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Fix CPPLint issues in framework/data_transform framework/prune.cc #10178

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Merged
abhinavarora merged 2 commits into from
Apr 24, 2018
Merged

Fix CPPLint issues in framework/data_transform framework/prune.cc #10178

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aa22ec2
Fic CPPLint issues with data_transform
Apr 24, 2018
e1757dd
Fic CPPLint issues with prune.cc
Apr 24, 2018
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6 changes: 3 additions & 3 deletions paddle/fluid/framework/data_transform.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -63,16 +63,16 @@ void DataTransform(const OpKernelType& expected_kernel_type,
}

void CopyVariableWithTensor(const Variable& in_var, const Tensor& tensor,
Variable& out_var) {
Variable* out_var) {
if (in_var.IsType<LoDTensor>()) {
auto& in_lod_tensor = in_var.Get<LoDTensor>();
auto* tran_lod_tensor = out_var.GetMutable<LoDTensor>();
auto* tran_lod_tensor = out_var->GetMutable<LoDTensor>();
tran_lod_tensor->set_lod(in_lod_tensor.lod());
tran_lod_tensor->set_layout(in_lod_tensor.layout());
tran_lod_tensor->ShareDataWith(tensor);
} else if (in_var.IsType<SelectedRows>()) {
auto& in_selected_rows = in_var.Get<SelectedRows>();
auto* trans_selected_rows = out_var.GetMutable<SelectedRows>();
auto* trans_selected_rows = out_var->GetMutable<SelectedRows>();
trans_selected_rows->set_height(in_selected_rows.height());
trans_selected_rows->set_rows(in_selected_rows.rows());
trans_selected_rows->mutable_value()->ShareDataWith(tensor);
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2 changes: 1 addition & 1 deletion paddle/fluid/framework/data_transform.h
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Expand Up @@ -35,7 +35,7 @@ void DataTransform(const OpKernelType& expected_kernel_type,
const Tensor& input_tensor, Tensor* out);

void CopyVariableWithTensor(const Variable& in_var, const Tensor& tensor,
Variable& out_var);
Variable* out_var);

} // namespace framework
} // namespace paddle
2 changes: 1 addition & 1 deletion paddle/fluid/framework/operator.cc
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Expand Up @@ -554,7 +554,7 @@ void OperatorWithKernel::RunImpl(const Scope& scope,
std::shared_ptr<Tensor> out(new Tensor);
DataTransform(expected_kernel_key, kernel_type_for_var, *tensor_in,
out.get());
CopyVariableWithTensor(*var, *(out.get()), *trans_var);
CopyVariableWithTensor(*var, *(out.get()), trans_var);
}
}
}
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18 changes: 9 additions & 9 deletions paddle/fluid/framework/prune.cc
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Expand Up @@ -14,19 +14,19 @@ limitations under the License. */

#include "paddle/fluid/framework/prune.h"

#include <glog/logging.h>

#include <algorithm>
#include <set>
#include <string>
#include <unordered_map>
#include <vector>

#include <glog/logging.h>

namespace paddle {
namespace framework {

const std::string kFeedOpType = "feed";
const std::string kFetchOpType = "fetch";
const char kFeedOpType[] = "feed";
const char kFetchOpType[] = "fetch";

bool HasDependentVar(const proto::OpDesc& op_desc,
const std::set<std::string>& dependent_vars) {
Expand Down Expand Up @@ -68,7 +68,7 @@ bool HasSubBlock(const proto::OpDesc& op_desc) {
// the child block to help pruning
void prune_impl(const proto::ProgramDesc& input, proto::ProgramDesc* output,
int block_id, int parent_block_id,
std::set<std::string>& dependent_vars) {
std::set<std::string>* dependent_vars) {
auto& block = input.blocks(block_id);
auto& ops = block.ops();

Expand All @@ -90,11 +90,11 @@ void prune_impl(const proto::ProgramDesc& input, proto::ProgramDesc* output,
std::vector<bool> should_run;
for (auto op_iter = ops.rbegin(); op_iter != ops.rend(); ++op_iter) {
auto& op_desc = *op_iter;
if (IsTarget(op_desc) || HasDependentVar(op_desc, dependent_vars)) {
if (IsTarget(op_desc) || HasDependentVar(op_desc, *dependent_vars)) {
// insert its input to the dependency graph
for (auto& var : op_desc.inputs()) {
for (auto& argu : var.arguments()) {
dependent_vars.insert(argu);
dependent_vars->insert(argu);
}
}
should_run.push_back(true);
Expand Down Expand Up @@ -138,7 +138,7 @@ void prune_impl(const proto::ProgramDesc& input, proto::ProgramDesc* output,
// GetSubBlockIndex(*op) is the idx of the sub_block in the input desc
// output_block_id is the idx of the current block in the output desc
prune_impl(input, output, GetSubBlockIndex(*op), output_block_id,
sub_block_dependent_vars);
&sub_block_dependent_vars);
}
}
}
Expand Down Expand Up @@ -181,7 +181,7 @@ void prune_impl(const proto::ProgramDesc& input, proto::ProgramDesc* output,
void Prune(const proto::ProgramDesc& input, proto::ProgramDesc* output) {
std::set<std::string> dependent_vars;
output->clear_blocks();
prune_impl(input, output, 0, -1, dependent_vars);
prune_impl(input, output, 0, -1, &dependent_vars);
}

void inference_optimize_impl(proto::ProgramDesc* input, int block_id) {
Expand Down