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f9065e15
编写于
5月 30, 2023
作者:
T
tianshuo78520a
提交者:
GitHub
5月 30, 2023
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差异文件
del sequence_enumerate_op (#54177)
* del sequence_enumerate_op * del analyzer_pyramid_dnn_tester * fix
上级
ecda253a
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9
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9 changed file
with
0 addition
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649 deletion
+0
-649
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc
+0
-96
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cu
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cu
+0
-100
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h
+0
-95
paddle/fluid/operators/sequence_ops/unity_build_rule.cmake
paddle/fluid/operators/sequence_ops/unity_build_rule.cmake
+0
-2
test/cpp/inference/api/CMakeLists.txt
test/cpp/inference/api/CMakeLists.txt
+0
-9
test/cpp/inference/api/analyzer_pyramid_dnn_tester.cc
test/cpp/inference/api/analyzer_pyramid_dnn_tester.cc
+0
-219
test/sequence/test_sequence_enumerate_op.py
test/sequence/test_sequence_enumerate_op.py
+0
-125
tools/parallel_UT_rule.py
tools/parallel_UT_rule.py
+0
-2
tools/static_mode_white_list.py
tools/static_mode_white_list.py
+0
-1
未找到文件。
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc
已删除
100644 → 0
浏览文件 @
ecda253a
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h"
namespace
paddle
{
namespace
operators
{
class
SequenceEnumerateOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"SequenceEnumerate"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
"Out"
),
"Output"
,
"Out"
,
"SequenceEnumerate"
);
const
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
const
auto
win_size
=
ctx
->
Attrs
().
Get
<
int
>
(
"win_size"
);
ctx
->
SetOutputDim
(
"Out"
,
{
x_dims
[
0
],
win_size
});
ctx
->
ShareLoD
(
"X"
,
"Out"
);
}
};
class
SequenceEnumerateOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"(2-D phi::DenseTensor with the 2nd dimension equal to 1) "
"Input phi::DenseTensor of SequenceEnumerate operator."
);
AddOutput
(
"Out"
,
"(2-D phi::DenseTensor with the 2nd dimension equal to win_size) "
"Output phi::DenseTensor of SequenceEnumerate operator."
);
AddAttr
<
int
>
(
"win_size"
,
"(int) The enumerate sequence window size."
)
.
AddCustomChecker
([](
const
int
&
win_size
)
{
PADDLE_ENFORCE_GE
(
win_size
,
2
,
platform
::
errors
::
InvalidArgument
(
"The window size should be not less than 2."
"Received window size is %d"
,
win_size
));
});
AddAttr
<
int
>
(
"pad_value"
,
"(int) The enumerate sequence padding value."
)
.
SetDefault
(
0
);
AddAttr
<
bool
>
(
framework
::
kAllKernelsMustComputeRuntimeShape
,
"Skip calling InferShape() function in the runtime."
)
.
SetDefault
(
true
);
AddComment
(
R"DOC(
Sequence Enumerate Operator.
Generate a new sequence for the input index sequence, which enumerates all the
sub-sequences with length `win_size` of the input.
The enumerated sequence has the same 1st dimension with variable `input`, and
the 2nd dimension is `win_size`, padded by `pad_value` if necessary in generation.
Examples:
Case 1:
Input:
X.lod = [[0, 3, 5]]
X.data = [[1], [2], [3], [4], [5]]
X.dims = [5, 1]
Attrs:
win_size = 2
pad_value = 0
Output:
Out.lod = [[0, 3, 5]]
Out.data = [[1, 2], [2, 3], [3, 0], [4, 5], [5, 0]]
Out.dims = [5, 2]
)DOC"
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_WITHOUT_GRADIENT
(
sequence_enumerate
,
ops
::
SequenceEnumerateOp
,
ops
::
SequenceEnumerateOpMaker
);
PD_REGISTER_STRUCT_KERNEL
(
sequence_enumerate
,
CPU
,
ALL_LAYOUT
,
ops
::
SequenceEnumerateKernel
,
int32_t
,
int64_t
)
{}
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cu
已删除
100644 → 0
浏览文件 @
ecda253a
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include <thrust/device_vector.h>
#include <thrust/host_vector.h>
#include "paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h"
#include "paddle/phi/backends/gpu/gpu_primitives.h"
namespace
paddle
{
namespace
operators
{
using
phi
::
PADDLE_CUDA_NUM_THREADS
;
template
<
typename
T
>
__global__
void
CalcOutPut
(
const
T
*
in_data
,
const
size_t
*
in_lod
,
const
size_t
lod_len
,
const
int64_t
win_size
,
const
int64_t
pad_value
,
T
*
out_data
)
{
int
index
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
if
(
index
<
in_lod
[
lod_len
-
1
])
{
int
end_idx
=
0
;
// Get LoD interval of index
for
(
int
i
=
1
;
i
<
lod_len
;
++
i
)
{
if
(
index
<
in_lod
[
i
])
{
end_idx
=
in_lod
[
i
];
break
;
}
}
for
(
size_t
i
=
0
;
i
<
win_size
;
++
i
)
{
int
word_pos
=
index
+
i
;
out_data
[
index
*
win_size
+
i
]
=
word_pos
<
end_idx
?
in_data
[
word_pos
]
:
pad_value
;
}
}
}
template
<
typename
T
,
typename
DeviceContext
>
class
SequenceEnumerateOpCUDAKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
in
=
context
.
Input
<
phi
::
DenseTensor
>
(
"X"
);
auto
*
out
=
context
.
Output
<
phi
::
DenseTensor
>
(
"Out"
);
int
win_size
=
context
.
Attr
<
int
>
(
"win_size"
);
int
pad_value
=
context
.
Attr
<
int
>
(
"pad_value"
);
auto
in_dims
=
in
->
dims
();
auto
in_lod
=
in
->
lod
();
PADDLE_ENFORCE_EQ
(
static_cast
<
uint64_t
>
(
in_dims
[
0
]),
in_lod
[
0
].
back
(),
platform
::
errors
::
InvalidArgument
(
"The actual input data's size mismatched with LoD information."
"Received input data size is %d (actual) vs %d (loD information)."
,
static_cast
<
uint64_t
>
(
in_dims
[
0
]),
in_lod
[
0
].
back
()));
/* Generate enumerate sequence set */
auto
stream
=
context
.
cuda_device_context
().
stream
();
auto
lod0
=
in_lod
[
0
];
auto
in_len
=
in
->
numel
();
auto
in_data
=
in
->
data
<
T
>
();
out
->
Resize
({
in_dims
[
0
],
win_size
});
auto
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
// Copy LoD to GPU
phi
::
MixVector
<
size_t
>
mixv_lod0
(
&
lod0
);
const
size_t
*
dev_in_lod_ptr
=
mixv_lod0
.
CUDAData
(
context
.
GetPlace
());
// Calc output tensor
CalcOutPut
<<<
(
in_len
-
1
)
/
PADDLE_CUDA_NUM_THREADS
+
1
,
PADDLE_CUDA_NUM_THREADS
,
0
,
stream
>>>
(
in_data
,
dev_in_lod_ptr
,
lod0
.
size
(),
win_size
,
pad_value
,
out_data
);
out
->
set_lod
(
in
->
lod
());
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
PD_REGISTER_STRUCT_KERNEL
(
sequence_enumerate
,
GPU
,
ALL_LAYOUT
,
ops
::
SequenceEnumerateOpCUDAKernel
,
int32_t
,
int64_t
)
{}
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h
已删除
100644 → 0
浏览文件 @
ecda253a
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
T
,
typename
DeviceContext
>
class
SequenceEnumerateKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
in
=
context
.
Input
<
phi
::
DenseTensor
>
(
"X"
);
auto
*
out
=
context
.
Output
<
phi
::
DenseTensor
>
(
"Out"
);
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
,
platform
::
errors
::
InvalidArgument
(
"Input(X) phi::DenseTensor of SequenceEnumerateOp does not contain "
"LoD information."
));
auto
in_dims
=
phi
::
vectorize
<
int
>
(
in
->
dims
());
auto
lod0
=
in
->
lod
()[
0
];
PADDLE_ENFORCE_EQ
(
static_cast
<
uint64_t
>
(
in_dims
[
0
]),
lod0
.
back
(),
platform
::
errors
::
InvalidArgument
(
"The actual input data's size mismatched with LoD information."
"Received input data size is %d (actual) vs %d (loD information)."
,
static_cast
<
uint64_t
>
(
in_dims
[
0
]),
lod0
.
back
()));
PADDLE_ENFORCE_EQ
(
in_dims
.
size
(),
2UL
,
platform
::
errors
::
InvalidArgument
(
"Input(X) of SequenceEnumerate operator's rank should be 2."
"Received %d instead."
,
in_dims
.
size
()));
PADDLE_ENFORCE_EQ
(
in_dims
[
1
],
1
,
platform
::
errors
::
InvalidArgument
(
"Input(X) of SequenceEnumerate operator's 2nd "
"dimension should be 1. Received %d instead."
,
in_dims
[
1
]));
// Generate enumerate sequence set
auto
in_data
=
in
->
data
<
T
>
();
out
->
Resize
({
in_dims
[
0
],
win_size
});
out
->
set_lod
(
in
->
lod
());
auto
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
for
(
size_t
i
=
0
;
i
<
lod0
.
size
()
-
1
;
++
i
)
{
if
(
lod0
[
i
]
==
lod0
[
i
+
1
])
continue
;
int
start
=
lod0
[
i
];
int
end
=
lod0
[
i
+
1
];
int
copy_size
=
win_size
<
end
-
start
+
1
?
win_size
:
end
-
start
+
1
;
int
mid
=
end
+
1
-
copy_size
;
int
pad_num
=
win_size
-
copy_size
;
copy_size
*=
sizeof
(
T
);
for
(
int
idx
=
start
;
idx
<
mid
;
++
idx
)
{
std
::
memcpy
(
out_data
,
in_data
+
idx
,
copy_size
);
out_data
+=
win_size
;
}
for
(
int
idx
=
mid
;
idx
<
end
;
++
idx
)
{
copy_size
-=
sizeof
(
T
);
pad_num
++
;
std
::
memcpy
(
out_data
,
in_data
+
idx
,
copy_size
);
T
*
pdata
=
out_data
+
copy_size
/
sizeof
(
T
);
for
(
int
i
=
0
;
i
<
pad_num
;
++
i
)
{
pdata
[
i
]
=
pad_value
;
}
out_data
+=
win_size
;
}
}
}
};
}
// namespace operators
}
// namespace paddle
paddle/fluid/operators/sequence_ops/unity_build_rule.cmake
浏览文件 @
f9065e15
...
...
@@ -8,7 +8,6 @@ register_unity_group(
cc
sequence_concat_op.cc
sequence_conv_op.cc
sequence_enumerate_op.cc
sequence_erase_op.cc
sequence_expand_op.cc
sequence_mask_op.cc
...
...
@@ -25,7 +24,6 @@ register_unity_group(
sequence_conv_op.cu.cc
)
register_unity_group
(
cu
sequence_enumerate_op.cu
sequence_erase_op.cu
sequence_expand_op.cu
sequence_pad_op.cu
...
...
test/cpp/inference/api/CMakeLists.txt
浏览文件 @
f9065e15
...
...
@@ -427,15 +427,6 @@ if(WITH_TESTING AND WITH_INFERENCE_API_TEST)
inference_analysis_api_test
(
test_analyzer_lac
${
LAC_INSTALL_DIR
}
analyzer_lac_tester.cc
)
# Pyramid DNN
set
(
PYRAMID_DNN_INSTALL_DIR
"
${
INFERENCE_DEMO_INSTALL_DIR
}
/pyramid_dnn"
)
download_model_and_data_without_verify
(
${
PYRAMID_DNN_INSTALL_DIR
}
"PyramidDNN_model.tar.gz"
"PyramidDNN_data.txt.tar.gz"
)
inference_analysis_api_test
(
test_analyzer_pyramid_dnn
${
PYRAMID_DNN_INSTALL_DIR
}
analyzer_pyramid_dnn_tester.cc
)
# Ernie
set
(
ERNIE_INSTALL_DIR
"
${
INFERENCE_DEMO_INSTALL_DIR
}
/Ernie"
)
download_model_and_data
(
...
...
test/cpp/inference/api/analyzer_pyramid_dnn_tester.cc
已删除
100644 → 0
浏览文件 @
ecda253a
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "test/cpp/inference/api/tester_helper.h"
namespace
paddle
{
namespace
inference
{
struct
DataRecord
{
std
::
vector
<
std
::
vector
<
int64_t
>>
query_basic
,
query_phrase
,
title_basic
,
title_phrase
;
std
::
vector
<
size_t
>
lod1
,
lod2
,
lod3
,
lod4
;
size_t
batch_iter
{
0
},
batch_size
{
1
},
num_samples
;
// total number of samples
DataRecord
()
=
default
;
explicit
DataRecord
(
const
std
::
string
&
path
,
int
batch_size
=
1
)
:
batch_size
(
batch_size
)
{
Load
(
path
);
}
DataRecord
NextBatch
()
{
DataRecord
data
;
size_t
batch_end
=
batch_iter
+
batch_size
;
// NOTE skip the final batch, if no enough data is provided.
if
(
batch_end
<=
query_basic
.
size
())
{
GetInputPerBatch
(
query_basic
,
&
data
.
query_basic
,
&
data
.
lod1
,
batch_iter
,
batch_end
);
GetInputPerBatch
(
query_phrase
,
&
data
.
query_phrase
,
&
data
.
lod2
,
batch_iter
,
batch_end
);
GetInputPerBatch
(
title_basic
,
&
data
.
title_basic
,
&
data
.
lod3
,
batch_iter
,
batch_end
);
GetInputPerBatch
(
title_phrase
,
&
data
.
title_phrase
,
&
data
.
lod4
,
batch_iter
,
batch_end
);
}
batch_iter
+=
batch_size
;
return
data
;
}
void
Load
(
const
std
::
string
&
path
)
{
std
::
ifstream
file
(
path
);
std
::
string
line
;
int
num_lines
=
0
;
while
(
std
::
getline
(
file
,
line
))
{
std
::
vector
<
std
::
string
>
data
;
split
(
line
,
';'
,
&
data
);
// load query data
std
::
vector
<
int64_t
>
query_basic_data
;
split_to_int64
(
data
[
1
],
' '
,
&
query_basic_data
);
std
::
vector
<
int64_t
>
query_phrase_data
;
split_to_int64
(
data
[
2
],
' '
,
&
query_phrase_data
);
// load title data
std
::
vector
<
int64_t
>
title_basic_data
;
split_to_int64
(
data
[
3
],
' '
,
&
title_basic_data
);
std
::
vector
<
int64_t
>
title_phrase_data
;
split_to_int64
(
data
[
4
],
' '
,
&
title_phrase_data
);
// filter the empty data
bool
flag
=
data
[
1
].
size
()
&&
data
[
2
].
size
()
&&
data
[
3
].
size
()
&&
data
[
4
].
size
();
if
(
flag
)
{
query_basic
.
push_back
(
std
::
move
(
query_basic_data
));
query_phrase
.
push_back
(
std
::
move
(
query_phrase_data
));
title_basic
.
push_back
(
std
::
move
(
title_basic_data
));
title_phrase
.
push_back
(
std
::
move
(
title_phrase_data
));
num_lines
++
;
}
}
num_samples
=
num_lines
;
}
};
void
PrepareInputs
(
std
::
vector
<
PaddleTensor
>
*
input_slots
,
DataRecord
*
data
,
int
batch_size
)
{
PaddleTensor
query_basic_tensor
,
query_phrase_tensor
,
title_basic_tensor
,
title_phrase_tensor
;
query_basic_tensor
.
name
=
"query_basic"
;
query_phrase_tensor
.
name
=
"query_phrase"
;
title_basic_tensor
.
name
=
"pos_title_basic"
;
title_phrase_tensor
.
name
=
"pos_title_phrase"
;
auto
one_batch
=
data
->
NextBatch
();
// assign data
TensorAssignData
<
int64_t
>
(
&
query_basic_tensor
,
one_batch
.
query_basic
,
one_batch
.
lod1
);
TensorAssignData
<
int64_t
>
(
&
query_phrase_tensor
,
one_batch
.
query_phrase
,
one_batch
.
lod2
);
TensorAssignData
<
int64_t
>
(
&
title_basic_tensor
,
one_batch
.
title_basic
,
one_batch
.
lod3
);
TensorAssignData
<
int64_t
>
(
&
title_phrase_tensor
,
one_batch
.
title_phrase
,
one_batch
.
lod4
);
// Set inputs.
input_slots
->
assign
({
query_basic_tensor
,
query_phrase_tensor
,
title_basic_tensor
,
title_phrase_tensor
});
for
(
auto
&
tensor
:
*
input_slots
)
{
tensor
.
dtype
=
PaddleDType
::
INT64
;
}
}
void
SetConfig
(
AnalysisConfig
*
cfg
)
{
cfg
->
SetModel
(
FLAGS_infer_model
);
cfg
->
DisableGpu
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SwitchIrOptim
();
cfg
->
SetCpuMathLibraryNumThreads
(
FLAGS_cpu_num_threads
);
if
(
FLAGS_zero_copy
)
{
cfg
->
SwitchUseFeedFetchOps
(
false
);
}
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
)
{
DataRecord
data
(
FLAGS_infer_data
,
FLAGS_batch_size
);
std
::
vector
<
PaddleTensor
>
input_slots
;
int
epoch
=
FLAGS_test_all_data
?
data
.
num_samples
/
FLAGS_batch_size
:
1
;
LOG
(
INFO
)
<<
"number of samples: "
<<
epoch
*
FLAGS_batch_size
;
for
(
int
bid
=
0
;
bid
<
epoch
;
++
bid
)
{
PrepareInputs
(
&
input_slots
,
&
data
,
FLAGS_batch_size
);
(
*
inputs
).
emplace_back
(
input_slots
);
}
}
// Easy for profiling independently.
TEST
(
Analyzer_Pyramid_DNN
,
profile
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
outputs
;
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
TestPrediction
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
,
&
outputs
,
FLAGS_num_threads
);
if
(
FLAGS_num_threads
==
1
&&
!
FLAGS_test_all_data
&&
!
FLAGS_zero_copy
)
{
PADDLE_ENFORCE_GT
(
outputs
.
size
(),
0
,
paddle
::
platform
::
errors
::
Fatal
(
"The size of output should be greater than 0."
));
auto
output
=
outputs
.
back
();
PADDLE_ENFORCE_EQ
(
output
.
size
(),
1UL
,
paddle
::
platform
::
errors
::
Fatal
(
"The size of output should be equal to 1."
));
size_t
size
=
GetSize
(
output
[
0
]);
PADDLE_ENFORCE_GT
(
size
,
0
,
paddle
::
platform
::
errors
::
Fatal
(
"The size of output should be greater than 0."
));
float
*
result
=
static_cast
<
float
*>
(
output
[
0
].
data
.
data
());
// output is probability, which is in (0, 1).
for
(
size_t
i
=
0
;
i
<
size
;
i
++
)
{
EXPECT_GT
(
result
[
i
],
0
);
EXPECT_LT
(
result
[
i
],
1
);
}
}
}
// Check the fuse status
TEST
(
Analyzer_Pyramid_DNN
,
fuse_statis
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
int
num_ops
;
auto
predictor
=
CreatePaddlePredictor
<
AnalysisConfig
>
(
cfg
);
auto
fuse_statis
=
GetFuseStatis
(
static_cast
<
AnalysisPredictor
*>
(
predictor
.
get
()),
&
num_ops
);
}
// Compare result of NativeConfig and AnalysisConfig
TEST
(
Analyzer_Pyramid_DNN
,
compare
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareNativeAndAnalysis
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
// Compare result of AnalysisConfig and AnalysisConfig + ZeroCopy
TEST
(
Analyzer_Pyramid_DNN
,
compare_zero_copy
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
AnalysisConfig
cfg1
;
SetConfig
(
&
cfg1
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
std
::
vector
<
std
::
string
>
outputs_name
;
outputs_name
.
emplace_back
(
"cos_sim_2.tmp_0"
);
CompareAnalysisAndZeroCopy
(
reinterpret_cast
<
PaddlePredictor
::
Config
*>
(
&
cfg
),
reinterpret_cast
<
PaddlePredictor
::
Config
*>
(
&
cfg1
),
input_slots_all
,
outputs_name
);
}
// Compare Deterministic result
TEST
(
Analyzer_Pyramid_DNN
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
}
// namespace inference
}
// namespace paddle
test/sequence/test_sequence_enumerate_op.py
已删除
100644 → 0
浏览文件 @
ecda253a
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import
sys
import
unittest
import
numpy
as
np
sys
.
path
.
append
(
"../../python/paddle/fluid/tests/unittests"
)
from
eager_op_test
import
OpTest
def
sequence_enumerate
(
input_seq
,
in_lod
,
win_size
,
pad_value
):
lod0
=
[
0
]
for
i
in
range
(
0
,
len
(
in_lod
[
0
])):
lod0
.
append
(
lod0
[
i
]
+
in_lod
[
0
][
i
])
out_seq
=
[]
for
i
in
range
(
0
,
len
(
lod0
)
-
1
):
for
idx
in
range
(
lod0
[
i
],
lod0
[
i
+
1
]):
single_seq
=
[]
for
word_idx
in
range
(
win_size
):
word_pos
=
idx
+
word_idx
dat
=
(
input_seq
[
word_pos
]
if
word_pos
<
lod0
[
i
+
1
]
else
pad_value
)
single_seq
.
append
(
dat
)
out_seq
.
append
(
single_seq
)
return
out_seq
class
TestSequenceEnumerateOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"sequence_enumerate"
self
.
init_test_case
()
self
.
inputs
=
{
'X'
:
(
self
.
in_seq
,
self
.
lod
)}
self
.
attrs
=
{
'win_size'
:
self
.
win_size
,
'pad_value'
:
self
.
pad_value
}
self
.
outputs
=
{
'Out'
:
(
self
.
out_seq
,
self
.
lod
)}
def
test_check_output
(
self
):
self
.
check_output
()
def
init_test_case
(
self
):
self
.
in_seq
=
np
.
random
.
randint
(
0
,
10
,
(
30
,
1
)).
astype
(
"int32"
)
self
.
lod
=
[[
9
,
4
,
11
,
6
]]
self
.
win_size
=
2
self
.
pad_value
=
0
out_seq
=
sequence_enumerate
(
self
.
in_seq
,
self
.
lod
,
self
.
win_size
,
self
.
pad_value
)
self
.
out_seq
=
np
.
array
(
out_seq
).
astype
(
"int32"
)
class
TesSequenceEnumerateOpInt64
(
TestSequenceEnumerateOp
):
def
init_test_case
(
self
):
self
.
in_seq
=
np
.
random
.
randint
(
0
,
10
,
(
30
,
1
)).
astype
(
"int64"
)
self
.
lod
=
[[
9
,
4
,
11
,
6
]]
self
.
win_size
=
2
self
.
pad_value
=
0
out_seq
=
sequence_enumerate
(
self
.
in_seq
,
self
.
lod
,
self
.
win_size
,
self
.
pad_value
)
self
.
out_seq
=
np
.
array
(
out_seq
).
astype
(
"int64"
)
class
TestSequenceEnumerateOpLargeWinSize
(
TestSequenceEnumerateOp
):
def
init_test_case
(
self
):
self
.
in_seq
=
np
.
random
.
randint
(
0
,
10
,
(
30
,
1
)).
astype
(
"int32"
)
self
.
lod
=
[[
9
,
4
,
11
,
6
]]
self
.
win_size
=
5
self
.
pad_value
=
0
out_seq
=
sequence_enumerate
(
self
.
in_seq
,
self
.
lod
,
self
.
win_size
,
self
.
pad_value
)
self
.
out_seq
=
np
.
array
(
out_seq
).
astype
(
"int32"
)
class
TestSequenceEnumerateOpMaxWinSize
(
TestSequenceEnumerateOp
):
def
init_test_case
(
self
):
self
.
in_seq
=
np
.
random
.
randint
(
0
,
10
,
(
30
,
1
)).
astype
(
"int32"
)
self
.
lod
=
[[
9
,
4
,
11
,
6
]]
self
.
win_size
=
30
self
.
pad_value
=
0
out_seq
=
sequence_enumerate
(
self
.
in_seq
,
self
.
lod
,
self
.
win_size
,
self
.
pad_value
)
self
.
out_seq
=
np
.
array
(
out_seq
).
astype
(
"int32"
)
class
TestSequenceEnumerateOpLargePadValue
(
TestSequenceEnumerateOp
):
def
init_test_case
(
self
):
self
.
in_seq
=
np
.
random
.
randint
(
0
,
10
,
(
30
,
1
)).
astype
(
"int32"
)
self
.
lod
=
[[
9
,
4
,
11
,
6
]]
self
.
win_size
=
5
self
.
pad_value
=
5
out_seq
=
sequence_enumerate
(
self
.
in_seq
,
self
.
lod
,
self
.
win_size
,
self
.
pad_value
)
self
.
out_seq
=
np
.
array
(
out_seq
).
astype
(
"int32"
)
class
TestSequenceEnumerateOpLargePadValueSeqLen0
(
TestSequenceEnumerateOp
):
def
init_test_case
(
self
):
self
.
in_seq
=
np
.
random
.
randint
(
0
,
10
,
(
30
,
1
)).
astype
(
"int32"
)
self
.
lod
=
[[
0
,
14
,
0
,
16
,
0
]]
self
.
win_size
=
5
self
.
pad_value
=
5
out_seq
=
sequence_enumerate
(
self
.
in_seq
,
self
.
lod
,
self
.
win_size
,
self
.
pad_value
)
self
.
out_seq
=
np
.
array
(
out_seq
).
astype
(
"int32"
)
if
__name__
==
"__main__"
:
unittest
.
main
()
tools/parallel_UT_rule.py
浏览文件 @
f9065e15
...
...
@@ -1293,7 +1293,6 @@ FOURTH_HIGH_PARALLEL_JOB_NEW = [
'test_adaptive_avg_pool3d'
,
'test_paddle_save_load_binary'
,
'test_fused_fc_elementwise_layernorm_op'
,
'test_sequence_enumerate_op'
,
'test_lgamma_op'
,
'test_modified_huber_loss_op'
,
'trt_quant_int8_test'
,
...
...
@@ -2722,7 +2721,6 @@ TWO_PARALLEL_JOB = [
'test_conv_shift_op'
,
'test_sequence_expand_as'
,
'test_cos_sim_op'
,
'test_sequence_enumerate_op'
,
'test_sequence_concat'
,
'test_data_norm_op'
,
'test_decoupled_py_reader_data_check'
,
...
...
tools/static_mode_white_list.py
浏览文件 @
f9065e15
...
...
@@ -539,7 +539,6 @@ STATIC_MODE_TESTING_LIST = [
'test_layers'
,
'test_sequence_concat'
,
'test_sequence_conv'
,
'test_sequence_enumerate_op'
,
'test_sequence_erase_op'
,
'test_sequence_expand'
,
'test_sequence_expand_as'
,
...
...
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