oneflow.nn.LogSoftmax¶
-
class
oneflow.nn.
LogSoftmax
(dim: Optional[int] = None)¶ Applies the LogSoftmax function to an n-dimensional input Tensor. The LogSoftmax formulation can be simplified as:
\[\text{LogSoftmax}(x_{i}) = \log\left(\frac{\exp(x_i) }{ \sum_j \exp(x_j)} \right) = x_i - \log({ \sum_j \exp(x_j)})\]- Parameters
dim (int) – A dimension along which LogSoftmax will be computed.
- Shape:
Input: \((N, *)\) where * means, any number of additional dimensions
Output: \((N, *)\), same shape as the input
For example:
>>> import numpy as np >>> import oneflow as flow >>> m = flow.nn.LogSoftmax(dim=1) >>> x = flow.Tensor( ... np.array( ... [[ 0.4296, -1.1957, 2.5463], ... [ 1.2552, -1.5747, 0.6923]] ... ) ... ) >>> out = m(x) >>> out tensor([[-2.2513, -3.8766, -0.1346], [-0.4877, -3.3176, -1.0506]], dtype=oneflow.float32)