gaussian_random_batch_size_like

paddle.fluid.layers.nn. gaussian_random_batch_size_like ( input, shape, input_dim_idx=0, output_dim_idx=0, mean=0.0, std=1.0, seed=0, dtype='float32' ) [source]

Warning: API “paddle.fluid.layers.nn.gaussian_random_batch_size_like” is deprecated since 1.8.0, and will be removed in future versions. Please use “paddle.normal” instead.

Used to initialize tensors with gaussian random generator. The default mean of the distribution is 0, and default standard deviation (std) of the distribution is 1.0. Uers can set mean and std via input arguments.

Args:

input (Variable): Tensor whose input_dim_idx’th dimension specifies the batch_size shape (tuple|list): The shape of the output input_dim_idx (int): default 0. The index of input’s batch size dimension output_dim_idx (int): default 0. The index of output’s batch size dimension mean (float): (float, default 0.0) The mean (or center) of the gaussian distribution std (float): (float, default 1.0) The standard deviation (std, or spread) of the gaussian distribution seed (int): (int, default 0) Random seed of generator.0 means don’t specify random seed.Note that if seed is not 0, this operator will always generate the same random numbers every time dtype(np.dtype|core.VarDesc.VarType|str): The type of output data, float32 or float_64.

Returns:

out (Variable): Tensor of specified shape will be filled with the specified value

Examples:
import paddle.fluid as fluid
input = fluid.data(name="input", shape=[13, 11], dtype='float32')

out = fluid.layers.gaussian_random_batch_size_like(
    input, shape=[-1, 11], mean=1.0, std=2.0)