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Changes for DNNL1.x fused_batch_norm and Pooling Ops(Max and Avg). #36767

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merged 19 commits into from
Feb 26, 2020
Merged

Changes for DNNL1.x fused_batch_norm and Pooling Ops(Max and Avg). #36767

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1fda61c
Changes for DNNL1.x fused batch norm
jojivk73 Feb 14, 2020
00e2cbf
Changes based on review
jojivk73 Feb 19, 2020
d1c26d2
Removing some comments
jojivk73 Feb 20, 2020
66a1f5f
Merge from master
jojivk73 Feb 21, 2020
a23c47c
Fixes based on review
jojivk73 Feb 21, 2020
9d51e2c
Changes based on review and other fixes
jojivk73 Feb 24, 2020
54e486b
Merge branch 'master' into dnnl1x_fbn
jojivk73 Feb 24, 2020
98480f7
Merge branch 'master' into dnnl0x_fbn
jojivk73 Feb 25, 2020
b17d4e5
Fixes for FBN and pooling
jojivk73 Feb 25, 2020
473d449
Fix for Fused batch norm and max pool
jojivk73 Feb 25, 2020
0d2bc78
Merge master with this branch
nammbash Feb 25, 2020
46cf7d4
Merge branch 'dnnl1x_fbn' of https://github.com/Intel-tensorflow/tens…
nammbash Feb 25, 2020
c2367d8
Clang 8.0.1 formatting
nammbash Feb 25, 2020
915c356
Update tensorflow/core/util/mkl_types.h
jojivk73 Feb 26, 2020
b6c1671
Review changes and fixes due to some test failures
jojivk73 Feb 26, 2020
5ee2706
Merge branch 'dnnl1x_fbn' of https://github.com/Intel-tensorflow/tens…
jojivk73 Feb 26, 2020
15aa555
Style fixes
jojivk73 Feb 26, 2020
9771b73
Adding comments
jojivk73 Feb 26, 2020
107a137
Fixes for comments and style
jojivk73 Feb 26, 2020
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12 changes: 0 additions & 12 deletions tensorflow/core/graph/mkl_layout_pass.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -365,7 +365,6 @@ class MklLayoutRewritePass : public GraphOptimizationPass {
rinfo_.push_back({csinfo_.addn, mkl_op_registry::GetMklOpName(csinfo_.addn),
CopyAttrsAll, AlwaysRewrite,
kRewriteForLayoutPropagation});
#ifndef ENABLE_MKLDNN_V1
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rinfo_.push_back({csinfo_.add, mkl_op_registry::GetMklOpName(csinfo_.add),
CopyAttrsAll, RewriteIfAtleastOneMklInput,
kRewriteForLayoutPropagation});
Expand Down Expand Up @@ -403,12 +402,10 @@ class MklLayoutRewritePass : public GraphOptimizationPass {
{csinfo_.conjugate_transpose,
mkl_op_registry::GetMklOpName(csinfo_.conjugate_transpose),
CopyAttrsAll, AlwaysRewrite, kRewriteForOpNameChange});
#endif // !ENABLE_MKLDNN_V1
rinfo_.push_back({csinfo_.conv2d,
mkl_op_registry::GetMklOpName(csinfo_.conv2d),
CopyAttrsConvCheckConstFilter, AlwaysRewrite,
kRewriteForLayoutPropagation});
#ifndef ENABLE_MKLDNN_V1
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rinfo_.push_back({csinfo_.conv2d_with_bias, csinfo_.mkl_conv2d_with_bias,
CopyAttrsConvCheckConstFilter, AlwaysRewrite,
kRewriteForLayoutPropagation});
Expand Down Expand Up @@ -477,20 +474,16 @@ class MklLayoutRewritePass : public GraphOptimizationPass {
{csinfo_.fused_batch_norm_grad_v3,
mkl_op_registry::GetMklOpName(csinfo_.fused_batch_norm_grad_v3),
CopyAttrsAll, AlwaysRewrite, kRewriteForLayoutPropagation});
#endif // !ENABLE_MKLDNN_V1

rinfo_.push_back({csinfo_.fused_conv2d, csinfo_.mkl_fused_conv2d,
CopyAttrsFusedConv2D, FusedConv2DRewrite,
kRewriteForLayoutPropagation});
rinfo_.push_back({csinfo_.fused_matmul, csinfo_.mkl_fused_matmul,
CopyAttrsAllCheckConstFilter, FusedMatMulRewrite});

#ifndef ENABLE_MKLDNN_V1
rinfo_.push_back({csinfo_.identity,
mkl_op_registry::GetMklOpName(csinfo_.identity),
CopyAttrsAll, RewriteIfAtleastOneMklInput,
kRewriteForLayoutPropagation});

rinfo_.push_back({csinfo_.lrn, mkl_op_registry::GetMklOpName(csinfo_.lrn),
CopyAttrsAll, LrnRewrite, kRewriteForLayoutPropagation});
rinfo_.push_back(
Expand Down Expand Up @@ -654,7 +647,6 @@ class MklLayoutRewritePass : public GraphOptimizationPass {
mkl_op_registry::GetMklOpName(csinfo_.quantize_v2),
CopyAttrsAll, QuantizeOpRewrite,
kRewriteForLayoutPropagation});
#endif // !ENABLE_MKLDNN_V1
rinfo_.push_back({csinfo_.relu, mkl_op_registry::GetMklOpName(csinfo_.relu),
CopyAttrsAll, AlwaysRewrite,
kRewriteForLayoutPropagation});
Expand All @@ -667,11 +659,9 @@ class MklLayoutRewritePass : public GraphOptimizationPass {
rinfo_.push_back(
{csinfo_.relu6_grad, mkl_op_registry::GetMklOpName(csinfo_.relu6_grad),
CopyAttrsAll, AlwaysRewrite, kRewriteForLayoutPropagation});
#ifndef ENABLE_MKLDNN_V1
rinfo_.push_back(
{csinfo_.requantize, mkl_op_registry::GetMklOpName(csinfo_.requantize),
CopyAttrsAll, AlwaysRewrite, kRewriteForLayoutPropagation});
#endif // !ENABLE_MKLDNN_V1
// Disable these two MKL operators for now due to some test failures caused
// by these two ops
/*
Expand All @@ -691,7 +681,6 @@ class MklLayoutRewritePass : public GraphOptimizationPass {
mkl_op_registry::GetMklOpName(csinfo_.slice),
CopyAttrsAll, RewriteIfAtleastOneMklInput,
kRewriteForLayoutPropagation});
#ifndef ENABLE_MKLDNN_V1
rinfo_.push_back(
{csinfo_.softmax, mkl_op_registry::GetMklOpName(csinfo_.softmax),
CopyAttrsAll, AlwaysRewrite, kRewriteForLayoutPropagation});
Expand Down Expand Up @@ -798,7 +787,6 @@ class MklLayoutRewritePass : public GraphOptimizationPass {
// CheckForMklOp
FuseMaxPool3D,
CopyAttrsPooling});
#endif // !ENABLE_MKLDNN_V1
}

// Standard interface to run pass
Expand Down
25 changes: 22 additions & 3 deletions tensorflow/core/kernels/mkl_avgpooling_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,9 @@ using mkldnn::algorithm;
using mkldnn::engine;
using mkldnn::error;
using mkldnn::memory;
#ifndef ENABLE_MKLDNN_V1
using mkldnn::padding_kind;
#endif
using mkldnn::pooling_backward;
using mkldnn::pooling_forward;
using mkldnn::prop_kind;
Expand Down Expand Up @@ -108,11 +110,19 @@ class MklAvgPoolingOp : public MklPoolingForwardOpBase<T> {
pooling_prop_kind = prop_kind::forward_inference;
else
pooling_prop_kind = prop_kind::forward_training;
#ifdef ENABLE_MKLDNN_V1
// TODO(DNNL): Find out what should we use input_md.data.format.
MklPoolingParams fwdParams(
src_dims, output_dims_mkl_order, filter_dims, strides, padding_left,
padding_right, ALGORITHM::pooling_avg_exclude_padding,
pooling_prop_kind, static_cast<memory::format>(input_md.data.format));

pooling_prop_kind,
static_cast<MEMORY_FORMAT>(this->data_format_mkldnn_));
#else
MklPoolingParams fwdParams(
src_dims, output_dims_mkl_order, filter_dims, strides, padding_left,
padding_right, ALGORITHM::pooling_avg_exclude_padding,
pooling_prop_kind, static_cast<MEMORY_FORMAT>(input_md.data.format));
#endif
pooling_fwd = MklPoolingFwdPrimitiveFactory<T>::Get(fwdParams);

// Allocate output tensor.
Expand Down Expand Up @@ -224,11 +234,20 @@ class MklAvgPoolingGradOp : public MklPoolingBackwardOpBase<T> {

// Pass prop_kind::forward_training to create a forward primitive
// that is used in the backward pass.
#ifdef ENABLE_MKLDNN_V1
// TODO(DNNL): Find out what should we use src_md.data.format.
MklPoolingParams bwdParams(
orig_input_dims_mkl_order, output_dims_mkl_order, filter_dims,
strides, padding_left, padding_right,
ALGORITHM::pooling_avg_exclude_padding, prop_kind::forward_training,
static_cast<MEMORY_FORMAT>(this->data_format_mkldnn_));
#else
MklPoolingParams bwdParams(
orig_input_dims_mkl_order, output_dims_mkl_order, filter_dims,
strides, padding_left, padding_right,
ALGORITHM::pooling_avg_exclude_padding, prop_kind::forward_training,
static_cast<memory::format>(src_md.data.format));
static_cast<MEMORY_FORMAT>(src_md.data.format));
#endif
MklPoolingBwdPrimitive<T>* pooling_bwd =
MklPoolingBwdPrimitiveFactory<T>::Get(bwdParams);

Expand Down