uniform_random_batch_size_like¶
- paddle.fluid.layers.nn. uniform_random_batch_size_like ( input, shape, dtype='float32', input_dim_idx=0, output_dim_idx=0, min=- 1.0, max=1.0, seed=0 ) [source]
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This OP initializes a variable with random values sampled from a uniform distribution in the range [min, max). The input_dim_idx used to get the input dimension value which will be used to resize the output dimension.
*Case 1: Given: input =[[0.946741 , 0.1357001 , 0.38086128]] # input.shape=[1,3] shape=[2,4] result.shape[output_dim_idx] = input.shape[input_dim_idx], output_dim_idx = 0, input_dim_idx = 0, result.shape[0] = input.shape[0], then: result=[[ 0.3443427 , -0.23056602, 0.3477049 , 0.06139076]] # result.shape=[1,4] *Case 2: Given: input =[[0.946741 , 0.1357001 , 0.38086128]] # input.shape=[1,3] shape=[2,4] input_dim_idx=1 output_dim_idx=1 result.shape[output_dim_idx] = input.shape[input_dim_idx], output_dim_idx = 1, input_dim_idx = 1, result.shape[1] = input.shape[1], then: result=[[-0.23133647, -0.84195036, 0.21441269], [-0.08774924, 0.25605237, -0.09403259]] # result.shape=[2,3]
- Parameters
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input (Variable) – A Tensor. Supported data types: float32, float64.
shape (tuple|list) – A python list or python tuple. The shape of the output Tensor, the data type is int.
input_dim_idx (int, optional) – An index used to get the input dimension value which will be used to resize the output dimension. Default 0.
output_dim_idx (int, optional) – An index used to indicate the specific dimension that will be replaced by corresponding input dimension value. Default 0.
min (float, optional) – The lower bound on the range of random values to generate, the min is included in the range. Default -1.0.
max (float, optional) – The upper bound on the range of random values to generate, the max is excluded in the range. Default 1.0.
seed (int, optional) – Random seed used for generating samples. 0 means use a seed generated by the system.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, optional) – The data type of output Tensor. Supported data types: float32, float64. Default float32.
- Returns
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A Tensor of the specified shape filled with uniform_random values. The shape of the Tensor is determined by the shape parameter and the specified dimension of the input Tensor.
- Return type
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Variable
Examples
import paddle import paddle.fluid as fluid paddle.enable_static() # example 1: input = fluid.data(name="input", shape=[1, 3], dtype='float32') out_1 = fluid.layers.uniform_random_batch_size_like(input, [2, 4]) # out_1.shape=[1, 4] # example 2: out_2 = fluid.layers.uniform_random_batch_size_like(input, [2, 4], input_dim_idx=1, output_dim_idx=1) # out_2.shape=[2, 3]