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Commit d705e483 authored by Paul's avatar Paul
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Merge branch 'jit-layernorm-merge' of... 

Merge branch 'jit-layernorm-merge' of github.com:ROCmSoftwarePlatform/AMDMIGraphX into jit-layernorm-merge
parents ed34d352 66d50268
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Showing with 4203 additions and 2935 deletions
.github/workflows/ci.yaml
View file @ d705e483
......@@ -53,6 +53,7 @@ jobs:
CXX=/opt/rocm/llvm/bin/clang++ CC=/opt/rocm/llvm/bin/clang cmake \
-DMIGRAPHX_ENABLE_GPU=On \
-DMIGRAPHX_ENABLE_CPU=On \
-DMIGRAPHX_ENABLE_FPGA=On \
-DROCM_ENABLE_GH_ANNOTATIONS=On \
-DCLANG_TIDY_DEPEND_ON_TARGET=Off \
-DCLANG_TIDY_CACHE=/data/tidy-cache \
......
src/CMakeLists.txt
View file @ d705e483
......@@ -90,7 +90,6 @@ add_library(migraphx
shape.cpp
simplify_algebra.cpp
simplify_reshapes.cpp
target_assignments.cpp
tmp_dir.cpp
value.cpp
verify_args.cpp
......
src/driver/alexnet.cpp
View file @ d705e483
......@@ -25,13 +25,10 @@
#include <migraphx/make_op.hpp>
#include <migraphx/program.hpp>
#include <migraphx/generate.hpp>
#include <migraphx/json.hpp>
#include "models.hpp"
namespace migraphx {
namespace driver {
inline namespace MIGRAPHX_INLINE_NS {
migraphx::program alexnet(unsigned batch) // NOLINT(readability-function-size)
{
migraphx::program p;
......@@ -42,179 +39,153 @@ migraphx::program alexnet(unsigned batch) // NOLINT(readability-function-size)
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1}}, 1)));
auto x_main_module_2 = mmain->add_literal(migraphx::abs(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1}}, 2)));
auto x_input_1 = mmain->add_parameter(
"input.1", migraphx::shape{migraphx::shape::float_type, {batch, 3, 224, 224}});
auto x_0 = mmain->add_parameter(
"0", migraphx::shape{migraphx::shape::float_type, {batch, 3, 224, 224}});
auto x_main_module_4 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 4096}}, 3));
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000}}, 3));
auto x_main_module_5 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 4));
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000, 4096}}, 4));
auto x_main_module_6 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 9216}}, 5));
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 5));
auto x_main_module_7 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 6));
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 4096}}, 6));
auto x_main_module_8 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000, 4096}}, 7));
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 7));
auto x_main_module_9 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000}}, 8));
auto x_main_module_10 = mmain->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {256, 384, 3, 3}}, 9));
auto x_main_module_11 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 10));
auto x_main_module_12 = mmain->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {384, 192, 3, 3}}, 11));
auto x_main_module_13 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {384}}, 12));
auto x_main_module_14 = mmain->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {192, 64, 5, 5}}, 13));
auto x_main_module_15 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {192}}, 14));
auto x_main_module_16 = mmain->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {256, 256, 3, 3}}, 15));
auto x_main_module_17 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 16));
auto x_main_module_18 = mmain->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {64, 3, 11, 11}}, 17));
auto x_main_module_19 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {64}}, 18));
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 9216}}, 8));
auto x_main_module_10 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 9));
auto x_main_module_11 = mmain->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {256, 256, 3, 3}}, 10));
auto x_main_module_12 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 11));
auto x_main_module_13 = mmain->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {256, 384, 3, 3}}, 12));
auto x_main_module_14 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {384}}, 13));
auto x_main_module_15 = mmain->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {384, 192, 3, 3}}, 14));
auto x_main_module_16 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {192}}, 15));
auto x_main_module_17 = mmain->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {192, 64, 5, 5}}, 16));
auto x_main_module_18 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {64}}, 17));
auto x_main_module_19 = mmain->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {64, 3, 11, 11}}, 18));
auto x_main_module_20 = mmain->add_instruction(
migraphx::make_op(
"convolution",
migraphx::from_json_string(
"{dilation:[1,1],group:1,padding:[2,2,2,2],padding_mode:0,stride:[4,4]}")),
x_input_1,
x_main_module_18);
auto x_main_module_21 = mmain->add_instruction(
migraphx::make_op("broadcast",
migraphx::from_json_string("{axis:1,out_lens:[1,64,55,55]}")),
migraphx::make_json_op("convolution",
"{dilation:[1,1],group:1,padding:[2,2,2,2],padding_mode:0,stride:[4,"
"4],use_dynamic_same_auto_pad:0}"),
x_0,
x_main_module_19);
auto x_main_module_21 = mmain->add_instruction(
migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,64,55,55]}"), x_main_module_18);
auto x_main_module_22 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_20, x_main_module_21);
auto x_main_module_23 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_22);
auto x_main_module_24 = mmain->add_instruction(
migraphx::make_op(
migraphx::make_json_op(
"pooling",
migraphx::from_json_string(
"{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}")),
"{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}"),
x_main_module_23);
auto x_main_module_25 = mmain->add_instruction(
migraphx::make_op(
"convolution",
migraphx::from_json_string(
"{dilation:[1,1],group:1,padding:[2,2,2,2],padding_mode:0,stride:[1,1]}")),
migraphx::make_json_op("convolution",
"{dilation:[1,1],group:1,padding:[2,2,2,2],padding_mode:0,stride:[1,"
"1],use_dynamic_same_auto_pad:0}"),
x_main_module_24,
x_main_module_14);
x_main_module_17);
auto x_main_module_26 = mmain->add_instruction(
migraphx::make_op("broadcast",
migraphx::from_json_string("{axis:1,out_lens:[1,192,27,27]}")),
x_main_module_15);
migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,192,27,27]}"), x_main_module_16);
auto x_main_module_27 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_25, x_main_module_26);
auto x_main_module_28 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_27);
auto x_main_module_29 = mmain->add_instruction(
migraphx::make_op(
migraphx::make_json_op(
"pooling",
migraphx::from_json_string(
"{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}")),
"{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}"),
x_main_module_28);
auto x_main_module_30 = mmain->add_instruction(
migraphx::make_op(
"convolution",
migraphx::from_json_string(
"{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,1]}")),
migraphx::make_json_op("convolution",
"{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,"
"1],use_dynamic_same_auto_pad:0}"),
x_main_module_29,
x_main_module_12);
x_main_module_15);
auto x_main_module_31 = mmain->add_instruction(
migraphx::make_op("broadcast",
migraphx::from_json_string("{axis:1,out_lens:[1,384,13,13]}")),
x_main_module_13);
migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,384,13,13]}"), x_main_module_14);
auto x_main_module_32 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_30, x_main_module_31);
auto x_main_module_33 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_32);
auto x_main_module_34 = mmain->add_instruction(
migraphx::make_op(
"convolution",
migraphx::from_json_string(
"{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,1]}")),
migraphx::make_json_op("convolution",
"{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,"
"1],use_dynamic_same_auto_pad:0}"),
x_main_module_33,
x_main_module_10);
x_main_module_13);
auto x_main_module_35 = mmain->add_instruction(
migraphx::make_op("broadcast",
migraphx::from_json_string("{axis:1,out_lens:[1,256,13,13]}")),
x_main_module_11);
migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,256,13,13]}"), x_main_module_12);
auto x_main_module_36 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_34, x_main_module_35);
auto x_main_module_37 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_36);
auto x_main_module_38 = mmain->add_instruction(
migraphx::make_op(
"convolution",
migraphx::from_json_string(
"{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,1]}")),
migraphx::make_json_op("convolution",
"{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,"
"1],use_dynamic_same_auto_pad:0}"),
x_main_module_37,
x_main_module_16);
x_main_module_11);
auto x_main_module_39 = mmain->add_instruction(
migraphx::make_op("broadcast",
migraphx::from_json_string("{axis:1,out_lens:[1,256,13,13]}")),
x_main_module_17);
migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,256,13,13]}"), x_main_module_10);
auto x_main_module_40 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_38, x_main_module_39);
auto x_main_module_41 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_40);
auto x_main_module_42 = mmain->add_instruction(
migraphx::make_op(
migraphx::make_json_op(
"pooling",
migraphx::from_json_string(
"{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}")),
"{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}"),
x_main_module_41);
auto x_main_module_43 = mmain->add_instruction(
migraphx::make_op("reshape", migraphx::from_json_string("{dims:[1,9216]}")),
x_main_module_42);
auto x_main_module_44 = mmain->add_instruction(
migraphx::make_op("transpose", migraphx::from_json_string("{permutation:[1,0]}")),
x_main_module_6);
auto x_main_module_45 =
mmain->add_instruction(migraphx::make_op("dot"), x_main_module_43, x_main_module_44);
auto x_main_module_46 = mmain->add_instruction(
migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,4096]}")),
x_main_module_7);
auto x_main_module_43 =
mmain->add_instruction(migraphx::make_json_op("flatten", "{axis:1}"), x_main_module_42);
auto x_main_module_44 = mmain->add_instruction(migraphx::make_op("identity"), x_main_module_43);
auto x_main_module_45 = mmain->add_instruction(
migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_9);
auto x_main_module_46 =
mmain->add_instruction(migraphx::make_op("dot"), x_main_module_44, x_main_module_45);
auto x_main_module_47 = mmain->add_instruction(
migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,4096]}")),
x_main_module_2);
auto x_main_module_48 =
mmain->add_instruction(migraphx::make_op("mul"), x_main_module_46, x_main_module_47);
migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_8);
auto x_main_module_48 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_2);
auto x_main_module_49 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_45, x_main_module_48);
auto x_main_module_50 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_49);
auto x_main_module_51 = mmain->add_instruction(
migraphx::make_op("transpose", migraphx::from_json_string("{permutation:[1,0]}")),
x_main_module_4);
auto x_main_module_52 =
mmain->add_instruction(migraphx::make_op("dot"), x_main_module_50, x_main_module_51);
mmain->add_instruction(migraphx::make_op("mul"), x_main_module_47, x_main_module_48);
auto x_main_module_50 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_46, x_main_module_49);
auto x_main_module_51 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_50);
auto x_main_module_52 = mmain->add_instruction(migraphx::make_op("identity"), x_main_module_51);
auto x_main_module_53 = mmain->add_instruction(
migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,4096]}")),
x_main_module_5);
auto x_main_module_54 = mmain->add_instruction(
migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,4096]}")),
x_main_module_1);
auto x_main_module_55 =
mmain->add_instruction(migraphx::make_op("mul"), x_main_module_53, x_main_module_54);
auto x_main_module_56 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_52, x_main_module_55);
auto x_main_module_57 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_56);
auto x_main_module_58 = mmain->add_instruction(
migraphx::make_op("transpose", migraphx::from_json_string("{permutation:[1,0]}")),
x_main_module_8);
auto x_main_module_59 =
mmain->add_instruction(migraphx::make_op("dot"), x_main_module_57, x_main_module_58);
migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_7);
auto x_main_module_54 =
mmain->add_instruction(migraphx::make_op("dot"), x_main_module_52, x_main_module_53);
auto x_main_module_55 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_6);
auto x_main_module_56 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_1);
auto x_main_module_57 =
mmain->add_instruction(migraphx::make_op("mul"), x_main_module_55, x_main_module_56);
auto x_main_module_58 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_54, x_main_module_57);
auto x_main_module_59 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_58);
auto x_main_module_60 = mmain->add_instruction(
migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,1000]}")),
x_main_module_9);
auto x_main_module_61 = mmain->add_instruction(
migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,1000]}")),
x_main_module_0);
auto x_main_module_62 =
mmain->add_instruction(migraphx::make_op("mul"), x_main_module_60, x_main_module_61);
auto x_main_module_63 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_59, x_main_module_62);
mmain->add_return({x_main_module_63});
migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_5);
auto x_main_module_61 =
mmain->add_instruction(migraphx::make_op("dot"), x_main_module_59, x_main_module_60);
auto x_main_module_62 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,1000]}"), x_main_module_4);
auto x_main_module_63 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,1000]}"), x_main_module_0);
auto x_main_module_64 =
mmain->add_instruction(migraphx::make_op("mul"), x_main_module_62, x_main_module_63);
auto x_main_module_65 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_61, x_main_module_64);
mmain->add_return({x_main_module_65});
return p;
}
......
src/driver/inceptionv3.cpp
View file @ d705e483
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src/driver/resnet50.cpp
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src/include/migraphx/make_op.hpp
View file @ d705e483
......@@ -27,6 +27,8 @@
#include <migraphx/config.hpp>
#include <migraphx/operation.hpp>
#include <migraphx/value.hpp>
#include <migraphx/json.hpp>
#include <migraphx/convert_to_json.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -46,6 +48,8 @@ operation make_op(const std::string& name, const Value& v)
return make_op_from_value(name, v);
}
operation make_json_op(const std::string& name, const std::string& s);
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
......
src/include/migraphx/onnx.hpp
View file @ d705e483
......@@ -35,17 +35,13 @@ struct onnx_options
{
/// Old way to set default fixed dimension size
std::size_t default_dim_value = 0;
/*!
* Default dynamic dimension size (if both default_dim_value and default_dyn_dim_value
* set parser throws)
*/
/// Default dynamic dimension size (if both default_dim_value and default_dyn_dim_value set
/// parser throws)
shape::dynamic_dimension default_dyn_dim_value = {1, 1, 0};
/// Explicitly specify the dims of an input
std::unordered_map<std::string, std::vector<std::size_t>> map_input_dims = {};
/*!
* Explicitly specify dynamic dims of an input (if both map_input_dims and
* map_dyn_input_dims set parser throws)
*/
/// Explicitly specify dynamic dims of an input (if both map_input_dims and map_dyn_input_dims
/// set parser throws)
std::unordered_map<std::string, std::vector<shape::dynamic_dimension>> map_dyn_input_dims = {};
/// Continue parsing onnx file if an unknown operator is found
bool skip_unknown_operators = false;
......@@ -53,6 +49,8 @@ struct onnx_options
bool print_program_on_error = false;
/// Max iter num for the loop operator
int64_t max_loop_iterations = 10;
/// Use dynamic output for operators when available
bool use_dyn_output = false;
};
/// Create a program from an onnx file
......
src/include/migraphx/op/convert.hpp
View file @ d705e483
......@@ -45,7 +45,15 @@ struct convert : unary<convert>
shape compute_shape(std::vector<shape> inputs) const
{
check_shapes{inputs, *this}.has(1);
return {target_type, inputs.at(0).lens(), inputs.at(0).strides()};
auto input = inputs.at(0);
if(input.dynamic())
{
return {target_type, input.dyn_dims()};
}
else
{
return {target_type, input.lens(), input.strides()};
}
}
std::string point_op() const
......
src/include/migraphx/op/nonmaxsuppression.hpp
View file @ d705e483
......@@ -45,11 +45,13 @@ namespace op {
struct nonmaxsuppression
{
bool center_point_box = false;
bool use_dyn_output = false;
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return pack(f(self.center_point_box, "center_point_box"));
return pack(f(self.center_point_box, "center_point_box"),
f(self.use_dyn_output, "use_dyn_output"));
}
std::string name() const { return "nonmaxsuppression"; }
......@@ -57,27 +59,81 @@ struct nonmaxsuppression
shape compute_shape(std::vector<shape> inputs) const
{
// requires at least 2 inputs
check_shapes{{inputs.at(0), inputs.at(1)}, *this}.only_dims(3);
auto lens = inputs.front().lens();
check_shapes{{inputs.at(0), inputs.at(1)}, *this, true}.only_dims(3).same_ndims();
auto boxes_max_lens = inputs.at(0).max_lens();
// num batches * num boxes
const auto max_num_boxes = boxes_max_lens.at(0) * boxes_max_lens.at(1);
// check input shape
if(lens[1] != inputs.at(1).lens()[2])
auto fixed_shape_error_check = [&]() {
auto lens = inputs.front().lens();
if(lens[1] != inputs.at(1).lens()[2])
{
MIGRAPHX_THROW(
"NonMaxSuppression: spatial dimension mismatch between boxes and scores input");
}
if(lens[0] != inputs.at(1).lens()[0])
{
MIGRAPHX_THROW(
"NonMaxSuppression: number of batches mismatch between boxes and scores input");
}
};
if(use_dyn_output)
{
MIGRAPHX_THROW(
"NonMaxSuppression: spatial dimension mismatch between boxes and scores input");
if(inputs.at(0).dynamic())
{
// both boxes and scores should be dynamic
// check dynamic dimensions are consistent
const auto boxes_dims = inputs.at(0).dyn_dims();
const auto scores_dims = inputs.at(1).dyn_dims();
if(boxes_dims.at(1) != scores_dims.at(2))
{
MIGRAPHX_THROW("NonMaxSuppression: dynamic spatial dimension mismatch between "
"boxes and scores input");
}
if(boxes_dims.at(0) != scores_dims.at(0))
{
MIGRAPHX_THROW("NonMaxSuppression: dynamic number of batches mismatch between "
"boxes and scores input");
}
}
else if(inputs.at(1).dynamic())
{
// scores has dynamic shape, boxes fixed shape
// check that it is only a dynamic number of classes
const auto scores_dims = inputs.at(1).dyn_dims();
const auto boxes_lens = inputs.at(0).lens();
if(not scores_dims.at(0).is_fixed() or scores_dims.at(0).max != boxes_lens.at(0))
{
MIGRAPHX_THROW("NonMaxSuppression: scores dynamic num_classes; num_batches not "
"fixed or mismatched");
}
if(not scores_dims.at(2).is_fixed() or scores_dims.at(2).max != boxes_lens.at(1))
{
MIGRAPHX_THROW("NonMaxSuppression: scores dynamic num_classes; "
"spatial_dimension not fixed or mismatches");
}
}
else
{
fixed_shape_error_check();
}
std::vector<shape::dynamic_dimension> out_lens = {};
out_lens.push_back({0, max_num_boxes, 0});
out_lens.push_back({3, 3, 0});
return {shape::int64_type, out_lens};
}
// check batch sizes
if(lens[0] != inputs.at(1).lens()[0])
else
{
MIGRAPHX_THROW(
"NonMaxSuppression: number of batches mismatch between boxes and scores input");
if(inputs.at(0).dynamic() or inputs.at(1).dynamic())
{
MIGRAPHX_THROW(
"NonMaxSuppression: dynamic input shape with use_dyn_output set to false");
}
fixed_shape_error_check();
std::vector<std::size_t> out_lens = {max_num_boxes, 3};
return {shape::int64_type, out_lens};
}
std::vector<int64_t> out_lens(2);
out_lens.at(0) = lens.at(1);
out_lens.at(1) = 3;
return {shape::int64_type, out_lens};
}
struct box
......@@ -181,13 +237,13 @@ struct nonmaxsuppression
}
template <class Output, class Boxes, class Scores>
void compute_nms(Output output,
Boxes boxes,
Scores scores,
const shape& output_shape,
std::size_t max_output_boxes_per_class,
double iou_threshold,
double score_threshold) const
std::size_t compute_nms(Output output,
Boxes boxes,
Scores scores,
const shape& max_output_shape,
std::size_t max_output_boxes_per_class,
double iou_threshold,
double score_threshold) const
{
std::fill(output.begin(), output.end(), 0);
const auto& lens = scores.get_shape().lens();
......@@ -197,7 +253,7 @@ struct nonmaxsuppression
// boxes of a class with NMS applied [score, index]
std::vector<std::pair<double, int64_t>> selected_boxes_inside_class;
std::vector<int64_t> selected_indices;
selected_boxes_inside_class.reserve(output_shape.elements());
selected_boxes_inside_class.reserve(max_output_shape.elements());
// iterate over batches and classes
shape comp_s{shape::double_type, {num_batches, num_classes}};
shape_for_each(comp_s, [&](auto idx) {
......@@ -237,11 +293,14 @@ struct nonmaxsuppression
}
});
std::copy(selected_indices.begin(), selected_indices.end(), output.begin());
return selected_indices.size() / 3;
}
argument compute(const shape& output_shape, std::vector<argument> args) const
{
argument result{output_shape};
// make buffer of maximum size
shape max_output_shape = {output_shape.type(), output_shape.max_lens()};
argument result{max_output_shape};
std::size_t max_output_boxes_per_class =
(args.size() > 2) ? (args.at(2).at<std::size_t>()) : 0;
......@@ -249,22 +308,29 @@ struct nonmaxsuppression
{
return result;
}
double iou_threshold = (args.size() > 3) ? (args.at(3).at<double>()) : 0.0f;
double score_threshold = (args.size() > 4) ? (args.at(4).at<double>()) : 0.0f;
double iou_threshold = (args.size() > 3) ? (args.at(3).at<double>()) : 0.0f;
double score_threshold = (args.size() > 4) ? (args.at(4).at<double>()) : 0.0f;
std::size_t num_selected = 0;
result.visit([&](auto output) {
visit_all(args[0], args[1])([&](auto boxes, auto scores) {
compute_nms(output,
boxes,
scores,
output_shape,
max_output_boxes_per_class,
iou_threshold,
score_threshold);
num_selected = compute_nms(output,
boxes,
scores,
max_output_shape,
max_output_boxes_per_class,
iou_threshold,
score_threshold);
});
});
return result;
if(use_dyn_output)
{
return result.reshape({output_shape.type(), {num_selected, 3}});
}
else
{
return result;
}
}
};
......
src/target_assignments.cpp → src/include/migraphx/supported_segments.hpp
View file @ d705e483
......@@ -21,16 +21,24 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#ifndef MIGRAPHX_GUARD_MIGRAPHX_SUPPORTED_SEGMENTS_HPP
#define MIGRAPHX_GUARD_MIGRAPHX_SUPPORTED_SEGMENTS_HPP
#include <migraphx/target_assignments.hpp>
#include <unordered_set>
#include <migraphx/instruction_ref.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
void target_assignments::add_assignment(instruction_ref ins, const std::string& target)
struct supported_segment
{
assignments.emplace(ins, target);
}
std::unordered_set<instruction_ref> instructions;
float metric;
};
using supported_segments = std::vector<supported_segment>;
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif // MIGRAPHX_GUARD_MIGRAPHX_SUPPORTED_SEGMENTS_HPP
src/include/migraphx/target.hpp
View file @ d705e483
......@@ -37,8 +37,10 @@
#include <migraphx/compile_options.hpp>
#include <migraphx/argument.hpp>
#include <migraphx/rank.hpp>
#include <migraphx/module_ref.hpp>
#include <migraphx/support_metric.hpp>
#include <migraphx/instruction_ref.hpp>
#include <migraphx/supported_segments.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -64,12 +66,12 @@ struct target
*/
context get_context() const;
/**
* @brief Check how well an instruction is supported on a target with the given metric
* @param ins Instruction to check if it's supported
* @param metric Used to define how the return value should be interpreted
* @return The value based on the chosen metric. Negative numbers mean unsupported
* @brief Get the ranges of instructions that are supported on a target
* @param module Module to check for supported instructions
* @param metric Used to define how the quality of the support should be measured
* @return the supported segments of the graph
*/
float is_supported(T&, instruction_ref ins, support_metric m) const;
supported_segments target_is_supported(T&, const_module_ref mod, support_metric metric) const;
/**
* @brief copy an argument to the current target.
*
......@@ -115,9 +117,9 @@ argument copy_from_target(T&, const argument& arg)
}
template <class T>
float target_is_supported(T&, instruction_ref, support_metric)
supported_segments target_find_supported(T&, const_module_ref, support_metric)
{
return 0;
return {};
}
#ifdef TYPE_ERASED_DECLARATION
......@@ -132,7 +134,7 @@ struct target
//
context get_context() const;
// (optional)
float is_supported(instruction_ref ins, support_metric m) const;
supported_segments find_supported(const_module_ref mod, support_metric m) const;
// (optional)
argument copy_to(const argument& input) const;
// (optional)
......@@ -224,10 +226,10 @@ struct target
return (*this).private_detail_te_get_handle().get_context();
}
float is_supported(instruction_ref ins, support_metric m) const
supported_segments find_supported(const_module_ref mod, support_metric m) const
{
assert((*this).private_detail_te_handle_mem_var);
return (*this).private_detail_te_get_handle().is_supported(ins, m);
return (*this).private_detail_te_get_handle().find_supported(mod, m);
}
argument copy_to(const argument& input) const
......@@ -261,33 +263,33 @@ struct target
virtual std::shared_ptr<private_detail_te_handle_base_type> clone() const = 0;
virtual const std::type_info& type() const = 0;
virtual std::string name() const = 0;
virtual std::string name() const = 0;
virtual std::vector<pass> get_passes(context& ctx,
const compile_options& options) const = 0;
virtual context get_context() const = 0;
virtual float is_supported(instruction_ref ins, support_metric m) const = 0;
virtual argument copy_to(const argument& input) const = 0;
virtual argument copy_from(const argument& input) const = 0;
virtual argument allocate(const shape& s) const = 0;
const compile_options& options) const = 0;
virtual context get_context() const = 0;
virtual supported_segments find_supported(const_module_ref mod, support_metric m) const = 0;
virtual argument copy_to(const argument& input) const = 0;
virtual argument copy_from(const argument& input) const = 0;
virtual argument allocate(const shape& s) const = 0;
};
template <class T>
static auto private_detail_te_default_is_supported(char,
T&& private_detail_te_self,
instruction_ref ins,
support_metric m)
-> decltype(private_detail_te_self.is_supported(ins, m))
static auto private_detail_te_default_find_supported(char,
T&& private_detail_te_self,
const_module_ref mod,
support_metric m)
-> decltype(private_detail_te_self.find_supported(mod, m))
{
return private_detail_te_self.is_supported(ins, m);
return private_detail_te_self.find_supported(mod, m);
}
template <class T>
static float private_detail_te_default_is_supported(float,
T&& private_detail_te_self,
instruction_ref ins,
support_metric m)
static supported_segments private_detail_te_default_find_supported(float,
T&& private_detail_te_self,
const_module_ref mod,
support_metric m)
{
return target_is_supported(private_detail_te_self, ins, m);
return target_find_supported(private_detail_te_self, mod, m);
}
template <class T>
......@@ -372,10 +374,11 @@ struct target
context get_context() const override { return private_detail_te_value.get_context(); }
float is_supported(instruction_ref ins, support_metric m) const override
supported_segments find_supported(const_module_ref mod, support_metric m) const override
{
return private_detail_te_default_is_supported(char(0), private_detail_te_value, ins, m);
return private_detail_te_default_find_supported(
char(0), private_detail_te_value, mod, m);
}
argument copy_to(const argument& input) const override
......
src/include/migraphx/target_assignments.hpp
View file @ d705e483
......@@ -33,10 +33,20 @@ inline namespace MIGRAPHX_INLINE_NS {
struct target_assignments
{
void add_assignment(instruction_ref ins, const std::string& target);
using iterator = std::unordered_map<instruction_ref, std::string>::const_iterator;
using value_type = std::pair<instruction_ref, std::string>;
auto begin() const { return assignments.cbegin(); }
auto end() const { return assignments.cend(); }
auto size() const { return assignments.size(); }
auto& at(instruction_ref ins) const { return assignments.at(ins); }
auto insert(iterator it, const std::pair<instruction_ref, std::string>& assignment)
{
return assignments.insert(it, assignment);
}
auto find(instruction_ref ins) const { return assignments.find(ins); }
auto begin() const { return assignments.begin(); }
auto end() const { return assignments.end(); }
private:
std::unordered_map<instruction_ref, std::string> assignments;
......
src/make_op.cpp
View file @ d705e483
......@@ -64,5 +64,10 @@ operation make_op_from_value(const std::string& name, const value& v)
});
}
operation make_json_op(const std::string& name, const std::string& s)
{
return make_op(name, from_json_string(convert_to_json(s)));
}
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
src/module.cpp
View file @ d705e483
......@@ -788,12 +788,15 @@ static std::string cpp_var_name(const std::string& name)
static void print_make_op(std::ostream& os, const operation& op)
{
os << "migraphx::make_op(" << enclose_name(op.name());
auto v = op.to_value();
if(not v.empty())
{
os << ", "
<< "migraphx::from_json_string(" << enclose_name(to_json_string(v)) << ")";
os << "migraphx::make_json_op(" << enclose_name(op.name());
os << ", " << enclose_name(to_json_string(v));
}
else
{
os << "migraphx::make_op(" << enclose_name(op.name());
}
os << ")";
}
......
src/onnx/include/migraphx/onnx/onnx_parser.hpp
View file @ d705e483
......@@ -97,6 +97,7 @@ struct onnx_parser
shape::dynamic_dimension default_dyn_dim_value = {1, 1, 0};
std::unordered_map<std::string, std::vector<std::size_t>> map_input_dims;
std::unordered_map<std::string, std::vector<shape::dynamic_dimension>> map_dyn_input_dims;
bool use_dyn_output = false;
bool skip_unknown_operators = false;
int64_t max_loop_iterations = 10;
int64_t opset_version = 13;
......
src/onnx/onnx.cpp
View file @ d705e483
......@@ -60,8 +60,14 @@ program parse_onnx_from(const onnx_options& options, Ts&&... xs)
{
parser.default_dyn_dim_value = options.default_dyn_dim_value;
}
if(not options.map_input_dims.empty() and not options.map_dyn_input_dims.empty())
{
MIGRAPHX_THROW("PARSE_ONNX_FROM: both map_input_dims and map_dyn_input_dims non-empty, only"
"one should be used");
}
parser.skip_unknown_operators = options.skip_unknown_operators;
parser.max_loop_iterations = options.max_loop_iterations;
parser.use_dyn_output = options.use_dyn_output;
if(options.print_program_on_error)
{
......@@ -80,6 +86,7 @@ program parse_onnx_from(const onnx_options& options, Ts&&... xs)
{
parser.parse_from(std::forward<Ts>(xs)...);
}
return std::move(parser.prog);
}
......
src/onnx/onnx_parser.cpp
View file @ d705e483
......@@ -256,11 +256,6 @@ int64_t onnx_parser::get_opset_version(const onnx::ModelProto& model)
void onnx_parser::parse_graph(module* mod, const onnx::GraphProto& graph)
{
if(not map_input_dims.empty() and not map_dyn_input_dims.empty())
{
MIGRAPHX_THROW("PARSE_GRAPH: both map_input_dims and map_dyn_input_dims non-empty, only"
"one should be used");
}
std::unordered_map<std::string, instruction_ref> mod_insts;
for(auto&& f : graph.initializer())
{
......
src/onnx/parse_generic_op.cpp
View file @ d705e483
......@@ -58,7 +58,6 @@ struct parse_generic_op : op_parser<parse_generic_op>
{"Log", "log"},
{"LRN", "lrn"},
{"Neg", "neg"},
{"NonMaxSuppression", "nonmaxsuppression"},
{"Reciprocal", "recip"},
{"Relu", "relu"},
{"Round", "round"},
......@@ -75,7 +74,7 @@ struct parse_generic_op : op_parser<parse_generic_op>
bool needs_contiguous(const std::string& op_name) const
{
return contains({"flatten", "gather", "nonmaxsuppression", "scatter"}, op_name);
return contains({"flatten", "gather", "scatter"}, op_name);
}
instruction_ref parse(const op_desc& opd,
......
src/onnx/parse_nonmaxsuppression.cpp 0 → 100644
View file @ d705e483
/*
* 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 <migraphx/onnx/op_parser.hpp>
#include <migraphx/ranges.hpp>
#include <migraphx/make_op.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace onnx {
struct parse_nonmaxsuppression : op_parser<parse_nonmaxsuppression>
{
std::vector<op_desc> operators() const { return {{"NonMaxSuppression", "nonmaxsuppression"}}; }
instruction_ref parse(const op_desc& opd,
const onnx_parser& parser,
const onnx_parser::node_info& info,
const std::vector<instruction_ref>& args) const
{
auto op = parser.load(opd.op_name, info);
op.from_value({{"use_dyn_output", parser.use_dyn_output}});
return info.add_instruction(op, args);
}
};
} // namespace onnx
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
src/program.cpp
View file @ d705e483
......@@ -37,6 +37,7 @@
#include <migraphx/output_iterator.hpp>
#include <migraphx/make_op.hpp>
#include <migraphx/marker.hpp>
#include <migraphx/supported_segments.hpp>
#include <iostream>
#include <sstream>
#include <algorithm>
......@@ -167,13 +168,37 @@ target_assignments program::get_target_assignments(const std::vector<target>& ta
target_assignments p;
const auto* mod = get_main_module();
for(auto it : iterator_for(*mod))
std::vector<std::pair<target, supported_segments>> target_subgraphs;
target_subgraphs.reserve(targets.size());
std::transform(targets.begin(),
targets.end(),
std::back_inserter(target_subgraphs),
[&](const auto& t) { return std::make_pair(t, t.find_supported(mod, m)); });
for(const auto ins : iterator_for(*mod))
{
auto t = std::max_element(
targets.begin(), targets.end(), [it, m](const target& lhs, const target& rhs) {
return lhs.is_supported(it, m) < rhs.is_supported(it, m);
});
p.add_assignment(it, t->name());
if(contains(p, ins))
{
continue;
}
for(const auto& [target, subgraph] : target_subgraphs)
{
// can't pass a structured binding into lambda in C++17 so create a variable for it
const auto& t = target;
for(const auto& segment : subgraph)
{
const auto& instructions = segment.instructions;
if(not contains(instructions, ins))
{
continue;
}
std::transform(instructions.begin(),
instructions.end(),
std::inserter(p, p.end()),
[&](auto instr) { return std::make_pair(instr, t.name()); });
}
}
}
return p;
}
......
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