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b1448ded
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b1448ded
编写于
9月 25, 2018
作者:
M
minqiyang
浏览文件
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浏览文件
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电子邮件补丁
差异文件
Port clip and clip_by_norm op to nn and change API.sepc
上级
0ff5d8b0
变更
3
显示空白变更内容
内联
并排
Showing
3 changed file
with
98 addition
and
121 deletion
+98
-121
paddle/fluid/API.spec
paddle/fluid/API.spec
+6
-6
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+92
-113
python/paddle/fluid/layers/ops.py
python/paddle/fluid/layers/ops.py
+0
-2
未找到文件。
paddle/fluid/API.spec
浏览文件 @
b1448ded
...
...
@@ -170,6 +170,12 @@ paddle.fluid.layers.elementwise_mul ArgSpec(args=['x', 'y', 'out', 'axis', 'use_
paddle.fluid.layers.elementwise_max ArgSpec(args=['x', 'y', 'out', 'axis', 'use_mkldnn', 'act', 'name'], varargs=None, keywords=None, defaults=(None, -1, False, None, None))
paddle.fluid.layers.elementwise_min ArgSpec(args=['x', 'y', 'out', 'axis', 'use_mkldnn', 'act', 'name'], varargs=None, keywords=None, defaults=(None, -1, False, None, None))
paddle.fluid.layers.elementwise_pow ArgSpec(args=['x', 'y', 'out', 'axis', 'use_mkldnn', 'act', 'name'], varargs=None, keywords=None, defaults=(None, -1, False, None, None))
paddle.fluid.layers.logical_and ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.logical_or ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.logical_xor ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.logical_not ArgSpec(args=['x', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.clip ArgSpec(args=['x', 'min', 'max', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.clip_by_norm ArgSpec(args=['x', 'max_norm', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.data ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True))
paddle.fluid.layers.open_files ArgSpec(args=['filenames', 'shapes', 'lod_levels', 'dtypes', 'thread_num', 'buffer_size', 'pass_num', 'is_test'], varargs=None, keywords=None, defaults=(None, None, 1, None))
paddle.fluid.layers.read_file ArgSpec(args=['reader'], varargs=None, keywords=None, defaults=None)
...
...
@@ -235,12 +241,6 @@ paddle.fluid.layers.is_empty ArgSpec(args=['x', 'cond'], varargs=None, keywords=
paddle.fluid.layers.mean ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.mul ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sigmoid_cross_entropy_with_logits ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.clip ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.clip_by_norm ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logical_and ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logical_or ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logical_xor ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logical_not ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.uniform_random_batch_size_like ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.gaussian_random ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sampling_id ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
b1448ded
...
...
@@ -29,114 +29,29 @@ from .. import unique_name
from
functools
import
reduce
__all__
=
[
'fc'
,
'embedding'
,
'dynamic_lstm'
,
'dynamic_lstmp'
,
'dynamic_gru'
,
'gru_unit'
,
'linear_chain_crf'
,
'crf_decoding'
,
'cos_sim'
,
'cross_entropy'
,
'square_error_cost'
,
'chunk_eval'
,
'sequence_conv'
,
'conv2d'
,
'conv3d'
,
'sequence_pool'
,
'sequence_softmax'
,
'softmax'
,
'pool2d'
,
'pool3d'
,
'batch_norm'
,
'beam_search_decode'
,
'conv2d_transpose'
,
'conv3d_transpose'
,
'sequence_expand'
,
'sequence_expand_as'
,
'sequence_pad'
,
'lstm_unit'
,
'reduce_sum'
,
'reduce_mean'
,
'reduce_max'
,
'reduce_min'
,
'reduce_prod'
,
'sequence_first_step'
,
'sequence_last_step'
,
'dropout'
,
'split'
,
'ctc_greedy_decoder'
,
'edit_distance'
,
'l2_normalize'
,
'matmul'
,
'topk'
,
'warpctc'
,
'sequence_reshape'
,
'transpose'
,
'im2sequence'
,
'nce'
,
'hsigmoid'
,
'beam_search'
,
'row_conv'
,
'multiplex'
,
'layer_norm'
,
'softmax_with_cross_entropy'
,
'smooth_l1'
,
'one_hot'
,
'autoincreased_step_counter'
,
'reshape'
,
'squeeze'
,
'unsqueeze'
,
'lod_reset'
,
'lrn'
,
'pad'
,
'pad_constant_like'
,
'label_smooth'
,
'roi_pool'
,
'dice_loss'
,
'image_resize'
,
'image_resize_short'
,
'resize_bilinear'
,
'gather'
,
'scatter'
,
'sequence_scatter'
,
'random_crop'
,
'mean_iou'
,
'relu'
,
'log'
,
'crop'
,
'rank_loss'
,
'elu'
,
'relu6'
,
'pow'
,
'stanh'
,
'hard_sigmoid'
,
'swish'
,
'prelu'
,
'brelu'
,
'leaky_relu'
,
'soft_relu'
,
'flatten'
,
'sequence_mask'
,
'stack'
,
'pad2d'
,
'unstack'
,
'sequence_enumerate'
,
'expand'
,
'sequence_concat'
,
'scale'
,
'elementwise_add'
,
'elementwise_div'
,
'elementwise_sub'
,
'elementwise_mul'
,
'elementwise_max'
,
'elementwise_min'
,
'elementwise_pow'
,
'logical_and'
,
'logical_or'
,
'logical_xor'
,
'logical_not'
,
'fc'
,
'embedding'
,
'dynamic_lstm'
,
'dynamic_lstmp'
,
'dynamic_gru'
,
'gru_unit'
,
'linear_chain_crf'
,
'crf_decoding'
,
'cos_sim'
,
'cross_entropy'
,
'square_error_cost'
,
'chunk_eval'
,
'sequence_conv'
,
'conv2d'
,
'conv3d'
,
'sequence_pool'
,
'sequence_softmax'
,
'softmax'
,
'pool2d'
,
'pool3d'
,
'batch_norm'
,
'beam_search_decode'
,
'conv2d_transpose'
,
'conv3d_transpose'
,
'sequence_expand'
,
'sequence_expand_as'
,
'sequence_pad'
,
'lstm_unit'
,
'reduce_sum'
,
'reduce_mean'
,
'reduce_max'
,
'reduce_min'
,
'reduce_prod'
,
'sequence_first_step'
,
'sequence_last_step'
,
'dropout'
,
'split'
,
'ctc_greedy_decoder'
,
'edit_distance'
,
'l2_normalize'
,
'matmul'
,
'topk'
,
'warpctc'
,
'sequence_reshape'
,
'transpose'
,
'im2sequence'
,
'nce'
,
'hsigmoid'
,
'beam_search'
,
'row_conv'
,
'multiplex'
,
'layer_norm'
,
'softmax_with_cross_entropy'
,
'smooth_l1'
,
'one_hot'
,
'autoincreased_step_counter'
,
'reshape'
,
'squeeze'
,
'unsqueeze'
,
'lod_reset'
,
'lrn'
,
'pad'
,
'pad_constant_like'
,
'label_smooth'
,
'roi_pool'
,
'dice_loss'
,
'image_resize'
,
'image_resize_short'
,
'resize_bilinear'
,
'gather'
,
'scatter'
,
'sequence_scatter'
,
'random_crop'
,
'mean_iou'
,
'relu'
,
'log'
,
'crop'
,
'rank_loss'
,
'elu'
,
'relu6'
,
'pow'
,
'stanh'
,
'hard_sigmoid'
,
'swish'
,
'prelu'
,
'brelu'
,
'leaky_relu'
,
'soft_relu'
,
'flatten'
,
'sequence_mask'
,
'stack'
,
'pad2d'
,
'unstack'
,
'sequence_enumerate'
,
'expand'
,
'sequence_concat'
,
'scale'
,
'elementwise_add'
,
'elementwise_div'
,
'elementwise_sub'
,
'elementwise_mul'
,
'elementwise_max'
,
'elementwise_min'
,
'elementwise_pow'
,
'logical_and'
,
'logical_or'
,
'logical_xor'
,
'logical_not'
,
'clip'
,
'clip_by_norm'
]
...
...
@@ -6622,7 +6537,7 @@ for func in [
])
def
_logical_op
(
op_name
,
x
,
y
,
name
=
None
,
out
=
None
,
binary_op
=
True
):
def
_logical_op
(
op_name
,
x
,
y
,
out
=
None
,
name
=
None
,
binary_op
=
True
):
helper
=
LayerHelper
(
op_name
,
**
locals
())
assert
x
.
dtype
==
y
.
dtype
...
...
@@ -6645,7 +6560,7 @@ def _logical_op(op_name, x, y, name=None, out=None, binary_op=True):
@
templatedoc
()
def
logical_and
(
x
,
y
,
name
=
None
,
out
=
None
):
def
logical_and
(
x
,
y
,
out
=
None
,
name
=
None
):
"""
${comment}
...
...
@@ -6664,7 +6579,7 @@ def logical_and(x, y, name=None, out=None):
@
templatedoc
()
def
logical_or
(
x
,
y
,
name
=
None
,
out
=
None
):
def
logical_or
(
x
,
y
,
out
=
None
,
name
=
None
):
"""
${comment}
...
...
@@ -6683,7 +6598,7 @@ def logical_or(x, y, name=None, out=None):
@
templatedoc
()
def
logical_xor
(
x
,
y
,
name
=
None
,
out
=
None
):
def
logical_xor
(
x
,
y
,
out
=
None
,
name
=
None
):
"""
${comment}
...
...
@@ -6702,7 +6617,7 @@ def logical_xor(x, y, name=None, out=None):
@
templatedoc
()
def
logical_not
(
x
,
name
=
None
,
out
=
None
):
def
logical_not
(
x
,
out
=
None
,
name
=
None
):
"""
${comment}
...
...
@@ -6717,3 +6632,67 @@ def logical_not(x, name=None, out=None):
return
_logical_op
(
op_name
=
"logical_not"
,
x
=
x
,
y
=
None
,
name
=
name
,
out
=
out
,
binary_op
=
False
)
@
templatedoc
()
def
clip
(
x
,
min
,
max
,
name
=
None
):
"""
${comment}
Args:
x(${x_type}): ${x_comment}
min(${min_type}): ${min_comment}
max(${max_type}): ${max_comment}
name(basestring|None): Name of the output.
Returns:
out(${out_type}): ${out_comment}
"""
helper
=
LayerHelper
(
"clip"
,
**
locals
())
if
name
is
None
:
out
=
helper
.
create_tmp_variable
(
dtype
=
x
.
dtype
)
else
:
out
=
helper
.
create_variable
(
name
=
name
,
dtype
=
x
.
dtype
,
persistable
=
False
)
helper
.
append_op
(
type
=
"clip"
,
inputs
=
{
"X"
:
x
},
attrs
=
{
"min"
:
min
,
"max"
:
max
},
outputs
=
{
"Out"
:
out
})
return
out
@
templatedoc
()
def
clip_by_norm
(
x
,
max_norm
,
name
=
None
):
"""
${comment}
Args:
x(${x_type}): ${x_comment}
max_norm(${max_norm_type}): ${max_norm_comment}
name(basestring|None): Name of the output.
Returns:
out(${out_type}): ${out_comment}
"""
helper
=
LayerHelper
(
"clip_by_norm"
,
**
locals
())
if
name
is
None
:
out
=
helper
.
create_tmp_variable
(
dtype
=
x
.
dtype
)
else
:
out
=
helper
.
create_variable
(
name
=
name
,
dtype
=
x
.
dtype
,
persistable
=
False
)
helper
.
append_op
(
type
=
"clip_by_norm"
,
inputs
=
{
"X"
:
x
},
attrs
=
{
"max_norm"
:
max_norm
},
outputs
=
{
"Out"
:
out
})
return
out
python/paddle/fluid/layers/ops.py
浏览文件 @
b1448ded
...
...
@@ -39,8 +39,6 @@ __all__ = [
'mean'
,
'mul'
,
'sigmoid_cross_entropy_with_logits'
,
'clip'
,
'clip_by_norm'
,
'uniform_random_batch_size_like'
,
'gaussian_random'
,
'sampling_id'
,
...
...
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