parameters: (input_tensor, reduction_indices=None, keep_dims=False,
                 name=None)
return_statement: return gen_math_ops._all(input_tensor, _ReductionDims(input_tensor,
                                                          reduction_indices),
                             keep_dims, name=name)
docstring: Computes the "logical and" of elements across dimensions of a tensor.
  
    Reduces `input_tensor` along the dimensions given in `reduction_indices`.
    Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each
    entry in `reduction_indices`. If `keep_dims` is true, the reduced dimensions
    are retained with length 1.
  
    If `reduction_indices` has no entries, all dimensions are reduced, and a
    tensor with a single element is returned.
  
    For example:
  
    ```python
    # 'x' is [[True,  True]
    #         [False, False]]
    tf.reduce_all(x) ==> False
    tf.reduce_all(x, 0) ==> [False, False]
    tf.reduce_all(x, 1) ==> [True, False]
    ```
  
    Args:
      input_tensor: The boolean tensor to reduce.
      reduction_indices: The dimensions to reduce. If `None` (the default),
        reduces all dimensions.
      keep_dims: If true, retains reduced dimensions with length 1.
      name: A name for the operation (optional).
  
    Returns:
      The reduced tensor.
docstring_summary: Computes the "logical and" of elements across dimensions of a tensor.
docstring_tokens: Computes the logical and of elements across dimensions of a tensor .
function: def reduce_all(input_tensor, reduction_indices=None, keep_dims=False,
                 name=None):
    """Computes the "logical and" of elements across dimensions of a tensor.
  
    Reduces `input_tensor` along the dimensions given in `reduction_indices`.
    Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each
    entry in `reduction_indices`. If `keep_dims` is true, the reduced dimensions
    are retained with length 1.
  
    If `reduction_indices` has no entries, all dimensions are reduced, and a
    tensor with a single element is returned.
  
    For example:
  
    ```python
    # 'x' is [[True,  True]
    #         [False, False]]
    tf.reduce_all(x) ==> False
    tf.reduce_all(x, 0) ==> [False, False]
    tf.reduce_all(x, 1) ==> [True, False]
    ```
  
    Args:
      input_tensor: The boolean tensor to reduce.
      reduction_indices: The dimensions to reduce. If `None` (the default),
        reduces all dimensions.
      keep_dims: If true, retains reduced dimensions with length 1.
      name: A name for the operation (optional).
  
    Returns:
      The reduced tensor.
    """
    return gen_math_ops._all(input_tensor, _ReductionDims(input_tensor,
                                                          reduction_indices),
                             keep_dims, name=name)
function_tokens: def reduce_all ( input_tensor , reduction_indices = None , keep_dims = False , name = None ) : return gen_math_ops . _all ( input_tensor , _ReductionDims ( input_tensor , reduction_indices ) , keep_dims , name = name )