未验证 提交 32da5e9c 编写于 作者: T Tao Luo 提交者: GitHub

remove unused expected_kernel_cache_pass (#17486)

test=develop
上级 65dd7ec2
......@@ -171,11 +171,6 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
AppendPass("runtime_context_cache_pass");
}
if (strategy_.cache_expected_kernel_) {
VLOG(10) << "Add expected_kernel_cache_pass";
AppendPass("expected_kernel_cache_pass");
}
AppendMultiDevPass(strategy_);
if (strategy_.fuse_all_reduce_ops_) {
......@@ -371,7 +366,6 @@ USE_PASS(fuse_sgd_op_pass);
USE_PASS(fuse_momentum_op_pass);
USE_PASS(fuse_all_reduce_op_pass);
USE_PASS(runtime_context_cache_pass);
USE_PASS(expected_kernel_cache_pass);
USE_PASS(record_skip_memory_opt_vars_pass);
#ifdef PADDLE_WITH_MKLDNN
USE_PASS(mkldnn_placement_pass);
......
......@@ -109,7 +109,6 @@ struct BuildStrategy {
bool remove_unnecessary_lock_{true};
bool cache_runtime_context_{false};
bool cache_expected_kernel_{true};
std::unordered_set<std::string> mkldnn_enabled_op_types_;
// NOTE:
......
......@@ -72,7 +72,6 @@ pass_library(transpose_flatten_concat_fuse_pass inference)
pass_library(identity_scale_op_clean_pass base)
pass_library(sync_batch_norm_pass base)
pass_library(runtime_context_cache_pass base)
pass_library(expected_kernel_cache_pass base)
pass_library(quant_conv2d_dequant_fuse_pass inference)
pass_library(fillconstant_elementwisemul_fuse inference)
pass_library(shuffle_channel_detect_pass inference)
......
/* Copyright (c) 2019 PaddlePaddle 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 "paddle/fluid/framework/ir/expected_kernel_cache_pass.h"
#include <memory>
#include "paddle/fluid/framework/operator.h"
namespace paddle {
namespace framework {
namespace ir {
void ExpectedKernelCachePass::ApplyImpl(ir::Graph* graph) const {
VLOG(3) << "Applies Expected Kernel Cache strategy.";
for (const Node* n : graph->Nodes()) {
if (n->IsOp() && n->Op()) {
n->Op()->SetAttr(kEnableCacheExpectedKernel, true);
}
}
}
} // namespace ir
} // namespace framework
} // namespace paddle
REGISTER_PASS(expected_kernel_cache_pass,
paddle::framework::ir::ExpectedKernelCachePass);
/* Copyright (c) 2019 PaddlePaddle 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. */
#pragma once
#include <memory>
#include "paddle/fluid/framework/ir/pass.h"
namespace paddle {
namespace framework {
namespace ir {
class ExpectedKernelCachePass : public Pass {
protected:
void ApplyImpl(ir::Graph* graph) const override;
};
} // namespace ir
} // namespace framework
} // namespace paddle
......@@ -71,12 +71,6 @@ constexpr char kNewGradSuffix[] = "@NEWGRAD@";
/// this Op's execution to save the elapsed time.
constexpr char kEnableCacheRuntimeContext[] = "@ENABLE_CACHE_RUNTIME_CONTEXT@";
/// If an Op has attribtue kEnableCacheExpectedKernel, it means that in a same
/// name scope and same place, since the expected kerenl of this Op does not
/// change in the execution, it could be recorded only at the first iteration of
/// this Op's execution to save the elapsed time.
constexpr char kEnableCacheExpectedKernel[] = "@ENABLE_CACHE_EXPECTED_KERNEL@";
/// If an Op has this attribute, all its kernels should calculate output
/// variable's shape in the corresponding Compute() function. And
/// OperatorWithKernel::RunImpl() would skip call this Op's InferShape()
......
......@@ -235,7 +235,6 @@ void AnalysisConfig::Update() {
pass_builder()->InsertPass(3, "tensorrt_subgraph_pass");
}
pass_builder()->DeletePass("runtime_context_cache_pass");
pass_builder()->DeletePass("expected_kernel_cache_pass");
}
if (use_mkldnn_) {
......
......@@ -98,9 +98,8 @@ GpuPassStrategy::GpuPassStrategy() : PassStrategy({}) {
"conv_elementwise_add_fuse_pass", //
#endif //
"transpose_flatten_concat_fuse_pass",
// following two passes should be located in the last, since they will
// following pass should be located in the last, since it will
// work on all fused ops.
"expected_kernel_cache_pass", //
"runtime_context_cache_pass"
});
......@@ -134,9 +133,8 @@ CpuPassStrategy::CpuPassStrategy() : PassStrategy({}) {
"conv_bn_fuse_pass", //
"conv_eltwiseadd_bn_fuse_pass", //
"is_test_pass", //
// following two passes should be located in the last, since
// they will work on all fused ops.
"expected_kernel_cache_pass", //
// following pass should be located in the last, since
// it will work on all fused ops.
"runtime_context_cache_pass"});
use_gpu_ = false;
......
......@@ -18,6 +18,7 @@ limitations under the License. */
#include <mutex> // NOLINT // for call_once
#include <string>
#include <unordered_map>
#include <unordered_set>
#include <utility>
#include <vector>
......@@ -1492,10 +1493,6 @@ All parameter, weight, gradient are variables in Paddle.
"cache_runtime_context",
[](const BuildStrategy &self) { return self.cache_runtime_context_; },
[](BuildStrategy &self, bool b) { self.cache_runtime_context_ = b; })
.def_property(
"cache_expected_kernel",
[](const BuildStrategy &self) { return self.cache_expected_kernel_; },
[](BuildStrategy &self, bool b) { self.cache_expected_kernel_ = b; })
.def_property(
"mkldnn_enabled_op_types",
[](const BuildStrategy &self) {
......
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