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Unverified Commit 360b1801 authored by Chris Austen's avatar Chris Austen Committed by GitHub
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Updates for RC1 (#1425) 



* rearrange default pass list; adjust_allocation must be run after rep… (#1418)
* Regenerate driver models (#1422)
* Add support in mlir for transposed and broadcasted shaped (#1378)
* Add relaxed standard shape assertion (#1416)
Co-authored-by: default avatarBrian Pickrell <95253842+bpickrel@users.noreply.github.com>
Co-authored-by: default avatarkahmed10 <15948690+kahmed10@users.noreply.github.com>
Co-authored-by: default avatarPaul Fultz II <pfultz2@yahoo.com>
Co-authored-by: default avatarjungpark-mlir <jungwook.park@amd.com>
parent 83784c52
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Showing with 8229 additions and 2593 deletions
Dockerfile 100755 → 100644
View file @ 360b1801
...@@ -86,7 +86,7 @@ RUN git clone --single-branch --branch ${ONNXRUNTIME_BRANCH} --recursive ${ONNXR ...@@ -86,7 +86,7 @@ RUN git clone --single-branch --branch ${ONNXRUNTIME_BRANCH} --recursive ${ONNXR
ADD tools/build_and_test_onnxrt.sh /onnxruntime/build_and_test_onnxrt.sh ADD tools/build_and_test_onnxrt.sh /onnxruntime/build_and_test_onnxrt.sh
RUN cget -p /usr/local install ROCmSoftwarePlatform/llvm-project-mlir@e8e77eb16be413d301ea8509726d47f265d9011f -DBUILD_MIXR_TARGET=On RUN cget -p /usr/local install ROCmSoftwarePlatform/llvm-project-mlir@c0723a7e50043d973cb73ae51dc30d36679ee7e5 -DBUILD_MIXR_TARGET=On
ENV MIOPEN_FIND_DB_PATH=/tmp/miopen/find-db ENV MIOPEN_FIND_DB_PATH=/tmp/miopen/find-db
ENV MIOPEN_USER_DB_PATH=/tmp/miopen/user-db ENV MIOPEN_USER_DB_PATH=/tmp/miopen/user-db
......
src/driver/alexnet.cpp
View file @ 360b1801
...@@ -25,7 +25,6 @@ ...@@ -25,7 +25,6 @@
#include <migraphx/make_op.hpp> #include <migraphx/make_op.hpp>
#include <migraphx/program.hpp> #include <migraphx/program.hpp>
#include <migraphx/generate.hpp> #include <migraphx/generate.hpp>
#include <migraphx/json.hpp>
#include "models.hpp" #include "models.hpp"
namespace migraphx { namespace migraphx {
namespace driver { namespace driver {
...@@ -40,161 +39,153 @@ migraphx::program alexnet(unsigned batch) // NOLINT(readability-function-size) ...@@ -40,161 +39,153 @@ migraphx::program alexnet(unsigned batch) // NOLINT(readability-function-size)
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1}}, 1))); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1}}, 1)));
auto x_main_module_2 = mmain->add_literal(migraphx::abs( auto x_main_module_2 = mmain->add_literal(migraphx::abs(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1}}, 2))); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1}}, 2)));
auto x_data_0 = mmain->add_parameter( auto x_0 = mmain->add_parameter(
"data_0", migraphx::shape{migraphx::shape::float_type, {batch, 3, 224, 224}}); "0", migraphx::shape{migraphx::shape::float_type, {batch, 3, 224, 224}});
auto x_main_module_4 = mmain->add_literal( auto x_main_module_4 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000, 4096}}, 3)); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000}}, 3));
auto x_main_module_5 = mmain->add_literal( auto x_main_module_5 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000}}, 4)); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000, 4096}}, 4));
auto x_main_module_6 = mmain->add_literal( auto x_main_module_6 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 4096}}, 5)); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 5));
auto x_main_module_7 = mmain->add_literal(migraphx::abs( 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( auto x_main_module_8 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 9216}}, 7)); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 7));
auto x_main_module_9 = mmain->add_literal( auto x_main_module_9 = mmain->add_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 8)); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 9216}}, 8));
auto x_main_module_10 = mmain->add_literal(migraphx::generate_literal( auto x_main_module_10 = mmain->add_literal(
migraphx::shape{migraphx::shape::float_type, {256, 192, 3, 3}}, 9)); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 9));
auto x_main_module_11 = mmain->add_literal( auto x_main_module_11 = mmain->add_literal(migraphx::generate_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 10)); migraphx::shape{migraphx::shape::float_type, {256, 256, 3, 3}}, 10));
auto x_main_module_12 = mmain->add_literal(migraphx::generate_literal( auto x_main_module_12 = mmain->add_literal(
migraphx::shape{migraphx::shape::float_type, {384, 192, 3, 3}}, 11)); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 11));
auto x_main_module_13 = mmain->add_literal( auto x_main_module_13 = mmain->add_literal(migraphx::generate_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {384}}, 12)); migraphx::shape{migraphx::shape::float_type, {256, 384, 3, 3}}, 12));
auto x_main_module_14 = mmain->add_literal(migraphx::generate_literal( auto x_main_module_14 = mmain->add_literal(
migraphx::shape{migraphx::shape::float_type, {384, 256, 3, 3}}, 13)); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {384}}, 13));
auto x_main_module_15 = mmain->add_literal( auto x_main_module_15 = mmain->add_literal(migraphx::generate_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {384}}, 14)); migraphx::shape{migraphx::shape::float_type, {384, 192, 3, 3}}, 14));
auto x_main_module_16 = mmain->add_literal(migraphx::generate_literal( auto x_main_module_16 = mmain->add_literal(
migraphx::shape{migraphx::shape::float_type, {256, 48, 5, 5}}, 15)); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {192}}, 15));
auto x_main_module_17 = mmain->add_literal(migraphx::abs( auto x_main_module_17 = mmain->add_literal(migraphx::generate_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 16))); migraphx::shape{migraphx::shape::float_type, {192, 64, 5, 5}}, 16));
auto x_main_module_18 = mmain->add_literal(migraphx::generate_literal( auto x_main_module_18 = mmain->add_literal(
migraphx::shape{migraphx::shape::float_type, {96, 3, 11, 11}}, 17)); migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {64}}, 17));
auto x_main_module_19 = mmain->add_literal( auto x_main_module_19 = mmain->add_literal(migraphx::generate_literal(
migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {96}}, 18)); migraphx::shape{migraphx::shape::float_type, {64, 3, 11, 11}}, 18));
auto x_main_module_20 = mmain->add_instruction( auto x_main_module_20 = mmain->add_instruction(
migraphx::make_json_op("convolution", migraphx::make_json_op(
"{dilation:[1,1],group:1,padding:[0,0,0,0],padding_mode:0,stride:[4," "convolution",
"4],use_dynamic_same_auto_pad:0}"), "{dilation:[1,1],group:1,padding:[2,2,2,2],padding_mode:0,stride:[4,4]}"),
x_data_0, x_0,
x_main_module_18); x_main_module_19);
auto x_main_module_21 = mmain->add_instruction( auto x_main_module_21 = mmain->add_instruction(
migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,96,54,54]}"), x_main_module_19); migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,64,55,55]}"), x_main_module_18);
auto x_main_module_22 = auto x_main_module_22 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_20, x_main_module_21); 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_23 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_22);
auto x_main_module_24 = mmain->add_instruction( auto x_main_module_24 = mmain->add_instruction(
migraphx::make_json_op("lrn", "{alpha:9.999999747378752e-05,beta:0.75,bias:1.0,size:5}"), migraphx::make_json_op(
"pooling",
"{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}"),
x_main_module_23); x_main_module_23);
auto x_main_module_25 = mmain->add_instruction( auto x_main_module_25 = mmain->add_instruction(
migraphx::make_json_op(
"convolution",
"{dilation:[1,1],group:1,padding:[2,2,2,2],padding_mode:0,stride:[1,1]}"),
x_main_module_24,
x_main_module_17);
auto x_main_module_26 = mmain->add_instruction(
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_json_op( migraphx::make_json_op(
"pooling", "pooling",
"{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_24); x_main_module_28);
auto x_main_module_26 = mmain->add_instruction(
migraphx::make_json_op("convolution",
"{dilation:[1,1],group:2,padding:[2,2,2,2],padding_mode:0,stride:[1,"
"1],use_dynamic_same_auto_pad:0}"),
x_main_module_25,
x_main_module_16);
auto x_main_module_27 = mmain->add_instruction(
migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,256,26,26]}"), x_main_module_17);
auto x_main_module_28 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_26, x_main_module_27);
auto x_main_module_29 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_28);
auto x_main_module_30 = mmain->add_instruction( auto x_main_module_30 = mmain->add_instruction(
migraphx::make_json_op("lrn", "{alpha:9.999999747378752e-05,beta:0.75,bias:1.0,size:5}"), migraphx::make_json_op(
x_main_module_29); "convolution",
"{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,1]}"),
x_main_module_29,
x_main_module_15);
auto x_main_module_31 = mmain->add_instruction( auto x_main_module_31 = mmain->add_instruction(
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_json_op( migraphx::make_json_op(
"pooling", "convolution",
"{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}"), "{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,1]}"),
x_main_module_30); x_main_module_33,
auto x_main_module_32 = mmain->add_instruction( x_main_module_13);
migraphx::make_json_op("convolution", auto x_main_module_35 = mmain->add_instruction(
"{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1," migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,256,13,13]}"), x_main_module_12);
"1],use_dynamic_same_auto_pad:0}"), auto x_main_module_36 =
x_main_module_31, mmain->add_instruction(migraphx::make_op("add"), x_main_module_34, x_main_module_35);
x_main_module_14); auto x_main_module_37 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_36);
auto x_main_module_33 = mmain->add_instruction( auto x_main_module_38 = mmain->add_instruction(
migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,384,12,12]}"), x_main_module_15); migraphx::make_json_op(
auto x_main_module_34 = "convolution",
mmain->add_instruction(migraphx::make_op("add"), x_main_module_32, x_main_module_33); "{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,1]}"),
auto x_main_module_35 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_34); x_main_module_37,
auto x_main_module_36 = mmain->add_instruction( x_main_module_11);
migraphx::make_json_op("convolution", auto x_main_module_39 = mmain->add_instruction(
"{dilation:[1,1],group:2,padding:[1,1,1,1],padding_mode:0,stride:[1," migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,256,13,13]}"), x_main_module_10);
"1],use_dynamic_same_auto_pad:0}"), auto x_main_module_40 =
x_main_module_35, mmain->add_instruction(migraphx::make_op("add"), x_main_module_38, x_main_module_39);
x_main_module_12); auto x_main_module_41 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_40);
auto x_main_module_37 = mmain->add_instruction( auto x_main_module_42 = mmain->add_instruction(
migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,384,12,12]}"), x_main_module_13);
auto x_main_module_38 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_36, x_main_module_37);
auto x_main_module_39 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_38);
auto x_main_module_40 = mmain->add_instruction(
migraphx::make_json_op("convolution",
"{dilation:[1,1],group:2,padding:[1,1,1,1],padding_mode:0,stride:[1,"
"1],use_dynamic_same_auto_pad:0}"),
x_main_module_39,
x_main_module_10);
auto x_main_module_41 = mmain->add_instruction(
migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,256,12,12]}"), x_main_module_11);
auto x_main_module_42 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_40, x_main_module_41);
auto x_main_module_43 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_42);
auto x_main_module_44 = mmain->add_instruction(
migraphx::make_json_op( migraphx::make_json_op(
"pooling", "pooling",
"{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,1,1],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_43); x_main_module_41);
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( auto x_main_module_45 = mmain->add_instruction(
migraphx::make_json_op("reshape", "{dims:[1,9216]}"), x_main_module_44); migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_9);
auto x_main_module_46 = mmain->add_instruction( auto x_main_module_46 =
migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_8); mmain->add_instruction(migraphx::make_op("dot"), x_main_module_44, x_main_module_45);
auto x_main_module_47 = auto x_main_module_47 = mmain->add_instruction(
mmain->add_instruction(migraphx::make_op("dot"), x_main_module_45, x_main_module_46); migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_8);
auto x_main_module_48 = mmain->add_instruction( auto x_main_module_48 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_9);
auto x_main_module_49 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_2); migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_2);
auto x_main_module_49 =
mmain->add_instruction(migraphx::make_op("mul"), x_main_module_47, x_main_module_48);
auto x_main_module_50 = auto x_main_module_50 =
mmain->add_instruction(migraphx::make_op("mul"), x_main_module_48, x_main_module_49); mmain->add_instruction(migraphx::make_op("add"), x_main_module_46, x_main_module_49);
auto x_main_module_51 = auto x_main_module_51 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_50);
mmain->add_instruction(migraphx::make_op("add"), x_main_module_47, x_main_module_50); auto x_main_module_52 = mmain->add_instruction(migraphx::make_op("identity"), x_main_module_51);
auto x_main_module_52 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_51); auto x_main_module_53 = mmain->add_instruction(
auto x_main_module_53 = mmain->add_instruction(migraphx::make_op("identity"), x_main_module_52); migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_7);
auto x_main_module_54 = mmain->add_instruction( auto x_main_module_54 =
migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_6); mmain->add_instruction(migraphx::make_op("dot"), x_main_module_52, x_main_module_53);
auto x_main_module_55 = auto x_main_module_55 = mmain->add_instruction(
mmain->add_instruction(migraphx::make_op("dot"), x_main_module_53, x_main_module_54); migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_6);
auto x_main_module_56 = mmain->add_instruction( auto x_main_module_56 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_7);
auto x_main_module_57 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_1); 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 = auto x_main_module_58 =
mmain->add_instruction(migraphx::make_op("mul"), x_main_module_56, x_main_module_57); mmain->add_instruction(migraphx::make_op("add"), x_main_module_54, x_main_module_57);
auto x_main_module_59 = auto x_main_module_59 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_58);
mmain->add_instruction(migraphx::make_op("add"), x_main_module_55, x_main_module_58); auto x_main_module_60 = mmain->add_instruction(
auto x_main_module_60 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_59); migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_5);
auto x_main_module_61 = mmain->add_instruction(migraphx::make_op("identity"), x_main_module_60); 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( auto x_main_module_62 = mmain->add_instruction(
migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_4); migraphx::make_json_op("multibroadcast", "{out_lens:[1,1000]}"), x_main_module_4);
auto x_main_module_63 = auto x_main_module_63 = mmain->add_instruction(
mmain->add_instruction(migraphx::make_op("dot"), x_main_module_61, x_main_module_62);
auto x_main_module_64 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,1000]}"), x_main_module_5);
auto x_main_module_65 = mmain->add_instruction(
migraphx::make_json_op("multibroadcast", "{out_lens:[1,1000]}"), x_main_module_0); migraphx::make_json_op("multibroadcast", "{out_lens:[1,1000]}"), x_main_module_0);
auto x_main_module_66 = auto x_main_module_64 =
mmain->add_instruction(migraphx::make_op("mul"), x_main_module_64, x_main_module_65); mmain->add_instruction(migraphx::make_op("mul"), x_main_module_62, x_main_module_63);
auto x_main_module_67 = auto x_main_module_65 =
mmain->add_instruction(migraphx::make_op("add"), x_main_module_63, x_main_module_66); mmain->add_instruction(migraphx::make_op("add"), x_main_module_61, x_main_module_64);
auto x_main_module_68 = mmain->add_return({x_main_module_65});
mmain->add_instruction(migraphx::make_json_op("softmax", "{axis:1}"), x_main_module_67);
mmain->add_return({x_main_module_68});
return p; return p;
} }
......
src/driver/inceptionv3.cpp
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src/driver/resnet50.cpp
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src/driver/verify.cpp
View file @ 360b1801
...@@ -145,7 +145,7 @@ void verify_reduced(program p, ...@@ -145,7 +145,7 @@ void verify_reduced(program p,
auto* mm = p.get_main_module(); auto* mm = p.get_main_module();
auto last = std::prev(mm->end(), n + 1); auto last = std::prev(mm->end(), n + 1);
mm->remove_instructions(last, mm->end()); mm->remove_instructions(last, mm->end());
std::cout << "Verify: " << std::endl; std::cout << "Verify: " << n << std::endl;
std::cout << p << std::endl; std::cout << p << std::endl;
verify_program(std::to_string(n), p, t, options, quantize, inputs, tolerance); verify_program(std::to_string(n), p, t, options, quantize, inputs, tolerance);
} }
...@@ -159,6 +159,7 @@ void verify_reduced_program(const program& p, ...@@ -159,6 +159,7 @@ void verify_reduced_program(const program& p,
{ {
const auto* mm = p.get_main_module(); const auto* mm = p.get_main_module();
auto n = std::distance(mm->begin(), mm->end()); auto n = std::distance(mm->begin(), mm->end());
std::cout << "Verify steps: " << n << std::endl;
for(std::size_t i = 0; i < n; i++) for(std::size_t i = 0; i < n; i++)
{ {
verify_reduced(p, i, t, options, quantize, inputs, tolerance); verify_reduced(p, i, t, options, quantize, inputs, tolerance);
......
src/targets/gpu/fuse_mlir.cpp
View file @ 360b1801
...@@ -49,7 +49,7 @@ struct mlir_conv ...@@ -49,7 +49,7 @@ struct mlir_conv
std::string name() const { return "gpu::mlir_conv"; } std::string name() const { return "gpu::mlir_conv"; }
shape compute_shape(std::vector<shape> inputs, const std::vector<module_ref>& mods) const shape compute_shape(std::vector<shape> inputs, const std::vector<module_ref>& mods) const
{ {
check_shapes{inputs, *this}.standard(); check_shapes{inputs, *this}.packed_or_broadcasted();
if(mods.size() != 1) if(mods.size() != 1)
MIGRAPHX_THROW("should have one submodule."); MIGRAPHX_THROW("should have one submodule.");
if(inputs.size() < 2) if(inputs.size() < 2)
...@@ -70,6 +70,9 @@ MIGRAPHX_PRED_MATCHER(is_mlir_conv, instruction_ref ins) ...@@ -70,6 +70,9 @@ MIGRAPHX_PRED_MATCHER(is_mlir_conv, instruction_ref ins)
auto group = v.at("group").to<int>(); auto group = v.at("group").to<int>();
if(group != 1) if(group != 1)
return false; return false;
// Avoid MLIR assertion: Index < Length && "Invalid index!"
if(ins->get_shape().lens().size() != 4)
return false;
return true; return true;
} }
...@@ -96,9 +99,10 @@ struct find_conv_pointwise ...@@ -96,9 +99,10 @@ struct find_conv_pointwise
i.name()); i.name());
})) }))
return; return;
// Only fuse with fp32 for now // Only fuse with fp32/fp16
if(std::any_of(ins->inputs().begin(), ins->inputs().end(), [&](auto i) { if(std::any_of(ins->inputs().begin(), ins->inputs().end(), [&](auto i) {
return i->get_shape().type() != shape::type_t::float_type; return not contains({shape::type_t::float_type, shape::type_t::half_type},
i->get_shape().type());
})) }))
return; return;
std::sort(names.begin(), names.end()); std::sort(names.begin(), names.end());
......
src/targets/gpu/include/migraphx/gpu/mlir.hpp
View file @ 360b1801
...@@ -36,7 +36,8 @@ struct module; ...@@ -36,7 +36,8 @@ struct module;
namespace gpu { namespace gpu {
std::string dump_mlir(const module& m); std::string dump_mlir(const module& m);
code_object_op compile_mlir(const context& ctx, const module& m); code_object_op
compile_mlir(const context& ctx, module m, const std::vector<instruction_ref>& inputs);
instruction_ref insert_mlir(module& m, instruction_ref insert_mlir(module& m,
instruction_ref ins, instruction_ref ins,
......
src/targets/gpu/include/migraphx/gpu/perfdb.hpp
View file @ 360b1801
...@@ -41,7 +41,7 @@ struct problem_params ...@@ -41,7 +41,7 @@ struct problem_params
shape output; shape output;
}; };
std::string get_mlir_perf_for_conv(const problem_params& pp); std::string get_mlir_perf_for_conv(const problem_params& pp, bool xdlops);
} // namespace gpu } // namespace gpu
} // namespace MIGRAPHX_INLINE_NS } // namespace MIGRAPHX_INLINE_NS
......
src/targets/gpu/jit/mlir.cpp
View file @ 360b1801
...@@ -41,7 +41,7 @@ struct mlir_compiler : compiler<mlir_compiler> ...@@ -41,7 +41,7 @@ struct mlir_compiler : compiler<mlir_compiler>
{ {
auto* smod = ins->module_inputs().front(); auto* smod = ins->module_inputs().front();
assert(smod->get_parameter_names().size() == ins->inputs().size() - 1); assert(smod->get_parameter_names().size() == ins->inputs().size() - 1);
return insert(compile_mlir(ctx, *smod)); return insert(compile_mlir(ctx, *smod, ins->inputs()));
} }
compiler_replace insert(code_object_op co) const compiler_replace insert(code_object_op co) const
......
src/targets/gpu/mlir.cpp
View file @ 360b1801
...@@ -21,6 +21,7 @@ ...@@ -21,6 +21,7 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE. * THE SOFTWARE.
*/ */
#include "migraphx/make_op.hpp"
#include <migraphx/gpu/mlir.hpp> #include <migraphx/gpu/mlir.hpp>
#ifdef MIGRAPHX_MLIR #ifdef MIGRAPHX_MLIR
...@@ -43,8 +44,9 @@ ...@@ -43,8 +44,9 @@
#include <migraphx/gpu/code_object_op.hpp> #include <migraphx/gpu/code_object_op.hpp>
#include <migraphx/gpu/context.hpp> #include <migraphx/gpu/context.hpp>
#include <migraphx/gpu/device_name.hpp> #include <migraphx/gpu/device_name.hpp>
#include <migraphx/iterator_for.hpp>
#include <migraphx/gpu/perfdb.hpp> #include <migraphx/gpu/perfdb.hpp>
#include <migraphx/iterator_for.hpp>
#include <migraphx/permutation.hpp>
#include <deque> #include <deque>
#include <variant> #include <variant>
...@@ -370,7 +372,11 @@ struct mlir_program ...@@ -370,7 +372,11 @@ struct mlir_program
mlir_operation_state& add_results(const std::vector<shape>& outputs) mlir_operation_state& add_results(const std::vector<shape>& outputs)
{ {
auto x = prog->make_tensors(outputs); std::vector<shape> reshaped(outputs.size());
std::transform(outputs.begin(), outputs.end(), reshaped.begin(), [](const shape& r) {
return shape{r.type(), r.lens()};
});
auto x = prog->make_tensors(reshaped);
mlirOperationStateAddResults(&op_state, x.size(), x.data()); mlirOperationStateAddResults(&op_state, x.size(), x.data());
return *this; return *this;
} }
...@@ -502,11 +508,12 @@ struct mlir_program ...@@ -502,11 +508,12 @@ struct mlir_program
{ {
pp = pp =
problem_params{ins->get_operator(), to_shapes(ins->inputs()), ins->get_shape()}; problem_params{ins->get_operator(), to_shapes(ins->inputs()), ins->get_shape()};
std::string tuned = get_tune_params(); // check if HW supports xdlops
bool xdlops = contains(get_xdlops_archs(), target_name);
std::string tuned = get_tune_params(xdlops);
if(not tuned.empty()) if(not tuned.empty())
ops.add_attributes({{"perf_config", tuned}}); ops.add_attributes({{"perf_config", tuned}});
// check if HW supports xdlops if(xdlops)
if(contains(get_xdlops_archs(), target_name))
ops.add_attributes({{"xdlopsV2", true}}); ops.add_attributes({{"xdlopsV2", true}});
} }
...@@ -571,7 +578,7 @@ struct mlir_program ...@@ -571,7 +578,7 @@ struct mlir_program
MIGRAPHX_THROW("Failed to compile mlir program"); MIGRAPHX_THROW("Failed to compile mlir program");
} }
std::string get_tune_params() { return get_mlir_perf_for_conv(pp); } std::string get_tune_params(bool xdlops) { return get_mlir_perf_for_conv(pp, xdlops); }
mlir_context ctx; mlir_context ctx;
MlirLocation location; MlirLocation location;
...@@ -589,8 +596,54 @@ std::string dump_mlir(const module& m) ...@@ -589,8 +596,54 @@ std::string dump_mlir(const module& m)
return mlir_print(&mlirOperationPrint, mod_op); return mlir_print(&mlirOperationPrint, mod_op);
} }
code_object_op compile_mlir(const context&, const module& m) void adjust_param_shapes(module& m, const std::vector<instruction_ref>& inputs)
{
auto names = m.get_parameter_names();
std::sort(names.begin(), names.end());
for(auto i : range(names.size()))
{
const auto& name = names[i];
const auto& input = inputs[i]->get_shape();
auto param = m.get_parameter(name);
if(input.standard())
continue;
auto lens = input.lens();
auto strides = input.strides();
std::vector<operation> ops;
if(input.transposed())
{
auto perm = find_permutation(input);
auto iperm = invert_permutation(perm);
lens = reorder_dims(lens, iperm);
strides = reorder_dims(strides, iperm);
ops.push_back(make_op("transpose", {{"permutation", perm}}));
}
if(input.broadcasted())
{
std::transform(lens.begin(),
lens.end(),
strides.begin(),
lens.begin(),
[](auto len, auto stride) -> std::size_t {
if(stride == 0)
return 1;
return len;
});
ops.push_back(make_op("multibroadcast", {{"out_lens", input.lens()}}));
}
auto new_param =
std::accumulate(ops.begin(),
ops.end(),
m.add_parameter(name + ".0", shape{input.type(), lens}),
[&](auto x, auto op) { return m.insert_instruction(param, op, x); });
m.replace_instruction(param, new_param);
m.remove_instruction(param);
}
}
code_object_op compile_mlir(const context&, module m, const std::vector<instruction_ref>& inputs)
{ {
adjust_param_shapes(m, inputs);
const bool trace = enabled(MIGRAPHX_TRACE_MLIR{}); const bool trace = enabled(MIGRAPHX_TRACE_MLIR{});
if(trace) if(trace)
std::cout << m << std::endl; std::cout << m << std::endl;
...@@ -662,13 +715,19 @@ instruction_ref insert_mlir(module& m, ...@@ -662,13 +715,19 @@ instruction_ref insert_mlir(module& m,
std::string dump_mlir(const module&) { return {}; } std::string dump_mlir(const module&) { return {}; }
code_object_op compile_mlir(const context&, const module&) { return {}; }
template <class T> template <class T>
void use(T&) void use(T&)
{ {
} }
// Disabling clang-tidy warning on non-real useage.
// NOLINTBEGIN(performance-unnecessary-value-param)
code_object_op compile_mlir(const context&, module, const std::vector<instruction_ref>&)
{
return {};
}
// NOLINTEND(performance-unnecessary-value-param)
instruction_ref instruction_ref
// cppcheck-suppress funcArgNamesDifferent // cppcheck-suppress funcArgNamesDifferent
insert_mlir(module& m, instruction_ref, code_object_op co, const std::vector<instruction_ref>&) insert_mlir(module& m, instruction_ref, code_object_op co, const std::vector<instruction_ref>&)
......
src/targets/gpu/perfdb.cpp
View file @ 360b1801
...@@ -108,16 +108,17 @@ auto query_miopen_db(const std::string& query) ...@@ -108,16 +108,17 @@ auto query_miopen_db(const std::string& query)
} // namespace } // namespace
std::string get_mlir_perf_for_conv(const problem_params& pp) std::string get_mlir_perf_for_conv(const problem_params& pp, bool xdlops)
{ {
std::string solver = xdlops ? "ConvMlirIgemmFwdXdlops" : "ConvMlirIgemmFwd";
std::string query = "select P.* \ std::string query = "select P.* \
from perf_db P, config C \ from perf_db P, config C \
where P.config = C.id AND \ where P.config = C.id AND \
P.solver = 'ConvMlirIgemmFwdXdlops' AND \ P.solver = '${solver}' AND \
${config}"; ${config}";
auto results = auto results = query_miopen_db(
query_miopen_db(interpolate_string(query, {{"config", generate_miopen_config(pp)}})); interpolate_string(query, {{"config", generate_miopen_config(pp)}, {"solver", solver}}));
if(results.empty()) if(results.empty())
return ""; return "";
return results.front().at("params"); return results.front().at("params");
......
src/targets/gpu/target.cpp
View file @ 360b1801
...@@ -138,12 +138,12 @@ std::vector<pass> target::get_passes(migraphx::context& gctx, const compile_opti ...@@ -138,12 +138,12 @@ std::vector<pass> target::get_passes(migraphx::context& gctx, const compile_opti
dead_code_elimination{}, dead_code_elimination{},
pack_int8_args{}, pack_int8_args{},
dead_code_elimination{}, dead_code_elimination{},
adjust_allocation{gpu_allocation_model{}},
dead_code_elimination{},
fuse_ops{&ctx, options.fast_math}, fuse_ops{&ctx, options.fast_math},
dead_code_elimination{}, dead_code_elimination{},
replace_allocate{gpu_allocation_model{}, options.offload_copy}, replace_allocate{gpu_allocation_model{}, options.offload_copy},
dead_code_elimination{}, dead_code_elimination{},
adjust_allocation{gpu_allocation_model{}},
dead_code_elimination{},
compile_ops{&ctx}, compile_ops{&ctx},
dead_code_elimination{}, dead_code_elimination{},
write_literals{&ctx}, write_literals{&ctx},
......
test/gpu/mlir.cpp
View file @ 360b1801
...@@ -84,7 +84,7 @@ migraphx::program create_program_from_mlir(const migraphx::module& mmlir) ...@@ -84,7 +84,7 @@ migraphx::program create_program_from_mlir(const migraphx::module& mmlir)
inputs.push_back(mm->add_parameter("output", mmlir.get_output_shapes().front())); inputs.push_back(mm->add_parameter("output", mmlir.get_output_shapes().front()));
migraphx::gpu::context ctx; migraphx::gpu::context ctx;
migraphx::gpu::insert_mlir(*mm, mm->end(), compile_mlir(ctx, mmlir), inputs); migraphx::gpu::insert_mlir(*mm, mm->end(), compile_mlir(ctx, mmlir, inputs), inputs);
return p; return p;
} }
......
test/verify/test_shape_alloc.cpp 0 → 100644
View file @ 360b1801
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#include "verify_program.hpp"
#include <migraphx/program.hpp>
#include <migraphx/generate.hpp>
#include <migraphx/make_op.hpp>
#include <migraphx/op/reduce_mean.hpp>
/**
* @brief test_shape_alloc sets up a situation that could lead to an exception "convolution: Shapes
* are not in standard layout" if a "replace_allocate" compiler pass is not followed with
* "adjust_allocation". The last transpose instruction generates a shape with a stride of 1 in
* the 2nd index, a non-standard layout that should be reallocated by adjust_allocation.
*/
struct test_shape_alloc : verify_program<test_shape_alloc>
{
migraphx::program create_program() const
{
migraphx::program p;
auto* mm = p.get_main_module();
auto weights = mm->add_literal(migraphx::generate_literal(
migraphx::shape{migraphx::shape::float_type, {11, 8, 1, 1}, {8, 1, 1, 1}}));
auto x = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 8, 7, 7}});
auto transpose1 =
mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {0, 2, 3, 1}}}),
x); // -> float_type, {1, 7, 7, 8}, {392, 7, 1, 49}
auto reduce_ins =
mm->add_instruction(migraphx::make_op("reduce_mean", {{"axes", {1, 2}}}),
transpose1); // -> float_type, {1, 1, 1, 8}, {8, 8, 8, 1}
auto transpose2 =
mm->add_instruction(migraphx::make_op("transpose", {{"permutation", {0, 3, 1, 2}}}),
reduce_ins); // -> float_type, {1, 8, 1, 1}, {8, 1, 8, 8}
auto conv_op = migraphx::make_op("convolution");
mm->add_instruction(conv_op, transpose2, weights);
return p;
}
};
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