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体验新版 GitCode,发现更多精彩内容 >>
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a164b10d
编写于
4月 23, 2020
作者:
0
0YuanZhang0
提交者:
GitHub
4月 23, 2020
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电子邮件补丁
差异文件
API/OP error message enhancement (#23717)
* test=develop
上级
652e804b
变更
18
隐藏空白更改
内联
并排
Showing
18 changed file
with
459 addition
and
114 deletion
+459
-114
paddle/fluid/operators/metrics/precision_recall_op.cc
paddle/fluid/operators/metrics/precision_recall_op.cc
+63
-27
paddle/fluid/operators/metrics/precision_recall_op.h
paddle/fluid/operators/metrics/precision_recall_op.h
+22
-5
paddle/fluid/operators/sequence_ops/sequence_concat_op.cc
paddle/fluid/operators/sequence_ops/sequence_concat_op.cc
+19
-6
paddle/fluid/operators/sequence_ops/sequence_concat_op.h
paddle/fluid/operators/sequence_ops/sequence_concat_op.h
+21
-7
paddle/fluid/operators/sequence_ops/sequence_pad_op.cc
paddle/fluid/operators/sequence_ops/sequence_pad_op.cc
+55
-24
paddle/fluid/operators/sequence_ops/sequence_pad_op.h
paddle/fluid/operators/sequence_ops/sequence_pad_op.h
+2
-1
paddle/fluid/operators/sequence_ops/sequence_reshape_op.cc
paddle/fluid/operators/sequence_ops/sequence_reshape_op.cc
+20
-10
paddle/fluid/operators/sequence_ops/sequence_reshape_op.h
paddle/fluid/operators/sequence_ops/sequence_reshape_op.h
+20
-9
paddle/fluid/operators/sequence_ops/sequence_reverse_op.h
paddle/fluid/operators/sequence_ops/sequence_reverse_op.h
+25
-9
paddle/fluid/operators/sequence_ops/sequence_unpad_op.cc
paddle/fluid/operators/sequence_ops/sequence_unpad_op.cc
+29
-11
paddle/fluid/operators/truncated_gaussian_random_op.cc
paddle/fluid/operators/truncated_gaussian_random_op.cc
+10
-5
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+9
-0
python/paddle/fluid/layers/sequence_lod.py
python/paddle/fluid/layers/sequence_lod.py
+23
-0
python/paddle/fluid/tests/unittests/sequence/test_sequence_concat.py
...le/fluid/tests/unittests/sequence/test_sequence_concat.py
+38
-0
python/paddle/fluid/tests/unittests/sequence/test_sequence_pad_op.py
...le/fluid/tests/unittests/sequence/test_sequence_pad_op.py
+31
-0
python/paddle/fluid/tests/unittests/sequence/test_sequence_reshape.py
...e/fluid/tests/unittests/sequence/test_sequence_reshape.py
+22
-0
python/paddle/fluid/tests/unittests/sequence/test_sequence_reverse.py
...e/fluid/tests/unittests/sequence/test_sequence_reverse.py
+17
-0
python/paddle/fluid/tests/unittests/sequence/test_sequence_unpad_op.py
.../fluid/tests/unittests/sequence/test_sequence_unpad_op.py
+33
-0
未找到文件。
paddle/fluid/operators/metrics/precision_recall_op.cc
浏览文件 @
a164b10d
...
...
@@ -22,18 +22,30 @@ class PrecisionRecallOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"MaxProbs"
),
"Input(MaxProbs) should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Indices"
),
"Input(Indices) should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Labels"
),
"Input(Labels) should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"BatchMetrics"
),
"Output(BatchMetrics) should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"AccumMetrics"
),
"Output(AccumMetrics) should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"AccumStatesInfo"
),
"Output(AccumStatesInfo) should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"MaxProbs"
),
true
,
platform
::
errors
::
NotFound
(
"PrecisionRecallOp Input(MaxProbs) should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"Indices"
),
true
,
platform
::
errors
::
NotFound
(
"PrecisionRecallOp Input(Indices) should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"Labels"
),
true
,
platform
::
errors
::
NotFound
(
"PrecisionRecallOp Input(Labels) should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"BatchMetrics"
),
true
,
platform
::
errors
::
NotFound
(
"PrecisionRecallOp Output(BatchMetrics) should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"AccumMetrics"
),
true
,
platform
::
errors
::
NotFound
(
"PrecisionRecallOp Output(AccumMetrics) should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"AccumStatesInfo"
),
true
,
platform
::
errors
::
NotFound
(
"PrecisionRecallOp Output(AccumStatesInfo) should not be null."
));
int64_t
cls_num
=
static_cast
<
int64_t
>
(
ctx
->
Attrs
().
Get
<
int
>
(
"class_number"
));
...
...
@@ -42,37 +54,61 @@ class PrecisionRecallOp : public framework::OperatorWithKernel {
if
(
ctx
->
IsRuntime
())
{
PADDLE_ENFORCE_EQ
(
max_probs_dims
[
1
],
1
,
"Each instance contains one max probability, so the "
"shape of Input(MaxProbs) should be [batch_size, 1]."
);
platform
::
errors
::
InvalidArgument
(
"Each instance of PrecisionRecallOp "
"Input(MaxProbs) contains one max probability, "
"the shape of Input(MaxProbs) should be "
"[batch_size, 1], the 2nd dimension of "
"Input(MaxProbs) should be 1. But the 2nd "
"dimension we received is %d"
,
max_probs_dims
[
1
]));
PADDLE_ENFORCE_EQ
(
ctx
->
GetInputDim
(
"Indices"
),
max_probs_dims
,
"The shape of Input(Indices) should bes same with max_probs_dims"
);
platform
::
errors
::
InvalidArgument
(
"The shape of PrecisionRecallOp Input(Indices) should be same "
"with "
"max_probs_dims. But received the shape of Input(Indices) is "
"[%d, %d], max_probs_dims is [%d, %d]"
,
ctx
->
GetInputDim
(
"Indices"
)[
0
],
ctx
->
GetInputDim
(
"Indices"
)[
1
],
max_probs_dims
[
0
],
max_probs_dims
[
1
]));
PADDLE_ENFORCE_EQ
(
max_probs_dims
[
0
],
labels_dims
[
0
],
"The 1st dimension of Input(MaxProbs) and "
"Input(Labels) both are batch_size and the shape should "
"be the same."
);
platform
::
errors
::
InvalidArgument
(
"The 1st dimension of PrecisionRecallOp Input(MaxProbs) and "
"Input(Labels) both should be batch_size"
"But the 1st dimension we received max_probs_dims[0] = %d, "
"labels_dims[0] = %d"
,
max_probs_dims
[
0
],
labels_dims
[
0
]));
PADDLE_ENFORCE_EQ
(
labels_dims
[
1
],
1
,
"The 2nd dimension of Input(Labels) contains instance "
"label and the shape should be equal to 1."
);
platform
::
errors
::
InvalidArgument
(
"The 2nd dimension of PrecisionRecallOp "
"Input(Labels) contains instance label and "
"the shape should be equal to 1. But the 2nd "
"dimension we received is %d"
,
labels_dims
[
1
]));
}
if
(
ctx
->
HasInput
(
"Weights"
))
{
auto
weights_dims
=
ctx
->
GetInputDim
(
"Weights"
);
if
(
ctx
->
IsRuntime
())
{
PADDLE_ENFORCE_EQ
(
weights_dims
,
framework
::
make_ddim
({
max_probs_dims
[
0
],
1
}),
"The shape of Input(Weights) should be "
"[batch_size, 1]."
);
PADDLE_ENFORCE_EQ
(
weights_dims
,
framework
::
make_ddim
({
max_probs_dims
[
0
],
1
}),
platform
::
errors
::
InvalidArgument
(
"The shape of PrecisionRecallOp Input(Weights) should be "
"[batch_size, 1]. But the shape we received is [%d, %d]"
,
weights_dims
[
0
],
weights_dims
[
1
]));
}
}
if
(
ctx
->
HasInput
(
"StatesInfo"
))
{
auto
states_dims
=
ctx
->
GetInputDim
(
"StatesInfo"
);
if
(
ctx
->
IsRuntime
())
{
PADDLE_ENFORCE_EQ
(
states_dims
,
framework
::
make_ddim
({
cls_num
,
4
}),
"The shape of Input(StatesInfo) should be "
"[class_number, 4]."
);
PADDLE_ENFORCE_EQ
(
states_dims
,
framework
::
make_ddim
({
cls_num
,
4
}),
platform
::
errors
::
InvalidArgument
(
"The shape of PrecisionRecallOp Input(StatesInfo) should be "
"[class_number, 4]. But the shape we received is [%d, %d]"
,
states_dims
[
0
],
states_dims
[
1
]));
}
}
...
...
paddle/fluid/operators/metrics/precision_recall_op.h
浏览文件 @
a164b10d
...
...
@@ -58,11 +58,28 @@ class PrecisionRecallKernel : public framework::OpKernel<T> {
size_t
idx
=
ids_data
[
i
];
size_t
label
=
labels_data
[
i
];
PADDLE_ENFORCE
(
idx
>=
0
&&
idx
<
cls_num
,
"Class index of each instance should be in "
"[0, class_number)."
);
PADDLE_ENFORCE
(
label
>=
0
&&
label
<
cls_num
,
"Label of each instance should be in [0, class_number)."
);
PADDLE_ENFORCE_GE
(
idx
,
0
,
platform
::
errors
::
InvalidArgument
(
"Class index of each instance should be "
"greater than or equal to 0, But the index we received is %d"
,
idx
));
PADDLE_ENFORCE_LT
(
idx
,
cls_num
,
platform
::
errors
::
InvalidArgument
(
"Class index of each instance should be less than "
"cls_num = %d, But the index we received is %d"
,
cls_num
,
idx
));
PADDLE_ENFORCE_GE
(
label
,
0
,
platform
::
errors
::
InvalidArgument
(
"Label of each instance should be greater than or "
"equal to 0, But the label we received is %d"
,
label
));
PADDLE_ENFORCE_LT
(
label
,
cls_num
,
platform
::
errors
::
InvalidArgument
(
"Label of each instance should be less than "
"cls_num = %d, But the label we received is %d"
,
cls_num
,
label
));
T
w
=
weights_data
?
weights_data
[
i
]
:
1.0
;
if
(
idx
==
label
)
{
...
...
paddle/fluid/operators/sequence_ops/sequence_concat_op.cc
浏览文件 @
a164b10d
...
...
@@ -41,13 +41,21 @@ class SequenceConcatOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
framework
::
InferShapeContext
*
context
)
const
override
{
PADDLE_ENFORCE
(
context
->
HasInputs
(
"X"
),
"Input(X) of Sequence Concat Op should not be null."
);
PADDLE_ENFORCE
(
context
->
HasOutput
(
"Out"
),
"Output(Out) of Sequence Concat Op should not be null."
);
PADDLE_ENFORCE_EQ
(
context
->
HasInputs
(
"X"
),
true
,
platform
::
errors
::
NotFound
(
"SequenceConcatOp Input(X) of Sequence "
"Concat Op should not be null."
));
PADDLE_ENFORCE_EQ
(
context
->
HasOutput
(
"Out"
),
true
,
platform
::
errors
::
NotFound
(
"SequenceConcatOp Output(Out) of Sequence "
"Concat Op should not be null."
));
PADDLE_ENFORCE_GT
(
context
->
Inputs
(
"X"
).
size
(),
1
,
"The number of input sequences is at least two."
);
platform
::
errors
::
InvalidArgument
(
"The number of SequenceConcatOp inputs should be "
"greater than 1. But "
"the number of inputs we received is %d"
,
context
->
Inputs
(
"X"
).
size
()));
auto
x_dims
=
context
->
GetInputsDim
(
"X"
);
int64_t
batch_size
=
0
;
int64_t
feature_size
=
0
;
...
...
@@ -62,7 +70,12 @@ class SequenceConcatOp : public framework::OperatorWithKernel {
}
else
{
PADDLE_ENFORCE_EQ
(
feature_size
,
framework
::
product
(
x_dim
)
/
x_dim
[
0
],
"Inputs of sequence concat must have same feature size"
);
platform
::
errors
::
InvalidArgument
(
"Each input of SequenceConcatOp inputs must have same feature "
"size, But "
"the feature size we received is %d, the feature size of 1st "
"input is %d"
,
feature_size
,
framework
::
product
(
x_dim
)
/
x_dim
[
0
]));
}
}
if
(
batch_size
<
0
)
{
...
...
paddle/fluid/operators/sequence_ops/sequence_concat_op.h
浏览文件 @
a164b10d
...
...
@@ -73,16 +73,25 @@ class SeqConcatKernel : public framework::OpKernel<T> {
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."
);
platform
::
errors
::
NotFound
(
"Input(X) Tensor of SequenceConcatOp does not "
"contain LoD information."
));
lod_size
=
x
.
get
().
lod
()[
0
].
size
();
}
else
{
PADDLE_ENFORCE_EQ
(
lod_size
,
x
.
get
().
lod
()[
0
].
size
(),
"The number of sequence must be same between each input"
);
PADDLE_ENFORCE_EQ
(
lod_size
,
x
.
get
().
lod
()[
0
].
size
(),
platform
::
errors
::
InvalidArgument
(
"The lod size of each input must be the same, "
"But the lod size of input we received is %d, "
"the first input is %d"
,
x
.
get
().
lod
()[
0
].
size
(),
lod_size
));
}
}
PADDLE_ENFORCE_NE
(
lod_size
,
0
,
"Each input must have sequence information"
);
PADDLE_ENFORCE_NE
(
lod_size
,
0
,
platform
::
errors
::
InvalidArgument
(
"Each input must have sequence lod information. But we "
"received input lod size is %d"
,
lod_size
));
std
::
vector
<
framework
::
Tensor
>
x_in_order
;
out
.
set_lod
(
detail
::
ConcatLoD
(
xs
,
&
x_in_order
));
...
...
@@ -100,7 +109,12 @@ class SeqConcatGradKernel : public framework::OpKernel<T> {
auto
xs
=
context
.
MultiInput
<
framework
::
LoDTensor
>
(
"X"
);
auto
dxs
=
context
.
MultiOutput
<
framework
::
LoDTensor
>
(
framework
::
GradVarName
(
"X"
));
PADDLE_ENFORCE_EQ
(
xs
.
size
(),
dxs
.
size
());
PADDLE_ENFORCE_EQ
(
xs
.
size
(),
dxs
.
size
(),
platform
::
errors
::
InvalidArgument
(
"The rank of Input X and Output Grad X must be "
"same, But the rank of Input X we received is %d, "
"the rank of Output Grad X is %d"
,
xs
.
size
(),
dxs
.
size
()));
for
(
size_t
i
=
0
;
i
<
dxs
.
size
();
++
i
)
{
if
(
dxs
[
i
]
!=
nullptr
)
{
dxs
[
i
]
->
set_lod
(
xs
[
i
]
->
lod
());
...
...
paddle/fluid/operators/sequence_ops/sequence_pad_op.cc
浏览文件 @
a164b10d
...
...
@@ -26,24 +26,35 @@ class SequencePadOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
"Input(X) of SequencePadOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"PadValue"
),
true
,
"Input(PadValue) of SequencePadOp should not be null."
);
platform
::
errors
::
NotFound
(
"Input(X) of SequencePadOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"PadValue"
),
true
,
platform
::
errors
::
NotFound
(
"Input(PadValue) of SequencePadOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Out"
),
true
,
"Output(Out) of SequencePadOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Length"
),
true
,
"Output(Length) of SequencePadOp should not be null."
);
platform
::
errors
::
NotFound
(
"Output(Out) of SequencePadOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Length"
),
true
,
platform
::
errors
::
NotFound
(
"Output(Length) of SequencePadOp should not be null."
));
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
PADDLE_ENFORCE_GE
(
x_dims
.
size
(),
2
,
"The rank of Input(X) can't be less than 2."
);
platform
::
errors
::
InvalidArgument
(
"The rank of SequencePadOp Input(X) can't be less "
"than 2. But the rank we received is %d"
,
x_dims
.
size
()));
auto
time_step_dims
=
framework
::
slice_ddim
(
x_dims
,
1
,
x_dims
.
size
());
auto
pad_value_dims
=
ctx
->
GetInputDim
(
"PadValue"
);
PADDLE_ENFORCE_EQ
(
pad_value_dims
==
framework
::
make_ddim
({
1
})
||
pad_value_dims
==
time_step_dims
,
true
,
"The Input(PadValue) must be a scalar or a tensor whose "
"shape equals to time steps in sequences"
);
PADDLE_ENFORCE_EQ
(
pad_value_dims
==
framework
::
make_ddim
({
1
})
||
pad_value_dims
==
time_step_dims
,
true
,
platform
::
errors
::
InvalidArgument
(
"The SequencePadOp Input(PadValue) must be a scalar or a tensor "
"whose shape equals to time steps in sequences"
));
int
out_dim_0
=
-
1
;
...
...
@@ -54,22 +65,37 @@ class SequencePadOp : public framework::OperatorWithKernel {
boost
::
get
<
framework
::
Variable
*>
(
ctx
->
GetInputVarPtrs
(
"X"
)[
0
]);
const
auto
&
x_lod
=
x_var
->
Get
<
LoDTensor
>
().
lod
();
PADDLE_ENFORCE_EQ
(
x_lod
.
empty
(),
false
,
"The Input(X) must hold lod info."
);
platform
::
errors
::
NotFound
(
"The SequencePadOp Input(X) must hold lod info."
));
const
auto
&
x_lod_0
=
x_lod
[
0
];
PADDLE_ENFORCE_GE
(
x_lod_0
.
size
(),
2
,
"The Input(X)'s lod info is corrupted."
);
PADDLE_ENFORCE_EQ
(
x_dims
[
0
],
static_cast
<
int64_t
>
(
x_lod_0
.
back
()),
"The Input(X)'s lod info mismatches the actual tensor shape."
);
PADDLE_ENFORCE_GE
(
x_lod_0
.
size
(),
2
,
platform
::
errors
::
InvalidArgument
(
"The size of SequencePadOp Input(X)'s lod info can't be less "
"than 2. But the size we received is %d"
,
x_lod_0
.
size
()));
PADDLE_ENFORCE_EQ
(
x_dims
[
0
],
static_cast
<
int64_t
>
(
x_lod_0
.
back
()),
platform
::
errors
::
InvalidArgument
(
"The SequencePadOp Input(X)'s lod info mismatches "
"the actual tensor shape. The 1st dimension of "
"Input(X)'s lod info is %d, the 1st dimension of "
"actual tensor shape is %d"
,
x_dims
[
0
],
static_cast
<
int64_t
>
(
x_lod_0
.
back
())));
int
seq_num
=
x_lod_0
.
size
()
-
1
;
int
max_seq_len
=
math
::
MaximumSequenceLength
(
x_lod_0
);
if
(
padded_length
==
-
1
)
{
padded_length
=
max_seq_len
;
}
PADDLE_ENFORCE_GE
(
padded_length
,
max_seq_len
,
"The Attr(padded_length) must be -1 or an int greater "
"than the length of the longest original sequence."
);
PADDLE_ENFORCE_GE
(
padded_length
,
max_seq_len
,
platform
::
errors
::
InvalidArgument
(
"The SequencePadOp Attr(padded_length) should be greater than or "
"equal to the "
"length of the longest original sequence. But the padded_length "
"we received is %d, the length of the longest original sequence "
"is %d"
,
padded_length
,
max_seq_len
));
out_dim_0
=
seq_num
;
}
else
{
// compile time
...
...
@@ -78,7 +104,10 @@ class SequencePadOp : public framework::OperatorWithKernel {
}
PADDLE_ENFORCE_GT
(
ctx
->
GetLoDLevel
(
"X"
),
0
,
"The LoD level Input(X) of sequence_pad should be larger than 0."
);
platform
::
errors
::
InvalidArgument
(
"The LoD level of SequencePadOp Input(X) should be "
"larger than 0. But the LoD level we received is %d"
,
ctx
->
GetLoDLevel
(
"X"
)));
}
std
::
vector
<
int
>
out_dims_vec
{
out_dim_0
,
padded_length
};
...
...
@@ -185,10 +214,12 @@ class SequencePadGradOp : public framework::OperatorWithKernel {
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
"Input(X) of SequencePadGradOp should not be null."
);
platform
::
errors
::
NotFound
(
"Input(X) of SequencePadGradOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
true
,
"Input(Out@GRAD) of SequencePadGradOp should not be null."
);
platform
::
errors
::
NotFound
(
"Input(Out@GRAD) of SequencePadGradOp should not be null."
));
if
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"X"
)))
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
"X"
));
...
...
paddle/fluid/operators/sequence_ops/sequence_pad_op.h
浏览文件 @
a164b10d
...
...
@@ -37,7 +37,8 @@ class SequencePadOpKernel : public framework::OpKernel<T> {
PADDLE_ENFORCE_EQ
(
x
->
lod
().
empty
(),
false
,
"Input(X) Tensor of SequencePadOp does not contain LoD information."
);
platform
::
errors
::
NotFound
(
"Input(X) Tensor of SequencePadOp does not "
"contain LoD information."
));
const
auto
*
pad_value
=
ctx
.
Input
<
LoDTensor
>
(
"PadValue"
);
...
...
paddle/fluid/operators/sequence_ops/sequence_reshape_op.cc
浏览文件 @
a164b10d
...
...
@@ -23,13 +23,20 @@ class SequenceReshapeOp : public framework::OperatorWithKernel {
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of SequenceReshapeOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of SequenceReshapeOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
platform
::
errors
::
NotFound
(
"Input(X) of SequenceReshapeOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Out"
),
true
,
platform
::
errors
::
NotFound
(
"Output(Out) of SequenceReshapeOp should not be null."
));
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
x_numel
=
product
(
x_dims
);
PADDLE_ENFORCE_EQ
(
x_dims
.
size
(),
2U
,
"Rank of Input(X) should be 2."
);
PADDLE_ENFORCE_EQ
(
x_dims
.
size
(),
2U
,
platform
::
errors
::
InvalidArgument
(
"The rank of SequenceReshapeOp Input(X) should be 2. "
"But the rank we received is %d"
,
x_dims
.
size
()));
int
new_dim
=
ctx
->
Attrs
().
Get
<
int
>
(
"new_dim"
);
if
(
ctx
->
IsRuntime
())
{
ctx
->
SetOutputDim
(
"Out"
,
...
...
@@ -90,11 +97,14 @@ class SequenceReshapeGradOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) of SequenceReshapeGradOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of SequenceReshapeGradOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
true
,
platform
::
errors
::
NotFound
(
"Input(Out@GRAD) of SequenceReshapeGradOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
platform
::
errors
::
NotFound
(
"Input(X) of SequenceReshapeGradOp should not be null."
));
ctx
->
ShareDim
(
"X"
,
/*->*/
framework
::
GradVarName
(
"X"
));
ctx
->
ShareLoD
(
"X"
,
/*->*/
framework
::
GradVarName
(
"X"
));
...
...
paddle/fluid/operators/sequence_ops/sequence_reshape_op.h
浏览文件 @
a164b10d
...
...
@@ -33,13 +33,22 @@ class SequenceReshapeKernel : public framework::OpKernel<T> {
auto
&
in_lod
=
in
->
lod
();
PADDLE_ENFORCE_EQ
(
in_lod
.
empty
(),
false
,
"Input(X) Tensor of SequenceReshapeOp does not contain "
"LoD information."
);
platform
::
errors
::
NotFound
(
"Input(X) Tensor of SequenceReshapeOp does not "
"contain LoD information."
));
PADDLE_ENFORCE_EQ
(
in_lod
.
size
(),
1UL
,
"Only support one level sequence now."
);
platform
::
errors
::
InvalidArgument
(
"Input(X) Tensor of SequenceReshapeOp Only support "
"one level sequence now. But lod size "
"of Input(X) is %d"
,
in_lod
.
size
()));
PADDLE_ENFORCE_EQ
(
(
uint64_t
)
in_dims
[
0
],
in_lod
[
0
].
back
(),
"Inconsistent size between X.shape[0] and X.lod()[0].back()."
);
platform
::
errors
::
InvalidArgument
(
"The size of SequenceReshapeOp X.shape[0] and X.lod()[0].back() "
"should "
"be same. But X.shape[0] = %d, X.lod()[0].back() = %d"
,
(
uint64_t
)
in_dims
[
0
],
in_lod
[
0
].
back
()));
auto
in_lod_l0
=
in_lod
[
0
];
int
seq_num
=
in_lod_l0
.
size
()
-
1
;
...
...
@@ -55,11 +64,13 @@ class SequenceReshapeKernel : public framework::OpKernel<T> {
size_t
seq_len
=
in_lod_l0
[
i
+
1
]
-
in_lod_l0
[
i
];
size_t
offset
=
0
;
offset
=
(
seq_len
*
in_width
)
/
out_width
;
PADDLE_ENFORCE_EQ
(
offset
*
out_width
,
seq_len
*
in_width
,
"Please make sure (sequence_length * dimension) can "
"be divided by new_dim with no remainder for each "
"sequence. The %dth sequence is invalid."
,
i
+
1
);
PADDLE_ENFORCE_EQ
(
offset
*
out_width
,
seq_len
*
in_width
,
platform
::
errors
::
InvalidArgument
(
"Please make sure (sequence_length * dimension) "
"can be divided by context Attr(new_dim) with no remainder for "
"each sequence. But the %dth sequence is invalid."
,
i
+
1
));
out_lod
[
0
][
i
+
1
]
=
out_lod
[
0
][
i
]
+
offset
;
}
}
...
...
paddle/fluid/operators/sequence_ops/sequence_reverse_op.h
浏览文件 @
a164b10d
...
...
@@ -27,12 +27,21 @@ class SequenceReverseOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) must exist"
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Y"
),
"Output(Y) must exist"
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
platform
::
errors
::
NotFound
(
"Input(X) of SequenceReverse must exist"
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Y"
),
true
,
platform
::
errors
::
NotFound
(
"Output(Y) of SequenceReverse must exist"
));
auto
x_dim
=
ctx
->
GetInputDim
(
"X"
);
PADDLE_ENFORCE_GE
(
x_dim
.
size
(),
2
,
"Rank of Input(X) must be not less than 2."
);
PADDLE_ENFORCE_GE
(
x_dim
.
size
(),
2
,
platform
::
errors
::
InvalidArgument
(
"The rank of SequenceReverseOp Input(X) must be greater "
"than or equal to 2. But the Input(X) tensor's rank we received is "
"%d"
,
x_dim
.
size
()));
ctx
->
SetOutputDim
(
"Y"
,
x_dim
);
ctx
->
ShareLoD
(
"X"
,
"Y"
);
...
...
@@ -108,10 +117,15 @@ class SequenceReverseOpKernel : public framework::OpKernel<T> {
auto
*
y
=
ctx
.
Output
<
LoDTensor
>
(
"Y"
);
PADDLE_ENFORCE_EQ
(
x
.
lod
().
empty
(),
false
,
"Input(X) Tensor of SequenceReverseOp does not contain "
"LoD information."
);
platform
::
errors
::
NotFound
(
"Input(X) Tensor of SequenceReverseOp does not "
"contain LoD information."
));
PADDLE_ENFORCE_EQ
(
x
.
lod
().
size
(),
1
,
"SequenceReverse Op only support one level lod."
);
platform
::
errors
::
InvalidArgument
(
"SequenceReverseOp only support one "
"level lod. But the Input(X) lod size is %d"
,
x
.
lod
().
size
()));
const
size_t
*
lod
;
size_t
lod_count
=
x
.
lod
()[
0
].
size
();
...
...
@@ -131,8 +145,10 @@ class SequenceReverseOpKernel : public framework::OpKernel<T> {
auto
*
x_data
=
x
.
data
<
T
>
();
auto
*
y_data
=
y
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
PADDLE_ENFORCE_NE
(
x_data
,
y_data
,
"SequenceReverse Op does not support in-place operation"
);
PADDLE_ENFORCE_NE
(
x_data
,
y_data
,
platform
::
errors
::
InvalidArgument
(
"SequenceReverse Op does not support in-place operation"
));
if
(
platform
::
is_cpu_place
(
ctx
.
GetPlace
()))
{
for
(
size_t
idx
=
0
;
idx
<
lod_count
-
1
;
idx
++
)
{
...
...
paddle/fluid/operators/sequence_ops/sequence_unpad_op.cc
浏览文件 @
a164b10d
...
...
@@ -26,22 +26,37 @@ class SequenceUnpadOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
"Input(X) of SequenceUnpadOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"Length"
),
true
,
"Input(Length) of SequenceUnpadOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Out"
),
true
,
"Output(Out) of SequenceUnpadOp should not be null."
);
platform
::
errors
::
NotFound
(
"Input(X) of SequenceUnpadOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"Length"
),
true
,
platform
::
errors
::
NotFound
(
"Input(Length) of SequenceUnpadOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Out"
),
true
,
platform
::
errors
::
NotFound
(
"Output(Out) of SequenceUnpadOp should not be null."
));
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
PADDLE_ENFORCE_GE
(
x_dims
.
size
(),
2
,
"The rank of Input(X) can't be less than 2."
);
platform
::
errors
::
InvalidArgument
(
"The rank of Input(X) can't be less than 2. But the "
"rank we received is %d"
,
x_dims
.
size
()));
auto
len_dims
=
ctx
->
GetInputDim
(
"Length"
);
PADDLE_ENFORCE_EQ
(
len_dims
.
size
(),
1
,
"The shape of Input(Length) should be [batch_size]."
);
platform
::
errors
::
InvalidArgument
(
"The rank of SequenceUnpadOp Input(Length) should "
"be 1. But the rank we received is %d"
,
len_dims
.
size
()));
PADDLE_ENFORCE_EQ
(
len_dims
[
0
],
x_dims
[
0
],
"Input(X) and Input(Length) should have the same first dimension."
);
platform
::
errors
::
InvalidArgument
(
"The 1st dimension of SequenceUnpadOp Input(X) and Input(Length)"
"should be same. But the 1st dimension of "
"Input(X) is %d, Input(Length) is %d"
,
x_dims
[
0
],
len_dims
[
0
]));
int64_t
out_dim_0
=
-
1
;
if
(
ctx
->
IsRuntime
())
{
...
...
@@ -115,11 +130,14 @@ class SequenceUnpadGradOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
"Input(X) of SequenceUnpadGradOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
"X"
),
true
,
platform
::
errors
::
NotFound
(
"Input(X) of SequenceUnpadGradOp should not be null."
));
PADDLE_ENFORCE_EQ
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
true
,
"Input(Out@GRAD) of SequenceUnpadGradOp should not be null."
);
platform
::
errors
::
NotFound
(
"Input(Out@GRAD) of SequenceUnpadGradOp should not be null."
));
if
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"X"
)))
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
"X"
));
...
...
paddle/fluid/operators/truncated_gaussian_random_op.cc
浏览文件 @
a164b10d
...
...
@@ -182,17 +182,22 @@ class TruncatedGaussianRandomOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of TruncatedGaussianRandomOp should not be null."
);
PADDLE_ENFORCE_EQ
(
ctx
->
HasOutput
(
"Out"
),
true
,
platform
::
errors
::
NotFound
(
"Output(Out) of TruncatedGaussianRandomOp should not be null."
));
auto
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"shape"
);
std
::
vector
<
int64_t
>
out_dim
;
out_dim
.
reserve
(
shape
.
size
());
for
(
auto
dim
:
shape
)
{
out_dim
.
push_back
(
static_cast
<
int64_t
>
(
dim
));
}
PADDLE_ENFORCE
(
shape
.
size
()
>
0UL
,
"shape can be one int or array. shape must be set."
);
PADDLE_ENFORCE_GT
(
shape
.
size
(),
0UL
,
platform
::
errors
::
InvalidArgument
(
"the input shape of TruncatedGaussianRandomOp must be set, "
"But the rank of shape we received is %d"
,
shape
.
size
()));
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
out_dim
));
}
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
a164b10d
...
...
@@ -10046,6 +10046,9 @@ def gaussian_random(shape, mean=0.0, std=1.0, seed=0, dtype='float32'):
"""
helper = LayerHelper('gaussian_random', **locals())
check_type(shape, 'shape', (list, tuple), 'fluid.layers.gaussian_random')
check_dtype(dtype, 'dtype', ['float32', 'float64'],
'fluid.layers.gaussian_random')
out = helper.create_variable_for_type_inference(dtype)
c_dtype = convert_np_dtype_to_dtype_(dtype)
helper.append_op(
...
...
@@ -10139,6 +10142,12 @@ def gaussian_random_batch_size_like(input,
"""
helper = LayerHelper('gaussian_random_batch_size_like', **locals())
check_type(input, 'input', (Variable),
'fluid.layers.gaussian_random_batch_size_like')
check_type(shape, 'shape', (list, tuple),
'fluid.layers.gaussian_random_batch_size_like')
check_dtype(dtype, 'dtype', ['float16', 'float32', 'int'],
'fluid.layers.gaussian_random_batch_size_like')
out = helper.create_variable_for_type_inference(dtype)
c_dtype = convert_np_dtype_to_dtype_(dtype)
helper.append_op(
...
...
python/paddle/fluid/layers/sequence_lod.py
浏览文件 @
a164b10d
...
...
@@ -17,6 +17,7 @@ from __future__ import print_function
from
.layer_function_generator
import
templatedoc
from
..framework
import
Variable
,
in_dygraph_mode
from
..layer_helper
import
LayerHelper
from
..data_feeder
import
check_variable_and_dtype
,
check_type
,
check_dtype
__all__
=
[
'sequence_conv'
,
...
...
@@ -405,6 +406,13 @@ def sequence_concat(input, name=None):
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_concat'
,
**
locals
())
check_type
(
input
,
'input'
,
list
,
'fluid.layers.sequence_concat'
)
for
i
,
input_x
in
enumerate
(
input
):
check_variable_and_dtype
(
input_x
,
'input['
+
str
(
i
)
+
']'
,
[
'int64'
,
'float32'
,
'float64'
],
'fluid.layers.sequence_concat'
)
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
helper
.
input_dtype
())
helper
.
append_op
(
type
=
'sequence_concat'
,
inputs
=
{
'X'
:
input
},
outputs
=
{
'Out'
:
[
out
]})
...
...
@@ -926,6 +934,11 @@ def sequence_pad(x, pad_value, maxlen=None, name=None):
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_pad'
,
input
=
x
,
**
locals
())
check_variable_and_dtype
(
x
,
'x'
,
[
'float32'
,
'float64'
,
'int32'
,
'int64'
],
'fluid.layers.sequence_pad'
)
check_variable_and_dtype
(
pad_value
,
'pad_value'
,
[
'float32'
,
'float64'
,
'int32'
,
'int64'
],
'fluid.layers.sequence_pad'
)
dtype
=
helper
.
input_dtype
()
out
=
helper
.
create_variable_for_type_inference
(
dtype
)
length
=
helper
.
create_variable_for_type_inference
(
dtype
)
...
...
@@ -1001,6 +1014,10 @@ def sequence_unpad(x, length, name=None):
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_unpad'
,
input
=
x
,
**
locals
())
check_variable_and_dtype
(
x
,
'x'
,
[
'float32'
,
'float64'
,
'int32'
,
'int64'
],
'fluid.layers.sequence_unpad'
)
check_variable_and_dtype
(
length
,
'length'
,
[
'int64'
],
'fluid.layers.sequence_unpad'
)
dtype
=
helper
.
input_dtype
()
out
=
helper
.
create_variable_for_type_inference
(
dtype
)
...
...
@@ -1062,6 +1079,9 @@ def sequence_reshape(input, new_dim):
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
'sequence_reshape'
,
**
locals
())
check_variable_and_dtype
(
input
,
'input'
,
[
'float32'
,
'float64'
,
'int32'
,
'int64'
],
'fluid.layers.sequence_reshape'
)
out
=
helper
.
create_variable_for_type_inference
(
helper
.
input_dtype
())
helper
.
append_op
(
type
=
'sequence_reshape'
,
...
...
@@ -1334,6 +1354,9 @@ def sequence_reverse(x, name=None):
assert
not
in_dygraph_mode
(),
(
"sequence layer is not supported in dygraph mode yet."
)
helper
=
LayerHelper
(
"sequence_reverse"
,
**
locals
())
check_variable_and_dtype
(
x
,
'x'
,
[
'float32'
,
'float64'
,
'int8'
,
'int32'
,
'int64'
],
'fluid.layers.sequence_reverse'
)
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
x
.
dtype
)
helper
.
append_op
(
...
...
python/paddle/fluid/tests/unittests/sequence/test_sequence_concat.py
浏览文件 @
a164b10d
...
...
@@ -20,6 +20,8 @@ import sys
sys
.
path
.
append
(
"../"
)
from
op_test
import
OpTest
from
paddle
import
fluid
class
TestSequenceConcat
(
OpTest
):
def
setLoD
(
self
):
...
...
@@ -76,5 +78,41 @@ class TestSequenceConcatCase5(TestSequenceConcat):
self
.
out_lod
=
[
20
,
10
]
class
TestSequenceConcatOpError
(
unittest
.
TestCase
):
def
test_errors
(
self
):
def
test_input_list
():
# the input type must be list
x_data
=
fluid
.
layers
.
data
(
name
=
'x'
,
shape
=
[
4
],
dtype
=
'float32'
)
fluid
.
layers
.
sequence_concat
(
input
=
x_data
)
self
.
assertRaises
(
TypeError
,
test_input_list
)
def
test_variable1
():
# the input element type must be Variable
x1_data
=
np
.
array
([[
3
,
5
]]).
astype
(
'float32'
)
y1_data
=
fluid
.
layers
.
data
(
name
=
'y1'
,
shape
=
[
4
],
dtype
=
'float32'
)
fluid
.
layers
.
sequence_concat
(
input
=
[
x1_data
,
y1_data
])
def
test_variable2
():
x2_data
=
np
.
array
([[
3
,
5
]]).
astype
(
'float32'
)
y2_data
=
fluid
.
layers
.
data
(
name
=
'y2'
,
shape
=
[
4
],
dtype
=
'float32'
)
fluid
.
layers
.
sequence_concat
(
input
=
[
y2_data
,
x2_data
])
for
i
in
range
(
2
):
if
i
==
0
:
self
.
assertRaises
(
TypeError
,
test_variable1
)
else
:
self
.
assertRaises
(
TypeError
,
test_variable2
)
def
test_dtype
():
# dtype must be 'float32', 'float64', 'int64'
x3_data
=
fluid
.
layers
.
data
(
name
=
"x3"
,
shape
=
[
3
,
5
],
dtype
=
'int32'
)
y3_data
=
fluid
.
layers
.
data
(
name
=
"y3"
,
shape
=
[
3
,
5
],
dtype
=
'int16'
)
input_list
=
[
x3_data
,
y3_data
]
fluid
.
layers
.
sequence_concat
(
input
=
input_list
)
self
.
assertRaises
(
TypeError
,
test_dtype
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/sequence/test_sequence_pad_op.py
浏览文件 @
a164b10d
...
...
@@ -18,6 +18,8 @@ import sys
sys
.
path
.
append
(
"../"
)
from
op_test
import
OpTest
import
paddle.fluid
as
fluid
class
TestSequencePadOp
(
OpTest
):
def
set_attr
(
self
):
...
...
@@ -143,5 +145,34 @@ class TestSequencePadOp8(TestSequencePadOp):
self
.
dtype
=
'float64'
class
TestSequencePadOpError
(
unittest
.
TestCase
):
def
test_error
(
self
):
def
test_x_variable
():
# the input x type must be Variable
x
=
np
.
random
.
random
((
2
,
4
)).
astype
(
"float32"
)
pad_value
=
fluid
.
layers
.
assign
(
input
=
np
.
array
(
[
0.0
],
dtype
=
np
.
float32
))
fluid
.
layers
.
sequence_pad
(
x
=
x
,
pad_value
=
pad_value
)
self
.
assertRaises
(
TypeError
,
test_x_variable
)
def
test_pad_value_variable
():
x1
=
fluid
.
layers
.
data
(
name
=
'x1'
,
shape
=
[
10
,
5
],
dtype
=
'float32'
,
lod_level
=
1
)
pad_value1
=
np
.
array
([
0.0
],
dtype
=
np
.
float32
)
fluid
.
layers
.
sequence_pad
(
x
=
x1
,
pad_value
=
pad_value1
)
self
.
assertRaises
(
TypeError
,
test_pad_value_variable
)
def
test_dtype
():
x2
=
fluid
.
layers
.
data
(
name
=
'x2'
,
shape
=
[
10
,
5
],
dtype
=
'int16'
,
lod_level
=
1
)
pad_value2
=
fluid
.
layers
.
assign
(
input
=
np
.
array
(
[
0.0
],
dtype
=
np
.
int32
))
fluid
.
layers
.
sequence_pad
(
x
=
x2
,
pad_value
=
pad_value2
)
self
.
assertRaises
(
TypeError
,
test_dtype
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/sequence/test_sequence_reshape.py
浏览文件 @
a164b10d
...
...
@@ -21,6 +21,8 @@ import sys
sys
.
path
.
append
(
"../"
)
from
op_test
import
OpTest
import
paddle.fluid
as
fluid
class
TestSequenceReshape
(
OpTest
):
def
init_data
(
self
):
...
...
@@ -83,5 +85,25 @@ class TestSequenceReshape_reduce_seq_len0_case1(TestSequenceReshape):
self
.
x
=
np
.
random
.
uniform
(
0.1
,
1
,
[
12
,
12
]).
astype
(
'float64'
)
class
TestSequenceReshapeOpError
(
unittest
.
TestCase
):
def
test_error
(
self
):
def
test_variable
():
x
=
np
.
random
.
random
((
2
,
4
)).
astype
(
"float32"
)
fluid
.
layers
.
sequence_reshape
(
x
=
x
,
new_dim
=
4
)
self
.
assertRaises
(
TypeError
,
test_variable
)
def
test_dtype
():
x1
=
fluid
.
layers
.
data
(
name
=
'x1'
,
shape
=
[
2
,
6
],
append_batch_size
=
False
,
dtype
=
'float16'
,
lod_level
=
1
)
fluid
.
layers
.
sequence_reshape
(
x
=
x1
,
new_dim
=
4
)
self
.
assertRaises
(
TypeError
,
test_dtype
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/sequence/test_sequence_reverse.py
浏览文件 @
a164b10d
...
...
@@ -79,5 +79,22 @@ class TestSequenceReverse3(TestSequenceReverseBase):
self
.
lod
=
[
0
,
2
,
10
,
0
]
class
TestSequenceReverseOpError
(
unittest
.
TestCase
):
def
test_error
(
self
):
def
test_variable
():
# the input type must be Variable
x_data
=
np
.
random
.
random
((
2
,
4
)).
astype
(
"float32"
)
fluid
.
layers
.
sequence_reverse
(
x
=
x_data
)
self
.
assertRaises
(
TypeError
,
test_variable
)
def
test_dtype
():
# dtype must be 'float32', 'float64', 'int8', 'int32', 'int64'
x2_data
=
fluid
.
layers
.
data
(
name
=
'x2'
,
shape
=
[
4
],
dtype
=
'float16'
)
fluid
.
layers
.
sequence_reverse
(
x
=
x2_data
)
self
.
assertRaises
(
TypeError
,
test_dtype
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/sequence/test_sequence_unpad_op.py
浏览文件 @
a164b10d
...
...
@@ -19,6 +19,8 @@ import sys
sys
.
path
.
append
(
"../"
)
from
op_test
import
OpTest
import
paddle.fluid
as
fluid
class
TestSequenceUnpadOp
(
OpTest
):
def
init
(
self
):
...
...
@@ -84,5 +86,36 @@ class TestSequenceUnpadOp4(TestSequenceUnpadOp):
self
.
dtype
=
"float64"
class
TestSequenceUnpadOpError
(
unittest
.
TestCase
):
def
test_error
(
self
):
def
test_x_variable
():
x
=
np
.
random
.
random
((
10
,
5
)).
astype
(
"float64"
)
len
=
fluid
.
data
(
name
=
'length2'
,
shape
=
[
10
],
dtype
=
'int64'
)
fluid
.
layers
.
sequence_pad
(
x
=
x
,
length
=
len
)
self
.
assertRaises
(
TypeError
,
test_x_variable
)
def
test_length_variable
():
x1
=
fluid
.
data
(
name
=
'x1'
,
shape
=
[
10
,
5
],
dtype
=
'float32'
)
len1
=
np
.
random
.
random
((
10
)).
astype
(
"int64"
)
fluid
.
layers
.
sequence_pad
(
x
=
x1
,
length
=
len1
)
self
.
assertRaises
(
TypeError
,
test_length_variable
)
def
test_x_dtype
():
x2
=
fluid
.
data
(
name
=
'x2'
,
shape
=
[
10
,
5
],
dtype
=
'float16'
)
len2
=
fluid
.
data
(
name
=
'length2'
,
shape
=
[
10
],
dtype
=
'int64'
)
fluid
.
layers
.
sequence_pad
(
x
=
x2
,
length
=
len2
)
self
.
assertRaises
(
TypeError
,
test_x_dtype
)
def
test_length_dtype
():
x3
=
fluid
.
data
(
name
=
'x3'
,
shape
=
[
10
,
5
],
dtype
=
'float64'
)
len3
=
fluid
.
data
(
name
=
'length3'
,
shape
=
[
10
],
dtype
=
'int32'
)
fluid
.
layers
.
sequence_pad
(
x
=
x3
,
length
=
len3
)
self
.
assertRaises
(
TypeError
,
test_length_dtype
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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