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体验新版 GitCode,发现更多精彩内容 >>
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6b83845c
编写于
2月 19, 2019
作者:
X
xuezhong
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差异文件
update for backward compatibility
test=develop
上级
d3286603
变更
2
隐藏空白更改
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2 changed file
with
19 addition
and
19 deletion
+19
-19
paddle/fluid/API.spec
paddle/fluid/API.spec
+1
-1
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+18
-18
未找到文件。
paddle/fluid/API.spec
浏览文件 @
6b83845c
...
...
@@ -71,7 +71,7 @@ paddle.fluid.initializer.NumpyArrayInitializer.__init__ ArgSpec(args=['self', 'v
paddle.fluid.layers.fc ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'act', 'is_test', 'name'], varargs=None, keywords=None, defaults=(1, None, None, None, False, None))
paddle.fluid.layers.embedding ArgSpec(args=['input', 'size', 'is_sparse', 'is_distributed', 'padding_idx', 'param_attr', 'dtype'], varargs=None, keywords=None, defaults=(False, False, None, None, 'float32'))
paddle.fluid.layers.dynamic_lstm ArgSpec(args=['input', 'size', 'h_0', 'c_0', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, None, None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'float32', None))
paddle.fluid.layers.dynamic_lstmp ArgSpec(args=['input', 'size', 'proj_size', '
h_0', 'c_0', 'param_attr', 'bias_attr', 'use_peepholes', 'cell_clip', 'proj_clip', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'proj_activation', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, None, None, None, True, None, None, False, 'sigmoid', 'tanh', 'tanh', 'identity', 'float32'
, None))
paddle.fluid.layers.dynamic_lstmp ArgSpec(args=['input', 'size', 'proj_size', '
param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'proj_activation', 'dtype', 'name', 'h_0', 'c_0', 'cell_clip', 'proj_clip'], varargs=None, keywords=None, defaults=(None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'tanh', 'float32', None, None, None, None
, None))
paddle.fluid.layers.dynamic_gru ArgSpec(args=['input', 'size', 'param_attr', 'bias_attr', 'is_reverse', 'gate_activation', 'candidate_activation', 'h_0', 'origin_mode'], varargs=None, keywords=None, defaults=(None, None, False, 'sigmoid', 'tanh', None, False))
paddle.fluid.layers.gru_unit ArgSpec(args=['input', 'hidden', 'size', 'param_attr', 'bias_attr', 'activation', 'gate_activation', 'origin_mode'], varargs=None, keywords=None, defaults=(None, None, 'tanh', 'sigmoid', False))
paddle.fluid.layers.linear_chain_crf ArgSpec(args=['input', 'label', 'param_attr'], varargs=None, keywords=None, defaults=(None,))
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
6b83845c
...
...
@@ -659,20 +659,20 @@ def lstm(input,
def
dynamic_lstmp
(
input
,
size
,
proj_size
,
h_0
=
None
,
c_0
=
None
,
param_attr
=
None
,
bias_attr
=
None
,
use_peepholes
=
True
,
cell_clip
=
None
,
proj_clip
=
None
,
is_reverse
=
False
,
gate_activation
=
'sigmoid'
,
cell_activation
=
'tanh'
,
candidate_activation
=
'tanh'
,
proj_activation
=
'
identity
'
,
proj_activation
=
'
tanh
'
,
dtype
=
'float32'
,
name
=
None
):
name
=
None
,
h_0
=
None
,
c_0
=
None
,
cell_clip
=
None
,
proj_clip
=
None
):
"""
**Dynamic LSTMP Layer**
...
...
@@ -740,12 +740,6 @@ def dynamic_lstmp(input,
mini-batch, D is the hidden size.
size(int): 4 * hidden size.
proj_size(int): The size of projection output.
h_0(Variable): The initial hidden state is an optional input, default is zero.
This is a tensor with shape (N x D), where N is the
batch size and D is the projection size.
c_0(Variable): The initial cell state is an optional input, default is zero.
This is a tensor with shape (N x D), where N is the
batch size. `h_0` and `c_0` can be NULL but only at the same time.
param_attr(ParamAttr|None): The parameter attribute for the learnable
hidden-hidden weight and projection weight.
...
...
@@ -780,11 +774,6 @@ def dynamic_lstmp(input,
the bias is initialized zero. Default: None.
use_peepholes(bool): Whether to enable diagonal/peephole connections,
default `True`.
cell_clip(float): If provided the cell state is clipped
by this value prior to the cell output activation.
proj_clip(float): If `num_proj > 0` and `proj_clip` is
provided, then the projected values are clipped elementwise to within
`[-proj_clip, proj_clip]`.
is_reverse(bool): Whether to compute reversed LSTM, default `False`.
gate_activation(str): The activation for input gate, forget gate and
output gate. Choices = ["sigmoid", "tanh", "relu",
...
...
@@ -796,10 +785,21 @@ def dynamic_lstmp(input,
default "tanh".
proj_activation(str): The activation for projection output.
Choices = ["sigmoid", "tanh", "relu", "identity"],
default "
identity
".
default "
tanh
".
dtype(str): Data type. Choices = ["float32", "float64"], default "float32".
name(str|None): A name for this layer(optional). If set None, the layer
will be named automatically.
h_0(Variable): The initial hidden state is an optional input, default is zero.
This is a tensor with shape (N x D), where N is the
batch size and D is the projection size.
c_0(Variable): The initial cell state is an optional input, default is zero.
This is a tensor with shape (N x D), where N is the
batch size. `h_0` and `c_0` can be NULL but only at the same time.
cell_clip(float): If provided the cell state is clipped
by this value prior to the cell output activation.
proj_clip(float): If `num_proj > 0` and `proj_clip` is
provided, then the projected values are clipped elementwise to within
`[-proj_clip, proj_clip]`.
Returns:
tuple: A tuple of two output variable: the projection of hidden state,
\
...
...
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