提交 228e14ad 编写于 作者: F fengjiayi

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into dev_global_norm_clip

from __future__ import absolute_import
from __future__ import print_function
from __future__ import unicode_literals
import argparse
import io, re
import sys, os
import subprocess
import platform
COPYRIGHT = '''
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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.
'''
LANG_COMMENT_MARK = None
NEW_LINE_MARK = None
COPYRIGHT_HEADER = None
if platform.system() == "Windows":
NEW_LINE_MARK = "\r\n"
else:
NEW_LINE_MARK = '\n'
COPYRIGHT_HEADER = COPYRIGHT.split(NEW_LINE_MARK)[1]
p = re.search('(\d{4})', COPYRIGHT_HEADER).group(0)
process = subprocess.Popen(["date", "+%Y"], stdout=subprocess.PIPE)
date, err = process.communicate()
date = date.decode("utf-8").rstrip("\n")
COPYRIGHT_HEADER = COPYRIGHT_HEADER.replace(p, date)
def generate_copyright(template, lang='C'):
if lang == 'Python':
LANG_COMMENT_MARK = '#'
else:
LANG_COMMENT_MARK = "//"
lines = template.split(NEW_LINE_MARK)
ans = LANG_COMMENT_MARK + COPYRIGHT_HEADER + NEW_LINE_MARK
for lino, line in enumerate(lines):
if lino == 0 or lino == 1 or lino == len(lines) - 1: continue
ans += LANG_COMMENT_MARK + line + NEW_LINE_MARK
return ans
def lang_type(filename):
if filename.endswith(".py"):
return "Python"
elif filename.endswith(".h"):
return "C"
elif filename.endswith(".hpp"):
return "C"
elif filename.endswith(".cc"):
return "C"
elif filename.endswith(".cpp"):
return "C"
elif filename.endswith(".cu"):
return "C"
elif filename.endswith(".cuh"):
return "C"
elif filename.endswith(".go"):
return "C"
elif filename.endswith(".proto"):
return "C"
else:
print("Unsupported filetype")
exit(0)
def main(argv=None):
parser = argparse.ArgumentParser(
description='Checker for copyright declaration.')
parser.add_argument('filenames', nargs='*', help='Filenames to check')
args = parser.parse_args(argv)
retv = 0
for filename in args.filenames:
first_line = io.open(filename).readline()
if "COPYRIGHT" in first_line.upper() : continue
original_contents = io.open(filename).read()
new_contents = generate_copyright(
COPYRIGHT, lang_type(filename)) + original_contents
print('Auto Insert Copyright Header {}'.format(filename))
retv = 1
with io.open(filename, 'w') as output_file:
output_file.write(new_contents)
return retv
if __name__ == '__main__':
exit(main())
......@@ -31,3 +31,11 @@
- id: go-fmt
types:
- go
- repo: local
hooks:
- id: copyright_checker
name: copyright_checker
entry: python ./.copyright.hook
language: system
files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|proto|py)$
exclude: (?!.*third_party)^.*$ | (?!.*book)^.*$
......@@ -37,6 +37,7 @@ Please refer to our [release announcement](https://github.com/PaddlePaddle/Paddl
- Optimized math operations through SSE/AVX intrinsics, BLAS libraries
(e.g. MKL, OpenBLAS, cuBLAS) or customized CPU/GPU kernels.
- Optimized CNN networks through MKL-DNN library.
- Highly optimized recurrent networks which can handle **variable-length**
sequence without padding.
- Optimized local and distributed training for models with high dimensional
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
"""
The base model of the model.
"""
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
"""
This module provide the attack method for FGSM's implement.
"""
......@@ -36,3 +49,39 @@ class GradientSignAttack(Attack):
FGSM = GradientSignAttack
class IteratorGradientSignAttack(Attack):
"""
This attack was originally implemented by Alexey Kurakin(Google Brain).
Paper link: https://arxiv.org/pdf/1607.02533.pdf
"""
def _apply(self, image_label, epsilons=100, steps=10):
"""
Apply the iterative gradient sign attack.
Args:
image_label(list): The image and label tuple list of one element.
epsilons(list|tuple|int): The epsilon (input variation parameter).
steps(int): The number of iterator steps.
Return:
numpy.ndarray: The adversarail sample generated by the algorithm.
"""
assert len(image_label) == 1
pre_label = np.argmax(self.model.predict(image_label))
gradient = self.model.gradient(image_label)
min_, max_ = self.model.bounds()
if not isinstance(epsilons, Iterable):
epsilons = np.linspace(0, 1, num=epsilons + 1)
for epsilon in epsilons:
adv_img = image_label[0][0].reshape(gradient.shape)
for _ in range(steps):
gradient = self.model.gradient([(adv_img, image_label[0][1])])
gradient_sign = np.sign(gradient) * (max_ - min_)
adv_img = adv_img + epsilon * gradient_sign
adv_img = np.clip(adv_img, min_, max_)
adv_label = np.argmax(self.model.predict([(adv_img, 0)]))
if pre_label != adv_label:
return adv_img
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
"""
The base model of the model.
"""
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 absolute_import
import numpy as np
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
"""
CNN on mnist data using fluid api of paddlepaddle
"""
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
"""
FGSM demos on mnist using advbox tool.
"""
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#!/usr/bin/env python
from paddle.trainer_config_helpers import *
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#!/usr/bin/env python
from paddle.trainer_config_helpers import *
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 io, os
import random
import numpy as np
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#!/usr/bin/env python
from paddle.trainer_config_helpers import *
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#!/usr/bin/env python
from paddle.trainer_config_helpers import *
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#!/usr/bin/env python
from paddle.trainer_config_helpers import *
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 io, os
import random
import numpy as np
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#!/usr/bin/env python
from paddle.trainer_config_helpers import *
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 six.moves import xrange # pylint: disable=redefined-builtin
from datetime import datetime
import math
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 six.moves import xrange # pylint: disable=redefined-builtin
from datetime import datetime
import math
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 six.moves import xrange
from datetime import datetime
import math
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 six.moves import xrange # pylint: disable=redefined-builtin
from datetime import datetime
import math
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 six.moves import xrange # pylint: disable=redefined-builtin
from datetime import datetime
import math
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 os.path
import io
import numpy as np
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#!/usr/bin/env python
from six.moves import xrange # pylint: disable=redefined-builtin
import math
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#!/usr/bin/env python
from six.moves import xrange # pylint: disable=redefined-builtin
import re
......
......@@ -33,7 +33,7 @@ ExternalProject_Add(
extern_grpc
DEPENDS protobuf zlib
GIT_REPOSITORY "https://github.com/grpc/grpc.git"
GIT_TAG "v1.7.x"
GIT_TAG "v1.8.x"
PREFIX ${GRPC_SOURCES_DIR}
UPDATE_COMMAND ""
CONFIGURE_COMMAND ""
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 os
import re
import sys
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 paddle.trainer_config_helpers import *
define_py_data_sources2(
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 paddle.trainer.PyDataProvider2 import *
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 paddle.trainer_config_helpers import *
dictionary = dict()
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 paddle.trainer.PyDataProvider2 import *
......
......@@ -15,4 +15,4 @@ Fluid
fluid/param_attr.rst
fluid/profiler.rst
fluid/regularizer.rst
fluid/io.rst
===========
IO
===========
is_parameter
-----------
.. autofunction:: paddle.v2.fluid.io.is_parameter
:noindex:
......@@ -358,3 +358,138 @@ reduce_min
.. autofunction:: paddle.v2.fluid.layers.reduce_min
:noindex:
split
-----
.. autofunction:: paddle.v2.fluid.layers.split
:noindex:
logsigmoid
----------
.. autofunction:: paddle.v2.fluid.layers.logsigmoid
:noindex:
exp
---
.. autofunction:: paddle.v2.fluid.layers.exp
:noindex:
relu
----
.. autofunction:: paddle.v2.fluid.layers.relu
:noindex:
tanh
----
.. autofunction:: paddle.v2.fluid.layers.tanh
:noindex:
tanh_shrink
-----------
.. autofunction:: paddle.v2.fluid.layers.tanh_shrink
:noindex:
softshrink
----------
.. autofunction:: paddle.v2.fluid.layers.softshrink
:noindex:
sqrt
----
.. autofunction:: paddle.v2.fluid.layers.sqrt
:noindex:
abs
----
.. autofunction:: paddle.v2.fluid.layers.abs
:noindex:
ceil
----
.. autofunction:: paddle.v2.fluid.layers.ceil
:noindex:
floor
-----
.. autofunction:: paddle.v2.fluid.layers.floor
:noindex:
round
-----
.. autofunction:: paddle.v2.fluid.layers.round
:noindex:
reciprocal
----------
.. autofunction:: paddle.v2.fluid.layers.reciprocal
:noindex:
log
---
.. autofunction:: paddle.v2.fluid.layers.log
:noindex:
square
------
.. autofunction:: paddle.v2.fluid.layers.square
:noindex:
softplus
--------
.. autofunction:: paddle.v2.fluid.layers.softplus
:noindex:
softsign
---------
.. autofunction:: paddle.v2.fluid.layers.softsign
:noindex:
brelu
-----
.. autofunction:: paddle.v2.fluid.layers.brelu
:noindex:
leaky_relu
----------
.. autofunction:: paddle.v2.fluid.layers.leaky_relu
:noindex:
soft_relu
---------
.. autofunction:: paddle.v2.fluid.layers.soft_relu
:noindex:
elu
----
.. autofunction:: paddle.v2.fluid.layers.elu
:noindex:
relu6
-----
.. autofunction:: paddle.v2.fluid.layers.relu6
:noindex:
pow
----
.. autofunction:: paddle.v2.fluid.layers.pow
:noindex:
hard_shrink
-----------
.. autofunction:: paddle.v2.fluid.layers.hard_shrink
:noindex:
thresholded_relu
----------------
.. autofunction:: paddle.v2.fluid.layers.thresholded_relu
:noindex:
hard_sigmoid
-------------
.. autofunction:: paddle.v2.fluid.layers.hard_sigmoid
:noindex:
swish
------
.. autofunction:: paddle.v2.fluid.layers.swish
:noindex:
......@@ -20,3 +20,8 @@ sequence_conv_pool
:noindex:
glu
---
.. autofunction:: paddle.v2.fluid.nets.glu
:noindex:
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
@provider(min_pool_size=0, ...)
def process(settings, filename):
os.system('shuf %s > %s.shuf' % (filename, filename)) # shuffle before.
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
... # the settings and define data provider is omitted.
DICT_DIM = 3000 # dictionary dimension.
word_ids = data_layer('word_ids', size=DICT_DIM)
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
DICT_DIM = 3000
......
......@@ -32,6 +32,16 @@ PaddlePaddle主要使用 `CMake <https://cmake.org>`_ 以及GCC, G++作为编译
pip install build/python/dist/*.whl
如果机器中已经安装过PaddlePaddle,有两种方法:
.. code-block:: bash
1. 先卸载之前的版本,再重新安装
pip uninstall paddlepaddle
pip install build/python/dist/*.whl
2. 直接升级到更新的版本
pip install build/python/dist/*.whl -U
.. _run_test:
......
......@@ -36,6 +36,16 @@ machine or copy it to the target machine.
pip install build/python/dist/*.whl
If the machine has installed PaddlePaddle before, there are two methods:
.. code-block:: bash
1. uninstall and reinstall
pip uninstall paddlepaddle
pip install build/python/dist/*.whl
2. upgrade directly
pip install build/python/dist/*.whl -U
.. _run_test:
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.v2 as paddle
import numpy as np
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.v2 as paddle
import numpy as np
......
......@@ -24,7 +24,7 @@
- `framework::OperatorWithKernel`:继承自OperatorBase,Op有计算函数,称作有Kernel。
- `class OpProtoAndCheckerMaker`:描述该Op的输入、输出、属性、注释,主要用于Python API接口生成
依据是否包含kernel,可以将Op分为两种:包含Kernel的Op和不包含kernel的Op,前者Op的定义继承自`OperatorBase`,后者继承自`OperatorWithKernel`。本教程主要介绍带Kernel的Op如何写,简单总结Op需要包含的内容如下:
依据是否包含kernel,可以将Op分为两种:包含Kernel的Op和不包含kernel的Op,前者Op的定义继承自`OperatorWithKernel`,后者继承自`OperatorBase`。本教程主要介绍带Kernel的Op如何写,简单总结Op需要包含的内容如下:
内容 | 定义位置
......
......@@ -26,10 +26,9 @@
### 准备预测模型
在准备预测模型部分的介绍,我们以手写数字识别任务为例。手写数字识别任务定义了一个含有[两个隐层的简单全连接网络](https://github.com/PaddlePaddle/book/blob/develop/02.recognize_digits/README.cn.md#softmax回归softmax-regression),网络接受一幅图片作为输入,将图片分类到 0 ~ 9 类别标签之一。完整代码可以查看[此目录](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/capi/examples/model_inference/dense) 中的相关脚本。
准备预测模型部分,我们以手写数字识别任务为例进行介绍。手写数字识别任务定义了一个含有[两个隐层的简单全连接网络](https://github.com/PaddlePaddle/book/blob/develop/02.recognize_digits/README.cn.md#softmax回归softmax-regression),网络接受一幅图片作为输入,将图片分类到 0 ~ 9 类别标签之一。完整代码可以查看[此目录](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/capi/examples/model_inference/dense) 中的相关脚本。
调用C-API开发预测程序需要一个训练好的模型,在终端执行`python mnist_v2.py`
运行[目录](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/capi/examples/model_inference/dense) 会使用 PaddlePaddle 内置的 [MNIST 数据集](http://yann.lecun.com/exdb/mnist/)进行训练。训练好的模型默认保存在当前运行目录下的`models`目录中。
调用C-API开发预测程序需要一个训练好的模型,运行[MNIST手写数字识别目录](https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/capi/examples/model_inference/dense)下的[mnist_v2.py](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/capi/examples/model_inference/dense/mnist_v2.py)脚本,在终端执行`python mnist_v2.py`,会使用 PaddlePaddle 内置的 [MNIST 数据集](http://yann.lecun.com/exdb/mnist/)进行训练。训练好的模型默认保存在当前运行目录下的`models`目录中。
下面,我们将训练结束后存储下来的模型转换成预测模型。
......@@ -113,7 +112,7 @@ C-API支持的所有输入数据类型和他们的组织方式,请参考“输
#### step 4. 前向计算
完成上述准备之后,通过调用 `[paddle_gradient_machine_forward](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/capi/gradient_machine.h#L73)` 接口完成神经网络的前向计算。
完成上述准备之后,通过调用 [`paddle_gradient_machine_forward`](https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/capi/gradient_machine.h#L73) 接口完成神经网络的前向计算。
#### step 5. 清理
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#!/usr/bin/python
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 gzip
import math
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 math
import os
import paddle.v2 as paddle
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.v2 as paddle
import gzip
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.v2 as paddle
import paddle.v2.dataset.uci_housing as uci_housing
import paddle.v2.master as master
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 paddle.trainer_config_helpers import *
settings(batch_size=100, learning_method=AdamOptimizer())
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
#ifndef __CAPI_EXAMPLE_COMMON_H__
#define __CAPI_EXAMPLE_COMMON_H__
#include <stdio.h>
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 paddle.utils.merge_model import merge_v2_model
from mnist_v2 import network
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 os
import sys
import gzip
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 paddle.trainer_config_helpers import *
img = data_layer(name='pixel', size=784)
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 paddle.trainer_config_helpers import *
WORD_DIM = 3000
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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 paddle.trainer_config_helpers import *
settings(batch_size=100)
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
/*
AVX implementation of sin, cos, sincos, exp and log
......
......@@ -47,7 +47,7 @@ cc_test(op_proto_maker_test SRCS op_proto_maker_test.cc DEPS op_proto_maker)
cc_library(op_info SRCS op_info.cc DEPS attribute framework_proto)
cc_library(shape_inference SRCS shape_inference.cc DEPS ddim attribute device_context)
cc_library(operator SRCS operator.cc DEPS op_info device_context tensor scope glog
shape_inference data_transform)
shape_inference data_transform lod_tensor)
cc_test(operator_test SRCS operator_test.cc DEPS operator op_registry init)
cc_library(proto_desc SRCS var_desc.cc op_desc.cc block_desc.cc program_desc.cc DEPS shape_inference op_info operator glog)
......
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
#include "paddle/framework/backward.h"
......
......@@ -31,15 +31,14 @@ static const platform::DeviceContext* GetDeviceContext(
}
}
Tensor* DeviceTransform(const Tensor& in, const platform::Place& dst_place) {
void DeviceTransform(const Tensor& in, const platform::Place& dst_place,
Tensor* out) {
VLOG(3) << "DeviceTransform in, src_place " << in.place()
<< " dst_place: " << dst_place;
Tensor* out = new Tensor();
auto* dev_ctx = GetDeviceContext(in.place(), dst_place);
dev_ctx->Wait();
Copy(in, dst_place, *dev_ctx, out);
dev_ctx->Wait();
return out;
}
} // namespace framework
......
......@@ -21,7 +21,8 @@ limitations under the License. */
namespace paddle {
namespace framework {
Tensor* DeviceTransform(const Tensor& in, const platform::Place& dst_place);
void DeviceTransform(const Tensor& in, const platform::Place& dst_place,
Tensor* out);
} // namespace framework
} // namespace paddle
......@@ -14,7 +14,9 @@ limitations under the License. */
#pragma once
#include <iostream>
#include <cctype>
#include <ostream>
#include "paddle/platform/enforce.h"
namespace paddle {
......@@ -27,12 +29,19 @@ enum class DataLayout {
};
inline DataLayout StringToDataLayout(const std::string& str) {
if (str == "NHWC" || str == "nhwc") {
std::string s(str);
for (size_t i = 0; i < s.size(); ++i) {
s[i] = toupper(s[i]);
}
if (s == "NHWC") {
return DataLayout::kNHWC;
} else if (str == "NCHW" || str == "nchw") {
} else if (s == "NCHW") {
return DataLayout::kNCHW;
} else if (s == "ANYLAYOUT") {
return DataLayout::kAnyLayout;
} else {
PADDLE_THROW("Unknown storage order string: %s", str);
PADDLE_THROW("Unknown storage order string: %s", s);
}
}
......@@ -49,7 +58,7 @@ inline std::string DataLayoutToString(const DataLayout& data_layout) {
}
}
inline std::ostream& operator<<(std::ostream& out, DataLayout l) {
inline std::ostream& operator<<(std::ostream& out, const DataLayout& l) {
out << DataLayoutToString(l);
return out;
}
......
......@@ -19,16 +19,14 @@ limitations under the License. */
namespace paddle {
namespace framework {
Tensor* DataTransform(const OpKernelType& expected_kernel_type,
const OpKernelType& kernel_type_for_var,
const Tensor& input_tensor) {
Tensor* out = nullptr;
void DataTransform(const OpKernelType& expected_kernel_type,
const OpKernelType& kernel_type_for_var,
const Tensor& input_tensor, Tensor* out) {
if (!platform::is_same_place(kernel_type_for_var.place_,
expected_kernel_type.place_)) {
out = DeviceTransform(input_tensor, expected_kernel_type.place_);
DeviceTransform(input_tensor, expected_kernel_type.place_, out);
}
PADDLE_ENFORCE_NOT_NULL(out, "out should not be null");
return out;
}
void CopyVariableWithTensor(const Variable& in_var, const Tensor& tensor,
......
......@@ -30,9 +30,9 @@ limitations under the License. */
namespace paddle {
namespace framework {
Tensor* DataTransform(const OpKernelType& expected_kernel_type,
const OpKernelType& kernel_type_for_var,
const Tensor& input_tensor);
void DataTransform(const OpKernelType& expected_kernel_type,
const OpKernelType& kernel_type_for_var,
const Tensor& input_tensor, Tensor* out);
void CopyVariableWithTensor(const Variable& in_var, const Tensor& tensor,
Variable& out_var);
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
#pragma once
#include <iostream>
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
#include <thrust/device_vector.h>
#include <sstream>
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
/*
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
......
......@@ -69,6 +69,12 @@ std::ostream &operator<<(std::ostream &os, const LoDTensor &t) {
return os;
}
std::string LoDToString(const LoD &lod) {
std::ostringstream stream;
stream << lod;
return stream.str();
}
LoD SliceInLevel(const LoD &in, size_t level, size_t elem_begin,
size_t elem_end) {
PADDLE_ENFORCE_LT(level, in.size());
......
......@@ -60,6 +60,8 @@ using LoD = std::vector<Vector<size_t>>;
std::ostream& operator<<(std::ostream& os, const LoD& lod);
std::ostream& operator<<(std::ostream& os, const LoDTensor& t);
std::string LoDToString(const LoD& lod);
LoD SliceInLevel(const LoD& in, size_t level, size_t elem_begin,
size_t elem_end);
/*
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
/*
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
/*
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
......
......@@ -85,5 +85,10 @@ inline std::string KernelTypeToString(const OpKernelType& kernel_key) {
return stream.str();
}
inline bool TransFromNeeded(const OpKernelType& l, const OpKernelType& r) {
return (!platform::places_are_same_class(l.place_, r.place_)) ||
(l.data_type_ != r.data_type_) || (l.data_layout_ != r.data_layout_);
}
} // namespace framework
} // namespace paddle
......@@ -368,24 +368,6 @@ TEST(OperatorRegistrar, OpWithMultiKernel) {
// TODO(qiao) add priority back
// use all available kernels
paddle::framework::UseALL();
op->Run(scope, cuda_place);
EXPECT_EQ(op_test_value, -10);
// remove cuda kernels
paddle::framework::UseCPU();
op->Run(scope, cpu_place);
EXPECT_EQ(op_test_value, -9);
// add cuda kernels
paddle::framework::UseCUDA();
op->Run(scope, cuda_place);
EXPECT_EQ(op_test_value, -10);
// use cudnn kernel
paddle::framework::UseCUDNN();
op->Run(scope, cuda_place);
EXPECT_EQ(op_test_value, -20);
}
......@@ -29,58 +29,20 @@ DEFINE_bool(op_sync, false,
namespace paddle {
namespace framework {
std::vector<std::tuple<platform::Place, LibraryType>> kKernelPriority;
void UseCPU() {
kKernelPriority.clear();
/*Plain CPU*/
auto pair0 = std::make_tuple(platform::CPUPlace(), LibraryType::kPlain);
kKernelPriority.insert(kKernelPriority.begin(), pair0);
}
void UseMKLDNN() {
UseCPU();
#if PADDLE_WITH_MKLML
{
/*MKLDNN Kernel*/
auto pair0 = std::make_tuple(platform::CPUPlace(), LibraryType::kMKLDNN);
kKernelPriority.insert(kKernelPriority.begin(), pair0);
}
#endif
}
void UseCUDA() {
UseMKLDNN();
#if PADDLE_WITH_CUDA
/*Plain GPU*/
auto pair0 = std::make_tuple(platform::CUDAPlace(0), LibraryType::kPlain);
kKernelPriority.insert(kKernelPriority.begin(), pair0);
#endif
}
void UseCUDNN() {
UseCUDA();
#if PADDLE_WITH_CUDA
if (platform::dynload::HasCUDNN()) {
/*CUDNN Kernel*/
auto pair0 = std::make_tuple(platform::CUDAPlace(0), LibraryType::kCUDNN);
kKernelPriority.insert(kKernelPriority.begin(), pair0);
}
#endif
}
void UseALL() {
UseCPU();
UseMKLDNN();
UseCUDA();
UseCUDNN();
}
std::vector<std::tuple<platform::Place, LibraryType>> kKernelPriority = {
std::make_tuple(platform::CUDAPlace(0), LibraryType::kCUDNN),
std::make_tuple(platform::CUDAPlace(0), LibraryType::kPlain),
std::make_tuple(platform::CPUPlace(), LibraryType::kMKLDNN),
std::make_tuple(platform::CPUPlace(), LibraryType::kPlain),
};
static DDim GetDims(const Scope& scope, const std::string& name) {
Variable* var = scope.FindVar(name);
if (var == nullptr) {
return DDim({-1});
} else if (var->IsType<LoDTensor>()) {
}
if (var->IsType<LoDTensor>()) {
return var->Get<LoDTensor>().dims();
} else if (var->IsType<SelectedRows>()) {
return var->Get<SelectedRows>().GetCompleteDims();
......@@ -89,6 +51,21 @@ static DDim GetDims(const Scope& scope, const std::string& name) {
}
}
static LoD GetLoD(const Scope& scope, const std::string& name) {
Variable* var = scope.FindVar(name);
auto default_lod = LoD({{}});
if (var == nullptr) {
return default_lod;
}
if (var->IsType<LoDTensor>()) {
return var->Get<LoDTensor>().lod();
} else {
return default_lod;
}
}
std::string OperatorBase::Input(const std::string& name) const {
auto& ins = Inputs(name);
PADDLE_ENFORCE_LE(ins.size(), 1UL,
......@@ -130,7 +107,8 @@ std::string OperatorBase::DebugStringEx(const Scope* scope) const {
for (size_t i = 0; i < input.second.size(); ++i) {
ss << input.second[i];
if (scope) {
ss << "(" << GetDims(*scope, input.second[i]) << ")";
ss << "[" << GetDims(*scope, input.second[i]) << "]";
ss << "(" << GetLoD(*scope, input.second[i]) << ")";
}
if (i != input.second.size() - 1) {
ss << ", ";
......@@ -149,7 +127,8 @@ std::string OperatorBase::DebugStringEx(const Scope* scope) const {
for (size_t i = 0; i < output.second.size(); ++i) {
ss << output.second[i];
if (scope) {
ss << "(" << GetDims(*scope, output.second[i]) << ")";
ss << "[" << GetDims(*scope, output.second[i]) << "]";
ss << "(" << GetLoD(*scope, output.second[i]) << ")";
}
if (i != output.second.size() - 1) {
ss << ", ";
......@@ -252,36 +231,33 @@ static bool VarIsTensor(const Variable* var) {
return var->IsType<LoDTensor>() || var->IsType<SelectedRows>();
}
static const Tensor* GetTensorFromVar(const Variable* var) {
const Tensor* t = nullptr;
static const Tensor* GetTensorFromVar(Variable* var) {
if (var->IsType<LoDTensor>()) {
t = &(var->Get<LoDTensor>());
return var->GetMutable<LoDTensor>();
} else if (var->IsType<SelectedRows>()) {
t = &(var->Get<SelectedRows>().value());
return var->GetMutable<SelectedRows>()->mutable_value();
} else {
PADDLE_THROW("Variable type_id %s, expect LoDTensor/SelectedRows.",
var->Type().name());
}
return t;
}
static Tensor* GetMutableTensorFromVar(Variable* var) {
Tensor* t = nullptr;
if (var->IsType<LoDTensor>()) {
t = var->GetMutable<LoDTensor>();
return var->GetMutable<LoDTensor>();
} else if (var->IsType<SelectedRows>()) {
t = var->GetMutable<SelectedRows>()->mutable_value();
return var->GetMutable<SelectedRows>()->mutable_value();
} else {
PADDLE_THROW("Variable type_id %s, expect LoDTensor/SelectedRows.",
var->Type().name());
}
return t;
}
template <>
const Tensor* ExecutionContext::Input<Tensor>(const std::string& name) const {
auto* var = InputVar(name);
return var == nullptr ? nullptr : GetTensorFromVar(var);
return var == nullptr ? nullptr
: GetTensorFromVar(const_cast<Variable*>(var));
}
template <>
......@@ -324,6 +300,7 @@ bool OpSupportGPU(const std::string& op_type) {
auto it = all_kernels.find(op_type);
if (it == all_kernels.end()) {
// All control operator must support GPU
return true;
}
for (auto& kern_pair : it->second) {
......@@ -497,21 +474,17 @@ void OperatorWithKernel::Run(const Scope& scope,
}
ExecutionContext ctx(*this, scope, *dev_ctx);
auto expected_kernel_key = this->GetExpectedKernelType(ctx);
OpKernelMap& kernels = kernels_iter->second;
for (auto& candidate : kKernelPriority) {
auto candidate_key =
OpKernelType(expected_kernel_key.data_type_, std::get<0>(candidate),
expected_kernel_key.data_layout_, std::get<1>(candidate));
// TODO(dzhwinter) : kernel fallback mechanism will be added when all the
// transform functions are ready.
if ((candidate_key == expected_kernel_key) ||
(kernels.count(candidate_key))) {
expected_kernel_key = candidate_key;
break;
}
}
// for (auto& candidate : kKernelPriority) {
// Do selection
// }
auto expected_kernel_key = this->GetExpectedKernelType(ctx);
VLOG(3) << "expected_kernel_key:" << expected_kernel_key;
......@@ -525,7 +498,7 @@ void OperatorWithKernel::Run(const Scope& scope,
if (tensor_in->IsInitialized()) {
auto kernel_type_for_var = this->GetKernelTypeForVar(
var_name_item.first, *tensor_in, expected_kernel_key);
if (kernel_type_for_var != expected_kernel_key) {
if (TransFromNeeded(kernel_type_for_var, expected_kernel_key)) {
auto out_var_names = OutputVars(true);
if (std::find(out_var_names.begin(), out_var_names.end(),
var_name) != out_var_names.end()) {
......@@ -534,11 +507,13 @@ void OperatorWithKernel::Run(const Scope& scope,
"does not support transform",
var_name);
}
VLOG(3) << "need to do transform for var " << var_name;
VLOG(3) << "Transform Variable " << var_name << " from "
<< kernel_type_for_var << " to " << expected_kernel_key;
auto* trans_var = new_scope.Var(var_name);
auto* out = DataTransform(expected_kernel_key, kernel_type_for_var,
*tensor_in);
CopyVariableWithTensor(*var, *out, *trans_var);
std::shared_ptr<Tensor> out(new Tensor);
DataTransform(expected_kernel_key, kernel_type_for_var, *tensor_in,
out.get());
CopyVariableWithTensor(*var, *(out.get()), *trans_var);
}
}
}
......
......@@ -54,33 +54,9 @@ constexpr char kGradVarSuffix[] = "@GRAD";
constexpr char kZeroVarSuffix[] = "@ZERO";
// define some kernel priority
/* Define multiple kernel type fallback order*/
extern std::vector<std::tuple<platform::Place, LibraryType>> kKernelPriority;
/**
* @brief Use cpu kernel only
*/
void UseCPU();
/**
* @brief Perfer MKLDNN kernel than Plain CPU kernel
*/
void UseMKLDNN();
/**
* @brief Perfer CUDA kernel than Plain CPU kernel
*/
void UseCUDA();
/**
* @brief Perfer cudnn kernel than Plain CUDA kernel
*/
void UseCUDNN();
/**
* @brief Use all available kernels
*/
void UseALL();
inline std::string GradVarName(const std::string& var_name) {
return var_name + kGradVarSuffix;
}
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
/*
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
......
......@@ -315,9 +315,8 @@ inline void DeserializeFromStream(std::istream& is, Tensor* tensor,
desc.data_type(),
DeserializedDataFunctor(&buf, &cpu_tensor, ctx.GetPlace()));
is.read(static_cast<char*>(buf), cpu_tensor.memory_size());
auto cpu_place = new platform::CPUPlace();
framework::Copy(cpu_tensor, *cpu_place, dev_ctx, tensor);
delete cpu_place;
auto dst_place = dev_ctx.GetPlace();
framework::Copy(cpu_tensor, dst_place, dev_ctx, tensor);
#else
PADDLE_THROW("Unexpected branch");
#endif
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
/*
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
......
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
//
// 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.
/*
Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#edit-mode: -*- python -*-
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#edit-mode: -*- python -*-
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#!/usr/bin/env python
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
# edit-mode: -*- python -*-
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
# edit-mode: -*- python -*-
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
......
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
#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.
#edit-mode: -*- python -*-
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
......
......@@ -135,9 +135,8 @@ op_library(detection_output_op DEPS softmax)
op_library(sequence_softmax_op DEPS softmax)
op_library(sum_op DEPS selected_rows_functor)
op_library(sgd_op DEPS selected_rows_functor)
op_library(print_op DEPS lod_tensor)
op_library(adagrad_op DEPS selected_rows_functor)
op_library(conv_op DEPS vol2col)
op_library(pool_op DEPS pooling)
op_library(maxout_op DEPS maxouting)
op_library(unpool_op DEPS unpooling)
op_library(pool_with_index_op DEPS pooling)
......@@ -148,12 +147,27 @@ op_library(max_sequence_len_op DEPS lod_rank_table)
op_library(sequence_conv_op DEPS context_project)
op_library(sequence_pool_op DEPS sequence_pooling)
op_library(lstm_op DEPS sequence2batch lstm_compute)
op_library(conv_transpose_op DEPS vol2col)
op_library(gru_op DEPS sequence2batch gru_compute)
op_library(recurrent_op DEPS executor)
op_library(warpctc_op DEPS dynload_warpctc sequence_padding math_function)
op_library(warpctc_op DEPS dynload_warpctc sequence_padding sequence_scale math_function)
op_library(cos_sim_op DEPS cos_sim_functor)
op_library(parallel_do_op DEPS executor)
# Regist multiple Kernel to pybind
if (WITH_GPU)
op_library(conv_op SRCS conv_op.cc conv_op.cu.cc conv_cudnn_op.cu.cc DEPS vol2col)
op_library(pool_op SRCS pool_op.cc pool_op.cu.cc pool_cudnn_op.cu.cc DEPS pooling)
op_library(conv_transpose_op SRCS conv_transpose_op.cc conv_transpose_op.cu.cc
conv_transpose_cudnn_op.cu.cc DEPS vol2col)
file(APPEND ${pybind_file} "USE_OP_DEVICE_KERNEL(conv2d, CUDNN);\n")
file(APPEND ${pybind_file} "USE_OP_DEVICE_KERNEL(pool2d, CUDNN);\n")
file(APPEND ${pybind_file} "USE_OP_DEVICE_KERNEL(conv2d_transpose, CUDNN);\n")
else()
op_library(conv_op SRCS conv_op.cc DEPS vol2col)
op_library(pool_op SRCS pool_op.cc DEPS pooling)
op_library(conv_transpose_op SRCS conv_transpose_op.cc DEPS vol2col)
endif()
# FIXME(typhoonzero): save/load depends lodtensor serialization functions
op_library(save_op DEPS lod_tensor)
op_library(load_op DEPS lod_tensor)
......
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#include "paddle/operators/conv_op.h"
namespace paddle {
namespace operators {
class CudnnConv2DOpMaker : public Conv2DOpMaker {
public:
CudnnConv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: Conv2DOpMaker(proto, op_checker) {
AddAttr<int>("workspace_size_MB",
"workspace size for cudnn, in MB, "
"workspace is a section of GPU memory which will be "
"allocated/freed each time the operator runs, larger "
"workspace size can increase performance but also requires "
"better hardware. This size should be chosen carefully.")
.SetDefault(4096);
}
};
class CudnnConv3DOpMaker : public Conv3DOpMaker {
public:
CudnnConv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: Conv3DOpMaker(proto, op_checker) {
AddAttr<int>("workspace_size_MB",
"workspace size for cudnn, in MB, "
"workspace is a section of GPU memory which will be "
"allocated/freed each time the operator runs, larger "
"workspace size can increase performance but also requires "
"better hardware. This size should be chosen carefully.")
.SetDefault(4096);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OP(conv2d_cudnn, ops::ConvOp, ops::CudnnConv2DOpMaker,
conv2d_cudnn_grad, ops::ConvOpGrad);
REGISTER_OP(conv3d_cudnn, ops::ConvOp, ops::CudnnConv3DOpMaker,
conv3d_cudnn_grad, ops::ConvOpGrad);
REGISTER_OP_CPU_KERNEL(
conv2d_cudnn,
ops::GemmConvKernel<paddle::platform::CPUDeviceContext, float>,
ops::GemmConvKernel<paddle::platform::CPUDeviceContext, double>);
REGISTER_OP_CPU_KERNEL(
conv2d_cudnn_grad,
ops::GemmConvGradKernel<paddle::platform::CPUDeviceContext, float>,
ops::GemmConvGradKernel<paddle::platform::CPUDeviceContext, double>);
REGISTER_OP_CPU_KERNEL(
conv3d_cudnn,
ops::GemmConvKernel<paddle::platform::CPUDeviceContext, float>,
ops::GemmConvKernel<paddle::platform::CPUDeviceContext, double>);
REGISTER_OP_CPU_KERNEL(
conv3d_cudnn_grad,
ops::GemmConvGradKernel<paddle::platform::CPUDeviceContext, float>,
ops::GemmConvGradKernel<paddle::platform::CPUDeviceContext, double>);
......@@ -32,7 +32,7 @@ static constexpr size_t kCONV_CUDNN_WORKSPACE_LIMIT_BYTES =
static_cast<size_t>(1024) * 1024 * 1024;
template <typename T>
class CudnnConvOpKernel : public framework::OpKernel<T> {
class CUDNNConvOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
......@@ -147,7 +147,7 @@ class CudnnConvOpKernel : public framework::OpKernel<T> {
};
template <typename T>
class CudnnConvGradOpKernel : public framework::OpKernel<T> {
class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
......@@ -315,17 +315,16 @@ class CudnnConvGradOpKernel : public framework::OpKernel<T> {
} // namespace operators
} // namespace paddle
// TODO(dzhwinter) : below register should be removed
REGISTER_OP_CUDA_KERNEL(conv2d_cudnn,
paddle::operators::CudnnConvOpKernel<float>,
paddle::operators::CudnnConvOpKernel<double>);
REGISTER_OP_CUDA_KERNEL(conv2d_cudnn_grad,
paddle::operators::CudnnConvGradOpKernel<float>,
paddle::operators::CudnnConvGradOpKernel<double>);
REGISTER_OP_CUDA_KERNEL(conv3d_cudnn,
paddle::operators::CudnnConvOpKernel<float>,
paddle::operators::CudnnConvOpKernel<double>);
REGISTER_OP_CUDA_KERNEL(conv3d_cudnn_grad,
paddle::operators::CudnnConvGradOpKernel<float>,
paddle::operators::CudnnConvGradOpKernel<double>);
REGISTER_OP_KERNEL(conv2d, CUDNN, ::paddle::platform::CUDAPlace,
paddle::operators::CUDNNConvOpKernel<float>,
paddle::operators::CUDNNConvOpKernel<double>);
REGISTER_OP_KERNEL(conv2d_grad, CUDNN, ::paddle::platform::CUDAPlace,
paddle::operators::CUDNNConvGradOpKernel<float>,
paddle::operators::CUDNNConvGradOpKernel<double>);
REGISTER_OP_KERNEL(conv3d, CUDNN, ::paddle::platform::CUDAPlace,
paddle::operators::CUDNNConvOpKernel<float>,
paddle::operators::CUDNNConvOpKernel<double>);
REGISTER_OP_KERNEL(conv3d_grad, CUDNN, ::paddle::platform::CUDAPlace,
paddle::operators::CUDNNConvGradOpKernel<float>,
paddle::operators::CUDNNConvGradOpKernel<double>);
......@@ -67,6 +67,23 @@ void ConvOp::InferShape(framework::InferShapeContext* ctx) const {
ctx->ShareLoD("Input", "Output");
}
framework::OpKernelType ConvOp::GetExpectedKernelType(
const framework::ExecutionContext& ctx) const {
bool use_cudnn = ctx.Attr<bool>("use_cudnn");
framework::LibraryType library_;
if (use_cudnn) {
library_ = framework::LibraryType::kCUDNN;
} else {
library_ = framework::LibraryType::kPlain;
}
std::string data_format = ctx.Attr<std::string>("data_format");
framework::DataLayout layout_ = framework::StringToDataLayout(data_format);
return framework::OpKernelType(
framework::ToDataType(ctx.Input<Tensor>("Input")->type()), ctx.GetPlace(),
layout_, library_);
}
Conv2DOpMaker::Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput(
......@@ -108,6 +125,26 @@ Conv2DOpMaker::Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
"dilations(h_dilation, w_dilation) of "
"convolution operator.")
.SetDefault({1, 1});
AddAttr<bool>(
"use_cudnn",
"(bool, default false) Only used in cudnn kernel, need install cudnn")
.SetDefault(false);
AddAttr<std::string>(
"data_format",
"(string, default NCHW) Only used in "
"An optional string from: \"NHWC\", \"NCHW\". "
"Defaults to \"NHWC\". Specify the data format of the output data, "
"the input will be transformed automatically. ")
.SetDefault("AnyLayout");
// TODO(dzhwinter): need to registered layout transform function
AddAttr<int>("workspace_size_MB",
"Only used in cudnn kernel. Need set use_cudnn to true."
"workspace size for cudnn, in MB, "
"workspace is a section of GPU memory which will be "
"allocated/freed each time the operator runs, larger "
"workspace size can increase performance but also requires "
"better hardware. This size should be chosen carefully.")
.SetDefault(4096);
AddComment(R"DOC(
Convolution Operator.
......@@ -181,6 +218,25 @@ Conv3DOpMaker::Conv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
"dilations(d_dilation, h_dilation, w_dilation) of "
"convolution operator.")
.SetDefault({1, 1, 1});
AddAttr<bool>(
"use_cudnn",
"(bool, default false) Only used in cudnn kernel, need install cudnn")
.SetDefault(false);
AddAttr<std::string>(
"data_format",
"(string, default NCHW) Only used in "
"An optional string from: \"NHWC\", \"NCHW\". "
"Defaults to \"NHWC\". Specify the data format of the output data, "
"the input will be transformed automatically. ")
.SetDefault("AnyLayout");
// TODO(dzhwinter): need to registered layout transform function
AddAttr<int>("workspace_size_MB",
"Only used in cudnn kernel. workspace size for cudnn, in MB, "
"workspace is a section of GPU memory which will be "
"allocated/freed each time the operator runs, larger "
"workspace size can increase performance but also requires "
"better hardware. This size should be chosen carefully.")
.SetDefault(4096);
AddComment(R"DOC(
Convolution3D Operator.
......@@ -224,6 +280,23 @@ void ConvOpGrad::InferShape(framework::InferShapeContext* ctx) const {
}
}
framework::OpKernelType ConvOpGrad::GetExpectedKernelType(
const framework::ExecutionContext& ctx) const {
bool use_cudnn = ctx.Attr<bool>("use_cudnn");
framework::LibraryType library_;
if (use_cudnn) {
library_ = framework::LibraryType::kCUDNN;
} else {
library_ = framework::LibraryType::kPlain;
}
std::string data_format = ctx.Attr<std::string>("data_format");
framework::DataLayout layout_ = framework::StringToDataLayout(data_format);
return framework::OpKernelType(
framework::ToDataType(ctx.Input<Tensor>("Input")->type()), ctx.GetPlace(),
layout_, library_);
}
} // namespace operators
} // namespace paddle
......
......@@ -62,12 +62,20 @@ class ConvOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override;
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override;
};
class ConvOpGrad : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override;
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override;
};
template <typename DeviceContext, typename T>
......
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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. */
#include "paddle/operators/conv_transpose_op.h"
namespace paddle {
namespace operators {
class CudnnConv2DTransposeOpMaker : public Conv2DTransposeOpMaker {
public:
CudnnConv2DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: Conv2DTransposeOpMaker(proto, op_checker) {
AddAttr<int>("workspace_size_MB",
"workspace size for cudnn, in MB, "
"workspace is a section of GPU memory which will be "
"allocated/freed each time the operator runs, larger "
"workspace size can increase performance but also requires "
"better hardward. This size should be carefully setted.")
.SetDefault(4096);
}
};
class CudnnConv3DTransposeOpMaker : public Conv3DTransposeOpMaker {
public:
CudnnConv3DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: Conv3DTransposeOpMaker(proto, op_checker) {
AddAttr<int>("workspace_size_MB",
"workspace size for cudnn, in MB, "
"workspace is a section of GPU memory which will be "
"allocated/freed each time the operator runs, larger "
"workspace size can increase performance but also requires "
"better hardward. This size should be carefully setted.")
.SetDefault(4096);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OP(conv2d_transpose_cudnn, ops::ConvTransposeOp,
ops::CudnnConv2DTransposeOpMaker, conv2d_transpose_cudnn_grad,
ops::ConvTransposeOpGrad);
REGISTER_OP_CPU_KERNEL(
conv2d_transpose_cudnn,
ops::GemmConvTransposeKernel<paddle::platform::CPUDeviceContext, float>,
ops::GemmConvTransposeKernel<paddle::platform::CPUDeviceContext, double>);
REGISTER_OP_CPU_KERNEL(
conv2d_transpose_cudnn_grad,
ops::GemmConvTransposeGradKernel<paddle::platform::CPUDeviceContext, float>,
ops::GemmConvTransposeGradKernel<paddle::platform::CPUDeviceContext,
double>);
REGISTER_OP(conv3d_transpose_cudnn, ops::ConvTransposeOp,
ops::CudnnConv3DTransposeOpMaker, conv3d_transpose_cudnn_grad,
ops::ConvTransposeOpGrad);
REGISTER_OP_CPU_KERNEL(
conv3d_transpose_cudnn,
ops::GemmConvTransposeKernel<paddle::platform::CPUDeviceContext, float>,
ops::GemmConvTransposeKernel<paddle::platform::CPUDeviceContext, double>);
REGISTER_OP_CPU_KERNEL(
conv3d_transpose_cudnn_grad,
ops::GemmConvTransposeGradKernel<paddle::platform::CPUDeviceContext, float>,
ops::GemmConvTransposeGradKernel<paddle::platform::CPUDeviceContext,
double>);
......@@ -28,10 +28,10 @@ using ScopedFilterDescriptor = platform::ScopedFilterDescriptor;
using ScopedConvolutionDescriptor = platform::ScopedConvolutionDescriptor;
using DataLayout = platform::DataLayout;
static constexpr size_t kConvCudnnWorkspaceLimitBytes = 1024 * 1024 * 1024;
static constexpr size_t kConvCUDNNWorkspaceLimitBytes = 1024 * 1024 * 1024;
template <typename T>
class CudnnConvTransposeOpKernel : public framework::OpKernel<T> {
class CUDNNConvTransposeOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
......@@ -77,7 +77,7 @@ class CudnnConvTransposeOpKernel : public framework::OpKernel<T> {
// ------------------- cudnn conv workspace ---------------------
void* cudnn_workspace = nullptr;
size_t workspace_size_in_bytes; // final workspace to allocate.
size_t workspace_size_limit = kConvCudnnWorkspaceLimitBytes;
size_t workspace_size_limit = kConvCUDNNWorkspaceLimitBytes;
if (user_workspace_size > 0) {
workspace_size_limit = user_workspace_size * 1024 * 1024;
}
......@@ -116,7 +116,7 @@ class CudnnConvTransposeOpKernel : public framework::OpKernel<T> {
};
template <typename T>
class CudnnConvTransposeGradOpKernel : public framework::OpKernel<T> {
class CUDNNConvTransposeGradOpKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
......@@ -161,7 +161,7 @@ class CudnnConvTransposeGradOpKernel : public framework::OpKernel<T> {
cudnnConvolutionBwdFilterAlgo_t filter_algo;
size_t bwd_filter_ws_size, fwd_ws_size;
size_t workspace_size_in_bytes = 0;
size_t workspace_size_limit = kConvCudnnWorkspaceLimitBytes;
size_t workspace_size_limit = kConvCUDNNWorkspaceLimitBytes;
if (user_workspace_size > 0) {
workspace_size_limit = user_workspace_size * 1024 * 1024;
}
......@@ -236,16 +236,16 @@ class CudnnConvTransposeGradOpKernel : public framework::OpKernel<T> {
namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(conv2d_transpose_cudnn,
ops::CudnnConvTransposeOpKernel<float>,
ops::CudnnConvTransposeOpKernel<double>);
REGISTER_OP_CUDA_KERNEL(conv2d_transpose_cudnn_grad,
ops::CudnnConvTransposeGradOpKernel<float>,
ops::CudnnConvTransposeGradOpKernel<double>);
REGISTER_OP_CUDA_KERNEL(conv3d_transpose_cudnn,
ops::CudnnConvTransposeOpKernel<float>,
ops::CudnnConvTransposeOpKernel<double>);
REGISTER_OP_CUDA_KERNEL(conv3d_transpose_cudnn_grad,
ops::CudnnConvTransposeGradOpKernel<float>,
ops::CudnnConvTransposeGradOpKernel<double>);
REGISTER_OP_KERNEL(conv2d_transpose, CUDNN, ::paddle::platform::CUDAPlace,
ops::CUDNNConvTransposeOpKernel<float>,
ops::CUDNNConvTransposeOpKernel<double>);
REGISTER_OP_KERNEL(conv2d_transpose_grad, CUDNN, ::paddle::platform::CUDAPlace,
ops::CUDNNConvTransposeGradOpKernel<float>,
ops::CUDNNConvTransposeGradOpKernel<double>);
REGISTER_OP_KERNEL(conv3d_transpose, CUDNN, ::paddle::platform::CUDAPlace,
ops::CUDNNConvTransposeOpKernel<float>,
ops::CUDNNConvTransposeOpKernel<double>);
REGISTER_OP_KERNEL(conv3d_transpose_grad, CUDNN, ::paddle::platform::CUDAPlace,
ops::CUDNNConvTransposeGradOpKernel<float>,
ops::CUDNNConvTransposeGradOpKernel<double>);
......@@ -58,6 +58,23 @@ void ConvTransposeOp::InferShape(framework::InferShapeContext* ctx) const {
ctx->SetOutputDim("Output", framework::make_ddim(output_shape));
}
framework::OpKernelType ConvTransposeOp::GetExpectedKernelType(
const framework::ExecutionContext& ctx) const {
bool use_cudnn = ctx.Attr<bool>("use_cudnn");
framework::LibraryType library_;
if (use_cudnn) {
library_ = framework::LibraryType::kCUDNN;
} else {
library_ = framework::LibraryType::kPlain;
}
std::string data_format = ctx.Attr<std::string>("data_format");
framework::DataLayout layout_ = framework::StringToDataLayout(data_format);
return framework::OpKernelType(
framework::ToDataType(ctx.Input<Tensor>("Input")->type()), ctx.GetPlace(),
layout_, library_);
}
Conv2DTransposeOpMaker::Conv2DTransposeOpMaker(OpProto* proto,
OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
......@@ -94,6 +111,25 @@ Conv2DTransposeOpMaker::Conv2DTransposeOpMaker(OpProto* proto,
"(vector<int> default:{0, 0}), the paddings(h_pad, w_pad) of convolution "
"transpose operator.")
.SetDefault({0, 0});
AddAttr<bool>(
"use_cudnn",
"(bool, default false) Only used in cudnn kernel, need install cudnn")
.SetDefault(false);
AddAttr<std::string>(
"data_format",
"(string, default NCHW) Only used in "
"An optional string from: \"NHWC\", \"NCHW\". "
"Defaults to \"NHWC\". Specify the data format of the output data, "
"the input will be transformed automatically. ")
.SetDefault("AnyLayout");
// TODO(dzhwinter): need to registered layout transform function
AddAttr<int>("workspace_size_MB",
"Used in cudnn kernel only. workspace size for cudnn, in MB, "
"workspace is a section of GPU memory which will be "
"allocated/freed each time the operator runs, larger "
"workspace size can increase performance but also requires "
"better hardward. This size should be carefully setted.")
.SetDefault(4096);
AddComment(R"DOC(
Convolution2D Transpose Operator.
......@@ -163,6 +199,25 @@ Conv3DTransposeOpMaker::Conv3DTransposeOpMaker(OpProto* proto,
"(vector<int> default:{0, 0, 0}), paddings(d_pad, "
"h_pad, w_pad) of convolution transpose operator.")
.SetDefault({0, 0, 0});
AddAttr<bool>(
"use_cudnn",
"(bool, default false) Only used in cudnn kernel, need install cudnn")
.SetDefault(false);
AddAttr<std::string>(
"data_format",
"(string, default NCHW) Only used in "
"An optional string from: \"NHWC\", \"NCHW\". "
"Defaults to \"NHWC\". Specify the data format of the output data, "
"the input will be transformed automatically. ")
.SetDefault("AnyLayout");
// TODO(dzhwinter): need to registered layout transform function
AddAttr<int>("workspace_size_MB",
"Used in cudnn kernel only. workspace size for cudnn, in MB, "
"workspace is a section of GPU memory which will be "
"allocated/freed each time the operator runs, larger "
"workspace size can increase performance but also requires "
"better hardward. This size should be carefully setted.")
.SetDefault(4096);
AddComment(R"DOC(
Convolution3D Transpose Operator.
......@@ -205,6 +260,23 @@ void ConvTransposeOpGrad::InferShape(framework::InferShapeContext* ctx) const {
}
}
framework::OpKernelType ConvTransposeOpGrad::GetExpectedKernelType(
const framework::ExecutionContext& ctx) const {
bool use_cudnn = ctx.Attr<bool>("use_cudnn");
framework::LibraryType library_;
if (use_cudnn) {
library_ = framework::LibraryType::kCUDNN;
} else {
library_ = framework::LibraryType::kPlain;
}
std::string data_format = ctx.Attr<std::string>("data_format");
framework::DataLayout layout_ = framework::StringToDataLayout(data_format);
return framework::OpKernelType(
framework::ToDataType(ctx.Input<Tensor>("Input")->type()), ctx.GetPlace(),
layout_, library_);
}
} // namespace operators
} // namespace paddle
......
......@@ -42,12 +42,20 @@ class ConvTransposeOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override;
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override;
};
class ConvTransposeOpGrad : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override;
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override;
};
template <typename DeviceContext, typename T>
......
......@@ -87,7 +87,7 @@ bool RPCClient::AsyncGetVariable(const std::string& ep,
return true;
}
bool RPCClient::wait() {
bool RPCClient::Wait() {
bool ok = true;
while (true) {
......@@ -96,7 +96,6 @@ bool RPCClient::wait() {
}
if (!Proceed()) {
LOG(ERROR) << "Get meets CompletionQueue error";
return false;
}
}
......@@ -110,9 +109,9 @@ bool RPCClient::Proceed() {
// request counts.
if (!cq_.Next(&tag, &ok)) {
LOG(ERROR) << "Get meets CompletionQueue error";
return false;
}
req_count_--;
GPR_ASSERT(ok);
PADDLE_ENFORCE(tag);
......@@ -120,12 +119,15 @@ bool RPCClient::Proceed() {
// TODO(gongwb): add more retries.
ClientBase* c = static_cast<ClientBase*>(tag);
if (!c->status_.ok()) {
LOG(ERROR) << "proc param error:" << c->var_h_.String()
<< " grpc error:" << c->status_.error_message();
delete c;
return true;
return false;
}
c->Process();
delete c;
req_count_--;
return true;
}
......@@ -135,8 +137,12 @@ std::shared_ptr<grpc::Channel> RPCClient::GetChannel(const std::string& ep) {
return it->second;
}
grpc::ChannelArguments args;
args.SetMaxSendMessageSize(std::numeric_limits<int>::max());
args.SetMaxReceiveMessageSize(std::numeric_limits<int>::max());
auto ch = std::shared_ptr<grpc::Channel>(
grpc::CreateChannel(ep, grpc::InsecureChannelCredentials()));
grpc::CreateCustomChannel(ep, grpc::InsecureChannelCredentials(), args));
channels_[ep] = ch;
return ch;
......
......@@ -130,7 +130,7 @@ class RPCClient {
const framework::Scope& scope,
const std::string& var_name,
int64_t time_out = 600 * 1000);
bool wait();
bool Wait();
private:
bool Proceed();
......
......@@ -28,12 +28,15 @@ class RequestBase {
public:
explicit RequestBase(sendrecv::SendRecvService::AsyncService* service,
grpc::ServerCompletionQueue* cq)
: service_(service), cq_(cq), status_(PROCESS) {}
: service_(service), cq_(cq), status_(PROCESS) {
PADDLE_ENFORCE(cq_);
}
virtual ~RequestBase() {}
virtual void Process() { assert(false); }
CallStatus Status() { return status_; }
void SetStatus(CallStatus status) { status_ = status; }
virtual std::string GetReqName() { assert(false); }
protected:
grpc::ServerContext ctx_;
......@@ -56,12 +59,14 @@ class RequestSend final : public RequestBase {
virtual ~RequestSend() {}
virtual std::string GetReqName() { return request_.varname(); }
virtual void Process() {
MessageWithName msg_with_name =
std::make_pair(request_.varname(), std::move(request_));
queue_->Push(std::move(msg_with_name));
// TODO(gongwb): check var's info.
responder_.Finish(reply_, grpc::Status::OK, this);
status_ = FINISH;
}
protected:
......@@ -74,20 +79,27 @@ class RequestSend final : public RequestBase {
class RequestGet final : public RequestBase {
public:
explicit RequestGet(sendrecv::SendRecvService::AsyncService* service,
grpc::ServerCompletionQueue* cq, framework::Scope* scope)
: RequestBase(service, cq), responder_(&ctx_), scope_(scope) {
grpc::ServerCompletionQueue* cq, framework::Scope* scope,
const platform::DeviceContext* dev_ctx)
: RequestBase(service, cq),
responder_(&ctx_),
scope_(scope),
dev_ctx_(dev_ctx) {
service_->RequestGetVariable(&ctx_, &request_, &responder_, cq_, cq_, this);
}
virtual ~RequestGet() {}
virtual std::string GetReqName() { return request_.varname(); }
virtual void Process() {
// proc request.
std::string var_name = request_.varname();
auto* var = scope_->FindVar(var_name);
SerializeToMessage(var_name, var, platform::CPUDeviceContext(), &reply_);
SerializeToMessage(var_name, var, *dev_ctx_, &reply_);
// TODO(gongwb): check var's info.
responder_.Finish(reply_, grpc::Status::OK, this);
status_ = FINISH;
}
protected:
......@@ -95,11 +107,14 @@ class RequestGet final : public RequestBase {
sendrecv::VariableMessage reply_;
ServerAsyncResponseWriter<sendrecv::VariableMessage> responder_;
framework::Scope* scope_;
const platform::DeviceContext* dev_ctx_;
};
void AsyncGRPCServer::RunSyncUpdate() {
grpc::ServerBuilder builder;
builder.AddListeningPort(address_, grpc::InsecureServerCredentials());
builder.SetMaxSendMessageSize(std::numeric_limits<int>::max());
builder.SetMaxReceiveMessageSize(std::numeric_limits<int>::max());
builder.RegisterService(&service_);
cq_send_ = builder.AddCompletionQueue();
......@@ -155,22 +170,10 @@ void AsyncGRPCServer::TryToRegisterNewGetOne() {
if (is_shut_down_) {
return;
}
RequestGet* get = new RequestGet(&service_, cq_get_.get(), scope_);
RequestGet* get = new RequestGet(&service_, cq_get_.get(), scope_, dev_ctx_);
VLOG(4) << "create Requestget status:" << get->Status();
}
void AsyncGRPCServer::SetFinishOrDelete(RequestBase*& last) {
std::unique_lock<std::mutex> lock(cq_mutex_);
if (is_shut_down_) {
delete last;
last = NULL;
return;
}
last->SetStatus(FINISH);
return;
}
void AsyncGRPCServer::HandleRequest(bool wait, grpc::ServerCompletionQueue* cq,
std::string cq_name,
std::function<void()> TryToRegisterNewOne) {
......@@ -184,13 +187,19 @@ void AsyncGRPCServer::HandleRequest(bool wait, grpc::ServerCompletionQueue* cq,
break;
}
PADDLE_ENFORCE(tag);
if (wait && !done_) {
Wait();
}
RequestBase* base = (RequestBase*)tag;
// reference:
// https://github.com/tensorflow/tensorflow/issues/5596
// https://groups.google.com/forum/#!topic/grpc-io/xftlRy-IQwM
// https://groups.google.com/forum/#!topic/grpc-io/ywATt88Ef_I
if (!ok) {
VLOG(4) << cq_name << " recv no regular event";
LOG(WARNING) << cq_name << " recv no regular event:argument name"
<< base->GetReqName();
TryToRegisterNewOne();
delete base;
continue;
......@@ -201,7 +210,6 @@ void AsyncGRPCServer::HandleRequest(bool wait, grpc::ServerCompletionQueue* cq,
VLOG(4) << cq_name << " status:" << base->Status();
TryToRegisterNewOne();
base->Process();
SetFinishOrDelete(base);
break;
}
case FINISH: {
......
......@@ -37,7 +37,7 @@ class RequestBase;
class AsyncGRPCServer final : public sendrecv::SendRecvService::Service {
public:
explicit AsyncGRPCServer(std::string address) { address_ = address; }
explicit AsyncGRPCServer(const std::string &address) : address_(address) {}
void RunSyncUpdate();
......@@ -47,6 +47,8 @@ class AsyncGRPCServer final : public sendrecv::SendRecvService::Service {
void SetScope(framework::Scope *scope) { scope_ = scope; }
void SetDevCtx(const platform::DeviceContext *dev_ctx) { dev_ctx_ = dev_ctx; }
const MessageWithName Get() { return this->var_recv_queue_.Pop(); }
void Push(const MessageWithName &msg) { this->var_recv_queue_.Push(msg); }
......@@ -60,7 +62,6 @@ class AsyncGRPCServer final : public sendrecv::SendRecvService::Service {
std::function<void()> TryToRegisterNewOne);
void TryToRegisterNewSendOne();
void TryToRegisterNewGetOne();
void SetFinishOrDelete(RequestBase *&last);
void ShutdownQueue();
private:
......@@ -74,6 +75,7 @@ class AsyncGRPCServer final : public sendrecv::SendRecvService::Service {
std::string address_;
framework::Scope *scope_;
const platform::DeviceContext *dev_ctx_;
// received variable from RPC, operators fetch variable from this queue.
SimpleBlockQueue<MessageWithName> var_recv_queue_;
......
......@@ -81,23 +81,6 @@ struct ElementwiseAddGradFunctor {
}
};
template <typename T>
struct ElementwiseAddOneGradFunctor {
template <typename Device, typename X, typename Y, typename Z, typename dX,
typename dY, typename dZ>
void operator()(Device d, X x, Y y, Z z, dX dx, dY dy, dZ dz) {
auto dz_e = framework::EigenVector<T>::Flatten(*dz);
if (dx) {
auto dx_e = framework::EigenVector<T>::Flatten(*dx);
dx_e.device(d) = dz_e;
}
if (dy) {
auto dy_e = framework::EigenVector<T>::Flatten(*dy);
dy_e.device(d) = dz_e.sum();
}
}
};
template <typename T>
struct ElementwiseAddBroadCastGradFunctor {
template <typename Device, typename X, typename Y, typename Z, typename dX,
......@@ -142,7 +125,6 @@ class ElementwiseAddGradKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
ElementwiseGradCompute<DeviceContext, T, ElementwiseAddGradFunctor<T>,
ElementwiseAddOneGradFunctor<T>,
ElementwiseAddBroadCastGradFunctor<T>,
ElementwiseAddBroadCast2GradFunctor<T>>(ctx);
}
......
......@@ -107,7 +107,6 @@ class ElementwiseDivGradKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
ElementwiseGradCompute<DeviceContext, T, ElementwiseDivGradFunctor<T>,
ElementwiseDivGradFunctor<T>,
ElementwiseDivBroadCastGradFunctor<T>,
ElementwiseDivBroadCast2GradFunctor<T>>(ctx);
}
......
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