Function reduce_euclidean_norm

tensorflow/python/ops/math_ops.py:1568–1605

Computes the Euclidean norm 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 len

(input_tensor, axis=None, keepdims=False, name=None)

@tf_export("math.reduce_euclidean_norm")
def reduce_euclidean_norm(input_tensor, axis=None, keepdims=False, name=None):
  """Computes the Euclidean norm 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, 2, 3], [1, 1, 1]])
  tf.reduce_euclidean_norm(x)  # sqrt(17)
  tf.reduce_euclidean_norm(x, 0)  # [sqrt(2), sqrt(5), sqrt(10)]
  tf.reduce_euclidean_norm(x, 1)  # [sqrt(14), sqrt(3)]
  tf.reduce_euclidean_norm(x, 1, keepdims=True)  # [[sqrt(14)], [sqrt(3)]]
  tf.reduce_euclidean_norm(x, [0, 1])  # sqrt(17)
  ```

  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).

  Returns:
    The reduced tensor, of the same dtype as the input_tensor.
  """
  return _may_reduce_to_scalar(
      keepdims, axis,
      gen_math_ops.euclidean_norm(
          input_tensor, _ReductionDims(input_tensor, axis), keepdims,
          name=name))


@tf_export(v1=["math.count_nonzero", "count_nonzero"])