tensorflow squeeze函数理解

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本文详细介绍了squeeze函数的功能，该函数用于从张量形状中移除所有大小为1的维度。此外，还介绍了如何指定特定的维度进行移除，并通过示例展示了在实际场景中的应用。

squeeze

def squeeze(input, axis=None, name=None, squeeze_dims=None):
  # pylint: disable=redefined-builtin
  """Removes dimensions of size 1 from the shape of a tensor.

  Given a tensor `input`, this operation returns a tensor of the same type with
  all dimensions of size 1 removed. If you don't want to remove all size 1
  dimensions, you can remove specific size 1 dimensions by specifying
  `axis`.

  For example:

  ```prettyprint
  # 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
  shape(squeeze(t)) ==> [2, 3]
            ```

  Or, to remove specific size 1 dimensions:

  ```prettyprint
  # 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
  shape(squeeze(t, [2, 4])) ==> [1, 2, 3, 1]
  ```

  Args:
    input: A `Tensor`. The `input` to squeeze.
    axis: An optional list of `ints`. Defaults to `[]`.
      If specified, only squeezes the dimensions listed. The dimension
      index starts at 0. It is an error to squeeze a dimension that is not 1.
    name: A name for the operation (optional).
    squeeze_dims: Deprecated keyword argument that is now axis.

  Returns:
    A `Tensor`. Has the same type as `input`.
    Contains the same data as `input`, but has one or more dimensions of
    size 1 removed.

  Raises:
    ValueError: When both `squeeze_dims` and `axis` are specified.
  """
  if squeeze_dims is not None:
    if axis is not None:
      raise ValueError("Cannot specify both 'squeeze_dims' and 'axis'")
    axis = squeeze_dims
  if np.isscalar(axis):
    axis = [axis]
  return gen_array_ops._squeeze(input, axis, name)

应用场景

假设输入数据类型为numpy的ndarray，样本数为100，即y_true的shape为（100,），但是经过sigmoid变换后的y_pred的shape为(100,1)，此时即可使用squeeze函数将y_pred的dimension中的1去掉，结果为(100,)。当然，在输入之前将y_true变换为(100,1)也是可行的，只要保证y_true和y_pred的dimension一致即可。