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optimize error message, test=develop (#24420)

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release/2.0-alpha
wangguanzhong 5 years ago committed by GitHub
parent 7fedf26b87
commit cd327e66df
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GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 62 additions and 36 deletions
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13
paddle/fluid/operators/detection/box_clip_op.cc
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@ -36,20 +36,19 @@ class BoxClipOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_EQ(
input_box_dims[input_box_size - 1], 4,
platform::errors::InvalidArgument(
"The last dimension "
"of Input must be 4. But received last dimension = %d",
"The last dimension of Input(Input) in BoxClipOp must be 4. "
"But received last dimension = %d",
input_box_dims[input_box_size - 1]));
PADDLE_ENFORCE_EQ(im_info_dims.size(), 2,
platform::errors::InvalidArgument(
"The rank of "
"Input(Input) in BoxClipOp must be 2. But received "
"rank = %d",
"The rank of Input(Input) in BoxClipOp must be 2."
" But received rank = %d",
im_info_dims.size()));
PADDLE_ENFORCE_EQ(
im_info_dims[1], 3,
platform::errors::InvalidArgument(
"The last dimension "
"of ImInfo must be 3. But received last dimension = %d",
"The last dimension of Input(ImInfo) of BoxClipOp must be 3. "
"But received last dimension = %d",
im_info_dims[1]));
}
ctx->ShareDim("Input", /*->*/ "Output");

6
paddle/fluid/operators/detection/box_clip_op.h
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@ -34,8 +34,10 @@ class BoxClipKernel : public framework::OpKernel<T> {
if (input_box->lod().size()) {
PADDLE_ENFORCE_EQ(input_box->lod().size(), 1UL,
platform::errors::InvalidArgument(
"Input(Input) of "
"BoxClip only supports 1 level of LoD."));
"Input(Input) of BoxClip only supports 1 level "
"of LoD. But received the "
"level = %d",
input_box->lod().size()));
}
auto box_lod = input_box->lod().back();
int64_t n = static_cast<int64_t>(box_lod.size() - 1);

18
paddle/fluid/operators/detection/box_coder_op.h
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@ -21,12 +21,18 @@ namespace operators {
enum class BoxCodeType { kEncodeCenterSize = 0, kDecodeCenterSize = 1 };
inline BoxCodeType GetBoxCodeType(const std::string &type) {
PADDLE_ENFORCE_EQ(
(type == "encode_center_size") || (type == "decode_center_size"), true,
platform::errors::InvalidArgument(
"The 'code_type' attribute in BoxCoder"
" must be 'encode_center_size' or 'decode_center_size'. "
"But received 'code_type' is %s",
type));
if (type == "encode_center_size") {
return BoxCodeType::kEncodeCenterSize;
} else if (type == "decode_center_size") {
} else {
return BoxCodeType::kDecodeCenterSize;
}
PADDLE_THROW("Not support type %s.", type);
}
template <typename DeviceContext, typename T>
@ -188,7 +194,9 @@ class BoxCoderKernel : public framework::OpKernel<T> {
PADDLE_ENFORCE_EQ(target_box->lod().size(), 1UL,
platform::errors::InvalidArgument(
"Input(TargetBox) of BoxCoder operator "
"supports LoD with only one level."));
"supports LoD with only one level. But received "
"level = %d",
target_box->lod().size()));
}
if (prior_box_var) {
PADDLE_ENFORCE_EQ(variance.empty(), true,
@ -201,7 +209,9 @@ class BoxCoderKernel : public framework::OpKernel<T> {
PADDLE_ENFORCE_EQ(static_cast<int>(variance.size()), 4,
platform::errors::InvalidArgument(
"Size of attribute 'variance' of BoxCoder "
"operator should be 4"));
"operator should be 4. But received "
"size = %d",
variance.size()));
}
auto code_type = GetBoxCodeType(context.Attr<std::string>("code_type"));
bool normalized = context.Attr<bool>("box_normalized");

19
paddle/fluid/operators/roi_align_op.cc
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@ -40,7 +40,7 @@ class ROIAlignOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_EQ(
rois_lod_dims.size(), 1,
platform::errors::InvalidArgument("The RoisLod dimension should be 1"
", but got dim = %d",
", but got dimension = %d",
rois_lod_dims.size()));
}
PADDLE_ENFORCE_EQ(
@ -69,20 +69,21 @@ class ROIAlignOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_GT(pooled_height, 0,
platform::errors::InvalidArgument(
"The pooled output "
"height must greater than 0. But received "
"pooled_height = %d",
"The 'pooled_height' attribute in RoIAlignOp is "
"invalid. The height must be greater than 0. But "
"received 'pooled_height' = %d",
pooled_height));
PADDLE_ENFORCE_GT(pooled_width, 0,
platform::errors::InvalidArgument(
"The pooled output "
"width must greater than 0. But received "
"pooled_width = %d",
"The 'pooled_width' attribute in RoIAlignOp is "
"invalid. The width must be greater than 0. But "
"received 'pooled_width' = %d",
pooled_width));
PADDLE_ENFORCE_GT(spatial_scale, 0.0f,
platform::errors::InvalidArgument(
"The spatial scale "
"must greater than 0 But received spatial_scale = %f",
"The 'spatial_scale' attribute in RoIAlignOp is "
"invalid. The scale must be greater than 0. But "
"received 'spatial_scale' = %f",
spatial_scale));
auto out_dims = input_dims;

19
paddle/fluid/operators/roi_align_op.cu
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@ -284,19 +284,26 @@ class GPUROIAlignOpKernel : public framework::OpKernel<T> {
auto lod = rois->lod();
PADDLE_ENFORCE_EQ(
lod.empty(), false,
"Input(ROIs) Tensor of ROIAlignOp does not contain LoD information.");
platform::errors::InvalidArgument("Input(ROIs) in ROIAlignOp does "
"not contain LoD information."));
auto rois_lod = lod.back();
int rois_batch_size = rois_lod.size() - 1;
PADDLE_ENFORCE_EQ(
rois_batch_size, batch_size,
platform::errors::InvalidArgument(
"The rois_batch_size and imgs "
"batch_size must be the same. But received rois_batch_size = %d, "
"batch_size = %d",
"The batch size of rois and batch size "
"of images must be the same. But received rois batch size = %d, "
"and images batch size = %d",
rois_batch_size, batch_size));
int rois_num_with_lod = rois_lod[rois_batch_size];
PADDLE_ENFORCE_EQ(rois_num, rois_num_with_lod,
"The rois_num from input and lod must be the same.");
PADDLE_ENFORCE_EQ(
rois_num, rois_num_with_lod,
platform::errors::InvalidArgument(
"The actual number of rois and the number of rois "
"provided from Input(RoIsLoD) in RoIAlign must be the same."
" But received actual number of rois is %d, and the number "
"of rois from RoIsLoD is %d",
rois_num, rois_num_with_lod));
for (int n = 0; n < rois_batch_size; ++n) {
for (size_t i = rois_lod[n]; i < rois_lod[n + 1]; ++i) {
roi_batch_id_data[i] = n;

23
paddle/fluid/operators/roi_align_op.h
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@ -171,9 +171,9 @@ class CPUROIAlignOpKernel : public framework::OpKernel<T> {
PADDLE_ENFORCE_EQ(
rois_batch_size - 1, batch_size,
platform::errors::InvalidArgument(
"The rois_batch_size and imgs "
"batch_size must be the same. But received rois_batch_size = %d, "
"batch_size = %d",
"The batch size of rois and the batch size of images "
" must be the same. But received the batch size of rois is %d, "
"and the batch size of images is %d",
rois_batch_size, batch_size));
auto* rois_lod = rois_lod_t->data<int64_t>();
for (int n = 0; n < rois_batch_size - 1; ++n) {
@ -183,9 +183,10 @@ class CPUROIAlignOpKernel : public framework::OpKernel<T> {
}
} else {
auto lod = rois->lod();
PADDLE_ENFORCE_EQ(
lod.empty(), false,
"Input(ROIs) Tensor of ROIAlignOp does not contain LoD information.");
PADDLE_ENFORCE_EQ(lod.empty(), false,
platform::errors::InvalidArgument(
"Input(ROIs) Tensor of ROIAlignOp "
"does not contain LoD information."));
auto rois_lod = lod.back();
int rois_batch_size = rois_lod.size() - 1;
PADDLE_ENFORCE_EQ(
@ -196,8 +197,14 @@ class CPUROIAlignOpKernel : public framework::OpKernel<T> {
"batch_size = %d",
rois_batch_size, batch_size));
int rois_num_with_lod = rois_lod[rois_batch_size];
PADDLE_ENFORCE_EQ(rois_num, rois_num_with_lod,
"The rois_num from input and lod must be the same.");
PADDLE_ENFORCE_EQ(
rois_num, rois_num_with_lod,
platform::errors::InvalidArgument(
"The actual number of rois and the number of rois "
"provided from Input(RoIsLoD) in RoIAlign must be the same."
" But received actual number of rois is %d, and the number "
"of rois from RoIsLoD is %d",
rois_num, rois_num_with_lod));
for (int n = 0; n < rois_batch_size; ++n) {
for (size_t i = rois_lod[n]; i < rois_lod[n + 1]; ++i) {
roi_batch_id_data[i] = n;

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