提交 7e140d87 编写于 作者: Z Zhang Ting 提交者: hong

modified doc of group_norm, test=develop, test=document_fix (#20234)

上级 2087f771
...@@ -188,7 +188,7 @@ paddle.fluid.layers.beam_search (ArgSpec(args=['pre_ids', 'pre_scores', 'ids', ' ...@@ -188,7 +188,7 @@ paddle.fluid.layers.beam_search (ArgSpec(args=['pre_ids', 'pre_scores', 'ids', '
paddle.fluid.layers.row_conv (ArgSpec(args=['input', 'future_context_size', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(None, None)), ('document', '1d8a1c8b686b55631ba1b77805e4eacf')) paddle.fluid.layers.row_conv (ArgSpec(args=['input', 'future_context_size', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(None, None)), ('document', '1d8a1c8b686b55631ba1b77805e4eacf'))
paddle.fluid.layers.multiplex (ArgSpec(args=['inputs', 'index'], varargs=None, keywords=None, defaults=None), ('document', '2c4d1ae83da6ed35e3b36ba1b3b51d23')) paddle.fluid.layers.multiplex (ArgSpec(args=['inputs', 'index'], varargs=None, keywords=None, defaults=None), ('document', '2c4d1ae83da6ed35e3b36ba1b3b51d23'))
paddle.fluid.layers.layer_norm (ArgSpec(args=['input', 'scale', 'shift', 'begin_norm_axis', 'epsilon', 'param_attr', 'bias_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(True, True, 1, 1e-05, None, None, None, None)), ('document', '79797f827d89ae72c77960e9696883a9')) paddle.fluid.layers.layer_norm (ArgSpec(args=['input', 'scale', 'shift', 'begin_norm_axis', 'epsilon', 'param_attr', 'bias_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(True, True, 1, 1e-05, None, None, None, None)), ('document', '79797f827d89ae72c77960e9696883a9'))
paddle.fluid.layers.group_norm (ArgSpec(args=['input', 'groups', 'epsilon', 'param_attr', 'bias_attr', 'act', 'data_layout', 'name'], varargs=None, keywords=None, defaults=(1e-05, None, None, None, 'NCHW', None)), ('document', '65231cc8281815124934b1439fbb750c')) paddle.fluid.layers.group_norm (ArgSpec(args=['input', 'groups', 'epsilon', 'param_attr', 'bias_attr', 'act', 'data_layout', 'name'], varargs=None, keywords=None, defaults=(1e-05, None, None, None, 'NCHW', None)), ('document', '87dd4b818f102bc1a780e1804c28bd38'))
paddle.fluid.layers.spectral_norm (ArgSpec(args=['weight', 'dim', 'power_iters', 'eps', 'name'], varargs=None, keywords=None, defaults=(0, 1, 1e-12, None)), ('document', '9461e67095a6fc5d568fb2ce8fef66ff')) paddle.fluid.layers.spectral_norm (ArgSpec(args=['weight', 'dim', 'power_iters', 'eps', 'name'], varargs=None, keywords=None, defaults=(0, 1, 1e-12, None)), ('document', '9461e67095a6fc5d568fb2ce8fef66ff'))
paddle.fluid.layers.softmax_with_cross_entropy (ArgSpec(args=['logits', 'label', 'soft_label', 'ignore_index', 'numeric_stable_mode', 'return_softmax', 'axis'], varargs=None, keywords=None, defaults=(False, -100, True, False, -1)), ('document', '54e1675aa0364f4a78fa72804ec0f413')) paddle.fluid.layers.softmax_with_cross_entropy (ArgSpec(args=['logits', 'label', 'soft_label', 'ignore_index', 'numeric_stable_mode', 'return_softmax', 'axis'], varargs=None, keywords=None, defaults=(False, -100, True, False, -1)), ('document', '54e1675aa0364f4a78fa72804ec0f413'))
paddle.fluid.layers.smooth_l1 (ArgSpec(args=['x', 'y', 'inside_weight', 'outside_weight', 'sigma'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'cbe8940643ac80ef75e1abdfbdb09e88')) paddle.fluid.layers.smooth_l1 (ArgSpec(args=['x', 'y', 'inside_weight', 'outside_weight', 'sigma'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'cbe8940643ac80ef75e1abdfbdb09e88'))
......
...@@ -4306,30 +4306,39 @@ def group_norm(input, ...@@ -4306,30 +4306,39 @@ def group_norm(input,
Refer to `Group Normalization <https://arxiv.org/abs/1803.08494>`_ . Refer to `Group Normalization <https://arxiv.org/abs/1803.08494>`_ .
Args: Parameters:
input(Variable): The input tensor variable. input(Variable): 4-D Tensor, the data type is float32 or float64.
groups(int): The number of groups that divided from channels. groups(int): The number of groups that divided from channels, the data type
epsilon(float): The small value added to the variance to prevent is int32.
division by zero. epsilon(float, optional): The small value added to the variance to prevent
param_attr(ParamAttr|None): The parameter attribute for the learnable division by zero, the data type is float32. Default: 1e-05.
scale :math:`g`. If it is set to False, no scale will be added to the output units. param_attr(ParamAttr|bool, optional): ParamAttr object that specifies weight parameter
If it is set to None, the bias is initialized one. Default: None. attribute. If a bool type, only False is supported, which means there is no weight parameter.
bias_attr(ParamAttr|None): The parameter attribute for the learnable Default: None, the default weight parameter attribute is used. For more information, please
bias :math:`b`. If it is set to False, no bias will be added to the output units. refer to :ref:`api_guide_ParamAttr` .
If it is set to None, the bias is initialized zero. Default: None. bias_attr(ParamAttr|bool, optional): ParamAttr object that specifies bias parameter
act(str): Activation to be applied to the output of group normalizaiton. attribute. If a bool type, only False is supported, which means there is no bias parameter.
data_layout(string, default NCHW): NCHW(num_batch, channels, h, w) or NHWC(num_batch, h, w, channels). Default: None, the default bias parameter attribute is used. For more information, please
name (str): The name of this layer. It is optional. refer to :ref:`api_guide_ParamAttr` .
act(str, optional): Activation to be applied to the output of group normalizaiton.
data_layout(str, optional): The data format of the input and output data. An optional string
from: `"NCHW"`, `"NHWC"`. When it is `"NCHW"`, the data is stored in the order of:
`[batch_size, channels, height, width]`. Default: "NCHW".
name (str, optional): The default value is None. Normally there is no need for user to set this
property. For more information, please refer to :ref:`api_guide_Name` .
Returns: Returns:
Variable: A tensor variable which is the result after applying group normalization on the input. Variable: A 4-D Tensor has same data type and data format with `input`.
Raises:
ValueError: If `data_layout` is neither 'NCHW' nor 'NHWC'.
Examples: Examples:
.. code-block:: python
>>> import paddle.fluid as fluid import paddle.fluid as fluid
>>> data = fluid.layers.data(name='data', shape=[8, 32, 32], data = fluid.data(name='data', shape=[None, 8, 32, 32], dtype='float32')
>>> dtype='float32') x = fluid.layers.group_norm(input=data, groups=4)
>>> x = fluid.layers.group_norm(input=data, groups=4)
""" """
helper = LayerHelper('group_norm', **locals()) helper = LayerHelper('group_norm', **locals())
dtype = helper.input_dtype() dtype = helper.input_dtype()
......
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