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Commit 68886f7d authored by raman jana's avatar raman jana
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merging with latest develop branch

parents a9ee2960 1677cf70
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Showing with 1258 additions and 297 deletions
script/profile_conv.sh
View file @ 68886f7d
...@@ -3,9 +3,9 @@ ...@@ -3,9 +3,9 @@
## GPU visibility ## GPU visibility
export HIP_VISIBLE_DEVICES=0 export HIP_VISIBLE_DEVICES=0
make -j ckProfiler # make -j ckProfiler
DRIVER="./profiler/ckProfiler" DRIVER="../build/bin/ckProfiler"
OP=$1 OP=$1
DATATYPE=$2 DATATYPE=$2
...@@ -51,56 +51,56 @@ REPEAT=$9 ...@@ -51,56 +51,56 @@ REPEAT=$9
# Resnet50 from Bing # Resnet50 from Bing
#################### op____________________ datatype in_layout wei_layout out_layout verify init log repeat N__ K___ C___ Y X Hi__ Wi__ Strides Dilations LeftPads RightPads ####### op_________________ datatype in_layout wei_layout out_layout verify init log repeat N__ K___ C_ Y X Hi_ Wi__ Strides Dilations LeftPads RightPads
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 3 7 7 224 224 2 2 1 1 3 3 3 3 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 3 7 7 224 224 2 2 1 1 3 3 3 3
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 64 1 1 56 56 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 64 1 1 56 56 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 64 3 3 56 56 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 64 3 3 56 56 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 64 1 1 56 56 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 64 1 1 56 56 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 256 1 1 56 56 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 256 1 1 56 56 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 64 3 3 56 56 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 64 3 3 56 56 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 64 1 1 56 56 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 64 1 1 56 56 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 256 1 1 56 56 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 256 1 1 56 56 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 64 3 3 56 56 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 64 64 3 3 56 56 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 64 1 1 56 56 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 64 1 1 56 56 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 256 1 1 56 56 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 256 1 1 56 56 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 128 3 3 56 56 2 2 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 128 3 3 56 56 2 2 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 128 1 1 28 28 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 128 1 1 28 28 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 512 1 1 28 28 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 512 1 1 28 28 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 128 3 3 28 28 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 128 3 3 28 28 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 128 1 1 28 28 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 128 1 1 28 28 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 512 1 1 28 28 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 512 1 1 28 28 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 128 3 3 28 28 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 128 3 3 28 28 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 128 1 1 28 28 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 128 1 1 28 28 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 512 1 1 28 28 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 512 1 1 28 28 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 128 3 3 28 28 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 128 128 3 3 28 28 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 128 1 1 28 28 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 128 1 1 28 28 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 512 1 1 28 28 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 512 1 1 28 28 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 28 28 2 2 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 28 28 2 2 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 1024 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 1024 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 14 14 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 14 14 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 1024 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 1024 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 14 14 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 14 14 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 1024 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 1024 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 14 14 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 14 14 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 1024 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 1024 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 14 14 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 14 14 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 1024 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 1024 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 14 14 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 256 256 3 3 14 14 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 1024 256 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 1024 1 1 14 14 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 1024 1 1 14 14 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 512 3 3 14 14 2 2 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 512 3 3 14 14 2 2 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 2048 512 1 1 7 7 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 2048 512 1 1 7 7 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 2048 1 1 7 7 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 2048 1 1 7 7 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 512 3 3 7 7 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 512 3 3 7 7 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 2048 512 1 1 7 7 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 2048 512 1 1 7 7 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 2048 1 1 7 7 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 2048 1 1 7 7 1 1 1 1 0 0 0 0
#profiler/ckProfiler conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 512 3 3 7 7 1 1 1 1 1 1 1 1 $DRIVER conv_fwd_bias_relu $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 512 512 3 3 7 7 1 1 1 1 1 1 1 1
#profiler/ckProfiler conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 2048 512 1 1 7 7 1 1 1 1 0 0 0 0 $DRIVER conv_fwd_bias_relu_add $DATATYPE $IN_LAYOUT $WEI_LAYOUT $OUT_LAYOUT $VERIFY $INIT $LOG $REPEAT $N 2048 512 1 1 7 7 1 1 1 1 0 0 0 0
# Resnet50 # Resnet50
......
script/test_reduce_no_index.sh
View file @ 68886f7d
...@@ -15,6 +15,17 @@ bin/test_reduce_no_index -D 64,4,280,82 -R 1 0 2 ...@@ -15,6 +15,17 @@ bin/test_reduce_no_index -D 64,4,280,82 -R 1 0 2
bin/test_reduce_no_index -D 64,4,280,82 -R 2 0 2 bin/test_reduce_no_index -D 64,4,280,82 -R 2 0 2
bin/test_reduce_no_index -D 64,4,280,82 -R 3 0 2 bin/test_reduce_no_index -D 64,4,280,82 -R 3 0 2
## for float64
bin/test_reduce_no_index -D 64,4,280,82 -R 0,1,2,3 6 2
bin/test_reduce_no_index -D 64,4,280,82 -R 0,1,2 6 2
bin/test_reduce_no_index -D 64,4,280,82 -R 0,1,3 6 2
bin/test_reduce_no_index -D 64,4,280,82 -R 0,2,3 6 2
bin/test_reduce_no_index -D 64,4,280,82 -R 1,2,3 6 2
bin/test_reduce_no_index -D 64,4,280,82 -R 0 6 2
bin/test_reduce_no_index -D 64,4,280,82 -R 1 6 2
bin/test_reduce_no_index -D 64,4,280,82 -R 2 6 2
bin/test_reduce_no_index -D 64,4,280,82 -R 3 6 2
## for float16 ## for float16
bin/test_reduce_no_index -D 64,4,280,82 -R 0,1,2,3 1 2 bin/test_reduce_no_index -D 64,4,280,82 -R 0,1,2,3 1 2
bin/test_reduce_no_index -D 64,4,280,82 -R 0,1,2 1 2 bin/test_reduce_no_index -D 64,4,280,82 -R 0,1,2 1 2
......
script/test_reduce_with_index.sh
View file @ 68886f7d
...@@ -15,6 +15,17 @@ bin/test_reduce_with_index -D 64,4,280,82 -R 1 0 2 ...@@ -15,6 +15,17 @@ bin/test_reduce_with_index -D 64,4,280,82 -R 1 0 2
bin/test_reduce_with_index -D 64,4,280,82 -R 2 0 2 bin/test_reduce_with_index -D 64,4,280,82 -R 2 0 2
bin/test_reduce_with_index -D 64,4,280,82 -R 3 0 2 bin/test_reduce_with_index -D 64,4,280,82 -R 3 0 2
## for float64
bin/test_reduce_with_index -D 64,4,280,82 -R 0,1,2,3 6 2
bin/test_reduce_with_index -D 64,4,280,82 -R 0,1,2 6 2
bin/test_reduce_with_index -D 64,4,280,82 -R 0,1,3 6 2
bin/test_reduce_with_index -D 64,4,280,82 -R 0,2,3 6 2
bin/test_reduce_with_index -D 64,4,280,82 -R 1,2,3 6 2
bin/test_reduce_with_index -D 64,4,280,82 -R 0 6 2
bin/test_reduce_with_index -D 64,4,280,82 -R 1 6 2
bin/test_reduce_with_index -D 64,4,280,82 -R 2 6 2
bin/test_reduce_with_index -D 64,4,280,82 -R 3 6 2
## for float16 ## for float16
bin/test_reduce_with_index -D 64,4,280,82 -R 0,1,2,3 1 2 bin/test_reduce_with_index -D 64,4,280,82 -R 0,1,2,3 1 2
bin/test_reduce_with_index -D 64,4,280,82 -R 0,1,2 1 2 bin/test_reduce_with_index -D 64,4,280,82 -R 0,1,2 1 2
......
test/CMakeLists.txt
View file @ 68886f7d
...@@ -2,6 +2,7 @@ include_directories(BEFORE ...@@ -2,6 +2,7 @@ include_directories(BEFORE
${PROJECT_SOURCE_DIR}/ ${PROJECT_SOURCE_DIR}/
${PROJECT_SOURCE_DIR}/include/ck ${PROJECT_SOURCE_DIR}/include/ck
${PROJECT_SOURCE_DIR}/include/ck/utility ${PROJECT_SOURCE_DIR}/include/ck/utility
${PROJECT_SOURCE_DIR}/include/ck/host_utility
${PROJECT_SOURCE_DIR}/include/ck/tensor_description ${PROJECT_SOURCE_DIR}/include/ck/tensor_description
${PROJECT_SOURCE_DIR}/include/ck/tensor ${PROJECT_SOURCE_DIR}/include/ck/tensor
${PROJECT_SOURCE_DIR}/include/ck/problem_transform ${PROJECT_SOURCE_DIR}/include/ck/problem_transform
...@@ -22,7 +23,8 @@ include_directories(BEFORE ...@@ -22,7 +23,8 @@ include_directories(BEFORE
${PROJECT_SOURCE_DIR}/external/include/half ${PROJECT_SOURCE_DIR}/external/include/half
) )
add_custom_target(check COMMAND ${CMAKE_CTEST_COMMAND} --output-on-failure -C ${CMAKE_CFG_INTDIR}) include(googletest)
add_custom_target(tests) add_custom_target(tests)
...@@ -61,3 +63,6 @@ add_subdirectory(grouped_gemm) ...@@ -61,3 +63,6 @@ add_subdirectory(grouped_gemm)
add_subdirectory(convnd_fwd) add_subdirectory(convnd_fwd)
add_subdirectory(reduce) add_subdirectory(reduce)
add_subdirectory(conv2d_bwd_weight) add_subdirectory(conv2d_bwd_weight)
add_subdirectory(convnd_bwd_data)
add_subdirectory(block_to_ctile_map)
# DONOT add client_app, that is tested via CI independently
test/batched_gemm_reduce/batched_gemm_reduce_fp16.cpp
View file @ 68886f7d
...@@ -22,7 +22,7 @@ int main() ...@@ -22,7 +22,7 @@ int main()
Row, Row,
Row, Row,
Row>( Row>(
true, 1, false, 1, M, N, K, K, N, N, BatchCount); true, 1, false, false, M, N, K, K, N, N, BatchCount);
pass = pass && ck::profiler::profile_batched_gemm_reduce_impl<ck::half_t, pass = pass && ck::profiler::profile_batched_gemm_reduce_impl<ck::half_t,
ck::half_t, ck::half_t,
...@@ -31,7 +31,7 @@ int main() ...@@ -31,7 +31,7 @@ int main()
Row, Row,
Col, Col,
Row>( Row>(
true, 1, false, 1, M, N, K, K, K, N, BatchCount); true, 1, false, false, M, N, K, K, K, N, BatchCount);
pass = pass && ck::profiler::profile_batched_gemm_reduce_impl<ck::half_t, pass = pass && ck::profiler::profile_batched_gemm_reduce_impl<ck::half_t,
ck::half_t, ck::half_t,
...@@ -40,7 +40,7 @@ int main() ...@@ -40,7 +40,7 @@ int main()
Col, Col,
Row, Row,
Row>( Row>(
true, 1, false, 1, M, N, K, M, N, N, BatchCount); true, 1, false, false, M, N, K, M, N, N, BatchCount);
pass = pass && ck::profiler::profile_batched_gemm_reduce_impl<ck::half_t, pass = pass && ck::profiler::profile_batched_gemm_reduce_impl<ck::half_t,
ck::half_t, ck::half_t,
...@@ -49,7 +49,7 @@ int main() ...@@ -49,7 +49,7 @@ int main()
Col, Col,
Col, Col,
Row>( Row>(
true, 1, false, 1, M, N, K, M, K, N, BatchCount); true, 1, false, false, M, N, K, M, K, N, BatchCount);
if(pass) if(pass)
{ {
......
test/block_to_ctile_map/CMakeLists.txt 0 → 100644
View file @ 68886f7d
add_gtest_executable(test_block_to_ctile_map test_block_to_ctile_map.cpp)
\ No newline at end of file
test/block_to_ctile_map/test_block_to_ctile_map.cpp 0 → 100644
View file @ 68886f7d
#include <ck/config.hpp>
#include "ck/tensor_operation/gpu/grid/block_to_ctile_map.hpp"
#include "gtest/gtest.h"
#include <iostream>
#include <vector>
using namespace ck;
static auto I0 = Number<0>{};
static auto I1 = Number<1>{};
static auto I2 = Number<2>{};
TEST(BlockToCTileMap, TestBlockToCTileMap_M00_N00_M01_N01_DeviceCTileIndexCheck1)
{
const index_t M = 384;
const index_t N = 384;
const index_t MPerBlock = 128;
const index_t NPerBlock = 128;
const index_t MBlock = M / MPerBlock;
const index_t NBlock = N / NPerBlock;
const index_t M01 = 4;
const index_t N01 = 4;
auto c_grid_desc_m_n = make_naive_tensor_descriptor_packed(make_tuple(M, N));
printf("(M, N, MPerBlock, NPerBlock, M01, N01) = (%d, %d, %d, %d, %d, %d)\n",
M,
N,
MPerBlock,
NPerBlock,
M01,
N01);
BlockToCTileMap_M00_N00_M01_N01<MPerBlock, NPerBlock, decltype(c_grid_desc_m_n), true> tile_map(
c_grid_desc_m_n, M01, N01);
EXPECT_TRUE(tile_map.CheckValidity(c_grid_desc_m_n) == true);
EXPECT_TRUE(tile_map.CalculateGridSize(c_grid_desc_m_n) == 16);
// clang-format off
std::vector<std::vector<int>> expected_m0idx_n0idx_valid = {
{0, 0, 1},
{0, 1, 1},
{0, 2, 1},
{0, 3, 0},
{1, 0, 1},
{1, 1, 1},
{1, 2, 1},
{1, 3, 0},
{2, 0, 1},
{2, 1, 1},
{2, 2, 1},
{2, 3, 0},
{3, 0, 0},
{3, 1, 0},
{3, 2, 0},
{3, 3, 0}
};
// clang-format on
for(index_t i = 0; i < tile_map.CalculateGridSize(c_grid_desc_m_n); i++)
{
auto m0n0_idx = tile_map.CalculateBottomIndex(make_multi_index(i));
std::cout << "block_1d_id = " << i << ", m0, n0 = " << m0n0_idx[I0] << ", " << m0n0_idx[I1];
std::cout << ", valid = " << tile_map.ValidCTileIndex(m0n0_idx, make_tuple(MBlock, NBlock))
<< std::endl;
bool equal =
expected_m0idx_n0idx_valid[i] ==
std::vector<int>{m0n0_idx[I0],
m0n0_idx[I1],
tile_map.ValidCTileIndex(m0n0_idx, make_tuple(MBlock, NBlock))};
EXPECT_TRUE(equal);
}
}
TEST(BlockToCTileMap, TestBlockToCTileMap_M00_N00_M01_N01_DeviceCTileIndexCheck0)
{
const index_t M = 384;
const index_t N = 384;
const index_t MPerBlock = 128;
const index_t NPerBlock = 128;
const index_t M01 = 4;
const index_t N01 = 4;
auto c_grid_desc_m_n = make_naive_tensor_descriptor_packed(make_tuple(M, N));
printf("(M, N, MPerBlock, NPerBlock, M01, N01) = (%d, %d, %d, %d, %d, %d)\n",
M,
N,
MPerBlock,
NPerBlock,
M01,
N01);
BlockToCTileMap_M00_N00_M01_N01<MPerBlock, NPerBlock, decltype(c_grid_desc_m_n), false>
tile_map(c_grid_desc_m_n, M01, N01);
EXPECT_TRUE(tile_map.CheckValidity(c_grid_desc_m_n) == false);
}
TEST(BlockToCTileMap, TestBlockToCTileMap_M00_N0_M01_DeviceCTileIndexCheck1)
{
const index_t M = 384;
const index_t N = 512;
const index_t MPerBlock = 128;
const index_t NPerBlock = 128;
const index_t MBlock = M / MPerBlock;
const index_t NBlock = N / NPerBlock;
const index_t M01 = 4;
auto c_grid_desc_m_n = make_naive_tensor_descriptor_packed(make_tuple(M, N));
printf("(M, N, MPerBlock, NPerBlock, M01) = (%d, %d, %d, %d, %d)\n",
M,
N,
MPerBlock,
NPerBlock,
M01);
BlockToCTileMap_M00_N0_M01<MPerBlock, NPerBlock, decltype(c_grid_desc_m_n), true> tile_map(
c_grid_desc_m_n, M01);
EXPECT_TRUE(tile_map.CheckValidity(c_grid_desc_m_n) == true);
EXPECT_TRUE(tile_map.CalculateGridSize(c_grid_desc_m_n) == 16);
// clang-format off
std::vector<std::vector<int>> expected_m0idx_n0idx_valid = {
{0, 0, 1},
{1, 0, 1},
{2, 0, 1},
{3, 0, 0},
{0, 1, 1},
{1, 1, 1},
{2, 1, 1},
{3, 1, 0},
{0, 2, 1},
{1, 2, 1},
{2, 2, 1},
{3, 2, 0},
{0, 3, 1},
{1, 3, 1},
{2, 3, 1},
{3, 3, 0}
};
// clang-format on
for(index_t i = 0; i < tile_map.CalculateGridSize(c_grid_desc_m_n); i++)
{
auto m0n0_idx = tile_map.CalculateBottomIndex(make_multi_index(i));
std::cout << "block_1d_id = " << i << ", m0, n0 = " << m0n0_idx[I0] << ", " << m0n0_idx[I1];
std::cout << ", valid = " << tile_map.ValidCTileIndex(m0n0_idx, make_tuple(MBlock, NBlock))
<< std::endl;
bool equal =
expected_m0idx_n0idx_valid[i] ==
std::vector<int>{m0n0_idx[I0],
m0n0_idx[I1],
tile_map.ValidCTileIndex(m0n0_idx, make_tuple(MBlock, NBlock))};
EXPECT_TRUE(equal);
}
}
TEST(BlockToCTileMap, TestBlockToCTileMap_M00_N0_M01_DeviceCTileIndexCheck0)
{
const index_t M = 512;
const index_t N = 384;
const index_t MPerBlock = 128;
const index_t NPerBlock = 128;
auto c_grid_desc_m_n = make_naive_tensor_descriptor_packed(make_tuple(M, N));
// clang-format off
std::vector<std::tuple<int, int, bool>> expected_m0_gridsize_validity = {
{5, 15, false},
{4, 12, true},
{3, 18, false},
{2, 12, true},
{1, 12, true}
};
// clang-format on
for(auto e : expected_m0_gridsize_validity)
{
const index_t M01 = std::get<0>(e);
printf("(M, N, MPerBlock, NPerBlock, M01) = (%d, %d, %d, %d, %d)\n",
M,
N,
MPerBlock,
NPerBlock,
M01);
BlockToCTileMap_M00_N0_M01<MPerBlock, NPerBlock, decltype(c_grid_desc_m_n), false> tile_map(
c_grid_desc_m_n, M01);
EXPECT_EQ(tile_map.CalculateGridSize(c_grid_desc_m_n), std::get<1>(e));
EXPECT_EQ(tile_map.CheckValidity(c_grid_desc_m_n), std::get<2>(e));
}
}
TEST(BlockToCTileMap, TestBlockToCTileMap_M00_N0_M01Adapt)
{
const index_t M = 768;
const index_t N = 384;
const index_t MPerBlock = 128;
const index_t NPerBlock = 128;
const index_t MBlock = M / MPerBlock;
const index_t NBlock = N / NPerBlock;
constexpr index_t M01 = 4;
auto c_grid_desc_m_n = make_naive_tensor_descriptor_packed(make_tuple(M, N));
printf("(M, N, MPerBlock, NPerBlock, M01) = (%d, %d, %d, %d, %d)\n",
M,
N,
MPerBlock,
NPerBlock,
M01);
BlockToCTileMap_M00_N0_M01Adapt<MPerBlock, NPerBlock, decltype(c_grid_desc_m_n)> tile_map(
c_grid_desc_m_n, M01);
EXPECT_TRUE(tile_map.CheckValidity(c_grid_desc_m_n) == true);
EXPECT_TRUE(tile_map.CalculateGridSize(c_grid_desc_m_n) == 18);
// clang-format off
std::vector<std::vector<int>> expected_m0idx_n0idx_valid = {
{0, 0, 1},
{1, 0, 1},
{2, 0, 1},
{3, 0, 1},
{0, 1, 1},
{1, 1, 1},
{2, 1, 1},
{3, 1, 1},
{0, 2, 1},
{1, 2, 1},
{2, 2, 1},
{3, 2, 1},
{4, 0, 1},
{5, 0, 1},
{4, 1, 1},
{5, 1, 1},
{4, 2, 1},
{5, 2, 1},
};
// clang-format on
for(index_t i = 0; i < tile_map.CalculateGridSize(c_grid_desc_m_n); i++)
{
auto m0n0_idx = tile_map.CalculateBottomIndex(make_multi_index(i));
std::cout << "block_1d_id = " << i << ", m0, n0 = " << m0n0_idx[I0] << ", " << m0n0_idx[I1];
std::cout << ", valid = " << tile_map.ValidCTileIndex(m0n0_idx, make_tuple(MBlock, NBlock))
<< std::endl;
bool equal =
expected_m0idx_n0idx_valid[i] ==
std::vector<int>{m0n0_idx[I0],
m0n0_idx[I1],
tile_map.ValidCTileIndex(m0n0_idx, make_tuple(MBlock, NBlock))};
EXPECT_TRUE(equal);
}
}
TEST(BlockToCTileMap, TestBlockToCTileMap_KSplit_M00_N0_M01Adapt)
{
const index_t M = 768;
const index_t N = 384;
const index_t MPerBlock = 128;
const index_t NPerBlock = 128;
const index_t MBlock = M / MPerBlock;
const index_t NBlock = N / NPerBlock;
constexpr index_t M01 = 4;
const index_t KSplit = 3;
auto c_grid_desc_m_n = make_naive_tensor_descriptor_packed(make_tuple(M, N));
printf("(M, N, MPerBlock, NPerBlock, M01) = (%d, %d, %d, %d, %d)\n",
M,
N,
MPerBlock,
NPerBlock,
M01);
BlockToCTileMap_KSplit_M00_N0_M01Adapt<MPerBlock, NPerBlock, decltype(c_grid_desc_m_n)>
tile_map(c_grid_desc_m_n, M01, KSplit);
EXPECT_TRUE(tile_map.CheckValidity(c_grid_desc_m_n) == true);
EXPECT_TRUE(tile_map.CalculateGridSize(c_grid_desc_m_n) == 18 * KSplit);
std::vector<std::vector<int>> expected_ksplitidx_m0idx_n0idx_valid = {
{0, 0, 0, 1}, {0, 1, 0, 1}, {0, 2, 0, 1}, {0, 3, 0, 1}, {0, 0, 1, 1}, {0, 1, 1, 1},
{0, 2, 1, 1}, {0, 3, 1, 1}, {0, 0, 2, 1}, {0, 1, 2, 1}, {0, 2, 2, 1}, {0, 3, 2, 1},
{0, 4, 0, 1}, {0, 5, 0, 1}, {0, 4, 1, 1}, {0, 5, 1, 1}, {0, 4, 2, 1}, {0, 5, 2, 1},
{1, 0, 0, 1}, {1, 1, 0, 1}, {1, 2, 0, 1}, {1, 3, 0, 1}, {1, 0, 1, 1}, {1, 1, 1, 1},
{1, 2, 1, 1}, {1, 3, 1, 1}, {1, 0, 2, 1}, {1, 1, 2, 1}, {1, 2, 2, 1}, {1, 3, 2, 1},
{1, 4, 0, 1}, {1, 5, 0, 1}, {1, 4, 1, 1}, {1, 5, 1, 1}, {1, 4, 2, 1}, {1, 5, 2, 1},
{2, 0, 0, 1}, {2, 1, 0, 1}, {2, 2, 0, 1}, {2, 3, 0, 1}, {2, 0, 1, 1}, {2, 1, 1, 1},
{2, 2, 1, 1}, {2, 3, 1, 1}, {2, 0, 2, 1}, {2, 1, 2, 1}, {2, 2, 2, 1}, {2, 3, 2, 1},
{2, 4, 0, 1}, {2, 5, 0, 1}, {2, 4, 1, 1}, {2, 5, 1, 1}, {2, 4, 2, 1}, {2, 5, 2, 1},
};
for(index_t i = 0; i < tile_map.CalculateGridSize(c_grid_desc_m_n); i++)
{
auto ksplitm0n0_idx = tile_map.CalculateBottomIndex(make_multi_index(i));
std::cout << "block_1d_id = " << i << ", ksplit, m0, n0 = " << ksplitm0n0_idx[I0] << ", "
<< ksplitm0n0_idx[I1] << ", " << ksplitm0n0_idx[I2];
std::cout << ", valid = "
<< tile_map.ValidCTileIndex(ksplitm0n0_idx, make_tuple(MBlock, NBlock))
<< std::endl;
bool equal =
expected_ksplitidx_m0idx_n0idx_valid[i] ==
std::vector<int>{ksplitm0n0_idx[I0],
ksplitm0n0_idx[I1],
ksplitm0n0_idx[I2],
tile_map.ValidCTileIndex(ksplitm0n0_idx, make_tuple(MBlock, NBlock))};
EXPECT_TRUE(equal);
}
}
test/client_app/CMakeLists.txt 0 → 100644
View file @ 68886f7d
cmake_minimum_required(VERSION 3.15)
project(ck_app)
add_compile_options(-std=c++14)
find_package(composable_kernel 1.0.0 COMPONENTS device_operations host_tensor)
find_package(hip REQUIRED PATHS /opt/rocm)
message(STATUS "Build with HIP ${hip_VERSION}")
add_executable(test_client_app client_app.cpp)
target_link_libraries(test_client_app PRIVATE composable_kernel::device_operations composable_kernel::host_tensor hip::host)
test/client_app/client_app.cpp 0 → 100644
View file @ 68886f7d
#include <iostream>
#include <numeric>
#include <initializer_list>
#include <cstdlib>
#include <stdlib.h>
#include <half.hpp>
#include <vector>
#include "client_app_impl.hpp"
int main(int argc, char* argv[])
{
if(argc != 25)
{
printf("arg1: tensor operation (conv_fwd: ForwardConvolution)\n");
printf("arg2: data type (0: fp32; 1: fp16)\n");
printf("arg3: input tensor layout (0: NCHW; 1: NHWC)\n");
printf("arg4: weight tensor layout (0: KCYX; 1: KYXC)\n");
printf("arg5: output tensor layout (0: NKHW; 1: NHWK)\n");
printf("arg6: verification (0: no; 1: yes)\n");
printf("arg7: initialization (0: no init; 1: integer value; 2: decimal value)\n");
printf("arg8: print tensor value (0: no; 1: yes)\n");
printf("arg9: time kernel (0=n0, 1=yes)\n");
printf("arg10 to 24: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, "
"RightPx\n");
exit(1);
}
const ConvDataType data_type = static_cast<ConvDataType>(std::stoi(argv[2]));
const int in_layout = static_cast<ConvInputLayout>(std::stoi(argv[3]));
const int wei_layout = static_cast<ConvWeightLayout>(std::stoi(argv[4]));
const int out_layout = static_cast<ConvOutputLayout>(std::stoi(argv[5]));
const bool do_verification = std::stoi(argv[6]);
const int init_method = std::stoi(argv[7]);
const bool do_log = std::stoi(argv[8]);
const bool time_kernel = std::stoi(argv[9]);
const ck::index_t N = std::stoi(argv[10]);
const ck::index_t K = std::stoi(argv[11]);
const ck::index_t C = std::stoi(argv[12]);
const ck::index_t Y = std::stoi(argv[13]);
const ck::index_t X = std::stoi(argv[14]);
const ck::index_t Hi = std::stoi(argv[15]);
const ck::index_t Wi = std::stoi(argv[16]);
const ck::index_t conv_stride_h = std::stoi(argv[17]);
const ck::index_t conv_stride_w = std::stoi(argv[18]);
const ck::index_t conv_dilation_h = std::stoi(argv[19]);
const ck::index_t conv_dilation_w = std::stoi(argv[20]);
const ck::index_t in_left_pad_h = std::stoi(argv[21]);
const ck::index_t in_left_pad_w = std::stoi(argv[22]);
const ck::index_t in_right_pad_h = std::stoi(argv[23]);
const ck::index_t in_right_pad_w = std::stoi(argv[24]);
const ck::index_t YEff = (Y - 1) * conv_dilation_h + 1;
const ck::index_t XEff = (X - 1) * conv_dilation_w + 1;
const ck::index_t Ho = (Hi + in_left_pad_h + in_right_pad_h - YEff) / conv_stride_h + 1;
const ck::index_t Wo = (Wi + in_left_pad_w + in_right_pad_w - XEff) / conv_stride_w + 1;
ck::app::profile_conv_fwd_impl(do_verification,
init_method,
do_log,
time_kernel,
data_type,
N,
K,
C,
std::vector<ck::index_t>{Hi, Wi},
std::vector<ck::index_t>{Y, X},
std::vector<ck::index_t>{Ho, Wo},
std::vector<ck::index_t>{conv_stride_h, conv_stride_w},
std::vector<ck::index_t>{conv_dilation_h, conv_dilation_w},
std::vector<ck::index_t>{in_left_pad_h, in_left_pad_w},
std::vector<ck::index_t>{in_right_pad_h, in_right_pad_w});
return 1;
}
test/client_app/client_app_impl.hpp 0 → 100644
View file @ 68886f7d
#pragma once
#include "host_interface.hpp"
enum ConvDataType
{
F32_F32_F32, // 0
F16_F16_F16, // 1
BF16_BF16_BF16, // 2
INT8_INT8_INT8, // 3
};
enum ConvInputLayout
{
NCHW, // 0
NHWC, // 1
};
enum ConvWeightLayout
{
KCYX, // 0
KYXC, // 1
};
enum ConvOutputLayout
{
NKHW, // 0
NHWK, // 1
};
void check_hip_error(void)
{
hipError_t err = hipGetLastError();
if(err != hipSuccess)
{
std::cerr << "Error: " << hipGetErrorString(err) << std::endl;
exit(err);
}
}
std::string getDeviceName(int device)
{
struct hipDeviceProp_t prop;
hipGetDeviceProperties(&prop, device);
check_hip_error();
return std::string(prop.name);
}
int getDriver(void)
{
int driver;
hipDriverGetVersion(&driver);
check_hip_error();
return driver;
}
namespace ck {
namespace app {
struct DeviceMem
{
DeviceMem() = delete;
DeviceMem(std::size_t mem_size);
void* GetDeviceBuffer();
void ToDevice(const void* p);
void FromDevice(void* p);
~DeviceMem();
void* mpDeviceBuf;
std::size_t mMemSize;
};
DeviceMem::DeviceMem(std::size_t mem_size) : mMemSize(mem_size)
{
hipGetErrorString(hipMalloc(static_cast<void**>(&mpDeviceBuf), mMemSize));
}
void* DeviceMem::GetDeviceBuffer() { return mpDeviceBuf; }
void DeviceMem::ToDevice(const void* p)
{
hipGetErrorString(
hipMemcpy(mpDeviceBuf, const_cast<void*>(p), mMemSize, hipMemcpyHostToDevice));
}
void DeviceMem::FromDevice(void* p)
{
hipGetErrorString(hipMemcpy(p, mpDeviceBuf, mMemSize, hipMemcpyDeviceToHost));
}
DeviceMem::~DeviceMem() { hipGetErrorString(hipFree(mpDeviceBuf)); }
void profile_conv_fwd_impl(int do_verification,
int init_method,
bool do_log,
bool time_kernel,
ConvDataType data_type,
ck::index_t N,
ck::index_t K,
ck::index_t C,
std::vector<ck::index_t> input_spatial_lengths,
std::vector<ck::index_t> filter_spatial_lengths,
std::vector<ck::index_t> output_spatial_lengths,
std::vector<ck::index_t> conv_filter_strides,
std::vector<ck::index_t> conv_filter_dilations,
std::vector<ck::index_t> input_left_pads,
std::vector<ck::index_t> input_right_pads)
{
const ck::index_t Y = filter_spatial_lengths[0];
const ck::index_t X = filter_spatial_lengths[1];
const ck::index_t Hi = input_spatial_lengths[0];
const ck::index_t Wi = input_spatial_lengths[1];
const ck::index_t Ho = output_spatial_lengths[0];
const ck::index_t Wo = output_spatial_lengths[1];
const auto in_sz = N * C * Hi * Wi;
const auto wei_sz = K * C * Y * X;
const auto out_sz = N * K * Ho * Wo;
using WeiDataType = float;
using InDataType = float;
using OutDataType = float;
app::DeviceMem in_device_buf(sizeof(InDataType) * in_sz);
app::DeviceMem wei_device_buf(sizeof(WeiDataType) * wei_sz);
app::DeviceMem out_device_buf(sizeof(OutDataType) * out_sz);
// data is already on device!
// add device Conv instances
std::vector<DeviceConvFwdPtr_t> conv_ptrs;
if(data_type == F16_F16_F16)
{
add_device_conv2d_fwd_xdl_c_shuffle_nhwc_kyxc_nhwk_f16_instances_t(conv_ptrs);
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f16_instances_t(conv_ptrs);
}
else if(data_type == BF16_BF16_BF16)
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_bf16_instances_t(conv_ptrs);
else if(data_type == F32_F32_F32)
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f32_instances_t(conv_ptrs);
else if(data_type == INT8_INT8_INT8)
add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_int8_instances_t(conv_ptrs);
else
throw std::runtime_error("wrong! Invalid data type");
if(conv_ptrs.empty())
{
throw std::runtime_error("wrong! no device Conv instance found");
}
std::string best_conv_name;
float best_ave_time = 0;
float best_tflops = 0;
float best_gb_per_sec = 0;
int deviceIndex = 0;
hipSetDevice(deviceIndex);
check_hip_error();
StreamConfig stream_config{nullptr, time_kernel};
hipStreamCreate(&stream_config.stream_id_);
check_hip_error();
// profile device Conv instances
for(auto& conv_ptr : conv_ptrs)
{
auto argument_ptr =
conv_ptr.MakeArgumentPointer(static_cast<void*>(in_device_buf.GetDeviceBuffer()),
static_cast<void*>(wei_device_buf.GetDeviceBuffer()),
static_cast<void*>(out_device_buf.GetDeviceBuffer()),
N,
K,
C,
input_spatial_lengths,
filter_spatial_lengths,
output_spatial_lengths,
conv_filter_strides,
conv_filter_dilations,
input_left_pads,
input_right_pads);
auto invoker_ptr = conv_ptr.MakeInvokerPointer();
if(conv_ptr.IsSupportedArgument(argument_ptr.get()))
{
std::string conv_name = conv_ptr.GetTypeString();
float ave_time = invoker_ptr->Run(argument_ptr.get(), stream_config);
std::size_t flop = std::size_t(2) * N * K * Ho * Wo * C * Y * X;
std::size_t num_btype = sizeof(InDataType) * (N * C * Hi * Wi) +
sizeof(WeiDataType) * (K * C * Y * X) +
sizeof(OutDataType) * (N * K * Ho * Wo);
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
float gb_per_sec = num_btype / 1.E6 / ave_time;
std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec
<< " GB/s, " << conv_name << std::endl;
if(tflops > best_tflops)
{
best_conv_name = conv_name;
best_tflops = tflops;
best_ave_time = ave_time;
best_gb_per_sec = gb_per_sec;
}
}
}
std::cout << "Best Perf: " << best_ave_time << " ms, " << best_tflops << " TFlops, "
<< best_gb_per_sec << " GB/s, " << best_conv_name << std::endl;
}
} // namespace app
} // namespace ck
test/conv2d_bwd_weight/conv2d_bwd_weight.cpp
View file @ 68886f7d
...@@ -28,10 +28,10 @@ int test_self() ...@@ -28,10 +28,10 @@ int test_self()
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>( ck::tensor_layout::convolution::NHWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -52,10 +52,10 @@ int test_self() ...@@ -52,10 +52,10 @@ int test_self()
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>( ck::tensor_layout::convolution::NHWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -72,8 +72,8 @@ int test_self() ...@@ -72,8 +72,8 @@ int test_self()
} }
int main(int argc, char* argv[]) int main(int argc, char* argv[])
{ {
int data_type = 0; int data_type = 1;
int init_method = 0; int init_method = 1;
// Conv shape // Conv shape
ck::index_t N = 128; ck::index_t N = 128;
...@@ -155,10 +155,10 @@ int main(int argc, char* argv[]) ...@@ -155,10 +155,10 @@ int main(int argc, char* argv[])
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>( ck::tensor_layout::convolution::NHWK>(
1, true, // do_verification
init_method, init_method,
0, false, // do_log
1, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -180,10 +180,10 @@ int main(int argc, char* argv[]) ...@@ -180,10 +180,10 @@ int main(int argc, char* argv[])
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>( ck::tensor_layout::convolution::NHWK>(
1, true, // do_verification
init_method, init_method,
0, false, // do_log
1, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
......
test/convnd_bwd_data/convnd_bwd_data.cpp
View file @ 68886f7d
...@@ -27,10 +27,10 @@ int main() ...@@ -27,10 +27,10 @@ int main()
ck::tensor_layout::convolution::NWC, ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC, ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>( ck::tensor_layout::convolution::NWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -50,10 +50,10 @@ int main() ...@@ -50,10 +50,10 @@ int main()
ck::tensor_layout::convolution::NWC, ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC, ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>( ck::tensor_layout::convolution::NWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -73,10 +73,10 @@ int main() ...@@ -73,10 +73,10 @@ int main()
ck::tensor_layout::convolution::NWC, ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC, ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>( ck::tensor_layout::convolution::NWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -96,10 +96,10 @@ int main() ...@@ -96,10 +96,10 @@ int main()
ck::tensor_layout::convolution::NWC, ck::tensor_layout::convolution::NWC,
ck::tensor_layout::convolution::KXC, ck::tensor_layout::convolution::KXC,
ck::tensor_layout::convolution::NWK>( ck::tensor_layout::convolution::NWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -128,10 +128,10 @@ int main() ...@@ -128,10 +128,10 @@ int main()
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>( ck::tensor_layout::convolution::NHWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -151,10 +151,10 @@ int main() ...@@ -151,10 +151,10 @@ int main()
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>( ck::tensor_layout::convolution::NHWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -174,10 +174,10 @@ int main() ...@@ -174,10 +174,10 @@ int main()
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>( ck::tensor_layout::convolution::NHWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -197,10 +197,10 @@ int main() ...@@ -197,10 +197,10 @@ int main()
ck::tensor_layout::convolution::NHWC, ck::tensor_layout::convolution::NHWC,
ck::tensor_layout::convolution::KYXC, ck::tensor_layout::convolution::KYXC,
ck::tensor_layout::convolution::NHWK>( ck::tensor_layout::convolution::NHWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -232,10 +232,10 @@ int main() ...@@ -232,10 +232,10 @@ int main()
ck::tensor_layout::convolution::NDHWC, ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC, ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK>( ck::tensor_layout::convolution::NDHWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -255,10 +255,10 @@ int main() ...@@ -255,10 +255,10 @@ int main()
ck::tensor_layout::convolution::NDHWC, ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC, ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK>( ck::tensor_layout::convolution::NDHWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -278,10 +278,10 @@ int main() ...@@ -278,10 +278,10 @@ int main()
ck::tensor_layout::convolution::NDHWC, ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC, ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK>( ck::tensor_layout::convolution::NDHWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
...@@ -301,10 +301,10 @@ int main() ...@@ -301,10 +301,10 @@ int main()
ck::tensor_layout::convolution::NDHWC, ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::KZYXC, ck::tensor_layout::convolution::KZYXC,
ck::tensor_layout::convolution::NDHWK>( ck::tensor_layout::convolution::NDHWK>(
1, // do_verification, true, // do_verification
1, // init_method, 1, // init_method
0, // do_log, false, // do_log
1, // nrepeat, false, // time_kernel
param.N_, param.N_,
param.K_, param.K_,
param.C_, param.C_,
......
test/gemm/CMakeLists.txt
View file @ 68886f7d
add_test_executable(test_gemm_fp32 gemm_fp32.cpp) # GEMM XDL
target_link_libraries(test_gemm_fp32 PRIVATE host_tensor) add_test_executable(test_gemm_xdl_fp32 gemm_xdl_fp32.cpp)
target_link_libraries(test_gemm_fp32 PRIVATE device_gemm_instance) target_link_libraries(test_gemm_xdl_fp32 PRIVATE host_tensor)
target_link_libraries(test_gemm_xdl_fp32 PRIVATE device_gemm_instance)
add_test_executable(test_gemm_fp16 gemm_fp16.cpp) add_test_executable(test_gemm_xdl_fp16 gemm_xdl_fp16.cpp)
target_link_libraries(test_gemm_fp16 PRIVATE host_tensor) target_link_libraries(test_gemm_xdl_fp16 PRIVATE host_tensor)
target_link_libraries(test_gemm_fp16 PRIVATE device_gemm_instance) target_link_libraries(test_gemm_xdl_fp16 PRIVATE device_gemm_instance)
add_test_executable(test_gemm_bf16 gemm_bf16.cpp) add_test_executable(test_gemm_xdl_bf16 gemm_xdl_bf16.cpp)
target_link_libraries(test_gemm_bf16 PRIVATE host_tensor) target_link_libraries(test_gemm_xdl_bf16 PRIVATE host_tensor)
target_link_libraries(test_gemm_bf16 PRIVATE device_gemm_instance) target_link_libraries(test_gemm_xdl_bf16 PRIVATE device_gemm_instance)
add_test_executable(test_gemm_int8 gemm_int8.cpp) add_test_executable(test_gemm_xdl_int8 gemm_xdl_int8.cpp)
target_link_libraries(test_gemm_int8 PRIVATE host_tensor) target_link_libraries(test_gemm_xdl_int8 PRIVATE host_tensor)
target_link_libraries(test_gemm_int8 PRIVATE device_gemm_instance) target_link_libraries(test_gemm_xdl_int8 PRIVATE device_gemm_instance)
# GEMM DL
add_test_executable(test_gemm_dl_fp32 gemm_dl_fp32.cpp)
target_link_libraries(test_gemm_dl_fp32 PRIVATE host_tensor)
target_link_libraries(test_gemm_dl_fp32 PRIVATE device_gemm_instance)
add_test_executable(test_gemm_dl_fp16 gemm_dl_fp16.cpp)
target_link_libraries(test_gemm_dl_fp16 PRIVATE host_tensor)
target_link_libraries(test_gemm_dl_fp16 PRIVATE device_gemm_instance)
add_test_executable(test_gemm_dl_int8 gemm_dl_int8.cpp)
target_link_libraries(test_gemm_dl_int8 PRIVATE host_tensor)
TArget_link_libraries(test_gemm_dl_int8 PRIVATE device_gemm_instance)
test/gemm/gemm_int8.cpp → test/gemm/gemm_dl_fp16.cpp
View file @ 68886f7d
#include <algorithm> #include <algorithm>
#include <cstdlib> #include <cstdlib>
#include <half.hpp> #include <half.hpp>
#include <iostream> #include <iostream>
#include <numeric> #include <numeric>
#include <tuple> #include <tuple>
#include <vector> #include <vector>
#include "gemm_util.hpp" #include "../gemm/gemm_util.hpp"
#include "config.hpp" #include "config.hpp"
#include "print.hpp" #include "print.hpp"
#include "device.hpp" #include "device.hpp"
#include "host_tensor.hpp" #include "host_tensor.hpp"
#include "host_tensor_generator.hpp" #include "host_tensor_generator.hpp"
#include "host_gemm.hpp" #include "host_gemm.hpp"
#include "device_tensor.hpp" #include "device_tensor.hpp"
#include "device_gemm_xdl.hpp" #include "device_gemm_dl.hpp"
#include "device_gemm_xdl_cshuffle.hpp" #include "element_wise_operation.hpp"
#include "element_wise_operation.hpp" #include "reference_gemm.hpp"
#include "reference_gemm.hpp" #include "gemm_specialization.hpp"
#include "gemm_specialization.hpp"
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using DeviceGemmNoOpPtr =
using DeviceGemmNoOpPtr = ck::tensor_operation::device::DeviceGemmPtr<ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::device::DeviceGemmPtr<ck::tensor_operation::element_wise::PassThrough, ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough, ck::tensor_operation::element_wise::PassThrough>;
ck::tensor_operation::element_wise::PassThrough>;
namespace ck {
namespace ck { namespace tensor_operation {
namespace tensor_operation { namespace device {
namespace device { namespace device_gemm_instance {
namespace device_gemm_instance {
void add_device_gemm_xdl_c_shuffle_int8_int8_int8_km_kn_mn_instances( void add_device_gemm_dl_f16_f16_f16_km_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
std::vector<DeviceGemmNoOpPtr>&); void add_device_gemm_dl_f16_f16_f16_km_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_c_shuffle_int8_int8_int8_km_nk_mn_instances( void add_device_gemm_dl_f16_f16_f16_mk_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
std::vector<DeviceGemmNoOpPtr>&); void add_device_gemm_dl_f16_f16_f16_mk_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_c_shuffle_int8_int8_int8_mk_nk_mn_instances(
std::vector<DeviceGemmNoOpPtr>&); } // namespace device_gemm_instance
void add_device_gemm_xdl_c_shuffle_int8_int8_int8_mk_kn_mn_instances( } // namespace device
std::vector<DeviceGemmNoOpPtr>&); } // namespace tensor_operation
} // namespace device_gemm_instance } // namespace ck
} // namespace device
} // namespace tensor_operation int main()
} // namespace ck {
using ADataType = ck::half_t;
int main() using BDataType = ck::half_t;
{ using CDataType = ck::half_t;
using ADataType = int8_t; using AccDataType = float;
using BDataType = int8_t;
using CDataType = int8_t; using RowMajor = ck::tensor_layout::gemm::RowMajor;
using ColumnMajor = ck::tensor_layout::gemm::ColumnMajor;
using RowMajor = ck::tensor_layout::gemm::RowMajor;
using ColumnMajor = ck::tensor_layout::gemm::ColumnMajor; bool res = true;
std::vector<DeviceGemmNoOpPtr> gemmPtrs; std::vector<DeviceGemmNoOpPtr> gemmPtrs;
bool res = true;
ck::tensor_operation::device::device_gemm_instance::
ck::tensor_operation::device::device_gemm_instance:: add_device_gemm_dl_f16_f16_f16_km_kn_mn_instances(gemmPtrs);
add_device_gemm_xdl_c_shuffle_int8_int8_int8_km_kn_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs)
for(auto& gemmPtr : gemmPtrs) {
{ res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr, ADataType,
ADataType, BDataType,
BDataType, CDataType,
CDataType, AccDataType,
ColumnMajor, ColumnMajor,
RowMajor, RowMajor,
RowMajor, RowMajor,
PassThrough, PassThrough,
PassThrough, PassThrough,
PassThrough>{}(gemmPtr); PassThrough>{}(gemmPtr);
} }
gemmPtrs.clear(); gemmPtrs.clear();
ck::tensor_operation::device::device_gemm_instance:: ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_xdl_c_shuffle_int8_int8_int8_km_nk_mn_instances(gemmPtrs); add_device_gemm_dl_f16_f16_f16_km_nk_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs) for(auto& gemmPtr : gemmPtrs)
{ {
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr, res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
ADataType, ADataType,
BDataType, BDataType,
CDataType, CDataType,
ColumnMajor, AccDataType,
ColumnMajor, ColumnMajor,
RowMajor, ColumnMajor,
PassThrough, RowMajor,
PassThrough, PassThrough,
PassThrough>{}(gemmPtr); PassThrough,
} PassThrough>{}(gemmPtr);
}
gemmPtrs.clear();
ck::tensor_operation::device::device_gemm_instance:: gemmPtrs.clear();
add_device_gemm_xdl_c_shuffle_int8_int8_int8_mk_kn_mn_instances(gemmPtrs); ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_dl_f16_f16_f16_mk_kn_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs)
{ for(auto& gemmPtr : gemmPtrs)
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr, {
ADataType, res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
BDataType, ADataType,
CDataType, BDataType,
RowMajor, CDataType,
RowMajor, AccDataType,
RowMajor, RowMajor,
PassThrough, RowMajor,
PassThrough, RowMajor,
PassThrough>{}(gemmPtr); PassThrough,
} PassThrough,
PassThrough>{}(gemmPtr);
gemmPtrs.clear(); }
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_xdl_c_shuffle_int8_int8_int8_mk_nk_mn_instances(gemmPtrs); gemmPtrs.clear();
ck::tensor_operation::device::device_gemm_instance::
for(auto& gemmPtr : gemmPtrs) add_device_gemm_dl_f16_f16_f16_mk_nk_mn_instances(gemmPtrs);
{
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr, for(auto& gemmPtr : gemmPtrs)
ADataType, {
BDataType, res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
CDataType, ADataType,
RowMajor, BDataType,
ColumnMajor, CDataType,
RowMajor, AccDataType,
PassThrough, RowMajor,
PassThrough, ColumnMajor,
PassThrough>{}(gemmPtr); RowMajor,
} PassThrough,
PassThrough,
std::cout << "TestGemm ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl; PassThrough>{}(gemmPtr);
return res ? 0 : 1; }
}
std::cout << "TestGemm ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
return res ? 0 : 1;
}
test/gemm/gemm_dl_fp32.cpp 0 → 100644
View file @ 68886f7d
#include <algorithm>
#include <cstdlib>
#include <half.hpp>
#include <iostream>
#include <numeric>
#include <tuple>
#include <vector>
#include "../gemm/gemm_util.hpp"
#include "config.hpp"
#include "print.hpp"
#include "device.hpp"
#include "host_tensor.hpp"
#include "host_tensor_generator.hpp"
#include "host_gemm.hpp"
#include "device_tensor.hpp"
#include "device_gemm_dl.hpp"
#include "element_wise_operation.hpp"
#include "reference_gemm.hpp"
#include "gemm_specialization.hpp"
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using DeviceGemmNoOpPtr =
ck::tensor_operation::device::DeviceGemmPtr<ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough>;
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
void add_device_gemm_dl_f32_f32_f32_km_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_dl_f32_f32_f32_km_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_dl_f32_f32_f32_mk_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_dl_f32_f32_f32_mk_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
} // namespace device_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
int main()
{
using ADataType = float;
using BDataType = float;
using CDataType = float;
using AccDataType = float;
using RowMajor = ck::tensor_layout::gemm::RowMajor;
using ColumnMajor = ck::tensor_layout::gemm::ColumnMajor;
bool res = true;
std::vector<DeviceGemmNoOpPtr> gemmPtrs;
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_dl_f32_f32_f32_km_kn_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs)
{
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
ADataType,
BDataType,
CDataType,
AccDataType,
ColumnMajor,
RowMajor,
RowMajor,
PassThrough,
PassThrough,
PassThrough>{}(gemmPtr);
}
gemmPtrs.clear();
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_dl_f32_f32_f32_km_nk_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs)
{
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
ADataType,
BDataType,
CDataType,
AccDataType,
ColumnMajor,
ColumnMajor,
RowMajor,
PassThrough,
PassThrough,
PassThrough>{}(gemmPtr);
}
gemmPtrs.clear();
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_dl_f32_f32_f32_mk_kn_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs)
{
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
ADataType,
BDataType,
CDataType,
AccDataType,
RowMajor,
RowMajor,
RowMajor,
PassThrough,
PassThrough,
PassThrough>{}(gemmPtr);
}
gemmPtrs.clear();
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_dl_f32_f32_f32_mk_nk_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs)
{
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
ADataType,
BDataType,
CDataType,
AccDataType,
RowMajor,
ColumnMajor,
RowMajor,
PassThrough,
PassThrough,
PassThrough>{}(gemmPtr);
}
std::cout << "TestGemm ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
return res ? 0 : 1;
}
test/gemm/gemm_dl_int8.cpp 0 → 100644
View file @ 68886f7d
#include <algorithm>
#include <cstdlib>
#include <half.hpp>
#include <iostream>
#include <numeric>
#include <tuple>
#include <vector>
#include "../gemm/gemm_util.hpp"
#include "config.hpp"
#include "print.hpp"
#include "device.hpp"
#include "host_tensor.hpp"
#include "host_tensor_generator.hpp"
#include "host_gemm.hpp"
#include "device_tensor.hpp"
#include "device_gemm_dl.hpp"
#include "element_wise_operation.hpp"
#include "reference_gemm.hpp"
#include "gemm_specialization.hpp"
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using DeviceGemmNoOpPtr =
ck::tensor_operation::device::DeviceGemmPtr<ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough>;
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
void add_device_gemm_dl_i8_i8_i8_km_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_dl_i8_i8_i8_km_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_dl_i8_i8_i8_mk_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_dl_i8_i8_i8_mk_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
} // namespace device_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
int main()
{
using ADataType = int8_t;
using BDataType = int8_t;
using CDataType = int8_t;
using AccDataType = int;
using RowMajor = ck::tensor_layout::gemm::RowMajor;
using ColumnMajor = ck::tensor_layout::gemm::ColumnMajor;
bool res = true;
std::vector<DeviceGemmNoOpPtr> gemmPtrs;
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_dl_i8_i8_i8_km_kn_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs)
{
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
ADataType,
BDataType,
CDataType,
AccDataType,
ColumnMajor,
RowMajor,
RowMajor,
PassThrough,
PassThrough,
PassThrough>{}(gemmPtr);
}
gemmPtrs.clear();
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_dl_i8_i8_i8_km_nk_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs)
{
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
ADataType,
BDataType,
CDataType,
AccDataType,
ColumnMajor,
ColumnMajor,
RowMajor,
PassThrough,
PassThrough,
PassThrough>{}(gemmPtr);
}
gemmPtrs.clear();
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_dl_i8_i8_i8_mk_kn_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs)
{
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
ADataType,
BDataType,
CDataType,
AccDataType,
RowMajor,
RowMajor,
RowMajor,
PassThrough,
PassThrough,
PassThrough>{}(gemmPtr);
}
gemmPtrs.clear();
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_dl_i8_i8_i8_mk_nk_mn_instances(gemmPtrs);
for(auto& gemmPtr : gemmPtrs)
{
res &= ck::gemm_util::TestGemm<DeviceGemmNoOpPtr,
ADataType,
BDataType,
CDataType,
AccDataType,
RowMajor,
ColumnMajor,
RowMajor,
PassThrough,
PassThrough,
PassThrough>{}(gemmPtr);
}
std::cout << "TestGemm ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
return res ? 0 : 1;
}
test/gemm/gemm_util.hpp
View file @ 68886f7d
...@@ -60,7 +60,7 @@ template <typename DeviceGemmPtr_, ...@@ -60,7 +60,7 @@ template <typename DeviceGemmPtr_,
typename AElementwiseOperation, typename AElementwiseOperation,
typename BElementwiseOperation, typename BElementwiseOperation,
typename CElementwiseOperation> typename CElementwiseOperation>
void RunDeviceGEMM(DeviceGemmPtr_& gemmPtr, bool RunDeviceGEMM(DeviceGemmPtr_& gemmPtr,
const ck::gemm_util::GemmParams& params, const ck::gemm_util::GemmParams& params,
const Tensor<ADataType>& A, const Tensor<ADataType>& A,
const Tensor<BDataType>& B, const Tensor<BDataType>& B,
...@@ -73,9 +73,6 @@ void RunDeviceGEMM(DeviceGemmPtr_& gemmPtr, ...@@ -73,9 +73,6 @@ void RunDeviceGEMM(DeviceGemmPtr_& gemmPtr,
DeviceMem b_k_n_device_buf(sizeof(BDataType) * B.mDesc.GetElementSpace()); DeviceMem b_k_n_device_buf(sizeof(BDataType) * B.mDesc.GetElementSpace());
DeviceMem c_m_n_device_buf(sizeof(CDataType) * C.mDesc.GetElementSpace()); DeviceMem c_m_n_device_buf(sizeof(CDataType) * C.mDesc.GetElementSpace());
a_m_k_device_buf.ToDevice(A.mData.data());
b_k_n_device_buf.ToDevice(B.mData.data());
auto invoker_ptr = gemmPtr->MakeInvokerPointer(); auto invoker_ptr = gemmPtr->MakeInvokerPointer();
auto argument_ptr = auto argument_ptr =
gemmPtr->MakeArgumentPointer(static_cast<ADataType*>(a_m_k_device_buf.GetDeviceBuffer()), gemmPtr->MakeArgumentPointer(static_cast<ADataType*>(a_m_k_device_buf.GetDeviceBuffer()),
...@@ -91,21 +88,30 @@ void RunDeviceGEMM(DeviceGemmPtr_& gemmPtr, ...@@ -91,21 +88,30 @@ void RunDeviceGEMM(DeviceGemmPtr_& gemmPtr,
b_element_op, b_element_op,
c_element_op); c_element_op);
if(!gemmPtr->IsSupportedArgument(argument_ptr.get())) if(gemmPtr->IsSupportedArgument(argument_ptr.get()))
{ {
throw std::runtime_error( a_m_k_device_buf.ToDevice(A.mData.data());
"wrong! device_gemm with the specified compilation parameters does " b_k_n_device_buf.ToDevice(B.mData.data());
"not support this GEMM problem"); invoker_ptr->Run(argument_ptr.get());
c_m_n_device_buf.FromDevice(C.mData.data());
return true;
} }
else
{
std::cout << "device_gemm with the specified compilation parameters does "
"not support this GEMM problem"
<< std::endl;
invoker_ptr->Run(argument_ptr.get()); return false;
c_m_n_device_buf.FromDevice(C.mData.data()); }
} }
template <typename DeviceGemmPtr_, template <typename DeviceGemmPtr_,
typename ADataType, typename ADataType,
typename BDataType, typename BDataType,
typename CDataType, typename CDataType,
typename AccDataType,
typename ALayout, typename ALayout,
typename BLayout, typename BLayout,
typename CLayout, typename CLayout,
...@@ -181,6 +187,7 @@ struct TestGemm ...@@ -181,6 +187,7 @@ struct TestGemm
ck::tensor_operation::host::ReferenceGemm<ADataType, ck::tensor_operation::host::ReferenceGemm<ADataType,
BDataType, BDataType,
CDataType, CDataType,
AccDataType,
AElementwiseOperation, AElementwiseOperation,
BElementwiseOperation, BElementwiseOperation,
CElementwiseOperation>; CElementwiseOperation>;
...@@ -188,28 +195,40 @@ struct TestGemm ...@@ -188,28 +195,40 @@ struct TestGemm
a, b, c_host, a_element_op, b_element_op, c_element_op); a, b, c_host, a_element_op, b_element_op, c_element_op);
// Act // Act
ck::gemm_util::RunDeviceGEMM( bool is_supported = ck::gemm_util::RunDeviceGEMM(
gemmPtr, params, a, b, c_device, a_element_op, b_element_op, c_element_op); gemmPtr, params, a, b, c_device, a_element_op, b_element_op, c_element_op);
// Assert if(is_supported)
bool res = false;
if(std::is_same<CDataType, float>::value)
{ {
res = ck::utils::check_err(c_device.mData, c_host.mData); // Assert
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl; bool res = false;
if(std::is_same<CDataType, float>::value)
{
res = ck::utils::check_err(c_device.mData, c_host.mData);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
else if(std::is_same<CDataType, ck::half_t>::value)
{
res = ck::utils::check_err(c_device.mData, c_host.mData);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
else if(std::is_same<CDataType, int8_t>::value)
{
res = ck::utils::check_err(c_device.mData, c_host.mData);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
else if(std::is_same<CDataType, double>::value)
{
res = ck::utils::check_err(c_device.mData, c_host.mData);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
return res;
} }
else if(std::is_same<CDataType, ck::half_t>::value) else
{ {
res = ck::utils::check_err(c_device.mData, c_host.mData); return true;
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
} }
else if(std::is_same<CDataType, int8_t>::value)
{
res = ck::utils::check_err(c_device.mData, c_host.mData);
std::cout << (res ? "SUCCESS" : "FAILURE") << std::endl;
}
return res;
} }
}; };
...@@ -299,6 +318,7 @@ struct TestGemmBF16 ...@@ -299,6 +318,7 @@ struct TestGemmBF16
// use fp32 host kernel to verify bf16 device kernel // use fp32 host kernel to verify bf16 device kernel
using ReferenceGemmInstance = using ReferenceGemmInstance =
ck::tensor_operation::host::ReferenceGemm<float, ck::tensor_operation::host::ReferenceGemm<float,
float,
float, float,
float, float,
AElementwiseOperation, AElementwiseOperation,
......
test/gemm/gemm_fp16.cpp → test/gemm/gemm_xdl_fp16.cpp
View file @ 68886f7d
...@@ -52,9 +52,10 @@ void add_device_gemm_xdl_c_shuffle_2_stage_f16_f16_f16_mk_nk_mn_instances( ...@@ -52,9 +52,10 @@ void add_device_gemm_xdl_c_shuffle_2_stage_f16_f16_f16_mk_nk_mn_instances(
int main() int main()
{ {
using ADataType = ck::half_t; using ADataType = ck::half_t;
using BDataType = ck::half_t; using BDataType = ck::half_t;
using CDataType = ck::half_t; using CDataType = ck::half_t;
using AccDataType = float;
using RowMajor = ck::tensor_layout::gemm::RowMajor; using RowMajor = ck::tensor_layout::gemm::RowMajor;
using ColumnMajor = ck::tensor_layout::gemm::ColumnMajor; using ColumnMajor = ck::tensor_layout::gemm::ColumnMajor;
...@@ -74,6 +75,7 @@ int main() ...@@ -74,6 +75,7 @@ int main()
ADataType, ADataType,
BDataType, BDataType,
CDataType, CDataType,
AccDataType,
ColumnMajor, ColumnMajor,
RowMajor, RowMajor,
RowMajor, RowMajor,
...@@ -96,6 +98,7 @@ int main() ...@@ -96,6 +98,7 @@ int main()
ADataType, ADataType,
BDataType, BDataType,
CDataType, CDataType,
AccDataType,
ColumnMajor, ColumnMajor,
ColumnMajor, ColumnMajor,
RowMajor, RowMajor,
...@@ -118,6 +121,7 @@ int main() ...@@ -118,6 +121,7 @@ int main()
ADataType, ADataType,
BDataType, BDataType,
CDataType, CDataType,
AccDataType,
RowMajor, RowMajor,
RowMajor, RowMajor,
RowMajor, RowMajor,
...@@ -142,6 +146,7 @@ int main() ...@@ -142,6 +146,7 @@ int main()
ADataType, ADataType,
BDataType, BDataType,
CDataType, CDataType,
AccDataType,
RowMajor, RowMajor,
ColumnMajor, ColumnMajor,
RowMajor, RowMajor,
......
test/gemm/gemm_fp32.cpp → test/gemm/gemm_xdl_fp32.cpp
View file @ 68886f7d
...@@ -53,9 +53,10 @@ void add_device_gemm_xdl_c_shuffle_f32_f32_f32_mk_kn_mn_instances(std::vector<De ...@@ -53,9 +53,10 @@ void add_device_gemm_xdl_c_shuffle_f32_f32_f32_mk_kn_mn_instances(std::vector<De
int main() int main()
{ {
using ADataType = float; using ADataType = float;
using BDataType = float; using BDataType = float;
using CDataType = float; using CDataType = float;
using AccDataType = float;
using RowMajor = ck::tensor_layout::gemm::RowMajor; using RowMajor = ck::tensor_layout::gemm::RowMajor;
using ColumnMajor = ck::tensor_layout::gemm::ColumnMajor; using ColumnMajor = ck::tensor_layout::gemm::ColumnMajor;
...@@ -75,6 +76,7 @@ int main() ...@@ -75,6 +76,7 @@ int main()
ADataType, ADataType,
BDataType, BDataType,
CDataType, CDataType,
AccDataType,
ColumnMajor, ColumnMajor,
RowMajor, RowMajor,
RowMajor, RowMajor,
...@@ -97,6 +99,7 @@ int main() ...@@ -97,6 +99,7 @@ int main()
ADataType, ADataType,
BDataType, BDataType,
CDataType, CDataType,
AccDataType,
ColumnMajor, ColumnMajor,
ColumnMajor, ColumnMajor,
RowMajor, RowMajor,
...@@ -119,6 +122,7 @@ int main() ...@@ -119,6 +122,7 @@ int main()
ADataType, ADataType,
BDataType, BDataType,
CDataType, CDataType,
AccDataType,
RowMajor, RowMajor,
RowMajor, RowMajor,
RowMajor, RowMajor,
...@@ -141,6 +145,7 @@ int main() ...@@ -141,6 +145,7 @@ int main()
ADataType, ADataType,
BDataType, BDataType,
CDataType, CDataType,
AccDataType,
RowMajor, RowMajor,
ColumnMajor, ColumnMajor,
RowMajor, RowMajor,
......
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