x (Tensor): : the input tensor, it's data type should be float32, float64, int32, int64.
x (Tensor): The input tensor, it's data type should be float32, float64, int32, int64.
name(str, optional): name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
y (Tensor): The input tensor, it's data type should be float32, float64, int32, int64.
dtype(str, optional): the data type of the output tensor, can be float32, float64, int32, int64.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
param_attr(ParamAttr, optional): the parameter attribute for learnable weights(Parameter) of this layer.
dtype (str, optional): The data type of the output tensor, can be float32, float64, int32, int64.
param_attr (ParamAttr, optional): The parameter attribute for learnable weights(Parameter) of this layer. For more information, please refer to :ref:`api_fluid_ParamAttr`.
bias_attr (ParamAttr, optional): The parameter attribute for learnable bias(Bias) of this layer. For more information, please refer to :ref:`api_fluid_ParamAttr`.
label (Tensor): The label value corresponding to input, it's data type should be int32, int64.
learning_rate (Tensor|float): The learning rate, can be a Tensor or a float value. Default is 1e-03.
axis (int, optional): The axis along which to operate. Default is 0.
epsilon (float, optional): Small float added to denominator to avoid dividing by zero. Default is 1e-05.
is_test (bool, optional): A flag indicating whether execution is in test phase. Default is False, means not in test phase.
shape (Tensor|tuple|list): Shape of the Tensor. If shape is a list or tuple, the elements of it should be integers or Tensors with shape [1]. If shape is Tensor, it should be an 1-D Tensor .
keep_dim (bool): Whether to reserve the reduced dimension in the output Tensor. The result tensor will have one fewer dimension than the input unless keep_dim is true. Default is False.
filter_size (tuple|list|int): The size of convolving kernel. It can be a single integer or a tuple/list containing two integers, representing the height and width of the convolution window respectively. If it is a single integer, the height and width are equal to the integer.
padding (tuple|int): The padding size. It can be a single integer or a tuple containing two integers, representing the size of padding added to the height and width of the input. If it is a single integer, the both sides of padding are equal to the integer. Default is 0.
include_sublayers (bool, optional): Whether include the sublayers. If True, return list includes the sublayers weights. Default is True.
stride (tuple|int): The stride size. It can be a single integer or a tuple containing two integers, representing the strides of the convolution along the height and width. If it is a single integer, the height and width are equal to the integer. Default is 1.
groups (int, optional): The group number of convolution layer. When group=n, the input and convolution kernels are divided into n groups equally, the first group of convolution kernels and the first group of inputs are subjected to convolution calculation, the second group of convolution kernels and the second group of inputs are subjected to convolution calculation, ……, the nth group of convolution kernels and the nth group of inputs perform convolution calculations. Default is 1.
regularization (WeightDecayRegularizer, optional) – The strategy of regularization. There are two method: :ref:`api_fluid_regularizer_L1Decay` 、 :ref:`api_fluid_regularizer_L2Decay` . If a parameter has set regularizer using :ref:`api_fluid_ParamAttr` already, the regularization setting here in optimizer will be ignored for this parameter. Otherwise, the regularization setting here in optimizer will take effect. Default None, meaning there is no regularization.
grad_clip (GradientClipBase, optional): Gradient cliping strategy, it's an instance of some derived class of ``GradientClipBase`` . There are three cliping strategies ( :ref:`api_fluid_clip_GradientClipByGlobalNorm` , :ref:`api_fluid_clip_GradientClipByNorm` , :ref:`api_fluid_clip_GradientClipByValue` ). Default None, meaning there is no gradient clipping.
dilation (tuple|int) – The dilation size. It can be a single integer or a tuple containing two integers, representing the height and width of dilation of the convolution kernel elements. If it is a single integer,the height and width of dilation are equal to the integer. Default is 1.
stop_gradient (bool, optional) – A boolean that mentions whether gradient should flow. Default is True, means stop calculate gradients.
"""
"""
common_args_cn="""
common_args_cn="""
x (Tensor) - 输入的Tensor，数据类型为：float32、float64、int32、int64。
x (Tensor) - 输入的Tensor，数据类型为：float32、float64、int32、int64。
