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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

- Incorrect links, empty cells, or wrong formats.

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- Minor inconsistencies between the UI and descriptions.

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Risk Warnings

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mindspore.nn.Flatten

class mindspore.nn.Flatten

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 $(N,\dots )$ to be flattened. The data type is Number. The shape is $(N,\ast )$ where $\ast$ 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)