tf.reduce_sum用法

 計算張量維度上的元素之和。

沿給定的“軸”減小“ input_tensor”。 除非“ keepdims”為真，否則對於“軸”中的每個條目，張量的秩都會降低1。 如果`keepdims`為true，則減小的維度保留為長度1。
如果`axis`為None，則縮小所有維度，並返回帶有單個元素的張量。

def reduce_sum_v1(input_tensor,
                  axis=None,
                  keepdims=None,
                  name=None,
                  reduction_indices=None,
                  keep_dims=None):
  """Computes the sum of elements across dimensions of a tensor.

  Reduces `input_tensor` along the dimensions given in `axis`.
  Unless `keepdims` is true, the rank of the tensor is reduced by 1 for each
  entry in `axis`. If `keepdims` is true, the reduced dimensions
  are retained with length 1.

  If `axis` is None, all dimensions are reduced, and a
  tensor with a single element is returned.

  For example:

  ```python
  x = tf.constant([[1, 1, 1], [1, 1, 1]])
  tf.reduce_sum(x)  # 6
  tf.reduce_sum(x, 0)  # [2, 2, 2]
  tf.reduce_sum(x, 1)  # [3, 3]
  tf.reduce_sum(x, 1, keepdims=True)  # [[3], [3]]
  tf.reduce_sum(x, [0, 1])  # 6
  ```

  Args:
    input_tensor: The tensor to reduce. Should have numeric type.
    axis: The dimensions to reduce. If `None` (the default),
      reduces all dimensions. Must be in the range
      `[-rank(input_tensor), rank(input_tensor))`.
    keepdims: If true, retains reduced dimensions with length 1.
    name: A name for the operation (optional).
    reduction_indices: The old (deprecated) name for axis.
    keep_dims: Deprecated alias for `keepdims`.

  Returns:
    The reduced tensor, of the same dtype as the input_tensor.

  @compatibility(numpy)
  Equivalent to np.sum apart the fact that numpy upcast uint8 and int32 to
  int64 while tensorflow returns the same dtype as the input.
  @end_compatibility
  """