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3d fusion relu #7

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daa76e1
enhancement with relu primitive reuse
gzmkl May 18, 2018
2bcd873
revert mkl_conv_ops.cc to avoid PR review confusion
gzmkl May 21, 2018
f369de2
code refactoring per Rasmus's suggestions on PR 19754
gzmkl Jun 12, 2018
3ee53e6
Merge branch 'master' into primreuse_relu
agramesh1 Jul 5, 2018
f814e24
Replace to use fast reorder path in MklRelu op.
yiqianglee Jul 15, 2018
f0f9a61
Merge branch 'master' into primreuse_relu
rmlarsen Jul 31, 2018
5ab0c8a
Fusing convolution and relu
agramesh1 Aug 1, 2018
478c416
Code changes based on Rasmus's code review suggestions on PR19403 and…
gzmkl Aug 1, 2018
8c23e1a
Conv3d enhancement
jzhoulon Aug 2, 2018
71bb5e0
Merge branch 'conv3d' into 3d_fusion_relu
agramesh1 Aug 3, 2018
84d4168
Merge branch 'agramesh/relu_fusion' into 3d_fusion_relu
agramesh1 Aug 3, 2018
bd131fc
Merge branch 'primreuse_relu' into 3d_fusion_relu
agramesh1 Aug 3, 2018
bef00c6
Merging PRs
agramesh1 Aug 3, 2018
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14 changes: 12 additions & 2 deletions tensorflow/compiler/tf2xla/kernels/BUILD
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,10 @@ package(

load("//tensorflow:tensorflow.bzl", "tf_copts")
load("//tensorflow:tensorflow.bzl", "tf_kernel_library")
load(
"//third_party/mkl:build_defs.bzl",
"if_mkl",
)

tf_kernel_library(
name = "xla_ops",
Expand Down Expand Up @@ -153,8 +157,14 @@ tf_kernel_library(
"//tensorflow/core/kernels:sparse_to_dense_op",
"//tensorflow/core/kernels:stack_ops",
"//tensorflow/core/kernels:training_ops",
"//tensorflow/core/kernels:transpose_op",
],
] + if_mkl(
[
"//tensorflow/core/kernels:mkl_transpose_op",
],
[
"//tensorflow/core/kernels:transpose_op",
],
),
)

tf_kernel_library(
Expand Down
433 changes: 402 additions & 31 deletions tensorflow/core/graph/mkl_layout_pass.cc
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116 changes: 115 additions & 1 deletion tensorflow/core/graph/mkl_layout_pass_test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -2147,6 +2147,28 @@ TEST_F(MklLayoutPassTest, NodeMerge_Conv2DWithBias_Negative_AttrMismatch) {
"DMT/_1->C:3");
}

// data_format attribute value mismatch. Merge should not be done
// in such case.
TEST_F(MklLayoutPassTest, NodeMerge_Conv2DWithBias_Negative_NoConv2D) {
InitGraph(
"node { name: 'A' op: 'Input'}"
"node { name: 'B' op: 'Input'}"
"node { name: 'C' op: 'MatMul'"
" attr { key: 'T' value { type: DT_FLOAT } }"
" attr { key: 'transpose_a' value { b: false } }"
" attr { key: 'transpose_b' value { b: false } }"
" input: ['A', 'B']}"
"node { name: 'D' op: 'Input'}"
"node { name: 'E' op: 'BiasAdd'"
" attr { key: 'T' value { type: DT_FLOAT } }"
" attr { key: 'data_format' value { s: 'NHCW' } }"
" input: ['C', 'D'] }");
EXPECT_EQ(DoMklLayoutOptimizationPass(),
"A(Input);B(Input);C(MatMul);D(Input);"
"E(BiasAdd)|A->C;"
"B->C:1;C->E;D->E:1");
}

// Test set 2: BiasAddGrad + Conv2DBackpropFilter fusion tests

TEST_F(MklLayoutPassTest, NodeMerge_Conv2DBackpropFilterFusion_Positive) {
Expand Down Expand Up @@ -2174,6 +2196,97 @@ TEST_F(MklLayoutPassTest, NodeMerge_Conv2DBackpropFilterFusion_Positive) {
"DMT/_0->D:3;DMT/_1->D:4;DMT/_2->D:5");
}

// Test set 3: Conv2DWithBias + Relu -> Conv2DWithBiasAndRelu merge tests
// C=Conv2D(A,B); E=BiasAdd(C,D); F=Relu(E); Z=Zeta(F,Y)
TEST_F(MklLayoutPassTest, NodeMerge_Conv2DWithBiasAndRelu_Positive) {
CHECK_EQ(kTensorOrdering, MklTfTensorOrdering::TENSORS_CONTIGUOUS);
InitGraph(
"node { name: 'A' op: 'Input'}"
"node { name: 'B' op: 'Input'}"
"node { name: 'C' op: 'Conv2D'"
" attr { key: 'T' value { type: DT_FLOAT } }"
" attr { key: 'data_format' value { s: 'NCHW' } }"
" attr { key: 'use_cudnn_on_gpu' value { b: false } }"
" attr { key: 'strides' value { list: {i: 1, i:1, i:1, i:1} } }"
" attr { key: 'padding' value { s: 'SAME' } }"
" attr { key: 'dilations' value { list: {i: 1, i:1, i:1, i:1} } }"
" input: ['A', 'B']}"
"node { name: 'D' op: 'Input'}"
"node { name: 'E' op: 'BiasAdd'"
" attr { key: 'T' value { type: DT_FLOAT } }"
" attr { key: 'data_format' value { s: 'NCHW' } }"
" input: ['C', 'D'] }"
"node { name: 'F' op: 'Relu'"
" attr { key: 'T' value { type: DT_FLOAT } }"
" input: ['E'] }"
"node { name: 'Y' op: 'Input'}"
"node { name: 'Z' op: 'Zeta'"
" attr {key: 'T' value { type: DT_FLOAT } }"
" input: ['F', 'Y']}");
EXPECT_EQ(DoMklLayoutOptimizationPass(),
"A(Input);B(Input);D(Input);DMT/_0(Const);DMT/_1(Const);"
"DMT/_2(Const);F(_MklConv2DWithBiasAndRelu);Y(Input);Z(Zeta)|A->F;"
"A:control->DMT/_0:control;A:control->DMT/_1:control;"
"A:control->DMT/_2:control;B->F:1;D->F:2;DMT/_0->F:3;DMT/_1->F:4;"
"DMT/_2->F:5;F->Z;Y->Z:1");
}

// Test set 5:
// C=Conv2D(A,B); D=Relu(C); Z=Zeta(D,Y)
TEST_F(MklLayoutPassTest, NodeMerge_Conv2DWithRelu_Positive) {
CHECK_EQ(kTensorOrdering, MklTfTensorOrdering::TENSORS_CONTIGUOUS);
InitGraph(
"node { name: 'A' op: 'Input'}"
"node { name: 'B' op: 'Input'}"
"node { name: 'C' op: 'Conv2D'"
" attr { key: 'T' value { type: DT_FLOAT } }"
" attr { key: 'data_format' value { s: 'NCHW' } }"
" attr { key: 'use_cudnn_on_gpu' value { b: false } }"
" attr { key: 'strides' value { list: {i: 1, i:1, i:1, i:1} } }"
" attr { key: 'padding' value { s: 'SAME' } }"
" attr { key: 'dilations' value { list: {i: 1, i:2, i:2, i:1} } }"
" input: ['A', 'B']}"
"node { name: 'D' op: 'Relu'"
" attr { key: 'T' value { type: DT_FLOAT } }"
" input: ['C'] }"
"node { name: 'Y' op: 'Input'}"
"node { name: 'Z' op: 'Zeta'"
" attr {key: 'T' value { type: DT_FLOAT } }"
" input: ['D', 'Y']}");
EXPECT_EQ(DoMklLayoutOptimizationPass(),
"A(Input);B(Input);D(_MklConv2DWithRelu);DMT/_0(Const);"
"DMT/_1(Const);Y(Input);Z(Zeta)|A->D;A:control->DMT/_0:control;"
"A:control->DMT/_1:control;B->D:1;D->Z;DMT/_0->D:2;DMT/_1->D:3;"
"Y->Z:1");
}

// Conv2D+ReLU fusion negative test - Conv2D feeds multiple nodes.
TEST_F(MklLayoutPassTest, NodeMerge_Conv2DWithRelu_Negative1) {
CHECK_EQ(kTensorOrdering, MklTfTensorOrdering::TENSORS_CONTIGUOUS);
InitGraph(
"node { name: 'A' op: 'Input'}"
"node { name: 'B' op: 'Input'}"
"node { name: 'C' op: 'Conv2D'"
" attr { key: 'T' value { type: DT_FLOAT } }"
" attr { key: 'data_format' value { s: 'NCHW' } }"
" attr { key: 'use_cudnn_on_gpu' value { b: false } }"
" attr { key: 'strides' value { list: {i: 1, i:1, i:1, i:1} } }"
" attr { key: 'padding' value { s: 'SAME' } }"
" attr { key: 'dilations' value { list: {i: 1, i:2, i:2, i:1} } }"
" input: ['A', 'B']}"
"node { name: 'D' op: 'Relu'"
" attr { key: 'T' value { type: DT_FLOAT } }"
" input: ['C'] }"
"node { name: 'Z' op: 'Zeta'"
" attr {key: 'T' value { type: DT_FLOAT } }"
" input: ['C', 'D']}");
EXPECT_EQ(DoMklLayoutOptimizationPass(),
"A(Input);B(Input);C(_MklConv2D);D(_MklRelu);DMT/_0(Const);"
"DMT/_1(Const);Z(Zeta)|A->C;A:control->DMT/_0:control;"
"A:control->DMT/_1:control;B->C:1;C->D;C->Z;C:2->D:1;D->Z:1;"
"DMT/_0->C:2;DMT/_1->C:3");
}

// BiasAddGrad fusion in the presence of BackpropFilter. But nodes do not match
// criteria for rewrite. So rewrite should not happen. 3rd input of
// Conv2DBackpropFilter is different than input to BiasAddGrad.
Expand Down Expand Up @@ -2357,7 +2470,7 @@ TEST_F(MklLayoutPassTest, NodeRewrite_Conv2D_Positive1) {
" attr { key: 'use_cudnn_on_gpu' value { b: false } }"
" attr { key: 'strides' value { list: {i: 1, i:1, i:1, i:1} } }"
" attr { key: 'padding' value { s: 'SAME' } }"
" attr { key: 'dilations' value { list: {i: 1, i:1, i:1, i:1} } }"
" attr { key: 'dilations' value { list: {i: 1, i:2, i:2, i:1} } }"
" input: ['A', 'B']}"
"node { name: 'D' op: 'Conv2D'"
" attr { key: 'T' value { type: DT_FLOAT } }"
Expand Down Expand Up @@ -3493,6 +3606,7 @@ TEST_F(MklLayoutPassTest, NodeMerge_Conv2DWithBias_DeviceTest) {
" attr { key: 'use_cudnn_on_gpu' value { b: false } }"
" attr { key: 'strides' value { list: {i: 1, i:1, i:1, i:1} } }"
" attr { key: 'padding' value { s: 'SAME' } }"
" attr { key: 'dilations' value { list: {i: 1, i:1, i:1, i:1} } }"
" input: ['A', 'B', 'M', 'N']}"
"node { name: 'D' op: 'Input'}"
"node { name: 'E' op: 'BiasAdd'"
Expand Down
42 changes: 29 additions & 13 deletions tensorflow/core/kernels/BUILD
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Original file line number Diff line number Diff line change
Expand Up @@ -649,7 +649,14 @@ cc_library(
":split_v_op",
":strided_slice_op",
":tile_ops",
":transpose_op",
] + if_mkl(
[
":mkl_transpose_op",
],
[
":transpose_op",
],
) + [
":unique_op",
":unpack_op",
":unravel_index_op",
Expand Down Expand Up @@ -886,18 +893,27 @@ tf_kernel_library(
deps = ARRAY_DEPS,
)

tf_kernel_library(
name = "transpose_op",
srcs = [
"transpose_op.cc",
] + if_mkl([
"mkl_transpose_op.cc",
]),
hdrs = ["transpose_op.h"],
deps = ARRAY_DEPS + if_mkl([
"//third_party/mkl:intel_binary_blob",
"@mkl_dnn",
]),
if_mkl(
[tf_mkl_kernel_library(
name = "mkl_transpose_op",
srcs = [
"transpose_op.cc",
"mkl_transpose_op.cc",
],
hdrs = ["transpose_op.h"],
deps = ARRAY_DEPS + if_mkl([
"//third_party/mkl:intel_binary_blob",
"@mkl_dnn",
]),
)],
[tf_kernel_library(
name = "transpose_op",
srcs = [
"transpose_op.cc",
],
hdrs = ["transpose_op.h"],
deps = ARRAY_DEPS,
)],
)

tf_kernel_library(
Expand Down
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