Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into add_py36_py37_dockerfile

panyx0718-patch-1
minqiyang 7 years ago
commit e5ca829437

@ -13,6 +13,7 @@
// limitations under the License.
#include "paddle/fluid/memory/allocation/best_fit_allocator.h"
#include <random>
#include <thread> // NOLINT
#include <vector>
#include "gtest/gtest.h"

@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <random>
#include <thread> // NOLINT
#include <vector>
#include "gtest/gtest.h"

@ -7702,6 +7702,15 @@ def logical_and(x, y, out=None, name=None):
Returns:
out(${out_type}): ${out_comment}
Examples:
.. code-block:: python
left = fluid.layers.data(
name='left', shape=[1], dtype='int32')
right = fluid.layers.data(
name='right', shape=[1], dtype='int32')
result = fluid.layers.logical_and(x=left, y=right)
"""
return _logical_op(
@ -7721,6 +7730,15 @@ def logical_or(x, y, out=None, name=None):
Returns:
out(${out_type}): ${out_comment}
Examples:
.. code-block:: python
left = fluid.layers.data(
name='left', shape=[1], dtype='int32')
right = fluid.layers.data(
name='right', shape=[1], dtype='int32')
result = fluid.layers.logical_or(x=left, y=right)
"""
return _logical_op(
@ -7740,6 +7758,15 @@ def logical_xor(x, y, out=None, name=None):
Returns:
out(${out_type}): ${out_comment}
Examples:
.. code-block:: python
left = fluid.layers.data(
name='left', shape=[1], dtype='int32')
right = fluid.layers.data(
name='right', shape=[1], dtype='int32')
result = fluid.layers.logical_xor(x=left, y=right)
"""
return _logical_op(
@ -7758,6 +7785,13 @@ def logical_not(x, out=None, name=None):
Returns:
out(${out_type}): ${out_comment}
Examples:
.. code-block:: python
left = fluid.layers.data(
name='left', shape=[1], dtype='int32')
result = fluid.layers.logical_not(x=left)
"""
return _logical_op(
@ -7777,6 +7811,13 @@ def clip(x, min, max, name=None):
Returns:
out(${out_type}): ${out_comment}
Examples:
.. code-block:: python
input = fluid.layers.data(
name='data', shape=[1], dtype='float32')
reward = fluid.layers.clip(x=input, min=-1.0, max=1.0)
"""
helper = LayerHelper("clip", **locals())
@ -7809,6 +7850,13 @@ def clip_by_norm(x, max_norm, name=None):
Returns:
out(${out_type}): ${out_comment}
Examples:
.. code-block:: python
input = fluid.layers.data(
name='data', shape=[1], dtype='float32')
reward = fluid.layers.clip_by_norm(x=input, max_norm=1.0)
"""
helper = LayerHelper("clip_by_norm", **locals())

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