mindspore.nn.Flatten
- class mindspore.nn.Flatten(start_dim=1, end_dim=- 1)[source]
Flatten the input Tensor along dimensions from start_dim to end_dim.
- Parameters
- Inputs:
x (Tensor) - The input Tensor to be flattened.
- Outputs:
Tensor. If no dimensions are flattened, returns the original x, otherwise return the flattened Tensor. If x is a 0-dimensional Tensor, a 1-dimensional Tensor will be returned.
- Raises
TypeError – If x is not a Tensor.
TypeError – If start_dim or end_dim is not int.
ValueError – If start_dim is greater than end_dim after canonicalized.
ValueError – If start_dim or end_dim is not in range of [-x.dim, x.dim-1]. For example, the default values are used for the args and the input is a 0-dimensional or 1-dimensional Tensor.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore >>> from mindspore import Tensor, nn >>> import numpy as np >>> 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)