parameters: (input_tensor,
                    axis=None,
                    keepdims=None,
                    name=None,
                    reduction_indices=None,
                    keep_dims=None)
return_statement: return reduce_min(input_tensor, axis, keepdims, name)
docstring: Computes the minimum 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.
  
    Args:
      input_tensor: The tensor to reduce. Should have real 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.
  
    @compatibility(numpy)
    Equivalent to np.min
    @end_compatibility
docstring_summary: Computes the minimum of elements across dimensions of a tensor.
docstring_tokens: Computes the minimum of elements across dimensions of a tensor .
function: def reduce_min_v1(input_tensor,
                    axis=None,
                    keepdims=None,
                    name=None,
                    reduction_indices=None,
                    keep_dims=None):
    """Computes the minimum 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.
  
    Args:
      input_tensor: The tensor to reduce. Should have real 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.
  
    @compatibility(numpy)
    Equivalent to np.min
    @end_compatibility
    """
    axis = deprecation.deprecated_argument_lookup("axis", axis,
                                                  "reduction_indices",
                                                  reduction_indices)
    keepdims = deprecation.deprecated_argument_lookup("keepdims", keepdims,
                                                      "keep_dims", keep_dims)
    return reduce_min(input_tensor, axis, keepdims, name)
function_tokens: def reduce_min_v1 ( input_tensor , axis = None , keepdims = None , name = None , reduction_indices = None , keep_dims = None ) : axis = deprecation . deprecated_argument_lookup ( "axis" , axis , "reduction_indices" , reduction_indices ) keepdims = deprecation . deprecated_argument_lookup ( "keepdims" , keepdims , "keep_dims" , keep_dims ) return reduce_min ( input_tensor , axis , keepdims , name )