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Convert SB->Conv->BS subgraph into the dilated convolution.

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PiperOrigin-RevId: 305154803
Change-Id: If7e127b4f55e6b0fa23dde7fdd9560e2b65fb586
This commit is contained in:
Terry Heo 2020-04-06 17:37:00 -07:00 committed by TensorFlower Gardener
parent ee27301273
commit cfc7eab980
4 changed files with 0 additions and 259 deletions
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29
tensorflow/lite/delegates/gpu/common/transformations/BUILD
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@ -109,7 +109,6 @@ cc_library(
":fuse_mul_to_conv", ":fuse_mul_to_conv",
":make_fully_connected", ":make_fully_connected",
":make_padding", ":make_padding",
":match_dilated_convolution",
":merge_padding_with", ":merge_padding_with",
":remove_noop", ":remove_noop",
"//tensorflow/lite/delegates/gpu/common:model_transformer", "//tensorflow/lite/delegates/gpu/common:model_transformer",
@ -177,34 +176,6 @@ cc_library(
deps = ["//tensorflow/lite/delegates/gpu/common:model"], deps = ["//tensorflow/lite/delegates/gpu/common:model"],
) )
cc_library(
name = "match_dilated_convolution",
srcs = ["match_dilated_convolution.cc"],
hdrs = ["match_dilated_convolution.h"],
deps = [
"//tensorflow/lite/delegates/gpu/common:model",
"//tensorflow/lite/delegates/gpu/common:model_transformer",
"//tensorflow/lite/delegates/gpu/common:operations",
"//tensorflow/lite/delegates/gpu/common:status",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/types:any",
],
)
cc_test(
name = "match_dilated_convolution_test",
srcs = ["match_dilated_convolution_test.cc"],
deps = [
":match_dilated_convolution",
"//tensorflow/lite/delegates/gpu/common:model",
"//tensorflow/lite/delegates/gpu/common:model_transformer",
"//tensorflow/lite/delegates/gpu/common:operations",
"//tensorflow/lite/delegates/gpu/common:shape",
"@com_google_absl//absl/types:any",
"@com_google_googletest//:gtest_main",
],
)
cc_library( cc_library(
name = "merge_padding_with", name = "merge_padding_with",
srcs = ["merge_padding_with.cc"], srcs = ["merge_padding_with.cc"],

97
tensorflow/lite/delegates/gpu/common/transformations/match_dilated_convolution.cc
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@ -1,97 +0,0 @@
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/lite/delegates/gpu/common/transformations/match_dilated_convolution.h"
#include <vector>
#include "absl/memory/memory.h"
#include "absl/types/any.h"
#include "tensorflow/lite/delegates/gpu/common/model.h"
#include "tensorflow/lite/delegates/gpu/common/operations.h"
#include "tensorflow/lite/delegates/gpu/common/status.h"
namespace tflite {
namespace gpu {
namespace {
class MatchDilatedConvolution : public SequenceTransformation {
public:
int ExpectedSequenceLength() const final { return 3; }
// TODO(eignasheva): use span instead of const reference b/131628066.
TransformResult ApplyToNodesSequence(const std::vector<Node*>& sequence,
GraphFloat32* graph) final {
auto& sb_node = *sequence[0];
auto& conv_node = *sequence[1];
auto& bs_node = *sequence[2];
if (sb_node.operation.type != ToString(OperationType::SPACE_TO_BATCH) &&
bs_node.operation.type != ToString(OperationType::BATCH_TO_SPACE)) {
return {TransformStatus::SKIPPED, ""};
}
if (conv_node.operation.type !=
ToString(OperationType::DEPTHWISE_CONVOLUTION) &&
conv_node.operation.type != ToString(OperationType::CONVOLUTION_2D)) {
return {TransformStatus::SKIPPED, ""};
}
auto sb_attr =
absl::any_cast<SpaceToBatchAttributes>(sb_node.operation.attributes);
auto bs_attr =
absl::any_cast<BatchToSpaceAttributes>(bs_node.operation.attributes);
if (sb_attr.block != bs_attr.block) {
return {TransformStatus::INVALID, "Invalid block size"};
}
if (conv_node.operation.type ==
ToString(OperationType::DEPTHWISE_CONVOLUTION)) {
auto dw_attr = absl::any_cast<DepthwiseConvolution2DAttributes>(
conv_node.operation.attributes);
dw_attr.padding = sb_attr.padding - bs_attr.crop;
dw_attr.dilations = sb_attr.block;
conv_node.operation.attributes = std::move(dw_attr);
} else {
auto conv2d_attr = absl::any_cast<Convolution2DAttributes>(
conv_node.operation.attributes);
conv2d_attr.padding = sb_attr.padding - bs_attr.crop;
conv2d_attr.dilations = sb_attr.block;
conv_node.operation.attributes = std::move(conv2d_attr);
}
absl::Status status = RemoveFollowingNode(graph, &bs_node, &conv_node);
if (!status.ok()) {
return {TransformStatus::INVALID,
"Unable to remove batch_to_space node after convolution."};
}
status = RemovePrecedingNode(graph, &sb_node, &conv_node);
if (!status.ok()) {
return {TransformStatus::INVALID,
"Unable to remove space_to_batch node before convolution."};
}
return {TransformStatus::APPLIED, ""};
}
};
} // namespace
std::unique_ptr<SequenceTransformation> NewMatchDilatedConvolution() {
return absl::make_unique<MatchDilatedConvolution>();
}
} // namespace gpu
} // namespace tflite

35
tensorflow/lite/delegates/gpu/common/transformations/match_dilated_convolution.h
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@ -1,35 +0,0 @@
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_LITE_DELEGATES_GPU_COMMON_TRANSFORMATIONS_MATCH_DILATED_CONVOLUTION_H_
#define TENSORFLOW_LITE_DELEGATES_GPU_COMMON_TRANSFORMATIONS_MATCH_DILATED_CONVOLUTION_H_
#include <memory>
#include "tensorflow/lite/delegates/gpu/common/model_transformer.h"
namespace tflite {
namespace gpu {
// TF->TFLite converter converts convolution with dilation into the chain of
// SpaceToBatch->Convolution->BatchToSpace. Our GPU backend natively supports
// dilation in convolutions, so we try to skip this inefficiency. For more
// information see b/131436214.
std::unique_ptr<SequenceTransformation> NewMatchDilatedConvolution();
} // namespace gpu
} // namespace tflite
#endif // TENSORFLOW_LITE_DELEGATES_GPU_COMMON_TRANSFORMATIONS_MATCH_DILATED_CONVOLUTION_H_

98
tensorflow/lite/delegates/gpu/common/transformations/match_dilated_convolution_test.cc
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@ -1,98 +0,0 @@
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/lite/delegates/gpu/common/transformations/match_dilated_convolution.h"
#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include "absl/types/any.h"
#include "tensorflow/lite/delegates/gpu/common/model.h"
#include "tensorflow/lite/delegates/gpu/common/model_transformer.h"
#include "tensorflow/lite/delegates/gpu/common/operations.h"
#include "tensorflow/lite/delegates/gpu/common/shape.h"
namespace tflite {
namespace gpu {
namespace {
TEST(MatchDilatedConvolutionTest, MakesDilatedConvolution) {
GraphFloat32 graph;
auto input = graph.NewValue();
input->tensor.shape = BHWC(1, 95, 1, 17);
SpaceToBatchAttributes sb_attr;
sb_attr.block = HW(128, 1);
sb_attr.padding.prepended = HW(128, 0);
sb_attr.padding.appended = HW(161, 0);
DepthwiseConvolution2DAttributes dw_attr;
dw_attr.padding.prepended = HW(0, 0);
dw_attr.padding.appended = HW(0, 0);
dw_attr.strides = HW(1, 1);
dw_attr.dilations = HW(1, 1);
dw_attr.weights.shape = OHWI(1, 3, 1, 17);
dw_attr.bias.shape = Linear(96);
BatchToSpaceAttributes bs_attr;
bs_attr.block = HW(128, 1);
bs_attr.crop.prepended = HW(0, 0);
bs_attr.crop.appended = HW(33, 0);
auto sb_node = graph.NewNode();
sb_node->operation.type = ToString(OperationType::SPACE_TO_BATCH);
sb_node->operation.attributes = sb_attr;
auto dw_node = graph.NewNode();
dw_node->operation.type = ToString(OperationType::DEPTHWISE_CONVOLUTION);
dw_node->operation.attributes = dw_attr;
auto bs_node = graph.NewNode();
bs_node->operation.type = ToString(OperationType::BATCH_TO_SPACE);
bs_node->operation.attributes = bs_attr;
ASSERT_TRUE(graph.AddConsumer(sb_node->id, input->id).ok());
Value<TensorRef<BHWC>>* output;
ASSERT_TRUE(AddOutput(&graph, bs_node, &output).ok());
output->tensor.shape = BHWC(1, 95, 1, 17);
Value<TensorRef<BHWC>>* sb_link;
ASSERT_TRUE(ConnectTwoNodes(&graph, sb_node, dw_node, &sb_link).ok());
sb_link->tensor.shape = BHWC(21, 128, 1, 17);
Value<TensorRef<BHWC>>* bs_link;
ASSERT_TRUE(ConnectTwoNodes(&graph, dw_node, bs_node, &bs_link).ok());
bs_link->tensor.shape = BHWC(1, 95, 1, 17);
ASSERT_EQ(graph.nodes().size(), 3);
ASSERT_EQ(graph.values().size(), 4);
auto transformation = NewMatchDilatedConvolution();
ModelTransformer transformer(&graph, nullptr);
transformer.Apply("match_dilated_convolution", transformation.get());
ASSERT_EQ(graph.nodes().size(), 1);
ASSERT_EQ(graph.values().size(), 2);
ASSERT_EQ(graph.nodes()[0]->operation.type,
ToString(OperationType::DEPTHWISE_CONVOLUTION));
auto updated_dw_attr = absl::any_cast<DepthwiseConvolution2DAttributes>(
graph.nodes()[0]->operation.attributes);
EXPECT_EQ(updated_dw_attr.padding.prepended, HW(128, 0));
EXPECT_EQ(updated_dw_attr.padding.appended, HW(128, 0));
EXPECT_EQ(updated_dw_attr.dilations, HW(128, 1));
}
} // namespace
} // namespace gpu
} // namespace tflite