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Add LoD empty check for all related sequence ops (#19980)

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* add lod check for sequence op, test=develop

* delete unnecessary check in expend op, test=develop
fix-python-transpose
Chen Weihang 6 years ago committed by Tao Luo
parent 88af4ab650
commit 1409586eaa
14 changed files with 54 additions and 3 deletions
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3
paddle/fluid/operators/sequence_ops/sequence_concat_op.h
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@ -61,6 +61,9 @@ class SeqConcatKernel : public framework::OpKernel<T> {
size_t lod_size = 0;
for (auto &x : xs) {
if (lod_size == 0) {
PADDLE_ENFORCE_EQ(x.get().lod().empty(), false,
"Input(X) Tensor of SequenceConcatOp does not "
"contain LoD information.");
lod_size = x.get().lod()[0].size();
} else {
PADDLE_ENFORCE_EQ(

3
paddle/fluid/operators/sequence_ops/sequence_conv_op.h
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@ -39,6 +39,9 @@ class SequenceConvKernel : public framework::OpKernel<T> {
int context_stride = context.Attr<int>("contextStride");
bool padding_trainable = context.Attr<bool>("paddingTrainable");
PADDLE_ENFORCE_EQ(
in->lod().empty(), false,
"Input(X) Tensor of SequenceConvOp does not contain LoD information.");
PADDLE_ENFORCE_EQ(in->lod().size(), 1UL,
"Only support one level sequence now.");

4
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h
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@ -29,6 +29,10 @@ class SequenceEnumerateKernel : public framework::OpKernel<T> {
int win_size = context.Attr<int>("win_size");
auto pad_value = static_cast<T>(context.Attr<int>("pad_value"));
PADDLE_ENFORCE_EQ(in->lod().empty(), false,
"Input(X) Tensor of SequenceEnumerateOp does not contain "
"LoD information.");
auto in_dims = in->dims();
auto lod0 = in->lod()[0];
PADDLE_ENFORCE_EQ(

3
paddle/fluid/operators/sequence_ops/sequence_erase_op.h
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@ -28,6 +28,9 @@ class SequenceEraseKernel : public framework::OpKernel<T> {
auto* out = ctx.Output<framework::LoDTensor>("Out");
auto lod = in->lod();
PADDLE_ENFORCE_EQ(
lod.empty(), false,
"Input(X) Tensor of SequenceEraseOp does not contain LoD information.");
PADDLE_ENFORCE_EQ(lod[lod.size() - 1].back(), (size_t)in->numel(),
"The actual size mismatches with the LoD information.");
auto tokens = ctx.Attr<std::vector<int>>("tokens");

4
paddle/fluid/operators/sequence_ops/sequence_expand_as_op.h
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@ -75,6 +75,10 @@ class SequenceExpandAsKernel : public framework::OpKernel<T> {
auto *y = context.Input<framework::LoDTensor>("Y");
auto *out = context.Output<framework::LoDTensor>("Out");
PADDLE_ENFORCE_EQ(y->lod().empty(), false,
"Input(Y) Tensor of SequenceExpandAsOp does not contain "
"LoD information.");
auto &y_lod = y->lod();
PADDLE_ENFORCE_EQ(y_lod.size(), 1, "LoD of Y should be 1.");
PADDLE_ENFORCE_GT(y_lod[0].size(), 1, ".");

4
paddle/fluid/operators/sequence_ops/sequence_expand_op.h
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@ -92,6 +92,10 @@ class SequenceExpandKernel : public framework::OpKernel<T> {
auto& x_lod = x->lod();
auto& y_lod = y->lod();
PADDLE_ENFORCE_EQ(y_lod.empty(), false,
"Input(Y) Tensor of SequenceExpandOp does not contain "
"LoD information.");
if (ref_level == -1) ref_level = y_lod.size() - 1;
out->mutable_data<T>(context.GetPlace());

4
paddle/fluid/operators/sequence_ops/sequence_pad_op.h
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@ -35,6 +35,10 @@ class SequencePadOpKernel : public framework::OpKernel<T> {
auto* len_t = ctx.Output<LoDTensor>("Length");
out->mutable_data<T>(ctx.GetPlace());
PADDLE_ENFORCE_EQ(
x->lod().empty(), false,
"Input(X) Tensor of SequencePadOp does not contain LoD information.");
const auto* pad_value = ctx.Input<LoDTensor>("PadValue");
int padded_length = ctx.Attr<int>("padded_length");

5
paddle/fluid/operators/sequence_ops/sequence_pool_op.h
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@ -38,8 +38,9 @@ class SequencePoolKernel : public framework::OpKernel<T> {
auto lod = in->lod();
auto lod_level = lod.size();
// InferShape by lod
PADDLE_ENFORCE_GE(lod_level, 1UL,
"The lod level of input shall be 1 at least.");
PADDLE_ENFORCE_GT(
lod_level, 0,
"Input(X) Tensor of SequencePoolOp does not contain LoD information.");
PADDLE_ENFORCE_LE(lod_level, 2UL,
"The lod level of input shall be no more than 2.");
PADDLE_ENFORCE_GE(

3
paddle/fluid/operators/sequence_ops/sequence_reshape_op.h
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@ -32,6 +32,9 @@ class SequenceReshapeKernel : public framework::OpKernel<T> {
int64_t in_width = in_dims[1];
auto& in_lod = in->lod();
PADDLE_ENFORCE_EQ(in_lod.empty(), false,
"Input(X) Tensor of SequenceReshapeOp does not contain "
"LoD information.");
PADDLE_ENFORCE_EQ(in_lod.size(), 1UL,
"Only support one level sequence now.");
PADDLE_ENFORCE_EQ(

3
paddle/fluid/operators/sequence_ops/sequence_reverse_op.h
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@ -107,6 +107,9 @@ class SequenceReverseOpKernel : public framework::OpKernel<T> {
auto &x = *ctx.Input<LoDTensor>("X");
auto *y = ctx.Output<LoDTensor>("Y");
PADDLE_ENFORCE_EQ(x.lod().empty(), false,
"Input(X) Tensor of SequenceReverseOp does not contain "
"LoD information.");
PADDLE_ENFORCE_EQ(x.lod().size(), 1,
"SequenceReverse Op only support one level lod.");

3
paddle/fluid/operators/sequence_ops/sequence_scatter_op.h
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@ -34,6 +34,9 @@ class SequenceScatterOpKernel : public framework::OpKernel<T> {
auto* out = ctx.Output<Tensor>("Out");
auto& ids_lod = ids->lod();
PADDLE_ENFORCE_EQ(ids_lod.empty(), false,
"Input(Ids) Tensor of SequenceScatterOp does not contain "
"LoD information.");
// Initialize out as same as x
out->mutable_data<T>(ctx.GetPlace());

5
paddle/fluid/operators/sequence_ops/sequence_slice_op.h
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@ -49,8 +49,11 @@ class SequenceSliceOpKernel : public framework::OpKernel<T> {
auto* out = ctx.Output<LoDTensor>("Out");
auto lod = in->lod();
auto n = lod[0].size() - 1;
PADDLE_ENFORCE_EQ(
lod.empty(), false,
"Input(X) Tensor of SequenceSliceOp does not contain LoD information.");
auto n = lod[0].size() - 1;
PADDLE_ENFORCE_EQ(lod.size(), 1UL, "Only support one level sequence now.");
PADDLE_ENFORCE_EQ(
n, static_cast<size_t>(length->dims()[0]),

3
paddle/fluid/operators/sequence_ops/sequence_softmax_op.h
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@ -95,6 +95,9 @@ class SequenceSoftmaxKernel : public framework::OpKernel<T> {
auto lod = x->lod();
auto dims = x->dims();
PADDLE_ENFORCE_EQ(lod.empty(), false,
"Input(X) Tensor of SequenceSoftmaxOp does not contain "
"LoD information.");
const size_t level = lod.size() - 1;
PADDLE_ENFORCE_GT(

10
paddle/fluid/operators/sequence_ops/sequence_topk_avg_pooling_op.h
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@ -70,6 +70,16 @@ class SequenceTopkAvgPoolingKernel : public framework::OpKernel<T> {
auto* out = context.Output<LoDTensor>("Out");
auto* pos = context.Output<Tensor>("pos");
PADDLE_ENFORCE_EQ(in->lod().empty(), false,
"Input(X) Tensor of SequenceTopkAvgPoolingOp does not "
"contain LoD information.");
PADDLE_ENFORCE_EQ(row->lod().empty(), false,
"Input(ROW) Tensor of SequenceTopkAvgPoolingOp does not "
"contain LoD information.");
PADDLE_ENFORCE_EQ(col->lod().empty(), false,
"Input(COLUMN) Tensor of SequenceTopkAvgPoolingOp does "
"not contain LoD information.");
auto channel_num = context.Attr<int>("channel_num");
auto topks = context.Attr<std::vector<int>>("topks");
auto k_num = topks.size();

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