From 07e87ff185647aa7351e3bfbe6b2c03f40b34102 Mon Sep 17 00:00:00 2001
From: Yancey1989 <yancey1989@gmail.com>
Date: Thu, 18 Jan 2018 10:17:59 +0800
Subject: [PATCH] Fix sequence_padding compile warning
---
paddle/operators/math/sequence_padding.cc | 38 ++++++++++++-----------
1 file changed, 20 insertions(+), 18 deletions(-)
diff --git a/paddle/operators/math/sequence_padding.cc b/paddle/operators/math/sequence_padding.cc
index fd66455eaef..2e69aa47eb8 100644
--- a/paddle/operators/math/sequence_padding.cc
+++ b/paddle/operators/math/sequence_padding.cc
@@ -32,7 +32,8 @@ class PaddingLoDTensorFunctor<platform::CPUDeviceContext, T> {
framework::LoD abs_offset_lod = framework::ToAbsOffset(lod);
auto seq_dims = seq.dims();
- PADDLE_ENFORCE_EQ(seq_dims[0], abs_offset_lod[level].back(),
+ PADDLE_ENFORCE_EQ(seq_dims[0],
+ static_cast<int64_t>(abs_offset_lod[level].back()),
"The first dimension of LoDTensor seq should be "
"equal to the sum of all sequences's length.");
@@ -41,32 +42,32 @@ class PaddingLoDTensorFunctor<platform::CPUDeviceContext, T> {
"The input padding should be a 3-D Tensor of shape "
"[max_sequence_length, num_sequences, sequence_width].");
- const size_t max_sequence_length = MaximumSequenceLength(lod, level);
+ const int64_t max_sequence_length = MaximumSequenceLength(lod, level);
PADDLE_ENFORCE_EQ(padding_dims[0], max_sequence_length,
"The first dimension of Tensor padding should be the "
"maximum length of all sequences in LoDTensor seq.");
- const size_t num_sequences = abs_offset_lod[level].size() - 1;
+ const int64_t num_sequences = abs_offset_lod[level].size() - 1;
PADDLE_ENFORCE_EQ(padding_dims[1], num_sequences,
"The second dimension of Tensor padding should be the "
"number of sequences in LoDTensor seq.");
- const size_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,
"The third dimension of Tensor padding should be the "
"width of sequence in LoDTensor seq.");
const T* seq_data = seq.data<T>();
T* padding_data = padding.data<T>();
- for (size_t i = 0; i < max_sequence_length; ++i) {
- for (size_t j = 0; j < num_sequences; ++j) {
- size_t start_pos = abs_offset_lod[level][j];
- size_t sequence_length = abs_offset_lod[level][j + 1] - start_pos;
+ for (int64_t i = 0; i < max_sequence_length; ++i) {
+ for (int64_t j = 0; j < num_sequences; ++j) {
+ int64_t start_pos = abs_offset_lod[level][j];
+ int64_t sequence_length = abs_offset_lod[level][j + 1] - start_pos;
if (i < sequence_length) {
// i > 0 => sequence_length > 0
T scale =
norm_by_times ? (1.0f / static_cast<T>(sequence_length)) : 1.0f;
- for (size_t k = 0; k < sequence_width; ++k) {
+ for (int64_t k = 0; k < sequence_width; ++k) {
padding_data[(i * num_sequences + j) * sequence_width + k] =
seq_data[(start_pos + i) * sequence_width + k] * scale;
}
@@ -93,7 +94,8 @@ class UnpaddingLoDTensorFunctor<platform::CPUDeviceContext, T> {
framework::LoD abs_offset_lod = framework::ToAbsOffset(lod);
auto seq_dims = seq.dims();
- PADDLE_ENFORCE_EQ(seq_dims[0], abs_offset_lod[level].back(),
+ PADDLE_ENFORCE_EQ(seq_dims[0],
+ static_cast<int64_t>(abs_offset_lod[level].back()),
"The first dimension of LoDTensor seq should be "
"equal to the sum of all sequences's length.");
@@ -102,31 +104,31 @@ class UnpaddingLoDTensorFunctor<platform::CPUDeviceContext, T> {
"The input padding should be a 3-D Tensor of shape "
"[max_sequnece_length, num_sequences, sequence_width].");
- const size_t max_sequence_length = MaximumSequenceLength(lod, level);
+ const int64_t max_sequence_length = MaximumSequenceLength(lod, level);
PADDLE_ENFORCE_EQ(padding_dims[0], max_sequence_length,
"The first dimension of Tensor padding should be "
"the maximum length of all sequences in LoDTensor seq.");
- const size_t num_sequences = abs_offset_lod[level].size() - 1;
+ const int64_t num_sequences = abs_offset_lod[level].size() - 1;
PADDLE_ENFORCE_EQ(padding_dims[1], num_sequences,
"The second dimension of Tensor padding should be "
"the number of sequences in LoDTensor seq.");
- const size_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,
"The third dimension of Tensor padding should be the "
"width of sequence in LoDTensor seq.");
const T* padding_data = padding.data<T>();
T* seq_data = seq.data<T>();
- for (size_t i = 0; i < num_sequences; ++i) {
- size_t start_pos = abs_offset_lod[level][i];
- size_t sequence_length = abs_offset_lod[level][i + 1] - start_pos;
- for (size_t j = 0; j < sequence_length; ++j) {
+ for (int64_t i = 0; i < num_sequences; ++i) {
+ int64_t start_pos = abs_offset_lod[level][i];
+ int64_t sequence_length = abs_offset_lod[level][i + 1] - start_pos;
+ for (int64_t j = 0; j < sequence_length; ++j) {
// sequence_width > j > 0
T scale =
norm_by_times ? (1.0f / static_cast<T>(sequence_length)) : 1.0f;
- for (size_t k = 0; k < sequence_width; ++k) {
+ for (int64_t k = 0; k < sequence_width; ++k) {
seq_data[(start_pos + j) * sequence_width + k] =
padding_data[(j * num_sequences + i) * sequence_width + k] *
scale;
--
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