提交 2e2726f1 编写于 作者: A Abhinav Arora

Fix cpplint issues in some operators

上级 817df54b
......@@ -13,8 +13,8 @@
limitations under the License. */
#include "mkldnn.hpp"
#include "mkldnn_activation_op.h"
#include "paddle/fluid/operators/activation_op.h"
#include "paddle/fluid/operators/mkldnn_activation_op.h"
namespace paddle {
namespace operators {
......@@ -50,8 +50,10 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
mkldnn::memory::format::nchw);
// create memory primitives
auto src_memory = mkldnn::memory({data_md, mkldnn_engine}, (void *)src_data);
auto dst_memory = mkldnn::memory({data_md, mkldnn_engine}, (void *)dst_data);
auto src_memory =
mkldnn::memory({data_md, mkldnn_engine}, static_cast<void *>(src_data));
auto dst_memory =
mkldnn::memory({data_md, mkldnn_engine}, static_cast<void *>(dst_data));
auto forward_desc = mkldnn::eltwise_forward::desc(
mkldnn::prop_kind::forward_training, algorithm, data_md, alpha, beta);
......@@ -95,11 +97,12 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
mkldnn::memory::format::nchw);
// create memory primitives
auto src_memory = mkldnn::memory({data_md, mkldnn_engine}, (void *)src);
auto src_memory =
mkldnn::memory({data_md, mkldnn_engine}, static_cast<void *>(src));
auto diff_src_memory =
mkldnn::memory({data_md, mkldnn_engine}, (void *)diff_src);
mkldnn::memory({data_md, mkldnn_engine}, static_cast<void *>(diff_src));
auto diff_dst_memory =
mkldnn::memory({data_md, mkldnn_engine}, (void *)diff_dst);
mkldnn::memory({data_md, mkldnn_engine}, static_cast<void *>(diff_dst));
auto backward_desc =
mkldnn::eltwise_backward::desc(algorithm, data_md, data_md, alpha, beta);
......
......@@ -13,6 +13,8 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <utility>
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
......
......@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/adagrad_op.h"
#include <vector>
#include <cmath>
......
......@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <string>
#include "paddle/fluid/framework/lod_tensor_array.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"
......
......@@ -13,6 +13,8 @@
// limitations under the License.
#include "paddle/fluid/operators/assign_value_op.h"
#include <string>
#include <vector>
namespace paddle {
namespace operators {
......
......@@ -14,6 +14,7 @@
#pragma once
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/enforce.h"
......
......@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/auc_op.h"
#include <string>
namespace paddle {
namespace operators {
......
......@@ -13,6 +13,8 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <string>
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
......@@ -40,7 +42,7 @@ class AucKernel : public framework::OpKernel<T> {
std::vector<float> thresholds_list;
thresholds_list.reserve(num_thresholds);
for (int i = 1; i < num_thresholds - 1; i++) {
thresholds_list[i] = (float)i / (num_thresholds - 1);
thresholds_list[i] = static_cast<float>(i) / (num_thresholds - 1);
}
const float kEpsilon = 1e-7;
thresholds_list[0] = 0.0f - kEpsilon;
......@@ -105,11 +107,12 @@ class AucKernel : public framework::OpKernel<T> {
float* fp_rate_data = fp_rate.mutable_data<float>(ctx.GetPlace());
float* rec_rate_data = rec_rate.mutable_data<float>(ctx.GetPlace());
for (int i = 0; i < num_thresholds; i++) {
tp_rate_data[i] =
((float)tp_data[i] + epsilon) / (tp_data[i] + fn_data[i] + epsilon);
fp_rate_data[i] = (float)fp_data[i] / (fp_data[i] + tn_data[i] + epsilon);
rec_rate_data[i] =
((float)tp_data[i] + epsilon) / (tp_data[i] + fp_data[i] + epsilon);
tp_rate_data[i] = (static_cast<float>(tp_data[i]) + epsilon) /
(tp_data[i] + fn_data[i] + epsilon);
fp_rate_data[i] =
static_cast<float>(fp_data[i]) / (fp_data[i] + tn_data[i] + epsilon);
rec_rate_data[i] = (static_cast<float>(tp_data[i]) + epsilon) /
(tp_data[i] + fp_data[i] + epsilon);
}
*auc_data = 0.0f;
if (curve == "ROC") {
......
......@@ -19,15 +19,15 @@ namespace operators {
template <>
void GetAccumulators<paddle::platform::CPUDeviceContext>(
const framework::ExecutionContext& ctx, int64_t& num_updates_,
int64_t& num_accumulates_, int64_t& old_num_accumulates_) {
const framework::ExecutionContext& ctx, int64_t* num_updates_,
int64_t* num_accumulates_, int64_t* old_num_accumulates_) {
auto* in_old_num_accumulates = ctx.Input<Tensor>("in_old_num_accumulates");
auto* in_num_accumulates = ctx.Input<Tensor>("in_num_accumulates");
auto* in_num_updates = ctx.Input<Tensor>("in_num_updates");
old_num_accumulates_ = in_old_num_accumulates->data<int64_t>()[0];
num_accumulates_ = in_num_accumulates->data<int64_t>()[0];
num_updates_ = in_num_updates->data<int64_t>()[0];
*old_num_accumulates_ = in_old_num_accumulates->data<int64_t>()[0];
*num_accumulates_ = in_num_accumulates->data<int64_t>()[0];
*num_updates_ = in_num_updates->data<int64_t>()[0];
}
template <>
......
......@@ -29,8 +29,8 @@ using EigenVector = framework::EigenVector<T, MajorType, IndexType>;
template <typename DeviceContext>
void GetAccumulators(const framework::ExecutionContext& ctx,
int64_t& num_updates, int64_t& num_accumulates,
int64_t& old_num_accumulates);
int64_t* num_updates, int64_t* num_accumulates,
int64_t* old_num_accumulates);
template <typename DeviceContext>
void SetAccumulators(const framework::ExecutionContext& ctx,
......@@ -47,8 +47,8 @@ class AverageAccumulatesKernel : public framework::OpKernel<T> {
int64_t num_updates = 0;
int64_t num_accumulates = 0;
int64_t old_num_accumulates = 0;
GetAccumulators<DeviceContext>(ctx, num_updates, num_accumulates,
old_num_accumulates);
GetAccumulators<DeviceContext>(ctx, &num_updates, &num_accumulates,
&old_num_accumulates);
// Get attrs
float average_window = ctx.Attr<float>("average_window");
......
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