {4, 4}}};
+        auto input                              = mm->add_parameter("data", s);
+        std::vector<migraphx::shape> sub_shapes = {};
+        sub_shapes.push_back(migraphx::shape{migraphx::shape::float_type, {{1, 4}, {4, 4}}});
+        sub_shapes.push_back(migraphx::shape{migraphx::shape::float_type, {{1, 4}, {4, 4}}});
+        migraphx::shape out_attr = migraphx::shape{sub_shapes};
+        auto sm_ins              = mm->add_instruction(
+            migraphx::make_op("select_module",
+                              {{"output_dyn_shapes", migraphx::to_value(out_attr)}}),
+            {input},
+            {batch1, batch2, batch3, batch4});
+        auto ret0 =
+            mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), sm_ins);
+        auto ret1 =
+            mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 1}}), sm_ins);
+        mm->add_return({ret0, ret1});
 
-} // namespace MIGRAPHX_INLINE_NS
-} // namespace migraphx
-#endif // MIGRAPHX_GUARD_PASS_CONFIG_HPP
+        return p;
+    }
+};

test/context_test.cpp → test/verify/test_select_module_conv.cpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * Copyright (c) 2015-2023 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
@@ -21,20 +21,51 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  * THE SOFTWARE.
  */
-#include <migraphx/serialize.hpp>
-#include <migraphx/context.hpp>
-#include <migraphx/ref/context.hpp>
-#include <migraphx/functional.hpp>
-#include <test.hpp>
 
-TEST_CASE(context)
+#include "verify_program.hpp"
+#include <migraphx/program.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/make_op.hpp>
+
+struct test_select_module_conv : verify_program<test_select_module_conv>
 {
-    migraphx::context ctx = migraphx::ref::context{};
-    migraphx::value v     = ctx.to_value();
-    EXPECT(v.empty());
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        auto* mm = p.get_main_module();
+
+        // create batch submodules
+        auto create_submodule = [&](std::size_t batch_size, const std::string& module_name) {
+            auto* submod = p.create_module(module_name);
+            migraphx::shape sm_shape{migraphx::shape::float_type, {batch_size, 3, 4, 4}};
+            auto sm_input = submod->add_parameter("data", sm_shape);
+            migraphx::shape weights_shape{migraphx::shape::float_type, {2, 3, 3, 3}};
+            std::vector<float> weights_data(2 * 3 * 3 * 3, 2.0);
+            auto weights  = submod->add_literal(migraphx::literal{weights_shape, weights_data});
+            auto conv_ins = submod->add_instruction(
+                migraphx::make_op("convolution", {{"padding", {1, 1}}}), sm_input, weights);
+            submod->add_return({conv_ins});
+            return submod;
+        };
+        auto* batch1 = create_submodule(1, "batch_1");
+        auto* batch2 = create_submodule(2, "batch_2");
+        auto* batch3 = create_submodule(3, "batch_3");
+        auto* batch4 = create_submodule(4, "batch_4");
 
-    migraphx::context cpu_ctx = migraphx::ref::context{};
-    cpu_ctx.from_value(v);
-}
+        migraphx::shape s{migraphx::shape::float_type, {{1, 4}, {3, 3}, {4, 4}, {4, 4}}};
+        auto input                              = mm->add_parameter("data", s);
+        std::vector<migraphx::shape> sub_shapes = {};
+        sub_shapes.push_back(
+            migraphx::shape{migraphx::shape::float_type, {{1, 4}, {2, 2}, {4, 4}, {4, 4}}});
+        migraphx::shape out_attr = migraphx::shape{sub_shapes};
+        auto sm_ins              = mm->add_instruction(
+            migraphx::make_op("select_module",
+                              {{"output_dyn_shapes", migraphx::to_value(out_attr)}}),
+            {input},
+            {batch1, batch2, batch3, batch4});
+        auto ret = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), sm_ins);
+        mm->add_return({ret});
 
-int main(int argc, const char* argv[]) { test::run(argc, argv); }
+        return p;
+    }
+};

src/opt/memory_coloring.cpp → test/verify/test_select_module_reduce.cpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * Copyright (c) 2015-2023 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
@@ -21,20 +21,49 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  * THE SOFTWARE.
  */
-#include <migraphx/memory_coloring.hpp>
-#include "memory_coloring_impl.hpp"
 
-namespace migraphx {
-inline namespace MIGRAPHX_INLINE_NS {
+#include "verify_program.hpp"
+#include <migraphx/program.hpp>
+#include <migraphx/generate.hpp>
+#include <migraphx/make_op.hpp>
 
-void memory_coloring::apply(module& m) const
+struct test_select_module_reduce : verify_program<test_select_module_reduce>
 {
-    if(not enabled(MIGRAPHX_DISABLE_MEMORY_COLORING{}))
+    migraphx::program create_program() const
     {
-        memory_coloring_impl opt(&m, allocation_op, verify);
-        opt.run();
-    }
-}
+        migraphx::program p;
+
+        // create batch submodules
+        auto create_submodule = [&](std::size_t batch_size, const std::string& module_name) {
+            auto* submod = p.create_module(module_name);
+            migraphx::shape sm_shape{migraphx::shape::float_type, {batch_size, 2, 2}};
+            auto sm_input = submod->add_parameter("data", sm_shape);
+            auto reduce_ins =
+                submod->add_instruction(migraphx::make_op("reduce_sum", {{"axes", {1}}}), sm_input);
+            auto squeeze_ins =
+                submod->add_instruction(migraphx::make_op("squeeze", {{"axes", {1}}}), reduce_ins);
+            submod->add_return({squeeze_ins});
+            return submod;
+        };
+        auto* batch1 = create_submodule(1, "batch_1");
+        auto* batch2 = create_submodule(2, "batch_2");
+        auto* batch3 = create_submodule(3, "batch_3");
+        auto* batch4 = create_submodule(4, "batch_4");
 
-} // namespace MIGRAPHX_INLINE_NS
-} // namespace migraphx
+        auto* mm = p.get_main_module();
+        migraphx::shape s{migraphx::shape::float_type, {{1, 4}, {2, 2}, {2, 2}}};
+        auto input                              = mm->add_parameter("data", s);
+        std::vector<migraphx::shape> sub_shapes = {};
+        sub_shapes.push_back(migraphx::shape{migraphx::shape::float_type, {{1, 4}, {2, 2}}});
+        migraphx::shape out_attr = migraphx::shape{sub_shapes};
+        auto sm_ins              = mm->add_instruction(
+            migraphx::make_op("select_module",
+                              {{"output_dyn_shapes", migraphx::to_value(out_attr)}}),
+            {input},
+            {batch1, batch2, batch3, batch4});
+        auto ret = mm->add_instruction(migraphx::make_op("get_tuple_elem", {{"index", 0}}), sm_ins);
+        mm->add_return({ret});
+
+        return p;
+    }
+};

tools/api/api.cpp

@@ -32,7 +32,6 @@
 #include <migraphx/register_target.hpp>
 #include <migraphx/generate.hpp>
 #include <migraphx/quantization.hpp>
-#include <migraphx/ref/target.hpp>
 #include <migraphx/load_save.hpp>
 #include <migraphx/make_op.hpp>
 #include <migraphx/register_op.hpp>
@@ -134,6 +133,11 @@ void set_offload_copy(compile_options& options, bool value) { options.offload_co
 
 void set_fast_math(compile_options& options, bool value) { options.fast_math = value; }
 
+void set_exhaustive_tune_flag(compile_options& options, bool value)
+{
+    options.exhaustive_tune = value;
+}
+
 void set_file_format(file_options& options, const char* format) { options.format = format; }
 
 void set_default_dim_value(onnx_options& options, size_t value)

tools/build_and_test_onnxrt.sh

@@ -22,10 +22,10 @@
 # THE SOFTWARE.
 #####################################################################################
 cd /onnxruntime
-pip3 install -r requirements.txt
+pip3 install -r requirements-dev.txt
 # Add newer cmake to the path
 export PATH="/opt/cmake/bin:$PATH"
-export CXXFLAGS="-D__HIP_PLATFORM_HCC__=1 -w"
+export CXXFLAGS="-D__HIP_PLATFORM_AMD__=1 -w"
 ./build.sh --config Release  --cmake_extra_defines CMAKE_HIP_COMPILER=/opt/rocm/llvm/bin/clang++ --update --build --parallel --cmake_extra_defines ONNXRUNTIME_VERSION=$(cat ./VERSION_NUMBER) --skip_tests --rocm_home /opt/rocm --use_migraphx --migraphx_home /opt/rocm --rocm_version=`cat /opt/rocm/.info/version-dev`
 
 cd build/Linux/Release

tools/download_models.sh

@@ -26,10 +26,12 @@
 
 if [ -z "$ONNX_HOME" ]
 then
-   ONNX_HOME=$HOME
+   # The onnx library uses ONNX_HOME, by default if it doesn't exist
+   # the path of " ~/.onnx " is used
+   ONNX_HOME=$HOME/.onnx
 fi
 
-model_dir=$ONNX_HOME/.onnx/models
+model_dir=$ONNX_HOME/models
 tmp_dir=$ONNX_HOME/tmp/
 mkdir -p $model_dir
 mkdir -p $tmp_dir
@@ -42,7 +44,6 @@ models="bvlc_alexnet \
 
 for name in $models
 do
-curl https://s3.amazonaws.com/download.onnx/models/opset_9/$name.tar.gz --output $tmp_dir/$name.tar.gz
+curl https://download.onnxruntime.ai/onnx/models/$name.tar.gz --output $tmp_dir/$name.tar.gz
 tar -xzvf $tmp_dir/$name.tar.gz --directory $model_dir && rm $tmp_dir/$name.tar.gz
 done
-

tools/include/context.hpp

@@ -66,6 +66,7 @@ any_ptr get_queue_context(T&)
 {
     return {};
 }
+
 template <class T>
 void wait_for_context(T&, any_ptr)
 {
@@ -87,6 +88,7 @@ void finish_on_context(T&, any_ptr){}
 {
     v = ctx.to_value();
 }
+
 inline void migraphx_from_value(const value& v, context& ctx) { ctx.from_value(v); }
 
 #endif

tools/include/operation.hpp

@@ -140,6 +140,8 @@ template <class T>
 auto compute_shape_op(rank<2>, const T& x, const std::vector<shape>& inputs)
     -> decltype(x.normalize_compute_shape(inputs))
 {
+    if(inputs.empty())
+        MIGRAPHX_THROW("At least one input is required for " + x.name());
     dependent_type<operation, T> y = x;
     normalize_attributes(y, inputs[0].max_lens());
     return any_cast<T>(y).normalize_compute_shape(inputs);

tools/install_prereqs.sh

@@ -57,7 +57,7 @@ echo "Dependencies are installed at $PREFIX"
 rbuild prepare -d $PREFIX -s develop
 
 # install onnx package for unit tests
-pip3 install onnx==1.10.0 numpy==1.21.6 typing==3.7.4 pytest==6.0.1 packaging==16.8
+pip3 install onnx==1.10.2 numpy==1.21.6 typing==3.7.4 pytest==6.0.1 packaging==23.0
 
 # pin version of protobuf in Python for onnx runtime unit tests
 pip3 install protobuf==3.20.0

tools/te.py

@@ -24,7 +24,8 @@
 import string, sys, re
 
 trivial = [
-    'std::size_t', 'instruction_ref', 'support_metric', 'const_module_ref'
+    'std::size_t', 'instruction_ref', 'support_metric', 'const_module_ref',
+    'bool', 'any_ptr'
 ]
 
 headers = '''