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88600d7d
编写于
6月 17, 2020
作者:
C
Chengmo
提交者:
GitHub
6月 17, 2020
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电子邮件补丁
差异文件
fix lod tensor return (#101)
Co-authored-by:
N
tangwei
<
tangwei12@baidu.com
>
上级
5a521800
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
49 addition
and
18 deletion
+49
-18
core/trainers/framework/runner.py
core/trainers/framework/runner.py
+48
-12
core/trainers/general_trainer.py
core/trainers/general_trainer.py
+1
-6
未找到文件。
core/trainers/framework/runner.py
浏览文件 @
88600d7d
...
@@ -16,10 +16,9 @@ from __future__ import print_function
...
@@ -16,10 +16,9 @@ from __future__ import print_function
import
os
import
os
import
time
import
time
import
warnings
import
numpy
as
np
import
datetime
import
paddle.fluid
as
fluid
import
paddle.fluid
as
fluid
from
paddlerec.core.utils
import
envs
from
paddlerec.core.utils
import
envs
__all__
=
[
__all__
=
[
...
@@ -27,6 +26,42 @@ __all__ = [
...
@@ -27,6 +26,42 @@ __all__ = [
]
]
def
as_numpy
(
tensor
):
"""
Convert a Tensor to a numpy.ndarray, its only support Tensor without LoD information.
For higher dimensional sequence data, please use LoDTensor directly.
Examples:
.. code-block:: python
import paddle.fluid as fluid
import numpy
new_scope = fluid.Scope()
with fluid.scope_guard(new_scope):
fluid.global_scope().var("data").get_tensor().set(numpy.ones((2, 2)), fluid.CPUPlace())
tensor = new_scope.find_var("data").get_tensor()
fluid.executor.as_numpy(tensor) # or numpy.array(new_scope.find_var("data").get_tensor())
Args:
tensor(Variable): a instance of Tensor
Returns:
numpy.ndarray
"""
if
isinstance
(
tensor
,
fluid
.
core
.
LoDTensorArray
):
return
[
as_numpy
(
t
)
for
t
in
tensor
]
if
isinstance
(
tensor
,
list
):
return
[
as_numpy
(
t
)
for
t
in
tensor
]
assert
isinstance
(
tensor
,
fluid
.
core
.
LoDTensor
)
lod
=
tensor
.
lod
()
# (todo) need print lod or return it for user
if
tensor
.
_is_initialized
():
return
np
.
array
(
tensor
)
else
:
return
None
class
RunnerBase
(
object
):
class
RunnerBase
(
object
):
"""R
"""R
"""
"""
...
@@ -92,9 +127,6 @@ class RunnerBase(object):
...
@@ -92,9 +127,6 @@ class RunnerBase(object):
model_class
=
context
[
"model"
][
model_dict
[
"name"
]][
"model"
]
model_class
=
context
[
"model"
][
model_dict
[
"name"
]][
"model"
]
program
=
self
.
_get_dataloader_program
(
model_dict
,
context
)
program
=
self
.
_get_dataloader_program
(
model_dict
,
context
)
reader_name
=
model_dict
[
"dataset_name"
]
fetch_vars
=
[]
fetch_alias
=
[]
fetch_period
=
int
(
fetch_period
=
int
(
envs
.
get_global_env
(
"runner."
+
context
[
"runner_name"
]
+
envs
.
get_global_env
(
"runner."
+
context
[
"runner_name"
]
+
".print_interval"
,
20
))
".print_interval"
,
20
))
...
@@ -103,9 +135,6 @@ class RunnerBase(object):
...
@@ -103,9 +135,6 @@ class RunnerBase(object):
else
:
else
:
metrics
=
model_class
.
get_metrics
()
metrics
=
model_class
.
get_metrics
()
if
metrics
:
fetch_vars
=
metrics
.
values
()
fetch_alias
=
metrics
.
keys
()
metrics_varnames
=
[]
metrics_varnames
=
[]
metrics_format
=
[]
metrics_format
=
[]
metrics_format
.
append
(
"{}: {{}}"
.
format
(
"batch"
))
metrics_format
.
append
(
"{}: {{}}"
.
format
(
"batch"
))
...
@@ -121,9 +150,16 @@ class RunnerBase(object):
...
@@ -121,9 +150,16 @@ class RunnerBase(object):
with
fluid
.
scope_guard
(
scope
):
with
fluid
.
scope_guard
(
scope
):
try
:
try
:
while
True
:
while
True
:
metrics_rets
=
context
[
"exe"
].
run
(
metrics_tensors
=
context
[
"exe"
].
run
(
program
=
program
,
fetch_list
=
metrics_varnames
)
program
=
program
,
fetch_list
=
metrics_varnames
,
return_numpy
=
False
)
metrics
=
[
batch_id
]
metrics
=
[
batch_id
]
metrics_rets
=
[
as_numpy
(
metrics_tensor
)
for
metrics_tensor
in
metrics_tensors
]
metrics
.
extend
(
metrics_rets
)
metrics
.
extend
(
metrics_rets
)
if
batch_id
%
fetch_period
==
0
and
batch_id
!=
0
:
if
batch_id
%
fetch_period
==
0
and
batch_id
!=
0
:
...
@@ -248,7 +284,7 @@ class RunnerBase(object):
...
@@ -248,7 +284,7 @@ class RunnerBase(object):
fetch_varnames
=
envs
.
get_global_env
(
fetch_varnames
=
envs
.
get_global_env
(
name
+
"save_inference_fetch_varnames"
,
[])
name
+
"save_inference_fetch_varnames"
,
[])
if
feed_varnames
is
None
or
fetch_varnames
is
None
or
feed_varnames
==
""
or
fetch_varnames
==
""
or
\
if
feed_varnames
is
None
or
fetch_varnames
is
None
or
feed_varnames
==
""
or
fetch_varnames
==
""
or
\
len
(
feed_varnames
)
==
0
or
len
(
fetch_varnames
)
==
0
:
len
(
feed_varnames
)
==
0
or
len
(
fetch_varnames
)
==
0
:
return
return
fetch_vars
=
[
fetch_vars
=
[
fluid
.
default_main_program
().
global_block
().
vars
[
varname
]
fluid
.
default_main_program
().
global_block
().
vars
[
varname
]
...
...
core/trainers/general_trainer.py
浏览文件 @
88600d7d
...
@@ -19,12 +19,7 @@ from __future__ import print_function
...
@@ -19,12 +19,7 @@ from __future__ import print_function
import
os
import
os
from
paddlerec.core.utils
import
envs
from
paddlerec.core.utils
import
envs
from
paddlerec.core.trainer
import
Trainer
,
EngineMode
,
FleetMode
,
Device
from
paddlerec.core.trainer
import
Trainer
,
EngineMode
,
FleetMode
from
paddlerec.core.trainers.framework.dataset
import
*
from
paddlerec.core.trainers.framework.runner
import
*
from
paddlerec.core.trainers.framework.instance
import
*
from
paddlerec.core.trainers.framework.network
import
*
from
paddlerec.core.trainers.framework.startup
import
*
class
GeneralTrainer
(
Trainer
):
class
GeneralTrainer
(
Trainer
):
...
...
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