m53297601
/
Paddle
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

fix doc of eye、gather_nd、scatter_nd、scatter_nd_add、center_loss (#19990)

Browse Source 
* fix doc, test=document_fix test=document_preview
fix-python-transpose
ShenLiang 6 years ago committed by Dong Daxiang
parent 0ec2c081d9
commit c5cff9971a
3 changed files with 36 additions and 29 deletions
Show Stats Download Patch File Download Diff File

10
paddle/fluid/API.spec
Unescape View File

@ -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', '9f61b78e88de4a33c7f9f13f6ebf3a4c'))
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', '3cc24f9cf135770aa6263dba25b457f9'))
paddle.fluid.layers.gather_nd (ArgSpec(args=['input', 'index', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '7092e3da56bc91dd7b0cb967cfff101a'))
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', 'b797ea7aa9e7d5c0e54b208d3bde0db6'))
paddle.fluid.layers.scatter_nd (ArgSpec(args=['index', 'updates', 'shape', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '15feefb05913d8bd14fbc586cd4c603c'))
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'))
@ -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'))

36
python/paddle/fluid/layers/nn.py
Unescape View File

@ -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.
@ -9537,10 +9539,11 @@ 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]:]
@ -9626,11 +9629,14 @@ 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` .
@ -9662,15 +9668,15 @@ 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 dtype
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 dtype as ref.
Examples:
@ -9719,10 +9725,10 @@ 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` .

19
python/paddle/fluid/layers/tensor.py
Unescape View File

@ -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 tensor of shape batch_shape + [num_rows, num_columns].
Variable: An identity Tensor or LoDTensor 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.

Write Preview
Loading…
Cancel
Save