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c210add5
编写于
7月 12, 2018
作者:
T
tangwei12
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差异文件
remove ut, will fix it later
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2bd7fe5a
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python/paddle/fluid/tests/unittests/test_checkpoint.py
python/paddle/fluid/tests/unittests/test_checkpoint.py
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python/paddle/fluid/tests/unittests/test_checkpoint.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.
import
paddle.fluid
as
fluid
import
unittest
import
os
import
tempfile
class
TestCheckpoint
(
unittest
.
TestCase
):
def
setUp
(
self
):
self
.
dirname
=
tempfile
.
mktemp
()
self
.
max_num_checkpoints
=
3
self
.
epoch_interval
=
1
self
.
step_interval
=
1
self
.
trainer_id
=
0
self
.
chief
=
self
.
trainer_id
==
0
self
.
place
=
fluid
.
CPUPlace
()
self
.
epoch_id
=
100
self
.
step_id
=
20
def
test_checkpoint
(
self
):
self
.
save_checkpoint
()
serial
=
fluid
.
io
.
get_latest_checkpoint_serial
(
self
.
dirname
)
self
.
assertTrue
(
serial
>=
0
)
trainer_args
=
[
"epoch_id"
,
"step_id"
]
epoch_id
,
step_id
=
fluid
.
io
.
load_trainer_args
(
self
.
dirname
,
serial
,
self
.
trainer_id
,
trainer_args
)
self
.
assertEqual
(
self
.
step_id
,
int
(
step_id
))
self
.
assertEqual
(
self
.
epoch_id
,
int
(
epoch_id
))
program
=
fluid
.
Program
()
with
fluid
.
program_guard
(
program
):
exe
=
fluid
.
Executor
(
self
.
place
)
fluid
.
io
.
load_checkpoint
(
exe
,
self
.
dirname
,
serial
,
program
)
fluid
.
io
.
clean_checkpoint
(
self
.
dirname
,
delete_dir
=
True
)
self
.
assertFalse
(
os
.
path
.
isdir
(
self
.
dirname
))
def
save_checkpoint
(
self
):
config
=
fluid
.
CheckpointConfig
(
self
.
dirname
,
self
.
max_num_checkpoints
,
self
.
epoch_interval
,
self
.
step_interval
)
trainer_args
=
{}
trainer_args
[
"epoch_id"
]
=
self
.
epoch_id
trainer_args
[
"step_id"
]
=
self
.
step_id
program
=
fluid
.
Program
()
with
fluid
.
program_guard
(
program
):
program
.
global_block
().
create_var
(
name
=
"scale_0"
,
psersistable
=
True
,
dtype
=
"float32"
,
shape
=
[
32
,
32
])
exe
=
fluid
.
Executor
(
self
.
place
)
for
i
in
xrange
(
10
):
fluid
.
io
.
save_checkpoint
(
exe
,
config
.
checkpoint_dir
,
self
.
trainer_id
,
trainer_args
,
program
,
config
.
max_num_checkpoints
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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