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10af966a
编写于
4月 07, 2021
作者:
C
CtfGo
提交者:
GitHub
4月 07, 2021
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差异文件
update the TraceLayer.save_inference_model method with add file suffix automatically (#31989)
As the title
上级
f5186c3c
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
88 addition
and
40 deletion
+88
-40
python/paddle/fluid/dygraph/jit.py
python/paddle/fluid/dygraph/jit.py
+49
-29
python/paddle/fluid/tests/unittests/test_imperative_trace_non_persistable_inputs.py
...unittests/test_imperative_trace_non_persistable_inputs.py
+6
-4
python/paddle/fluid/tests/unittests/test_traced_layer_err_msg.py
...paddle/fluid/tests/unittests/test_traced_layer_err_msg.py
+33
-7
未找到文件。
python/paddle/fluid/dygraph/jit.py
浏览文件 @
10af966a
...
...
@@ -509,33 +509,33 @@ def save(layer, path, input_spec=None, **configs):
Saves input Layer as ``paddle.jit.TranslatedLayer``
format model, which can be used for inference or fine-tuning after loading.
It will save the translated program and all related persistable
It will save the translated program and all related persistable
variables of input Layer to given ``path`` .
``path`` is the prefix of saved objects, and the saved translated program file
``path`` is the prefix of saved objects, and the saved translated program file
suffix is ``.pdmodel`` , the saved persistable variables file suffix is ``.pdiparams`` ,
and here also saved some additional variable description information to a file,
and here also saved some additional variable description information to a file,
its suffix is ``.pdiparams.info``, these additional information is used in fine-tuning.
The saved model can be loaded by follow APIs:
- ``paddle.jit.load``
- ``paddle.static.load_inference_model``
- ``paddle.jit.load``
- ``paddle.static.load_inference_model``
- Other C++ inference APIs
Args:
layer (Layer): The Layer to be saved.
path (str): The path prefix to save model. The format is ``dirname/file_prefix`` or ``file_prefix``.
input_spec (list[InputSpec|Tensor], optional): Describes the input of the saved model's forward
method, which can be described by InputSpec or example Tensor. If None, all input variables of
input_spec (list[InputSpec|Tensor], optional): Describes the input of the saved model's forward
method, which can be described by InputSpec or example Tensor. If None, all input variables of
the original Layer's forward method would be the inputs of the saved model. Default None.
**configs (dict, optional): Other save configuration options for compatibility. We do not
recommend using these configurations, they may be removed in the future. If not necessary,
**configs (dict, optional): Other save configuration options for compatibility. We do not
recommend using these configurations, they may be removed in the future. If not necessary,
DO NOT use them. Default None.
The following options are currently supported:
(1) output_spec (list[Tensor]): Selects the output targets of the saved model.
By default, all return variables of original Layer's forward method are kept as the
output of the saved model. If the provided ``output_spec`` list is not all output variables,
the saved model will be pruned according to the given ``output_spec`` list.
By default, all return variables of original Layer's forward method are kept as the
output of the saved model. If the provided ``output_spec`` list is not all output variables,
the saved model will be pruned according to the given ``output_spec`` list.
Returns:
None
...
...
@@ -793,8 +793,8 @@ def load(path, **configs):
"""
:api_attr: imperative
Load model saved by ``paddle.jit.save`` or ``paddle.static.save_inference_model`` or
paddle 1.x API ``paddle.fluid.io.save_inference_model`` as ``paddle.jit.TranslatedLayer``,
Load model saved by ``paddle.jit.save`` or ``paddle.static.save_inference_model`` or
paddle 1.x API ``paddle.fluid.io.save_inference_model`` as ``paddle.jit.TranslatedLayer``,
then performing inference or fine-tune training.
.. note::
...
...
@@ -807,14 +807,14 @@ def load(path, **configs):
Args:
path (str): The path prefix to load model. The format is ``dirname/file_prefix`` or ``file_prefix`` .
**configs (dict, optional): Other load configuration options for compatibility. We do not
recommend using these configurations, they may be removed in the future. If not necessary,
**configs (dict, optional): Other load configuration options for compatibility. We do not
recommend using these configurations, they may be removed in the future. If not necessary,
DO NOT use them. Default None.
The following options are currently supported:
(1) model_filename (str): The inference model file name of the paddle 1.x
``save_inference_model`` save format. Default file name is :code:`__model__` .
(2) params_filename (str): The persistable variables file name of the paddle 1.x
``save_inference_model`` save format. No default file name, save variables separately
(1) model_filename (str): The inference model file name of the paddle 1.x
``save_inference_model`` save format. Default file name is :code:`__model__` .
(2) params_filename (str): The persistable variables file name of the paddle 1.x
``save_inference_model`` save format. No default file name, save variables separately
by default.
...
...
@@ -960,7 +960,7 @@ def load(path, **configs):
loader = paddle.io.DataLoader(dataset,
feed_list=[image, label],
places=place,
batch_size=BATCH_SIZE,
batch_size=BATCH_SIZE,
shuffle=True,
drop_last=True,
num_workers=2)
...
...
@@ -969,7 +969,7 @@ def load(path, **configs):
for data in loader():
exe.run(
static.default_main_program(),
feed=data,
feed=data,
fetch_list=[avg_loss])
model_path = "fc.example.model"
...
...
@@ -1052,7 +1052,7 @@ def _trace(layer,
class
TracedLayer
(
object
):
"""
:api_attr: imperative
TracedLayer is used to convert a forward dygraph model to a static
graph model. This is mainly used to save the dygraph model for online
inference using C++. Besides, users can also do inference in Python
...
...
@@ -1132,7 +1132,7 @@ class TracedLayer(object):
def forward(self, input):
return self._fc(input)
layer = ExampleLayer()
in_var = paddle.uniform(shape=[2, 3], dtype='float32')
out_dygraph, static_layer = paddle.jit.TracedLayer.trace(layer, inputs=[in_var])
...
...
@@ -1244,13 +1244,16 @@ class TracedLayer(object):
return
self
.
_run
(
self
.
_build_feed
(
inputs
))
@
switch_to_static_graph
def
save_inference_model
(
self
,
dirname
,
feed
=
None
,
fetch
=
None
):
def
save_inference_model
(
self
,
path
,
feed
=
None
,
fetch
=
None
):
"""
Save the TracedLayer to a model for inference. The saved
inference model can be loaded by C++ inference APIs.
``path`` is the prefix of saved objects, and the saved translated program file
suffix is ``.pdmodel`` , the saved persistable variables file suffix is ``.pdiparams`` .
Args:
dirname (str): the directory to save the inference model
.
path(str): The path prefix to save model. The format is ``dirname/file_prefix`` or ``file_prefix``
.
feed (list[int], optional): the input variable indices of the saved
inference model. If None, all input variables of the
TracedLayer object would be the inputs of the saved inference
...
...
@@ -1294,7 +1297,7 @@ class TracedLayer(object):
fetch, = exe.run(program, feed={feed_vars[0]: in_np}, fetch_list=fetch_vars)
print(fetch.shape) # (2, 10)
"""
check_type
(
dirname
,
"dirname
"
,
str
,
check_type
(
path
,
"path
"
,
str
,
"fluid.dygraph.jit.TracedLayer.save_inference_model"
)
check_type
(
feed
,
"feed"
,
(
type
(
None
),
list
),
"fluid.dygraph.jit.TracedLayer.save_inference_model"
)
...
...
@@ -1309,6 +1312,18 @@ class TracedLayer(object):
check_type
(
f
,
"each element of fetch"
,
int
,
"fluid.dygraph.jit.TracedLayer.save_inference_model"
)
# path check
file_prefix
=
os
.
path
.
basename
(
path
)
if
file_prefix
==
""
:
raise
ValueError
(
"The input path MUST be format of dirname/file_prefix "
"[dirname
\\
file_prefix in Windows system], but received "
"file_prefix is empty string."
)
dirname
=
os
.
path
.
dirname
(
path
)
if
dirname
and
not
os
.
path
.
exists
(
dirname
):
os
.
makedirs
(
dirname
)
from
paddle.fluid.io
import
save_inference_model
def
get_feed_fetch
(
all_vars
,
partial_vars
):
...
...
@@ -1326,9 +1341,14 @@ class TracedLayer(object):
assert
target_var
is
not
None
,
"{} cannot be found"
.
format
(
name
)
target_vars
.
append
(
target_var
)
model_filename
=
file_prefix
+
INFER_MODEL_SUFFIX
params_filename
=
file_prefix
+
INFER_PARAMS_SUFFIX
save_inference_model
(
dirname
=
dirname
,
feeded_var_names
=
feeded_var_names
,
target_vars
=
target_vars
,
executor
=
self
.
_exe
,
main_program
=
self
.
_program
.
clone
())
main_program
=
self
.
_program
.
clone
(),
model_filename
=
model_filename
,
params_filename
=
params_filename
)
python/paddle/fluid/tests/unittests/test_imperative_trace_non_persistable_inputs.py
浏览文件 @
10af966a
...
...
@@ -75,10 +75,12 @@ class TestTracedLayerRecordNonPersistableInput(unittest.TestCase):
self
.
assertEqual
(
actual_persistable_vars
,
expected_persistable_vars
)
dirname
=
'./traced_layer_test_non_persistable_vars'
traced_layer
.
save_inference_model
(
dirname
=
dirname
)
filenames
=
set
([
f
for
f
in
os
.
listdir
(
dirname
)
if
f
!=
'__model__'
])
self
.
assertEqual
(
filenames
,
expected_persistable_vars
)
traced_layer
.
save_inference_model
(
path
=
'./traced_layer_test_non_persistable_vars'
)
self
.
assertTrue
(
'traced_layer_test_non_persistable_vars.pdmodel'
in
os
.
listdir
(
'./'
))
self
.
assertTrue
(
'traced_layer_test_non_persistable_vars.pdiparams'
in
os
.
listdir
(
'./'
))
if
__name__
==
'__main__'
:
...
...
python/paddle/fluid/tests/unittests/test_traced_layer_err_msg.py
浏览文件 @
10af966a
...
...
@@ -18,6 +18,7 @@ import paddle.fluid as fluid
import
six
import
unittest
import
paddle.nn
as
nn
import
os
class
SimpleFCLayer
(
nn
.
Layer
):
...
...
@@ -115,36 +116,41 @@ class TestTracedLayerErrMsg(unittest.TestCase):
dygraph_out
,
traced_layer
=
fluid
.
dygraph
.
TracedLayer
.
trace
(
self
.
layer
,
[
in_x
])
dirname
=
'./traced_layer_err_msg'
path
=
'./traced_layer_err_msg'
with
self
.
assertRaises
(
TypeError
)
as
e
:
traced_layer
.
save_inference_model
([
0
])
self
.
assertEqual
(
"The type of '
dirname
' in fluid.dygraph.jit.TracedLayer.save_inference_model must be <{} 'str'>, but received <{} 'list'>. "
.
"The type of '
path
' in fluid.dygraph.jit.TracedLayer.save_inference_model must be <{} 'str'>, but received <{} 'list'>. "
.
format
(
self
.
type_str
,
self
.
type_str
),
str
(
e
.
exception
))
with
self
.
assertRaises
(
TypeError
)
as
e
:
traced_layer
.
save_inference_model
(
dirname
,
[
0
],
[
None
])
traced_layer
.
save_inference_model
(
path
,
[
0
],
[
None
])
self
.
assertEqual
(
"The type of 'each element of fetch' in fluid.dygraph.jit.TracedLayer.save_inference_model must be <{} 'int'>, but received <{} 'NoneType'>. "
.
format
(
self
.
type_str
,
self
.
type_str
),
str
(
e
.
exception
))
with
self
.
assertRaises
(
TypeError
)
as
e
:
traced_layer
.
save_inference_model
(
dirname
,
[
0
],
False
)
traced_layer
.
save_inference_model
(
path
,
[
0
],
False
)
self
.
assertEqual
(
"The type of 'fetch' in fluid.dygraph.jit.TracedLayer.save_inference_model must be (<{} 'NoneType'>, <{} 'list'>), but received <{} 'bool'>. "
.
format
(
self
.
type_str
,
self
.
type_str
,
self
.
type_str
),
str
(
e
.
exception
))
with
self
.
assertRaises
(
TypeError
)
as
e
:
traced_layer
.
save_inference_model
(
dirname
,
[
None
],
[
0
])
traced_layer
.
save_inference_model
(
path
,
[
None
],
[
0
])
self
.
assertEqual
(
"The type of 'each element of feed' in fluid.dygraph.jit.TracedLayer.save_inference_model must be <{} 'int'>, but received <{} 'NoneType'>. "
.
format
(
self
.
type_str
,
self
.
type_str
),
str
(
e
.
exception
))
with
self
.
assertRaises
(
TypeError
)
as
e
:
traced_layer
.
save_inference_model
(
dirname
,
True
,
[
0
])
traced_layer
.
save_inference_model
(
path
,
True
,
[
0
])
self
.
assertEqual
(
"The type of 'feed' in fluid.dygraph.jit.TracedLayer.save_inference_model must be (<{} 'NoneType'>, <{} 'list'>), but received <{} 'bool'>. "
.
format
(
self
.
type_str
,
self
.
type_str
,
self
.
type_str
),
str
(
e
.
exception
))
with
self
.
assertRaises
(
ValueError
)
as
e
:
traced_layer
.
save_inference_model
(
""
)
self
.
assertEqual
(
"The input path MUST be format of dirname/file_prefix [dirname
\\
file_prefix in Windows system], "
"but received file_prefix is empty string."
,
str
(
e
.
exception
))
traced_layer
.
save_inference_model
(
dirname
)
traced_layer
.
save_inference_model
(
path
)
def
_train_simple_net
(
self
):
layer
=
None
...
...
@@ -174,5 +180,25 @@ class TestOutVarWithNoneErrMsg(unittest.TestCase):
[
in_x
])
class
TestTracedLayerSaveInferenceModel
(
unittest
.
TestCase
):
"""test save_inference_model will automaticlly create non-exist dir"""
def
setUp
(
self
):
self
.
save_path
=
"./nonexist_dir/fc"
import
shutil
if
os
.
path
.
exists
(
os
.
path
.
dirname
(
self
.
save_path
)):
shutil
.
rmtree
(
os
.
path
.
dirname
(
self
.
save_path
))
def
test_mkdir_when_input_path_non_exist
(
self
):
fc_layer
=
SimpleFCLayer
(
3
,
4
,
2
)
input_var
=
paddle
.
to_tensor
(
np
.
random
.
random
([
4
,
3
]).
astype
(
'float32'
))
with
fluid
.
dygraph
.
guard
():
dygraph_out
,
traced_layer
=
fluid
.
dygraph
.
TracedLayer
.
trace
(
fc_layer
,
inputs
=
[
input_var
])
self
.
assertFalse
(
os
.
path
.
exists
(
os
.
path
.
dirname
(
self
.
save_path
)))
traced_layer
.
save_inference_model
(
self
.
save_path
)
self
.
assertTrue
(
os
.
path
.
exists
(
os
.
path
.
dirname
(
self
.
save_path
)))
if
__name__
==
'__main__'
:
unittest
.
main
()
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