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c9877bee
编写于
9月 17, 2020
作者:
myq406450149
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
enhance array_to_lod_tensor_op lod_tensor_to_array_op errors information. test=develop
上级
435ab2aa
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
62 addition
and
33 deletion
+62
-33
paddle/fluid/operators/array_to_lod_tensor_op.cc
paddle/fluid/operators/array_to_lod_tensor_op.cc
+42
-20
paddle/fluid/operators/lod_tensor_to_array_op.cc
paddle/fluid/operators/lod_tensor_to_array_op.cc
+20
-13
未找到文件。
paddle/fluid/operators/array_to_lod_tensor_op.cc
浏览文件 @
c9877bee
...
@@ -48,7 +48,8 @@ struct ArrayToLoDFunctor : public boost::static_visitor<void> {
...
@@ -48,7 +48,8 @@ struct ArrayToLoDFunctor : public boost::static_visitor<void> {
#ifdef PADDLE_WITH_CUDA
#ifdef PADDLE_WITH_CUDA
Apply
(
static_cast
<
platform
::
CUDADeviceContext
*>
(
pool
.
Get
(
place
)));
Apply
(
static_cast
<
platform
::
CUDADeviceContext
*>
(
pool
.
Get
(
place
)));
#else
#else
PADDLE_THROW
(
"Fluid is not compiled with CUDA"
);
PADDLE_THROW
(
platform
::
errors
::
Unavailable
(
"Fluid is not compiled with CUDA"
));
#endif
#endif
}
}
}
}
...
@@ -88,7 +89,9 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
...
@@ -88,7 +89,9 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
// Check dims, place and data type of input's elements and infer output's
// Check dims, place and data type of input's elements and infer output's
// dim
// dim
PADDLE_ENFORCE
(
!
x
.
empty
(),
"There's no element in the input array."
);
PADDLE_ENFORCE_EQ
(
x
.
empty
(),
false
,
platform
::
errors
::
PreconditionNotMet
(
"There's no element in the input array."
));
int
rank
=
x
[
0
].
dims
().
size
();
int
rank
=
x
[
0
].
dims
().
size
();
platform
::
Place
place
=
x
[
0
].
place
();
platform
::
Place
place
=
x
[
0
].
place
();
auto
data_type
=
x
[
0
].
type
();
auto
data_type
=
x
[
0
].
type
();
...
@@ -99,18 +102,24 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
...
@@ -99,18 +102,24 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
for
(
size_t
i
=
1
;
i
<
x
.
size
();
++
i
)
{
for
(
size_t
i
=
1
;
i
<
x
.
size
();
++
i
)
{
auto
ins_i_dims
=
rank
>
1
?
framework
::
slice_ddim
(
x
[
i
].
dims
(),
1
,
rank
)
auto
ins_i_dims
=
rank
>
1
?
framework
::
slice_ddim
(
x
[
i
].
dims
(),
1
,
rank
)
:
framework
::
make_ddim
({
0
});
:
framework
::
make_ddim
({
0
});
PADDLE_ENFORCE_EQ
(
ins_i_dims
,
ins_dims
,
PADDLE_ENFORCE_EQ
(
"The dimension of the %zu'th element in LoDTensorArray "
ins_i_dims
,
ins_dims
,
"differs from previous ones."
,
platform
::
errors
::
InvalidArgument
(
i
);
"The dimension of the %zu'th element in LoDTensorArray "
PADDLE_ENFORCE
(
x
[
i
].
place
()
==
place
,
"differs from previous ones."
,
"The place class of the %zu'th element in LoDTensorArray "
i
));
"differs from previous ones."
,
PADDLE_ENFORCE_EQ
(
i
);
x
[
i
].
place
(),
place
,
PADDLE_ENFORCE
(
x
[
i
].
type
()
==
data_type
,
platform
::
errors
::
InvalidArgument
(
"The date type of the %zu'th element in LoDTensorArray "
"The place class of the %zu'th element in LoDTensorArray "
"differs from previous ones."
,
"differs from previous ones."
,
i
);
i
));
PADDLE_ENFORCE_EQ
(
x
[
i
].
type
(),
data_type
,
platform
::
errors
::
InvalidArgument
(
"The date type of the %zu'th element in LoDTensorArray "
"differs from previous ones."
,
i
));
batch_size
+=
x
[
i
].
dims
()[
0
];
batch_size
+=
x
[
i
].
dims
()[
0
];
}
}
auto
ins_dim_vec
=
framework
::
vectorize
(
ins_dims
);
auto
ins_dim_vec
=
framework
::
vectorize
(
ins_dims
);
...
@@ -138,7 +147,13 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
...
@@ -138,7 +147,13 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
ArrayToLoDFunctor
functor
;
ArrayToLoDFunctor
functor
;
for
(
size_t
idx
:
table_item_idx
)
{
for
(
size_t
idx
:
table_item_idx
)
{
cur_level_lod
.
push_back
(
cur_level_lod
.
back
()
+
table_items
[
idx
].
length
);
cur_level_lod
.
push_back
(
cur_level_lod
.
back
()
+
table_items
[
idx
].
length
);
PADDLE_ENFORCE_LE
(
table_items
[
idx
].
length
,
x
.
size
());
PADDLE_ENFORCE_LE
(
table_items
[
idx
].
length
,
x
.
size
(),
platform
::
errors
::
InvalidArgument
(
"The RankTable items length should less than or "
"equal Input(X) size,"
"but receive TankTable items length is %d , longer "
"than Input(X) size %d."
,
table_items
[
idx
].
length
,
x
.
size
()));
for
(
size_t
x_idx
=
0
;
x_idx
<
table_items
[
idx
].
length
;
++
x_idx
)
{
for
(
size_t
x_idx
=
0
;
x_idx
<
table_items
[
idx
].
length
;
++
x_idx
)
{
auto
lod_and_offset
=
framework
::
GetSubLoDAndAbsoluteOffset
(
auto
lod_and_offset
=
framework
::
GetSubLoDAndAbsoluteOffset
(
x
[
x_idx
].
lod
(),
idx
,
idx
+
1
,
0
);
x
[
x_idx
].
lod
(),
idx
,
idx
+
1
,
0
);
...
@@ -151,7 +166,12 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
...
@@ -151,7 +166,12 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
VLOG
(
10
)
<<
"idx="
<<
idx
<<
" x_idx="
<<
x_idx
<<
" ["
VLOG
(
10
)
<<
"idx="
<<
idx
<<
" x_idx="
<<
x_idx
<<
" ["
<<
", "
<<
end_offset
<<
"]"
;
<<
", "
<<
end_offset
<<
"]"
;
// Copy data
// Copy data
PADDLE_ENFORCE_GE
(
end_offset
,
start_offset
);
PADDLE_ENFORCE_GE
(
end_offset
,
start_offset
,
platform
::
errors
::
InvalidArgument
(
"The lod data start offset should smaller or equal end offset,"
"but the start offset is %d, larger than end offset %d."
,
start_offset
,
end_offset
));
size_t
len
=
end_offset
-
start_offset
;
size_t
len
=
end_offset
-
start_offset
;
if
(
len
==
0
)
{
if
(
len
==
0
)
{
continue
;
continue
;
...
@@ -188,10 +208,12 @@ class ArrayToLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
...
@@ -188,10 +208,12 @@ class ArrayToLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
class
ArrayToLoDTensorInferShape
:
public
framework
::
InferShapeBase
{
class
ArrayToLoDTensorInferShape
:
public
framework
::
InferShapeBase
{
public:
public:
void
operator
()(
framework
::
InferShapeContext
*
context
)
const
override
{
void
operator
()(
framework
::
InferShapeContext
*
context
)
const
override
{
PADDLE_ENFORCE
(
context
->
HasInput
(
"X"
),
PADDLE_ENFORCE_EQ
(
"ArrayToLoDTensorOp must have input X."
);
context
->
HasInput
(
"X"
),
true
,
PADDLE_ENFORCE
(
context
->
HasInput
(
"RankTable"
),
platform
::
errors
::
NotFound
(
"Input(X) of BmmOp should not be null"
));
"ArrayToLoDTensorOp must have input RankTable."
);
PADDLE_ENFORCE_EQ
(
context
->
HasInput
(
"RankTable"
,
true
),
platform
::
errors
::
NotFound
(
"Input(RankTable) of BmmOp should not be null"
));
// For compile-time, the first dim of input X and output Out should be -1.
// For compile-time, the first dim of input X and output Out should be -1.
// For runtime, the first dim of output Out should be the sum of all
// For runtime, the first dim of output Out should be the sum of all
// elements's first dim in input X. The output's dims will be re-computed in
// elements's first dim in input X. The output's dims will be re-computed in
...
...
paddle/fluid/operators/lod_tensor_to_array_op.cc
浏览文件 @
c9877bee
...
@@ -61,7 +61,8 @@ struct LoDTensorToArrayFunctor : public boost::static_visitor<void> {
...
@@ -61,7 +61,8 @@ struct LoDTensorToArrayFunctor : public boost::static_visitor<void> {
#ifdef PADDLE_WITH_CUDA
#ifdef PADDLE_WITH_CUDA
Apply
(
static_cast
<
platform
::
CUDADeviceContext
*>
(
dev_ctx
));
Apply
(
static_cast
<
platform
::
CUDADeviceContext
*>
(
dev_ctx
));
#else
#else
PADDLE_THROW
(
"Not compiled with cuda"
);
PADDLE_THROW
(
platform
::
errors
::
Unavailable
(
"Fluid is not compiled with CUDA"
));
#endif
#endif
}
}
}
}
...
@@ -107,10 +108,11 @@ class LoDTensorToArrayOp : public framework::OperatorBase {
...
@@ -107,10 +108,11 @@ class LoDTensorToArrayOp : public framework::OperatorBase {
auto
max_seq_len
=
items
[
0
].
length
;
auto
max_seq_len
=
items
[
0
].
length
;
auto
rank_level
=
rank_table
.
level
();
auto
rank_level
=
rank_table
.
level
();
PADDLE_ENFORCE_LT
(
PADDLE_ENFORCE_LT
(
rank_level
,
x
.
lod
().
size
(),
rank_level
,
x
.
lod
().
size
(),
platform
::
errors
::
InvalidArgument
(
"Input should be a LoDTensor, and its lod_level should be at least %d"
,
`
"Input should be a LoDTensor, and its lod_level should be at "
rank_level
+
1
);
"least %d"
,
rank_level
+
1
));
out
.
resize
(
max_seq_len
);
out
.
resize
(
max_seq_len
);
std
::
vector
<
std
::
vector
<
CopyRange
>>
copy_ranges
(
max_seq_len
);
std
::
vector
<
std
::
vector
<
CopyRange
>>
copy_ranges
(
max_seq_len
);
...
@@ -190,14 +192,19 @@ NOTE: this operator is an internal component of DynamicRNN, and cannot be called
...
@@ -190,14 +192,19 @@ NOTE: this operator is an internal component of DynamicRNN, and cannot be called
class
LoDTensorToArrayInferShape
:
public
framework
::
InferShapeBase
{
class
LoDTensorToArrayInferShape
:
public
framework
::
InferShapeBase
{
public:
public:
void
operator
()(
framework
::
InferShapeContext
*
context
)
const
override
{
void
operator
()(
framework
::
InferShapeContext
*
context
)
const
override
{
PADDLE_ENFORCE
(
context
->
HasInput
(
"X"
),
PADDLE_ENFORCE_EQ
(
"Input(X) of LoDTensorToArrayOp should not be null."
);
context
->
HasInput
(
"X"
),
true
,
PADDLE_ENFORCE
(
platform
::
errors
::
NotFound
(
context
->
HasInput
(
"RankTable"
),
"Input(X) of LoDTensorToArrayOp should not be null."
));
"Input(RankTable) of LoDTensorToArrayOp should not be null."
);
PADDLE_ENFORCE_EQ
(
context
->
HasInput
(
"RankTable"
),
true
,
PADDLE_ENFORCE
(
context
->
HasOutput
(
"Out"
),
platform
::
errors
::
NotFound
(
"Output(Out) of LoDTensorToArrayOp should not be null."
);
"Input(RankTable) of LoDTensorToArrayOp should not be null."
));
PADDLE_ENFORCE_EQ
(
context
->
HasOutput
(
"Out"
),
true
,
platform
::
errors
::
NotFound
(
"Output(Out) of LoDTensorToArrayOp should not be null."
));
auto
x_dim
=
context
->
GetInputDim
(
"X"
);
auto
x_dim
=
context
->
GetInputDim
(
"X"
);
// For compile-time, the first dim of input X and output Out should be -1.
// For compile-time, the first dim of input X and output Out should be -1.
...
...
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