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gongweibaogongweibao
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Modify style (#12465)
1 parent 046de2a commit 819ac3d

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8 files changed

+22
-17
lines changed

8 files changed

+22
-17
lines changed

‎paddle/fluid/inference/analysis/argument.h

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@@ -23,6 +23,7 @@
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#pragma once
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#include <string>
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/inference/analysis/data_flow_graph.h"
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‎paddle/fluid/inference/analysis/data_flow_graph.h

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@@ -176,7 +176,7 @@ struct GraphTraits<DataFlowGraph> {
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// sub-graph is the inputs nodes and output nodes that doesn't inside the
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// sub-graph.
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std::pair<std::vector<Node *>, std::vector<Node *>>
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ExtractInputAndOutputOfSubGraph(std::vector<Node *> &graph);
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ExtractInputAndOutputOfSubGraph(std::vector<Node *> &graph); // NOLINT
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} // namespace analysis
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} // namespace inference

‎paddle/fluid/inference/analysis/model_store_pass.cc

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@@ -12,11 +12,13 @@
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/inference/analysis/model_store_pass.h"
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#include <stdio.h>
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#include <stdlib.h>
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#include <string>
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#include "paddle/fluid/inference/analysis/analyzer.h"
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#include "paddle/fluid/inference/analysis/argument.h"
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#include "paddle/fluid/inference/analysis/model_store_pass.h"
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namespace paddle {
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namespace inference {

‎paddle/fluid/inference/analysis/model_store_pass.h

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@@ -17,6 +17,8 @@
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* model in the disk, and that model can be reloaded for prediction.
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*/
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#pragma once
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#include <string>
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#include "paddle/fluid/inference/analysis/pass.h"
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namespace paddle {

‎paddle/fluid/inference/api/demo_ci/vis_demo.cc

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@@ -20,8 +20,8 @@ limitations under the License. */
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#include <glog/logging.h> // use glog instead of PADDLE_ENFORCE to avoid importing other paddle header files.
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#include <fstream>
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#include <iostream>
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#include "paddle/fluid/inference/demo_ci/utils.h"
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#include "paddle/fluid/platform/enforce.h"
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#include "utils.h"
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#ifdef PADDLE_WITH_CUDA
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DECLARE_double(fraction_of_gpu_memory_to_use);

‎paddle/fluid/inference/api/paddle_inference_api.h

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@@ -44,7 +44,7 @@ class PaddleBuf {
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PaddleBuf(void* data, size_t length)
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: data_(data), length_(length), memory_owned_{false} {}
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// Own memory.
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PaddleBuf(size_t length)
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explicit PaddleBuf(size_t length)
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: data_(new char[length]), length_(length), memory_owned_(true) {}
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// Resize to `length` bytes.
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void Resize(size_t length);

‎paddle/fluid/inference/tensorrt/convert/fc_op.cc

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@@ -38,7 +38,7 @@ void Reorder2(nvinfer1::DimsHW shape, const T* idata, nvinfer1::DimsHW istrides,
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}
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// indata c * k
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// Reorder the data layout from CK to KC.
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void ReorderCKtoKC(TensorRTEngine::Weight& iweights,
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void ReorderCKtoKC(TensorRTEngine::Weight& iweights, // NOLINT
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TensorRTEngine::Weight* oweights) {
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int c = iweights.dims[0];
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int k = iweights.dims[1];

‎paddle/fluid/operators/conv_mkldnn_op.cc

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@@ -55,7 +55,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
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std::shared_ptr<mkldnn::memory> AcquireSrcMemoryFromWeightsPrimitive(
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const std::shared_ptr<mkldnn::memory> user_memory_p,
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std::vector<mkldnn::primitive>& pipeline) {
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std::vector<mkldnn::primitive>& pipeline) { // NOLINT
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auto src_pd = conv_bwd_weights_pd_->src_primitive_desc();
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auto user_pd = user_memory_p->get_primitive_desc();
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return this->AcquireMemory(src_pd, user_pd, user_memory_p,
@@ -64,7 +64,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
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std::shared_ptr<mkldnn::memory> AcquireDiffDstMemoryFromWeightsPrimitive(
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const std::shared_ptr<mkldnn::memory> user_memory_p,
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std::vector<mkldnn::primitive>& pipeline) {
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std::vector<mkldnn::primitive>& pipeline) { // NOLINT
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auto diff_dst_pd = conv_bwd_weights_pd_->diff_dst_primitive_desc();
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auto user_pd = user_memory_p->get_primitive_desc();
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return this->AcquireMemory(diff_dst_pd, user_pd, user_memory_p,
@@ -80,7 +80,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
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std::shared_ptr<mkldnn::memory> AcquireDiffDstMemoryFromDataPrimitive(
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const std::shared_ptr<mkldnn::memory> user_memory_p,
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std::vector<mkldnn::primitive>& pipeline) {
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std::vector<mkldnn::primitive>& pipeline) { // NOLINT
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auto diff_dst_pd = conv_bwd_data_pd_->diff_dst_primitive_desc();
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auto user_pd = user_memory_p->get_primitive_desc();
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return this->AcquireMemory(diff_dst_pd, user_pd, user_memory_p,
@@ -89,7 +89,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
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std::shared_ptr<mkldnn::memory> AcquireWeightsMemoryFromDataPrimitive(
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const std::shared_ptr<mkldnn::memory> user_weights_memory_p,
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std::vector<mkldnn::primitive>& pipeline) {
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std::vector<mkldnn::primitive>& pipeline) { // NOLINT
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auto weights_pd = conv_bwd_data_pd_->weights_primitive_desc();
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auto user_pd = user_weights_memory_p->get_primitive_desc();
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return this->AcquireMemory(weights_pd, user_pd, user_weights_memory_p,
@@ -109,7 +109,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
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std::shared_ptr<mkldnn::memory> AcquireSrcMemoryFromPrimitive(
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const std::shared_ptr<mkldnn::memory> user_memory_p,
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std::vector<mkldnn::primitive>& pipeline) {
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std::vector<mkldnn::primitive>& pipeline) { // NOLINT
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auto src_pd = conv_pd_->src_primitive_desc();
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auto user_pd = user_memory_p->get_primitive_desc();
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return this->AcquireMemory(src_pd, user_pd, user_memory_p, "@src_mem_p",
@@ -118,7 +118,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
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std::shared_ptr<mkldnn::memory> AcquireWeightsMemoryFromPrimitive(
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const std::shared_ptr<mkldnn::memory> user_weights_memory_p,
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std::vector<mkldnn::primitive>& pipeline) {
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std::vector<mkldnn::primitive>& pipeline) { // NOLINT
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auto user_weights_pd = user_weights_memory_p->get_primitive_desc();
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auto weights_pd = conv_pd_->weights_primitive_desc();
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return this->AcquireMemory(weights_pd, user_weights_pd,
@@ -197,12 +197,12 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
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// Generate keys for storing/retriving primitives for this operator
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// TODO(jczaja): Make hashing function more optimial
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static std::string GetHash(memory::dims& input_dims,
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memory::dims& weights_dims,
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std::vector<int>& strides,
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std::vector<int>& paddings,
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std::vector<int>& dilations, int groups,
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const std::string& suffix) {
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static std::string GetHash(memory::dims& input_dims, // NOLINT
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memory::dims& weights_dims, // NOLINT
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std::vector<int>& strides, // NOLINT
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std::vector<int>& paddings, // NOLINT
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std::vector<int>& dilations, // NOLINT
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int groups, const std::string& suffix) {
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return dims2str(input_dims) + dims2str(weights_dims) + dims2str(strides) +
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dims2str(paddings) + dims2str(dilations) + std::to_string(groups) +
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suffix;

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