Skip to content

Commit ebb3697

Browse files
chenwhqlXing Wu
chenwhql
and
Xing Wu
authored
[Cherry-pick] Aome SL Api/Op error msg polish (#24495)
* API/OP (Some SL API) error message enhancement (#24441) * polish some sl api error message, test=develop * polish python input check of stride slice, test=develop * fix unittest bugs, test=develop * fix error info for transpose sequence_conv_pool max_sequence_len sequ… (#24437) * fix error info for transpose sequence_conv_pool max_sequence_len sequence_erase, test=develop * fix error info for transpose sequence_conv_pool max_sequence_len sequence_erase, test=develop * update modify, test=develop * update modify, test=develop * fixed some modifications, test=develop Co-authored-by: Xing Wu <[email protected]>
1 parent 7d0e903 commit ebb3697

18 files changed

+310
-163
lines changed

‎paddle/fluid/operators/max_sequence_len_op.cc

Lines changed: 2 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -57,7 +57,8 @@ class MaxSeqenceLenOpProtoMaker : public framework::OpProtoAndCheckerMaker {
5757
class MaxSeqenceLenInferShape : public framework::InferShapeBase {
5858
public:
5959
void operator()(framework::InferShapeContext *context) const override {
60-
PADDLE_ENFORCE(context->HasInput("RankTable"));
60+
OP_INOUT_CHECK(context->HasInput("RankTable"), "Input", "RankTable",
61+
"MaxSeqenceLen");
6162
context->SetOutputDim("Out", {1});
6263
}
6364
};

‎paddle/fluid/operators/sequence_ops/sequence_erase_op.cc

Lines changed: 7 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -23,14 +23,15 @@ class SequenceEraseOp : public framework::OperatorWithKernel {
2323
using framework::OperatorWithKernel::OperatorWithKernel;
2424

2525
void InferShape(framework::InferShapeContext* ctx) const override {
26-
PADDLE_ENFORCE(ctx->HasInput("X"),
27-
"Input(X) of SequenceErase operator should not be null.");
28-
PADDLE_ENFORCE(ctx->HasOutput("Out"),
29-
"Output(Out) of SequenceErase operator should not be null.");
26+
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "SequenceErase");
27+
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "SequenceErase");
3028
auto x_dims = ctx->GetInputDim("X");
3129
PADDLE_ENFORCE(x_dims.size() == 2 && x_dims[1] == 1,
32-
"Input(X) of SequenceEraseOp should be a 2-D LoDTensor "
33-
"with the 2nd dimension equal to 1.");
30+
platform::errors::InvalidArgument(
31+
"Input(X) of SequenceEraseOp should be a 2-D LoDTensor "
32+
"with the 2nd dimension equal to 1,"
33+
"but received size %d with the 2nd dimension %d.",
34+
x_dims.size(), x_dims[1]));
3435
ctx->SetOutputDim("Out", x_dims);
3536
// The output LoDTensor's lod_level should be input X's lod_level.
3637
// For compile-time, we call SetLoDLevel to set output's lod_level.

‎paddle/fluid/operators/sequence_ops/sequence_erase_op.cu

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -64,8 +64,10 @@ class SequenceEraseOpCUDAKernel : public framework::OpKernel<T> {
6464
auto* out = ctx.Output<LoDTensor>("Out");
6565

6666
auto lod = in->lod();
67-
PADDLE_ENFORCE_EQ(lod[lod.size() - 1].back(), (size_t)in->numel(),
68-
"The actual size mismatches with the LoD information.");
67+
PADDLE_ENFORCE_EQ(
68+
lod[lod.size() - 1].back(), (size_t)in->numel(),
69+
platform::errors::InvalidArgument(
70+
"The actual size mismatches with the LoD information."));
6971
auto tokens = ctx.Attr<std::vector<int>>("tokens");
7072
auto in_len = in->numel();
7173
auto in_dat = in->data<T>();

‎paddle/fluid/operators/sequence_ops/sequence_erase_op.h

Lines changed: 6 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -30,9 +30,13 @@ class SequenceEraseKernel : public framework::OpKernel<T> {
3030
auto lod = in->lod();
3131
PADDLE_ENFORCE_EQ(
3232
lod.empty(), false,
33-
"Input(X) Tensor of SequenceEraseOp does not contain LoD information.");
33+
platform::errors::InvalidArgument("Input(X) Tensor of SequenceEraseOp "
34+
"does not contain LoD information."));
3435
PADDLE_ENFORCE_EQ(lod[lod.size() - 1].back(), (size_t)in->numel(),
35-
"The actual size mismatches with the LoD information.");
36+
platform::errors::InvalidArgument(
37+
"The actual input size %d mismatches with the LoD "
38+
"information size %d.",
39+
lod[lod.size() - 1].back(), (size_t)in->numel()));
3640
auto tokens = ctx.Attr<std::vector<int>>("tokens");
3741
auto in_len = in->numel();
3842
auto in_dat = in->data<T>();

‎paddle/fluid/operators/sequence_ops/sequence_scatter_op.cc

Lines changed: 28 additions & 17 deletions
Original file line numberDiff line numberDiff line change
@@ -74,23 +74,25 @@ class SequenceScatterOp : public framework::OperatorWithKernel {
7474

7575
void InferShape(framework::InferShapeContext* ctx) const override {
7676
// Enforce has inputs and outputs
77-
PADDLE_ENFORCE(ctx->HasInput("X"),
78-
"Input(X) of SequenceScatterOp should not be null.");
79-
PADDLE_ENFORCE(ctx->HasInput("Ids"),
80-
"Input(Ids) of SequenceScatterOp should not be null.");
81-
PADDLE_ENFORCE(ctx->HasInput("Updates"),
82-
"Input(Updates) of SequenceScatterOp should not be null.");
83-
PADDLE_ENFORCE(ctx->HasOutput("Out"),
84-
"Output(Out) of SequenceScatterOp should not be null.");
77+
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "SequenceScatter");
78+
OP_INOUT_CHECK(ctx->HasInput("Ids"), "Input", "Ids", "SequenceScatter");
79+
OP_INOUT_CHECK(ctx->HasInput("Updates"), "Input", "Updates",
80+
"SequenceScatter");
81+
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "SequenceScatter");
8582

8683
// Set output dim the same as input
8784
auto ref_dims = ctx->GetInputDim("X");
8885
ctx->SetOutputDim("Out", ref_dims);
8986

9087
// Enforce the Updates and Ids are the same shape
91-
PADDLE_ENFORCE_EQ(ctx->GetInputDim("Updates")[0],
92-
ctx->GetInputDim("Ids")[0],
93-
"Updates and Ids should have same shape.");
88+
auto updates_dim = ctx->GetInputDim("Updates");
89+
auto ids_dim = ctx->GetInputDim("Ids");
90+
PADDLE_ENFORCE_EQ(
91+
updates_dim[0], ids_dim[0],
92+
platform::errors::InvalidArgument(
93+
"The shape of SequenceScatter operator's input Updates and Ids do "
94+
"not match, receive Updates's shape is [%s], Ids's shape is [%s].",
95+
updates_dim, ids_dim));
9496

9597
// Enforce LoD of ids and updates be the same
9698
if (ctx->IsRuntime()) {
@@ -101,12 +103,21 @@ class SequenceScatterOp : public framework::OperatorWithKernel {
101103

102104
auto& ids_lod = ids_var->Get<LoDTensor>().lod();
103105
auto& updates_lod = updates_var->Get<LoDTensor>().lod();
104-
PADDLE_ENFORCE_EQ(ids_lod.size(), 1,
105-
"Currently only level 1 LoD could be"
106-
" processed by sequence scatter op.");
107-
PADDLE_ENFORCE_EQ(updates_lod.size(), 1,
108-
"Currently only level 1 LoD "
109-
"could be processed by sequence scatter op.");
106+
PADDLE_ENFORCE_EQ(
107+
ids_lod.size(), 1,
108+
platform::errors::InvalidArgument(
109+
"The SequenceScatter operator’s Input Ids holds wrong LoD "
110+
"information. Currently SequenceScatter operator can only deal "
111+
"with one level LoD for input Ids, but received LoD level is %d.",
112+
ids_lod.size()));
113+
PADDLE_ENFORCE_EQ(
114+
updates_lod.size(), 1,
115+
platform::errors::InvalidArgument(
116+
"The SequenceScatter operator’s Input Updates holds wrong LoD "
117+
"information. Currently SequenceScatter operator can only deal "
118+
"with one level LoD for input Updates, but received LoD level is "
119+
"%d.",
120+
ids_lod.size()));
110121
}
111122
}
112123

‎paddle/fluid/operators/sequence_ops/sequence_scatter_op.h

Lines changed: 35 additions & 14 deletions
Original file line numberDiff line numberDiff line change
@@ -35,8 +35,9 @@ class SequenceScatterOpKernel : public framework::OpKernel<T> {
3535

3636
auto& ids_lod = ids->lod();
3737
PADDLE_ENFORCE_EQ(ids_lod.empty(), false,
38-
"Input(Ids) Tensor of SequenceScatterOp does not contain "
39-
"LoD information.");
38+
platform::errors::InvalidArgument(
39+
"Input(Ids) Tensor of SequenceScatter operator does "
40+
"not contain LoD information."));
4041

4142
// Initialize out as same as x
4243
out->mutable_data<T>(ctx.GetPlace());
@@ -46,18 +47,26 @@ class SequenceScatterOpKernel : public framework::OpKernel<T> {
4647
auto out_dims = out->dims();
4748

4849
for (int i = 0; i < x_dims.size(); ++i)
49-
PADDLE_ENFORCE(x_dims[i] == out_dims[i],
50-
"Input and output shape of "
51-
"sequence scatter op must exactly be the same.");
50+
PADDLE_ENFORCE_EQ(x_dims[i], out_dims[i],
51+
platform::errors::InvalidArgument(
52+
"Input(X) and output(Out) shape of SequenceScatter "
53+
"operator do not match. Received input(X)'s shape "
54+
"is [%s], output(Out)'s shape is [%s].",
55+
x_dims, out_dims));
5256

5357
size_t slice_size = 1;
5458
for (int i = 1; i < x_dims.size(); ++i) slice_size *= x_dims[i];
5559

5660
auto lod_vec = ids_lod[0];
5761
unsigned int seg = 0;
5862
for (int i = 0; i < ids->dims()[0]; ++i) {
59-
PADDLE_ENFORCE_LT(seg, lod_vec.size() - 1,
60-
"Segment num must not exceed batch size.\n");
63+
PADDLE_ENFORCE_LT(
64+
seg, lod_vec.size() - 1,
65+
platform::errors::OutOfRange("The segment index is out of bound in "
66+
"SequenceScatter operator, it must be "
67+
"less than batch size. The segment "
68+
"index is %d, the batch size is %d.",
69+
seg, lod_vec.size()));
6170
int lower_bound = lod_vec[seg];
6271
int upper_bound = lod_vec[seg + 1];
6372
if (i >= lower_bound && i < upper_bound) {
@@ -77,8 +86,11 @@ template <typename T>
7786
class SequenceScatterGradientOpKernel : public framework::OpKernel<T> {
7887
public:
7988
void Compute(const framework::ExecutionContext& ctx) const override {
80-
PADDLE_ENFORCE(platform::is_cpu_place(ctx.GetPlace()),
81-
"This kernel only runs on CPU.");
89+
PADDLE_ENFORCE_EQ(
90+
platform::is_cpu_place(ctx.GetPlace()), true,
91+
platform::errors::Unimplemented("Device dose not match. The "
92+
"SequenceScatterGradientOpKernel can "
93+
"only run on CPU device."));
8294
auto* dX = ctx.Output<Tensor>(framework::GradVarName("X"));
8395
auto* dUpdates = ctx.Output<LoDTensor>(framework::GradVarName("Updates"));
8496
auto* ids = ctx.Input<LoDTensor>("Ids");
@@ -94,9 +106,13 @@ class SequenceScatterGradientOpKernel : public framework::OpKernel<T> {
94106
auto dout_dims = dOut->dims();
95107

96108
for (int i = 0; i < dx_dims.size(); ++i)
97-
PADDLE_ENFORCE(dx_dims[i] == dout_dims[i],
98-
"Input and output shape of "
99-
"sequence scatter grad op must exactly be the same.");
109+
PADDLE_ENFORCE_EQ(dx_dims[i], dout_dims[i],
110+
platform::errors::InvalidArgument(
111+
"Input(Out@GRAD) and output(X@GRAD) shape of "
112+
"SequenceScatterGradient operator do not match. "
113+
"Received input(Out@GRAD)'s shape is [%s], "
114+
"output(X@GRAD)'s shape is [%s].",
115+
dout_dims, dx_dims));
100116

101117
size_t slice_size = 1;
102118
for (int i = 1; i < dx_dims.size(); ++i) slice_size *= dx_dims[i];
@@ -105,8 +121,13 @@ class SequenceScatterGradientOpKernel : public framework::OpKernel<T> {
105121
unsigned int seg = 0;
106122

107123
for (int i = 0; i < ids->dims()[0]; ++i) {
108-
PADDLE_ENFORCE_LT(seg, lod_vec.size() - 1,
109-
"Segment num must not exceed batch size.\n");
124+
PADDLE_ENFORCE_LT(
125+
seg, lod_vec.size() - 1,
126+
platform::errors::OutOfRange(
127+
"The segment index is out of bound in SequenceScatterGradient "
128+
"operator, it must be less than batch size. The segment index is "
129+
"%d, the batch size is %d.",
130+
seg, lod_vec.size()));
110131
int lower_bound = lod_vec[seg];
111132
int upper_bound = lod_vec[seg + 1];
112133
if (i >= lower_bound && i < upper_bound) {

‎paddle/fluid/operators/sequence_ops/sequence_slice_op.cc

Lines changed: 18 additions & 14 deletions
Original file line numberDiff line numberDiff line change
@@ -23,25 +23,29 @@ class SequenceSliceOp : public framework::OperatorWithKernel {
2323
using framework::OperatorWithKernel::OperatorWithKernel;
2424

2525
void InferShape(framework::InferShapeContext* ctx) const override {
26-
PADDLE_ENFORCE(ctx->HasInput("X"),
27-
"Input(X) of SequenceSliceOp should not be null.");
28-
PADDLE_ENFORCE(ctx->HasInput("Offset"),
29-
"Input(Offset) of SequenceSliceOp should not be null.");
30-
PADDLE_ENFORCE(ctx->HasInput("Length"),
31-
"Input(Length) of SequenceSliceOp should not be null.");
32-
PADDLE_ENFORCE(ctx->HasOutput("Out"),
33-
"Output(Out) of SequenceSliceOp should not be null.");
26+
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "SequenceSlice");
27+
OP_INOUT_CHECK(ctx->HasInput("Offset"), "Input", "Offset", "SequenceSlice");
28+
OP_INOUT_CHECK(ctx->HasInput("Length"), "Input", "Length", "SequenceSlice");
29+
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "SequenceSlice");
3430
auto input_dims = ctx->GetInputDim("X");
3531

3632
auto offset_dim = ctx->GetInputDim("Offset");
3733
auto length_dim = ctx->GetInputDim("Length");
3834

3935
PADDLE_ENFORCE_EQ(
4036
offset_dim.size(), 2UL,
41-
"Only support one level sequence now, The rank of offset must be 2.");
37+
platform::errors::InvalidArgument(
38+
"Input Offset dimension error. SequenceSlice operator only support "
39+
"one level sequence now, the dimension of input Offset must be 2, "
40+
"but received dimension is %d.",
41+
offset_dim.size()));
4242
PADDLE_ENFORCE_EQ(
4343
length_dim.size(), 2UL,
44-
"Only support one level sequence now, The rank of Length must be 2.");
44+
platform::errors::InvalidArgument(
45+
"Input Length dimension error. SequenceSlice operator only support "
46+
"one level sequence now, the dimension of input Length must be 2, "
47+
"but received dimension is %d.",
48+
offset_dim.size()));
4549

4650
// Initialize the output's dims to maximum,
4751
// and re-set to real dims by the value of Offset and Length at kernel
@@ -62,10 +66,10 @@ class SequenceSliceGradOp : public framework::OperatorWithKernel {
6266
using framework::OperatorWithKernel::OperatorWithKernel;
6367

6468
void InferShape(framework::InferShapeContext* ctx) const override {
65-
PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
66-
"The gradient of Out should not be null.");
67-
PADDLE_ENFORCE(ctx->HasOutputs(framework::GradVarName("X")),
68-
"The gradient of X should not be null.");
69+
OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
70+
framework::GradVarName("Out"), "SequenceSliceGrad");
71+
OP_INOUT_CHECK(ctx->HasOutputs(framework::GradVarName("X")), "Output",
72+
framework::GradVarName("X"), "SequenceSliceGrad");
6973
ctx->SetOutputsDim(framework::GradVarName("X"), ctx->GetInputsDim("X"));
7074
}
7175

‎paddle/fluid/operators/sequence_ops/sequence_slice_op.h

Lines changed: 34 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -49,18 +49,32 @@ class SequenceSliceOpKernel : public framework::OpKernel<T> {
4949
auto* out = ctx.Output<LoDTensor>("Out");
5050

5151
auto lod = in->lod();
52-
PADDLE_ENFORCE_EQ(
53-
lod.empty(), false,
54-
"Input(X) Tensor of SequenceSliceOp does not contain LoD information.");
52+
PADDLE_ENFORCE_EQ(lod.empty(), false,
53+
platform::errors::InvalidArgument(
54+
"Input(X) Tensor of SequenceSlice operator does not "
55+
"contain LoD information."));
5556

57+
PADDLE_ENFORCE_EQ(
58+
lod.size(), 1UL,
59+
platform::errors::InvalidArgument(
60+
"LoD information error. SequenceSlice operator only support one "
61+
"level sequence now, but received LoD level is %d.",
62+
lod.size()));
5663
auto n = lod[0].size() - 1;
57-
PADDLE_ENFORCE_EQ(lod.size(), 1UL, "Only support one level sequence now.");
5864
PADDLE_ENFORCE_EQ(
5965
n, static_cast<size_t>(length->dims()[0]),
60-
"The size of input-sequence and length-array should be the same");
66+
platform::errors::InvalidArgument(
67+
"Input length shape error. The length of input LoD sequence and "
68+
"input length-array‘s first dimension should be equal, but the LoD "
69+
"sequence length is %d, the length-array‘s first dimension is %d.",
70+
n, static_cast<size_t>(length->dims()[0])));
6171
PADDLE_ENFORCE_EQ(
6272
n, static_cast<size_t>(offset->dims()[0]),
63-
"The size of input-sequence and offset-array should be the same");
73+
platform::errors::InvalidArgument(
74+
"Input offset shape error. The length of input LoD sequence and "
75+
"input offset-array‘s first dimension should be equal, but the LoD "
76+
"sequence length is %d, the offset-array‘s first dimension is %d.",
77+
n, static_cast<size_t>(offset->dims()[0])));
6478

6579
const int64_t* offset_data = offset->data<int64_t>();
6680
const int64_t* length_data = length->data<int64_t>();
@@ -79,11 +93,21 @@ class SequenceSliceOpKernel : public framework::OpKernel<T> {
7993

8094
for (size_t i = 0; i < n; ++i) {
8195
PADDLE_ENFORCE_LE(0, offset_data[i],
82-
"The offset[%d] must be nonnegative.", i);
96+
platform::errors::InvalidArgument(
97+
"The input offset[%d]'s value is negative, its "
98+
"value is %d, expect it to be non-negative.",
99+
i, offset_data[i]));
83100
PADDLE_ENFORCE_LE(0, length_data[i],
84-
"The length[%d] must be nonnegative.", i);
85-
PADDLE_ENFORCE_LE(lod[0][i] + offset_data[i] + length_data[i],
86-
lod[0][i + 1], "The target tensor's length overflow.");
101+
platform::errors::InvalidArgument(
102+
"The input length[%d]'s value is negative, its "
103+
"value is %d, expect it to be non-negative.",
104+
i, offset_data[i]));
105+
PADDLE_ENFORCE_LE(
106+
lod[0][i] + offset_data[i] + length_data[i], lod[0][i + 1],
107+
platform::errors::OutOfRange(
108+
"The slice end index of target tensor is out of range. expect it "
109+
"less than or equal to %d, but the actual slice end index is %d.",
110+
lod[0][i + 1], lod[0][i] + offset_data[i] + length_data[i]));
87111
}
88112

89113
out->mutable_data<T>(ctx.GetPlace());

‎paddle/fluid/operators/sequence_ops/sequence_softmax_op.cc

Lines changed: 17 additions & 18 deletions
Original file line numberDiff line numberDiff line change
@@ -23,10 +23,8 @@ class SequenceSoftmaxOp : public framework::OperatorWithKernel {
2323
using framework::OperatorWithKernel::OperatorWithKernel;
2424

2525
void InferShape(framework::InferShapeContext* ctx) const override {
26-
PADDLE_ENFORCE(ctx->HasInput("X"),
27-
"Input(X) of SequenceSoftmaxOp should not be null.");
28-
PADDLE_ENFORCE(ctx->HasOutput("Out"),
29-
"Output(Out) of SequenceSoftmaxOp should not be null.");
26+
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "SequenceSoftmax");
27+
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "SequenceSoftmax");
3028

3129
ctx->ShareDim("X", /*->*/ "Out");
3230
ctx->ShareLoD("X", /*->*/ "Out");
@@ -108,21 +106,22 @@ class SequenceSoftmaxGradOp : public framework::OperatorWithKernel {
108106
using framework::OperatorWithKernel::OperatorWithKernel;
109107

110108
void InferShape(framework::InferShapeContext* ctx) const override {
111-
PADDLE_ENFORCE(ctx->HasInput("Out"),
112-
"Input(Out) of SequenceSoftmaxGradOp should not be null.");
113-
PADDLE_ENFORCE(
114-
ctx->HasInput(framework::GradVarName("Out")),
115-
"Input(Out@GRAD) of SequenceSoftmaxGradOp should not be null.");
116-
PADDLE_ENFORCE(ctx->HasInput("X"),
117-
"Input(X) of SequenceSoftmaxOp should not be null.");
118-
PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("X")),
119-
"Output(X@GRAD) of SequenceSoftmaxOp should not be null.");
120-
109+
OP_INOUT_CHECK(ctx->HasInput("Out"), "Input", "Out", "SequenceSoftmaxGrad");
110+
OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
111+
"Out@GRAD", "SequenceSoftmaxGrad");
112+
OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "SequenceSoftmaxGrad");
113+
OP_INOUT_CHECK(ctx->HasOutput(framework::GradVarName("X")), "Output",
114+
"X@GRAD", "SequenceSoftmaxGrad");
115+
116+
auto out_dim = ctx->GetInputDim("Out");
117+
auto out_grad_dim = ctx->GetInputDim(framework::GradVarName("Out"));
121118
PADDLE_ENFORCE_EQ(
122-
ctx->GetInputDim("Out"),
123-
ctx->GetInputDim(framework::GradVarName("Out")),
124-
"Input(Out) and Input(Out@GRAD) of SequenceSoftmaxGradOp should be of "
125-
"the same shape.");
119+
out_dim, out_grad_dim,
120+
platform::errors::InvalidArgument(
121+
"The shape of Input(Out) and Input(Out@GRAD) of "
122+
"SequenceSoftmaxGrad operator do not match. The Input(Out)'s shape "
123+
"is [%s], the Input(Out@GRAD)'s shape is [%s].",
124+
out_dim, out_grad_dim));
126125

127126
ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X"));
128127
}

0 commit comments

Comments
 (0)