mindspore.nn.Flatten
- class mindspore.nn.Flatten[source]
Flatten layer for the input.
Flattens a tensor without changing dimension of batch size on the 0-th axis.
- Inputs:
x (Tensor) - Tensor of shape \((N, \ldots)\) to be flattened. The data type is Number. The shape is \((N,*)\) where \(*\) means, any number of additional dimensions and the shape can’t be ().
- Outputs:
Tensor, the shape of the output tensor is \((N, X)\), where \(X\) is the product of the remaining dimensions.
- Raises
TypeError – If x is not a subclass of Tensor.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> x = Tensor(np.array([[[1.2, 1.2], [2.1, 2.1]], [[2.2, 2.2], [3.2, 3.2]]]), mindspore.float32) >>> net = nn.Flatten() >>> output = net(x) >>> print(output) [[1.2 1.2 2.1 2.1] [2.2 2.2 3.2 3.2]] >>> print(f"before flatten the x shape is {x.shape}") before flatten the x shape is (2, 2, 2) >>> print(f"after flatten the output shape is {output.shape}") after flatten the output shape is (2, 4)