Flatten

class torch.nn.modules.flatten.Flatten(start_dim=1, end_dim=-1) [source]

Flattens a contiguous range of dims into a tensor.

For use with Sequential, see torch.flatten() for details.

Shape:

• Input: $(*, S_{\text{start}},..., S_{i}, ..., S_{\text{end}}, *)$,’ where $S_{i}$ is the size at dimension $i$ and $*$ means any number of dimensions including none.
• Output: $(*, \prod_{i=\text{start}}^{\text{end}} S_{i}, *)$.

Parameters

• start_dim (int) – first dim to flatten (default = 1).
• end_dim (int) – last dim to flatten (default = -1).

Examples::

>>> input = torch.randn(32, 1, 5, 5)
>>> # With default parameters
>>> m = nn.Flatten()
>>> output = m(input)
>>> output.size()
torch.Size([32, 25])
>>> # With non-default parameters
>>> m = nn.Flatten(0, 2)
>>> output = m(input)
>>> output.size()
torch.Size([160, 5])

extra_repr() [source]

Returns the extra representation of the module.

Return type

str

forward(input) [source]

Runs the forward pass.

Return type

Tensor