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de1b390b
编写于
3月 05, 2020
作者:
A
Aurelius84
提交者:
GitHub
3月 05, 2020
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Add unittest for dict in dygraph_to_static test=develop (#22854)
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python/paddle/fluid/tests/unittests/dygraph_to_static/test_dict.py
...ddle/fluid/tests/unittests/dygraph_to_static/test_dict.py
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python/paddle/fluid/tests/unittests/dygraph_to_static/test_dict.py
0 → 100644
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de1b390b
# Copyright (c) 2020 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
six
import
numpy
as
np
import
unittest
import
paddle.fluid
as
fluid
from
paddle.fluid.dygraph.jit
import
dygraph_to_static_graph
PLACE
=
fluid
.
CUDAPlace
(
0
)
if
fluid
.
is_compiled_with_cuda
()
else
fluid
.
CPUPlace
(
)
class
SubNetWithDict
(
fluid
.
dygraph
.
Layer
):
def
__init__
(
self
,
hidden_size
=
16
,
output_size
=
16
):
super
(
SubNetWithDict
,
self
).
__init__
()
init_weight
=
lambda
x
:
fluid
.
ParamAttr
(
initializer
=
fluid
.
initializer
.
Constant
(
x
))
self
.
q_fc
=
fluid
.
dygraph
.
Linear
(
input_dim
=
hidden_size
,
output_dim
=
output_size
,
bias_attr
=
False
,
param_attr
=
init_weight
(
0.6
))
self
.
k_fc
=
fluid
.
dygraph
.
Linear
(
input_dim
=
hidden_size
,
output_dim
=
output_size
,
bias_attr
=
False
,
param_attr
=
init_weight
(
0.5
))
self
.
v_fc
=
fluid
.
dygraph
.
Linear
(
input_dim
=
hidden_size
,
output_dim
=
output_size
,
bias_attr
=
False
,
param_attr
=
init_weight
(
0.2
))
@
dygraph_to_static_graph
def
forward
(
self
,
input
,
cache
=
None
):
input
=
fluid
.
dygraph
.
to_variable
(
input
)
q
=
self
.
q_fc
(
input
)
k
=
self
.
k_fc
(
input
)
v
=
self
.
v_fc
(
input
)
if
cache
is
not
None
:
cache_k
,
cache_v
=
cache
[
"k"
],
cache
[
"v"
]
k
=
0.1
*
cache_k
+
k
v
=
0.2
*
cache_v
+
v
cache
[
"k"
],
cache
[
"v"
]
=
k
,
v
weight
=
fluid
.
layers
.
matmul
(
x
=
q
,
y
=
k
,
transpose_y
=
True
)
weight
=
fluid
.
layers
.
softmax
(
weight
)
out
=
fluid
.
layers
.
matmul
(
weight
,
v
)
return
out
class
MainNetWithDict
(
fluid
.
dygraph
.
Layer
):
def
__init__
(
self
,
batch_size
=
64
,
hidden_size
=
16
,
output_size
=
16
):
super
(
MainNetWithDict
,
self
).
__init__
()
self
.
batch_size
=
batch_size
self
.
hidden_size
=
hidden_size
self
.
output_size
=
output_size
self
.
sub_net
=
SubNetWithDict
(
hidden_size
,
output_size
)
@
dygraph_to_static_graph
def
forward
(
self
,
input
,
max_len
=
4
):
input
=
fluid
.
dygraph
.
to_variable
(
input
)
cache
=
{
"k"
:
fluid
.
layers
.
fill_constant
(
shape
=
[
self
.
batch_size
,
self
.
output_size
],
dtype
=
'float32'
,
value
=
0
),
"v"
:
fluid
.
layers
.
fill_constant
(
shape
=
[
self
.
batch_size
,
self
.
output_size
],
dtype
=
'float32'
,
value
=
0
),
}
max_len
=
input
.
shape
[
0
]
if
input
.
shape
[
0
]
!=
max_len
else
max_len
out
=
input
for
i
in
range
(
max_len
):
out
=
self
.
sub_net
(
out
,
cache
)
cache
=
self
.
update_cache
(
cache
)
return
out
def
update_cache
(
self
,
cache
):
for
k
,
val
in
six
.
iteritems
(
cache
):
cache
[
k
]
=
fluid
.
layers
.
softmax
(
val
)
return
cache
class
TestNetWithDict
(
unittest
.
TestCase
):
"""
TestCase for the transformation from control flow `if/else`
dependent on tensor in Dygraph into Static `fluid.layers.cond`.
"""
def
setUp
(
self
):
self
.
x
=
np
.
random
.
random
([
10
,
16
]).
astype
(
'float32'
)
self
.
batch_size
=
self
.
x
.
shape
[
0
]
def
_run_static
(
self
):
main_program
=
fluid
.
Program
()
with
fluid
.
program_guard
(
main_program
):
net
=
MainNetWithDict
(
batch_size
=
self
.
batch_size
)
# Transform into static graph
out
=
net
(
self
.
x
)
exe
=
fluid
.
Executor
(
PLACE
)
exe
.
run
(
fluid
.
default_startup_program
())
ret
=
exe
.
run
(
main_program
,
fetch_list
=
out
)
return
ret
[
0
]
def
_run_dygraph
(
self
):
with
fluid
.
dygraph
.
guard
(
PLACE
):
net
=
MainNetWithDict
(
batch_size
=
self
.
batch_size
)
ret
=
net
(
self
.
x
)
return
ret
.
numpy
()
def
test_ast_to_func
(
self
):
self
.
assertTrue
((
self
.
_run_dygraph
()
==
self
.
_run_static
()).
all
())
if
__name__
==
'__main__'
:
unittest
.
main
()
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