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a6aa782e
编写于
11月 30, 2018
作者:
P
phlrain
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python/paddle/fluid/tests/unittests/test_lstm_cudnn_op.py
python/paddle/fluid/tests/unittests/test_lstm_cudnn_op.py
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python/paddle/fluid/tests/unittests/test_lstm_cudnn_op.py
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# 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.
from
__future__
import
print_function
import
unittest
import
numpy
as
np
import
paddle.fluid.core
as
core
from
op_test
import
OpTest
def
lstm_naive
(
input
,
w
,
):
seq_len
,
batch_size
,
hidden_size
=
input
.
shape
offset
=
0
wi
=
w
[
offset
:
offset
+
hidden_size
*
hidden_size
].
reshape
(
(
hidden_size
,
hidden_size
)).
transpose
()
offset
+=
hidden_size
*
hidden_size
wf
=
w
[
offset
:
offset
+
hidden_size
*
hidden_size
].
reshape
(
(
hidden_size
,
hidden_size
)).
transpose
()
offset
+=
hidden_size
*
hidden_size
wc
=
w
[
offset
:
offset
+
hidden_size
*
hidden_size
].
reshape
(
(
hidden_size
,
hidden_size
)).
transpose
()
offset
+=
hidden_size
*
hidden_size
wo
=
w
[
offset
:
offset
+
hidden_size
*
hidden_size
].
reshape
(
(
hidden_size
,
hidden_size
)).
transpose
()
offset
+=
hidden_size
*
hidden_size
ri
=
w
[
offset
:
offset
+
hidden_size
*
hidden_size
].
reshape
(
(
hidden_size
,
hidden_size
)).
transpose
()
offset
+=
hidden_size
*
hidden_size
rf
=
w
[
offset
:
offset
+
hidden_size
*
hidden_size
].
reshape
(
(
hidden_size
,
hidden_size
)).
transpose
()
offset
+=
hidden_size
*
hidden_size
rc
=
w
[
offset
:
offset
+
hidden_size
*
hidden_size
].
reshape
(
(
hidden_size
,
hidden_size
)).
transpose
()
offset
+=
hidden_size
*
hidden_size
ro
=
w
[
offset
:
offset
+
hidden_size
*
hidden_size
].
reshape
(
(
hidden_size
,
hidden_size
)).
transpose
()
offset
+=
hidden_size
*
hidden_size
bi_1
=
w
[
offset
:
offset
+
hidden_size
]
offset
+=
hidden_size
bf_1
=
w
[
offset
:
offset
+
hidden_size
]
offset
+=
hidden_size
bc_1
=
w
[
offset
:
offset
+
hidden_size
]
offset
+=
hidden_size
bo_1
=
w
[
offset
:
offset
+
hidden_size
]
offset
+=
hidden_size
bi_2
=
w
[
offset
:
offset
+
hidden_size
]
offset
+=
hidden_size
bf_2
=
w
[
offset
:
offset
+
hidden_size
]
offset
+=
hidden_size
bc_2
=
w
[
offset
:
offset
+
hidden_size
]
offset
+=
hidden_size
bo_2
=
w
[
offset
:
offset
+
hidden_size
]
def
sigmoid
(
x
):
return
1.0
/
(
1.0
+
np
.
exp
(
-
x
))
def
tanh
(
x
):
return
(
np
.
exp
(
x
)
-
np
.
exp
(
-
x
))
/
(
np
.
exp
(
x
)
+
np
.
exp
(
-
x
))
output
=
[]
pre_h
=
np
.
zeros
((
batch_size
,
hidden_size
),
dtype
=
input
.
dtype
)
pre_c
=
np
.
zeros
((
batch_size
,
hidden_size
),
dtype
=
input
.
dtype
)
for
i
in
range
(
seq_len
):
emb_1
=
input
[
i
]
input_gate
=
sigmoid
(
np
.
matmul
(
emb_1
,
wi
)
+
np
.
matmul
(
pre_h
,
ri
)
+
bi_1
+
bi_2
)
forget_gate
=
sigmoid
(
np
.
matmul
(
emb_1
,
wf
)
+
np
.
matmul
(
pre_h
,
rf
)
+
bf_1
+
bf_2
)
output_gate
=
sigmoid
(
np
.
matmul
(
emb_1
,
wo
)
+
np
.
matmul
(
pre_h
,
ro
)
+
bo_1
+
bo_2
)
c_t_temp
=
tanh
(
np
.
matmul
(
emb_1
,
wc
)
+
np
.
matmul
(
pre_h
,
rc
)
+
bc_1
+
bc_2
)
new_c
=
input_gate
*
c_t_temp
+
forget_gate
*
pre_c
new_h
=
output_gate
*
tanh
(
new_c
)
pre_h
=
new_h
pre_c
=
new_c
output
.
append
(
new_h
)
output
=
np
.
concatenate
(
output
,
-
1
)
output
=
output
.
reshape
((
batch_size
,
-
1
,
hidden_size
))
output
=
output
.
transpose
((
1
,
0
,
2
))
return
output
class
TestCUDNNLstmOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"cudnn_lstm"
self
.
dtype
=
np
.
float32
num_steps
=
50
batch_size
=
20
hidden_size
=
200
input_weight_size
=
(
hidden_size
*
hidden_size
)
*
4
hidden_weight_size
=
(
hidden_size
*
hidden_size
)
*
4
weight_size
=
input_weight_size
+
hidden_weight_size
weight_size
+=
hidden_size
*
8
input
=
np
.
random
.
random
(
(
num_steps
,
batch_size
,
hidden_size
)).
astype
(
self
.
dtype
)
flat_w
=
np
.
random
.
random
((
weight_size
)).
astype
(
self
.
dtype
)
output
=
lstm_naive
(
input
,
flat_w
)
init_h
=
np
.
zeros
((
batch_size
,
hidden_size
),
dtype
=
np
.
float32
)
init_c
=
np
.
zeros
((
batch_size
,
hidden_size
),
dtype
=
np
.
float32
)
self
.
inputs
=
{
'Input'
:
OpTest
.
np_dtype_to_fluid_dtype
(
input
),
'W'
:
OpTest
.
np_dtype_to_fluid_dtype
(
flat_w
),
'InitH'
:
OpTest
.
np_dtype_to_fluid_dtype
(
init_h
),
'InitC'
:
OpTest
.
np_dtype_to_fluid_dtype
(
init_c
),
}
self
.
attrs
=
{
'max_len'
:
num_steps
,
'dropout_prob'
:
0.0
,
'is_bidirec'
:
False
,
'input_size'
:
hidden_size
,
'hidden_size'
:
hidden_size
,
'num_layers'
:
1
,
}
self
.
outputs
=
{
'Out'
:
output
}
def
test_grad_with_place
(
self
):
place
=
core
.
CUDAPlace
(
0
)
self
.
check_grad_with_place
(
place
,
atol
=
1e-5
)
def
test_output_with_place
(
self
):
place
=
core
.
CUDAPlace
(
0
)
self
.
check_output_with_place
(
place
,
atol
=
1e-5
,
no_check_set
=
[
'last_h'
,
'last_c'
])
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