parameters: (t1, out_format, dtype=None)
return_statement: return _compute_unary_elt_eise_op(f, t1, out_format, dtype)
docstring: Takes the hyperbolic tangent of each input in the tensor.
  
          This is applied to all elements in the tensor not just non-zeros.
  
          Parameters
          ------------
          t1: tensor, array_like
              input tensor or array_like object
  
          out_format: format, mode_format, optional
              * If a :class:`format` is specified, the result tensor is stored in the format out_format.
              * If a :class:`mode_format` is specified, the result the result tensor has a with all of the dimensions
                stored in the :class:`mode_format` passed in.
  
          dtype: Datatype
              The datatype of the output tensor.
  
          Returns
          --------
          hyperbolic_tangent: tensor
              The element wise hyperbolic tangent of the input tensor.
docstring_summary: Takes the hyperbolic tangent of each input in the tensor.
docstring_tokens: Takes the hyperbolic tangent of each input in the tensor .
function: def tensor_tanh(t1, out_format, dtype=None):
      """
          Takes the hyperbolic tangent of each input in the tensor.
  
          This is applied to all elements in the tensor not just non-zeros.
  
          Parameters
          ------------
          t1: tensor, array_like
              input tensor or array_like object
  
          out_format: format, mode_format, optional
              * If a :class:`format` is specified, the result tensor is stored in the format out_format.
              * If a :class:`mode_format` is specified, the result the result tensor has a with all of the dimensions
                stored in the :class:`mode_format` passed in.
  
          dtype: Datatype
              The datatype of the output tensor.
  
          Returns
          --------
          hyperbolic_tangent: tensor
              The element wise hyperbolic tangent of the input tensor.
      """
      t1 = as_tensor(t1, copy=False)
      cast_val = _cm.max_type(_cm.float32, t1.dtype)
      f = lambda x: _cm.tanh(_cm.cast(x, cast_val))
      return _compute_unary_elt_eise_op(f, t1, out_format, dtype)
function_tokens: def tensor_tanh ( t1 , out_format , dtype = None ) : t1 = as_tensor ( t1 , copy = False ) cast_val = _cm . max_type ( _cm . float32 , t1 . dtype ) f = lambda x : _cm . tanh ( _cm . cast ( x , cast_val ) ) return _compute_unary_elt_eise_op ( f , t1 , out_format , dtype )