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538f028e
编写于
10月 09, 2019
作者:
S
ShenLiang
提交者:
Yi Liu
10月 09, 2019
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电子邮件补丁
差异文件
fix the en_doc, test=develop test=document_fix test=document_preview (#20327)
上级
b76a6dee
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
49 addition
and
41 deletion
+49
-41
paddle/fluid/API.spec
paddle/fluid/API.spec
+6
-6
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+33
-26
python/paddle/fluid/layers/tensor.py
python/paddle/fluid/layers/tensor.py
+10
-9
未找到文件。
paddle/fluid/API.spec
浏览文件 @
538f028e
...
...
@@ -126,7 +126,7 @@ paddle.fluid.initializer.NumpyArrayInitializer.__init__ (ArgSpec(args=['self', '
paddle.fluid.embedding (ArgSpec(args=['input', 'size', 'is_sparse', 'is_distributed', 'padding_idx', 'param_attr', 'dtype'], varargs=None, keywords=None, defaults=(False, False, None, None, 'float32')), ('document', 'd4ac047e0d5e6b7b1c5ff6ef7d7cfff5'))
paddle.fluid.one_hot (ArgSpec(args=['input', 'depth', 'allow_out_of_range'], varargs=None, keywords=None, defaults=(False,)), ('document', 'eef66730acc806088f9e8ba90252bda1'))
paddle.fluid.layers.fc (ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(1, None, None, None, None)), ('document', '0dc8181f14a33f91fbae9385a9b3d9fd'))
paddle.fluid.layers.center_loss (ArgSpec(args=['input', 'label', 'num_classes', 'alpha', 'param_attr', 'update_center'], varargs=None, keywords=None, defaults=(True,)), ('document', '
7129819d94625c6104054e8187768589
'))
paddle.fluid.layers.center_loss (ArgSpec(args=['input', 'label', 'num_classes', 'alpha', 'param_attr', 'update_center'], varargs=None, keywords=None, defaults=(True,)), ('document', '
18112442f55b5862bbec8feee841c905
'))
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')), ('document', 'd8e405486a1e4e189b51d6ee28d67b1e'))
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)), ('document', '6d3ee14da70adfa36d85c40b18716ef2'))
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)), ('document', 'c37d51aad655c8a9f9b045c64717320a'))
...
...
@@ -212,10 +212,10 @@ paddle.fluid.layers.resize_bilinear (ArgSpec(args=['input', 'out_shape', 'scale'
paddle.fluid.layers.resize_trilinear (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'actual_shape', 'align_corners', 'align_mode', 'data_format'], varargs=None, keywords=None, defaults=(None, None, None, None, True, 1, 'NCDHW')), ('document', '5b4d0f823f94c260fe5e6f7eec60a797'))
paddle.fluid.layers.resize_nearest (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'actual_shape', 'align_corners', 'data_format'], varargs=None, keywords=None, defaults=(None, None, None, None, True, 'NCHW')), ('document', '0107a5cbae1aef3f381d3d769a6068eb'))
paddle.fluid.layers.gather (ArgSpec(args=['input', 'index', 'overwrite'], varargs=None, keywords=None, defaults=(True,)), ('document', 'f985c9b66e3aec96fa753a8eb44c991c'))
paddle.fluid.layers.gather_nd (ArgSpec(args=['input', 'index', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '
3cc24f9cf135770aa6263dba25b457
f9'))
paddle.fluid.layers.gather_nd (ArgSpec(args=['input', 'index', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '
a7d625028525167b138106f574dffd
f9'))
paddle.fluid.layers.scatter (ArgSpec(args=['input', 'index', 'updates', 'name', 'overwrite'], varargs=None, keywords=None, defaults=(None, True)), ('document', '69b22affd4a6326502af166f04c095ab'))
paddle.fluid.layers.scatter_nd_add (ArgSpec(args=['ref', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '
c2fa5ee7484b52b95a28abf1d8827cd0
'))
paddle.fluid.layers.scatter_nd (ArgSpec(args=['index', 'updates', 'shape', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '
14b5449ce42f8ff4ac4ce79b41c86cc5
'))
paddle.fluid.layers.scatter_nd_add (ArgSpec(args=['ref', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '
2607b5c9369fbc52f208de066a80fc25
'))
paddle.fluid.layers.scatter_nd (ArgSpec(args=['index', 'updates', 'shape', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '
e43f1d3a938b35da246aea3e72a020ec
'))
paddle.fluid.layers.sequence_scatter (ArgSpec(args=['input', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'abe3f714120117a5a3d3e639853932bf'))
paddle.fluid.layers.random_crop (ArgSpec(args=['x', 'shape', 'seed'], varargs=None, keywords=None, defaults=(None,)), ('document', '042af0b8abea96b40c22f6e70d99e042'))
paddle.fluid.layers.mean_iou (ArgSpec(args=['input', 'label', 'num_classes'], varargs=None, keywords=None, defaults=None), ('document', 'e714b4aa7993dfe9c1a38886875dbaac'))
...
...
@@ -307,7 +307,7 @@ paddle.fluid.layers.deformable_conv (ArgSpec(args=['input', 'offset', 'mask', 'n
paddle.fluid.layers.unfold (ArgSpec(args=['x', 'kernel_sizes', 'strides', 'paddings', 'dilations', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None)), ('document', '3f884662ad443d9ecc2b3734b4f61ad6'))
paddle.fluid.layers.deformable_roi_pooling (ArgSpec(args=['input', 'rois', 'trans', 'no_trans', 'spatial_scale', 'group_size', 'pooled_height', 'pooled_width', 'part_size', 'sample_per_part', 'trans_std', 'position_sensitive', 'name'], varargs=None, keywords=None, defaults=(False, 1.0, [1, 1], 1, 1, None, 1, 0.1, False, None)), ('document', '47c5d1c890b36fa00ff3285c9398f613'))
paddle.fluid.layers.filter_by_instag (ArgSpec(args=['ins', 'ins_tag', 'filter_tag', 'is_lod'], varargs=None, keywords=None, defaults=None), ('document', '7703a2088af8de4128b143ff1164ca4a'))
paddle.fluid.layers.shard_index (ArgSpec(args=['input', 'index_num', 'nshards', 'shard_id', 'ignore_value'], varargs=None, keywords=None, defaults=(-1,)), ('document', '
c4969dd6bf164f9e6a90414ea4f4e5ad
'))
paddle.fluid.layers.shard_index (ArgSpec(args=['input', 'index_num', 'nshards', 'shard_id', 'ignore_value'], varargs=None, keywords=None, defaults=(-1,)), ('document', '
3c6b30e9cd57b38d4a5fa1ade887f779
'))
paddle.fluid.layers.hard_swish (ArgSpec(args=['x', 'threshold', 'scale', 'offset', 'name'], varargs=None, keywords=None, defaults=(6.0, 6.0, 3.0, None)), ('document', '6a5152a7015c62cb8278fc24cb456459'))
paddle.fluid.layers.mse_loss (ArgSpec(args=['input', 'label'], varargs=None, keywords=None, defaults=None), ('document', 'd9ede6469288636e1b3233b461a165c9'))
paddle.fluid.layers.uniform_random (ArgSpec(args=['shape', 'dtype', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', -1.0, 1.0, 0)), ('document', '126ede8ce0e751244b1b54cd359c89d7'))
...
...
@@ -341,7 +341,7 @@ paddle.fluid.layers.linspace (ArgSpec(args=['start', 'stop', 'num', 'dtype'], va
paddle.fluid.layers.zeros_like (ArgSpec(args=['x', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd88a23bcdc443719b3953593f7cef14a'))
paddle.fluid.layers.ones_like (ArgSpec(args=['x', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd18d42059c6b189cbd3fab2fcb206c15'))
paddle.fluid.layers.diag (ArgSpec(args=['diagonal'], varargs=None, keywords=None, defaults=None), ('document', '88a15e15f0098d549f07a01eaebf9ce3'))
paddle.fluid.layers.eye (ArgSpec(args=['num_rows', 'num_columns', 'batch_shape', 'dtype'], varargs=None, keywords=None, defaults=(None, None, 'float32')), ('document', '
25389d1e239a5d1cda66298f908ec549
'))
paddle.fluid.layers.eye (ArgSpec(args=['num_rows', 'num_columns', 'batch_shape', 'dtype'], varargs=None, keywords=None, defaults=(None, None, 'float32')), ('document', '
60cdc70ae43ba69fae36d720ef3016a1
'))
paddle.fluid.layers.While ('paddle.fluid.layers.control_flow.While', ('document', '50110155608a00f43d3d3fd1be41dcb4'))
paddle.fluid.layers.While.__init__ (ArgSpec(args=['self', 'cond', 'is_test', 'name'], varargs=None, keywords=None, defaults=(False, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.layers.While.block (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
538f028e
...
...
@@ -375,8 +375,10 @@ def center_loss(input,
"""
**Center loss Cost layer**
This layer accepts input (deep features,the output of the last hidden layer)
and target label and return the center loss cost
This OP accepts input (deep features,the output of the last hidden layer)
and target label and return the center loss cost. The average of the
distances of each sample in the mini-batch from the center of the
corresponding category is calculated as the center loss.
For deep features, :math:`X`, and target labels, :math:`Y`, the equation is:
...
...
@@ -385,9 +387,9 @@ def center_loss(input,
Out = \\frac{1}{2}(X - Y)^2
Args:
input (Variable): a 2-D tensor with shape[N x M].
input (Variable): a 2-D tensor with shape[N x M].
Its dtype should be float32 or float64.
label (Variable): the groud truth which is a 2-D tensor
with shape[N x 1],where N is the batch size.
with shape[N x 1],where N is the batch size.
Its dtype should be int32.
num_classes (int): the number of classification categories.
alpha (float|Variable): learning rate of centers.
param_attr (ParamAttr): Attribute initializer of centers.
...
...
@@ -401,8 +403,8 @@ def center_loss(input,
import paddle.fluid as fluid
input = fluid.
layers.
data(name='x',shape=[20,30],dtype='float32')
label = fluid.
layers.
data(name='y',shape=[20,1],dtype='int64')
input = fluid.data(name='x',shape=[20,30],dtype='float32')
label = fluid.data(name='y',shape=[20,1],dtype='int64')
num_classes = 1000
alpha = 0.01
param_attr = fluid.initializer.Xavier(uniform=False)
...
...
@@ -9573,10 +9575,11 @@ def gather_nd(input, index, name=None):
= [23]
Args:
input (Variable): The source input
index (Variable): The index input with rank > 1, index.shape[-1] <= input.rank
input (Variable): The source input. Its dtype should be int32, int64, float32, float64.
index (Variable): The index input with rank > 1, index.shape[-1] <= input.rank.
Its dtype should be int32, int64.
name (str|None): A name for this layer(optional). If set None, the
layer will be named automatically
layer will be named automatically
.
Returns:
output (Variable): A tensor with the shape index.shape[:-1] + input.shape[index.shape[-1]:]
...
...
@@ -9586,8 +9589,8 @@ def gather_nd(input, index, name=None):
.. code-block:: python
import paddle.fluid as fluid
x = fluid.
layers.
data(name='x', shape=[3, 4, 5], dtype='float32')
index = fluid.
layers.
data(name='index', shape=[2, 2], dtype='int32')
x = fluid.data(name='x', shape=[3, 4, 5], dtype='float32')
index = fluid.data(name='index', shape=[2, 2], dtype='int32')
output = fluid.layers.gather_nd(x, index)
"""
...
...
@@ -9662,11 +9665,14 @@ def scatter_nd_add(ref, index, updates, name=None):
**Scatter_nd_add Layer**
Output is obtained by applying sparse addition to a single value
or slice in a Variable. :attr:`ref` is a Tensor with rank :math:`R`
or slice in a Variable.
:attr:`ref` is a Tensor with rank :math:`R`
and :attr:`index` is a Tensor with rank :math:`K` . Thus, :attr:`index`
has shape :math:`[i_0, i_1, ..., i_{K-2}, Q]` where :math:`Q \leq R` . :attr:`updates`
is a Tensor with rank :math:`K - 1 + R - Q` and its
shape is :math:`index.shape[:-1] + ref.shape[index.shape[-1]:]` .
According to the :math:`[i_0, i_1, ..., i_{K-2}]` of :attr:`index` ,
add the corresponding :attr:`updates` slice to the :attr:`ref` slice
which is obtained by the last one dimension of :attr:`index` .
...
...
@@ -9698,15 +9704,15 @@ def scatter_nd_add(ref, index, updates, name=None):
output = [[67, 19], [-16, -27]]
Args:
ref (Variable): The ref input.
ref (Variable): The ref input.
Its dtype should be int32, int64, float32, float64.
index (Variable): The index input with rank > 1 and index.shape[-1] <= ref.rank.
Its dtype should be int32 or int64 as it is used as indexes.
updates (Variable): The updated value of scatter_nd_add op, and it must have the same type
as ref. It must have the shape index.shape[:-1] + ref.shape[index.shape[-1]:]
name (str|None): The output variable name.
Default None
.
updates (Variable): The updated value of scatter_nd_add op, and it must have the same
d
type
as ref. It must have the shape index.shape[:-1] + ref.shape[index.shape[-1]:]
.
name (str|None): The output variable name.
If set None, the layer will be named automatically
.
Returns:
output (Variable): The output is a tensor with the same shape and type as ref.
output (Variable): The output is a tensor with the same shape and
d
type as ref.
Examples:
...
...
@@ -9714,9 +9720,9 @@ def scatter_nd_add(ref, index, updates, name=None):
import paddle.fluid as fluid
ref = fluid.
layers.data(name='ref', shape=[3, 5, 9, 10], dtype='float32', append_batch_size=False
)
index = fluid.
layers.data(name='index', shape=[3, 2], dtype='int32', append_batch_size=False
)
updates = fluid.
layers.data(name='update', shape=[3, 9, 10], dtype='float32', append_batch_size=False
)
ref = fluid.
data(name='ref', shape=[3, 5, 9, 10], dtype='float32'
)
index = fluid.
data(name='index', shape=[3, 2], dtype='int32'
)
updates = fluid.
data(name='update', shape=[3, 9, 10], dtype='float32'
)
output = fluid.layers.scatter_nd_add(ref, index, updates)
"""
...
...
@@ -9755,10 +9761,10 @@ def scatter_nd(index, updates, shape, name=None):
Args:
index (Variable): The index input with rank > 1 and index.shape[-1] <= len(shape).
Its dtype should be int32 or int64 as it is used as indexes.
updates (Variable): The updated value of scatter_nd op.
updates (Variable): The updated value of scatter_nd op.
Its dtype should be int32, int64, float32, float64.
It must have the shape index.shape[:-1] + shape[index.shape[-1]:]
shape(tuple|list): Shape of output tensor.
name (str|None): The output variable name.
Default None
.
name (str|None): The output variable name.
If set None, the layer will be named automatically
.
Returns:
output (Variable): The output is a tensor with the same type as :attr:`updates` .
...
...
@@ -9769,8 +9775,8 @@ def scatter_nd(index, updates, shape, name=None):
import paddle.fluid as fluid
index = fluid.
layers.data(name='index', shape=[3, 2], dtype='int64', append_batch_size=False
)
updates = fluid.
layers.data(name='update', shape=[3, 9, 10], dtype='float32', append_batch_size=False
)
index = fluid.
data(name='index', shape=[3, 2], dtype='int64'
)
updates = fluid.
data(name='update', shape=[3, 9, 10], dtype='float32'
)
shape = [3, 5, 9, 10]
output = fluid.layers.scatter_nd(index, updates, shape)
...
...
@@ -15359,7 +15365,7 @@ def deformable_roi_pooling(input,
def shard_index(input, index_num, nshards, shard_id, ignore_value=-1):
"""
This
function
recomputes the `input` indices according to the offset of the
This
operator
recomputes the `input` indices according to the offset of the
shard. The length of the indices is evenly divided into N shards, and if
the `shard_id` matches the shard with the input index inside, the index is
recomputed on the basis of the shard offset, elsewise it is set to
...
...
@@ -15404,7 +15410,8 @@ def shard_index(input, index_num, nshards, shard_id, ignore_value=-1):
.. code-block:: python
import paddle.fluid as fluid
label = fluid.layers.data(name="label", shape=[1], dtype="int64")
batch_size = 32
label = fluid.data(name="label", shape=[batch_size, 1], dtype="int64")
shard_label = fluid.layers.shard_index(input=label,
index_num=20,
nshards=2,
...
...
python/paddle/fluid/layers/tensor.py
浏览文件 @
538f028e
...
...
@@ -1018,25 +1018,26 @@ def eye(num_rows, num_columns=None, batch_shape=None, dtype='float32'):
If None, default: num_rows.
batch_shape(list(int)): If provided, the returned tensor will have a leading
batch size of this shape.
dtype(string): 'float32'|'int32'|..., the data type of the returned tensor.
dtype(string): The data type of the returned tensor.
It should be int32, int64, float16, float32, float64.
Returns:
Variable: An identity
t
ensor of shape batch_shape + [num_rows, num_columns].
Variable: An identity
Tensor or LoDT
ensor of shape batch_shape + [num_rows, num_columns].
Examples:
.. code-block:: python
import paddle.fluid as fluid
data = fluid.layers.eye(3, dtype='int32')
# [[1, 0, 0]
data = fluid.layers.eye(3, dtype='int32')
# [[1, 0, 0]
# [0, 1, 0]
# [0, 0, 1]]
# [0, 0, 1]]
data = fluid.layers.eye(2, 3, dtype='int32')
# [[1, 0, 0]
# [[1, 0, 0]
# [0, 1, 0]]
data = fluid.layers.eye(2, batch_shape=[3])
data = fluid.layers.eye(2, batch_shape=[3])
# Construct a batch of 3 identity tensors, each 2 x 2.
# data[i, :, :] is a 2 x 2 identity tensor, i = 0, 1, 2.
...
...
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