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Fix CPPLint issues with math/sequence_padding (#10317)

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* Fix cpplint issues in sequence_padding

* Fix typo in cu file

* Fix dependencies of sequence_padding

* Add include
trainerSaveLoadParams
Abhinav Arora 7 years ago committed by GitHub
parent 9bcd9f661b
commit 1945b729b6
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GPG Key ID: 4AEE18F83AFDEB23
5 changed files with 28 additions and 26 deletions
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16
paddle/fluid/operators/math/sequence_padding.cc
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@ -22,7 +22,7 @@ template <typename T>
class PaddingLoDTensorFunctor<platform::CPUDeviceContext, T> { class PaddingLoDTensorFunctor<platform::CPUDeviceContext, T> {
public: public:
void operator()(const platform::CPUDeviceContext& context, void operator()(const platform::CPUDeviceContext& context,
const framework::LoDTensor& seq, framework::Tensor& padding, const framework::LoDTensor& seq, framework::Tensor* padding,
bool norm_by_times) { bool norm_by_times) {
auto lod = seq.lod(); auto lod = seq.lod();
PADDLE_ENFORCE_GT(lod.size(), 0UL, PADDLE_ENFORCE_GT(lod.size(), 0UL,
@ -37,7 +37,7 @@ class PaddingLoDTensorFunctor<platform::CPUDeviceContext, T> {
"The first dimension of LoDTensor seq should be " "The first dimension of LoDTensor seq should be "
"equal to the sum of all sequences's length."); "equal to the sum of all sequences's length.");
auto padding_dims = padding.dims(); auto padding_dims = padding->dims();
PADDLE_ENFORCE_EQ(padding_dims.size(), 3UL, PADDLE_ENFORCE_EQ(padding_dims.size(), 3UL,
"The input padding should be a 3-D Tensor of shape " "The input padding should be a 3-D Tensor of shape "
"[max_sequence_length, num_sequences, sequence_width]."); "[max_sequence_length, num_sequences, sequence_width].");
@ -58,7 +58,7 @@ class PaddingLoDTensorFunctor<platform::CPUDeviceContext, T> {
"width of sequence in LoDTensor seq."); "width of sequence in LoDTensor seq.");
const T* seq_data = seq.data<T>(); const T* seq_data = seq.data<T>();
T* padding_data = padding.data<T>(); T* padding_data = padding->data<T>();
for (int64_t i = 0; i < max_sequence_length; ++i) { for (int64_t i = 0; i < max_sequence_length; ++i) {
for (int64_t j = 0; j < num_sequences; ++j) { for (int64_t j = 0; j < num_sequences; ++j) {
int64_t start_pos = abs_offset_lod[level][j]; int64_t start_pos = abs_offset_lod[level][j];
@ -84,16 +84,16 @@ template <typename T>
class UnpaddingLoDTensorFunctor<platform::CPUDeviceContext, T> { class UnpaddingLoDTensorFunctor<platform::CPUDeviceContext, T> {
public: public:
void operator()(const platform::CPUDeviceContext& context, void operator()(const platform::CPUDeviceContext& context,
framework::LoDTensor& seq, const framework::Tensor& padding, framework::LoDTensor* seq, const framework::Tensor& padding,
bool norm_by_times) { bool norm_by_times) {
auto lod = seq.lod(); auto lod = seq->lod();
PADDLE_ENFORCE_GT(lod.size(), 0UL, PADDLE_ENFORCE_GT(lod.size(), 0UL,
"The LoD of LoDTensor seq should not be null."); "The LoD of LoDTensor seq should not be null.");
const size_t level = 0; const size_t level = 0;
framework::LoD abs_offset_lod = framework::ToAbsOffset(lod); framework::LoD abs_offset_lod = framework::ToAbsOffset(lod);
auto seq_dims = seq.dims(); auto seq_dims = seq->dims();
PADDLE_ENFORCE_EQ(seq_dims[0], PADDLE_ENFORCE_EQ(seq_dims[0],
static_cast<int64_t>(abs_offset_lod[level].back()), static_cast<int64_t>(abs_offset_lod[level].back()),
"The first dimension of LoDTensor seq should be " "The first dimension of LoDTensor seq should be "
@ -114,13 +114,13 @@ class UnpaddingLoDTensorFunctor<platform::CPUDeviceContext, T> {
"The second dimension of Tensor padding should be " "The second dimension of Tensor padding should be "
"the number of sequences in LoDTensor seq."); "the number of sequences in LoDTensor seq.");
const int64_t sequence_width = seq.numel() / seq_dims[0]; const int64_t sequence_width = seq->numel() / seq_dims[0];
PADDLE_ENFORCE_EQ(padding_dims[2], sequence_width, PADDLE_ENFORCE_EQ(padding_dims[2], sequence_width,
"The third dimension of Tensor padding should be the " "The third dimension of Tensor padding should be the "
"width of sequence in LoDTensor seq."); "width of sequence in LoDTensor seq.");
const T* padding_data = padding.data<T>(); const T* padding_data = padding.data<T>();
T* seq_data = seq.data<T>(); T* seq_data = seq->data<T>();
for (int64_t i = 0; i < num_sequences; ++i) { for (int64_t i = 0; i < num_sequences; ++i) {
int64_t start_pos = abs_offset_lod[level][i]; int64_t start_pos = abs_offset_lod[level][i];
int64_t sequence_length = abs_offset_lod[level][i + 1] - start_pos; int64_t sequence_length = abs_offset_lod[level][i + 1] - start_pos;

25
paddle/fluid/operators/math/sequence_padding.cu
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@ -12,6 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#include <algorithm>
#include "paddle/fluid/operators/math/sequence_padding.h" #include "paddle/fluid/operators/math/sequence_padding.h"
namespace paddle { namespace paddle {
@ -61,7 +62,7 @@ template <typename T>
class PaddingLoDTensorFunctor<platform::CUDADeviceContext, T> { class PaddingLoDTensorFunctor<platform::CUDADeviceContext, T> {
public: public:
void operator()(const platform::CUDADeviceContext& context, void operator()(const platform::CUDADeviceContext& context,
const framework::LoDTensor& seq, framework::Tensor& padding, const framework::LoDTensor& seq, framework::Tensor* padding,
bool norm_by_times) { bool norm_by_times) {
auto lod = seq.lod(); auto lod = seq.lod();
PADDLE_ENFORCE_GT(lod.size(), 0UL, PADDLE_ENFORCE_GT(lod.size(), 0UL,
@ -76,7 +77,7 @@ class PaddingLoDTensorFunctor<platform::CUDADeviceContext, T> {
"The first dimension of LoDTensor seq should be " "The first dimension of LoDTensor seq should be "
"equal to the sum of all sequences's length."); "equal to the sum of all sequences's length.");
auto padding_dims = padding.dims(); auto padding_dims = padding->dims();
PADDLE_ENFORCE_EQ(padding_dims.size(), 3UL, PADDLE_ENFORCE_EQ(padding_dims.size(), 3UL,
"The input padding should be a 3-D Tensor of shape " "The input padding should be a 3-D Tensor of shape "
"[max_sequence_length, num_sequences, sequence_width]."); "[max_sequence_length, num_sequences, sequence_width].");
@ -97,8 +98,8 @@ class PaddingLoDTensorFunctor<platform::CUDADeviceContext, T> {
"width of sequence in LoDTensor seq."); "width of sequence in LoDTensor seq.");
if (!norm_by_times && num_sequences == 1UL) { if (!norm_by_times && num_sequences == 1UL) {
TensorCopy(seq, context.GetPlace(), context, &padding); TensorCopy(seq, context.GetPlace(), context, padding);
padding.Resize(padding_dims); padding->Resize(padding_dims);
return; return;
} }
@ -117,7 +118,7 @@ class PaddingLoDTensorFunctor<platform::CUDADeviceContext, T> {
dim3 grid(grid_dim_x, grid_dim_y); dim3 grid(grid_dim_x, grid_dim_y);
const T* seq_data = seq.data<T>(); const T* seq_data = seq.data<T>();
T* padding_data = padding.data<T>(); T* padding_data = padding->data<T>();
if (norm_by_times) { if (norm_by_times) {
SequencePaddingKernel<T, 1, 1><<<grid, threads, 0, context.stream()>>>( SequencePaddingKernel<T, 1, 1><<<grid, threads, 0, context.stream()>>>(
padding_data, const_cast<T*>(seq_data), padding_data, const_cast<T*>(seq_data),
@ -136,16 +137,16 @@ template <typename T>
class UnpaddingLoDTensorFunctor<platform::CUDADeviceContext, T> { class UnpaddingLoDTensorFunctor<platform::CUDADeviceContext, T> {
public: public:
void operator()(const platform::CUDADeviceContext& context, void operator()(const platform::CUDADeviceContext& context,
framework::LoDTensor& seq, const framework::Tensor& padding, framework::LoDTensor* seq, const framework::Tensor& padding,
bool norm_by_times) { bool norm_by_times) {
auto lod = seq.lod(); auto lod = seq->lod();
PADDLE_ENFORCE_GT(lod.size(), 0UL, PADDLE_ENFORCE_GT(lod.size(), 0UL,
"The lod of LoDTensor seq should not be null."); "The lod of LoDTensor seq should not be null.");
const size_t level = 0; const size_t level = 0;
framework::LoD abs_offset_lod = framework::ToAbsOffset(lod); framework::LoD abs_offset_lod = framework::ToAbsOffset(lod);
auto seq_dims = seq.dims(); auto seq_dims = seq->dims();
PADDLE_ENFORCE_EQ(seq_dims[0], PADDLE_ENFORCE_EQ(seq_dims[0],
static_cast<int64_t>(abs_offset_lod[level].back()), static_cast<int64_t>(abs_offset_lod[level].back()),
"The first dimension of LoDTensor seq should be " "The first dimension of LoDTensor seq should be "
@ -166,14 +167,14 @@ class UnpaddingLoDTensorFunctor<platform::CUDADeviceContext, T> {
"The second dimension of Tensor padding should be " "The second dimension of Tensor padding should be "
"the number of sequences in LoDTensor seq."); "the number of sequences in LoDTensor seq.");
const int64_t sequence_width = seq.numel() / seq_dims[0]; const int64_t sequence_width = seq->numel() / seq_dims[0];
PADDLE_ENFORCE_EQ(padding_dims[2], sequence_width, PADDLE_ENFORCE_EQ(padding_dims[2], sequence_width,
"The third dimension of Tensor padding should be the " "The third dimension of Tensor padding should be the "
"width of sequence in LoDTensor seq."); "width of sequence in LoDTensor seq.");
if (!norm_by_times && num_sequences == 1UL) { if (!norm_by_times && num_sequences == 1UL) {
TensorCopy(padding, context.GetPlace(), context, &seq); TensorCopy(padding, context.GetPlace(), context, seq);
seq.Resize(seq_dims); seq->Resize(seq_dims);
return; return;
} }
@ -192,7 +193,7 @@ class UnpaddingLoDTensorFunctor<platform::CUDADeviceContext, T> {
dim3 grid(grid_dim_x, grid_dim_y); dim3 grid(grid_dim_x, grid_dim_y);
const T* padding_data = padding.data<T>(); const T* padding_data = padding.data<T>();
T* seq_data = seq.data<T>(); T* seq_data = seq->data<T>();
if (norm_by_times) { if (norm_by_times) {
SequencePaddingKernel<T, 1, 0><<<grid, threads, 0, context.stream()>>>( SequencePaddingKernel<T, 1, 0><<<grid, threads, 0, context.stream()>>>(
const_cast<T*>(padding_data), seq_data, const_cast<T*>(padding_data), seq_data,

5
paddle/fluid/operators/math/sequence_padding.h
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@ -14,6 +14,7 @@ limitations under the License. */
#pragma once #pragma once
#include <algorithm>
#include "paddle/fluid/framework/lod_tensor.h" #include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/platform/device_context.h" #include "paddle/fluid/platform/device_context.h"
@ -64,13 +65,13 @@ template <typename DeviceContext, typename T>
class PaddingLoDTensorFunctor { class PaddingLoDTensorFunctor {
public: public:
void operator()(const DeviceContext& context, const framework::LoDTensor& seq, void operator()(const DeviceContext& context, const framework::LoDTensor& seq,
framework::Tensor& padding, bool norm_by_times); framework::Tensor* padding, bool norm_by_times);
}; };
template <typename DeviceContext, typename T> template <typename DeviceContext, typename T>
class UnpaddingLoDTensorFunctor { class UnpaddingLoDTensorFunctor {
public: public:
void operator()(const DeviceContext& context, framework::LoDTensor& seq, void operator()(const DeviceContext& context, framework::LoDTensor* seq,
const framework::Tensor& padding, bool norm_by_times); const framework::Tensor& padding, bool norm_by_times);
}; };

4
paddle/fluid/operators/math/sequence_padding_test.cc
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@ -54,12 +54,12 @@ void TestSequencePadding(const paddle::framework::LoD& lod,
static_cast<int64_t>(sequence_width)}); static_cast<int64_t>(sequence_width)});
padding.mutable_data<T>(padding_dims, *place); padding.mutable_data<T>(padding_dims, *place);
paddle::operators::math::PaddingLoDTensorFunctor<DeviceContext, T>()( paddle::operators::math::PaddingLoDTensorFunctor<DeviceContext, T>()(
*context, seq, padding, false); *context, seq, &padding, false);
seq_back.set_lod(lod); seq_back.set_lod(lod);
seq_back.mutable_data<T>(seq_dims, *place); seq_back.mutable_data<T>(seq_dims, *place);
paddle::operators::math::UnpaddingLoDTensorFunctor<DeviceContext, T>()( paddle::operators::math::UnpaddingLoDTensorFunctor<DeviceContext, T>()(
*context, seq_back, padding, false); *context, &seq_back, padding, false);
if (paddle::platform::is_cpu_place(*place)) { if (paddle::platform::is_cpu_place(*place)) {
cpu_seq_back = seq_back; cpu_seq_back = seq_back;

4
paddle/fluid/operators/warpctc_op.h
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@ -162,7 +162,7 @@ class WarpCTCKernel : public framework::OpKernel<T> {
static_cast<int64_t>(sequence_width)}); static_cast<int64_t>(sequence_width)});
warpctc_logits.mutable_data<T>(warpctc_logits_dims, ctx.GetPlace()); warpctc_logits.mutable_data<T>(warpctc_logits_dims, ctx.GetPlace());
math::PaddingLoDTensorFunctor<DeviceContext, T>()( math::PaddingLoDTensorFunctor<DeviceContext, T>()(
ctx.template device_context<DeviceContext>(), *logits, warpctc_logits, ctx.template device_context<DeviceContext>(), *logits, &warpctc_logits,
false); false);
const T* warpctc_logits_data = warpctc_logits.data<T>(); const T* warpctc_logits_data = warpctc_logits.data<T>();
@ -217,7 +217,7 @@ class WarpCTCGradKernel : public framework::OpKernel<T> {
logits_grad->mutable_data<T>(ctx.GetPlace()); logits_grad->mutable_data<T>(ctx.GetPlace());
bool norm_by_times = ctx.Attr<bool>("norm_by_times"); bool norm_by_times = ctx.Attr<bool>("norm_by_times");
math::UnpaddingLoDTensorFunctor<DeviceContext, T>()( math::UnpaddingLoDTensorFunctor<DeviceContext, T>()(
ctx.template device_context<DeviceContext>(), *logits_grad, ctx.template device_context<DeviceContext>(), logits_grad,
*warpctc_grad, norm_by_times); *warpctc_grad, norm_by_times);
const T* loss_grad_data = loss_grad->data<T>(); const T* loss_grad_data = loss_grad->data<T>();

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