parameters: (sorted_sequence,
                   values,
                   side="left",
                   out_type=dtypes.int32,
                   name=None)
return_statement: return reshape(output, shape_internal(values))
docstring: Searches input tensor for values on the innermost dimension.
  
    A 2-D example:
  
    ```
      sorted_sequence = [[0, 3, 9, 9, 10],
                         [1, 2, 3, 4, 5]]
      values = [[2, 4, 9],
                [0, 2, 6]]
  
      result = searchsorted(sorted_sequence, values, side="left")
  
      result == [[1, 2, 2],
                 [0, 1, 5]]
  
      result = searchsorted(sorted_sequence, values, side="right")
  
      result == [[1, 2, 4],
                 [0, 2, 5]]
    ```
  
    Args:
      sorted_sequence: N-D `Tensor` containing a sorted sequence.
      values: N-D `Tensor` containing the search values.
      side: 'left' or 'right'; 'left' corresponds to lower_bound and 'right' to
        upper_bound.
      out_type: The output type (`int32` or `int64`).  Default is `tf.int32`.
      name: Optional name for the operation.
  
    Returns:
      An N-D `Tensor` the size of values containing the result of applying either
      lower_bound or upper_bound (depending on side) to each value.  The result
      is not a global index to the entire `Tensor`, but the index in the last
      dimension.
  
    Raises:
      ValueError: If the last dimension of `sorted_sequence >= 2^31-1` elements.
                  If the total size of values exceeds `2^31 - 1` elements.
                  If the first `N-1` dimensions of the two tensors don't match.
docstring_summary: Searches input tensor for values on the innermost dimension.
docstring_tokens: Searches input tensor for values on the innermost dimension .
function: def searchsorted(sorted_sequence,
                   values,
                   side="left",
                   out_type=dtypes.int32,
                   name=None):
    """Searches input tensor for values on the innermost dimension.
  
    A 2-D example:
  
    ```
      sorted_sequence = [[0, 3, 9, 9, 10],
                         [1, 2, 3, 4, 5]]
      values = [[2, 4, 9],
                [0, 2, 6]]
  
      result = searchsorted(sorted_sequence, values, side="left")
  
      result == [[1, 2, 2],
                 [0, 1, 5]]
  
      result = searchsorted(sorted_sequence, values, side="right")
  
      result == [[1, 2, 4],
                 [0, 2, 5]]
    ```
  
    Args:
      sorted_sequence: N-D `Tensor` containing a sorted sequence.
      values: N-D `Tensor` containing the search values.
      side: 'left' or 'right'; 'left' corresponds to lower_bound and 'right' to
        upper_bound.
      out_type: The output type (`int32` or `int64`).  Default is `tf.int32`.
      name: Optional name for the operation.
  
    Returns:
      An N-D `Tensor` the size of values containing the result of applying either
      lower_bound or upper_bound (depending on side) to each value.  The result
      is not a global index to the entire `Tensor`, but the index in the last
      dimension.
  
    Raises:
      ValueError: If the last dimension of `sorted_sequence >= 2^31-1` elements.
                  If the total size of values exceeds `2^31 - 1` elements.
                  If the first `N-1` dimensions of the two tensors don't match.
    """
    sequence_size = shape_internal(sorted_sequence)[-1]
    values_size = shape_internal(values)[-1]
    sorted_sequence_2d = reshape(sorted_sequence, [-1, sequence_size])
    values_2d = reshape(values, [-1, values_size])
    if side == "right":
      output = gen_array_ops.upper_bound(sorted_sequence_2d, values_2d, out_type,
                                         name)
    elif side == "left":
      output = gen_array_ops.lower_bound(sorted_sequence_2d, values_2d, out_type,
                                         name)
    else:
      raise ValueError("side must be either 'right' or 'left'.  Saw: %s." % side)
    return reshape(output, shape_internal(values))
function_tokens: def searchsorted ( sorted_sequence , values , side = "left" , out_type = dtypes . int32 , name = None ) : sequence_size = shape_internal ( sorted_sequence ) [ - 1 ] values_size = shape_internal ( values ) [ - 1 ] sorted_sequence_2d = reshape ( sorted_sequence , [ - 1 , sequence_size ] ) values_2d = reshape ( values , [ - 1 , values_size ] ) if side == "right" : output = gen_array_ops . upper_bound ( sorted_sequence_2d , values_2d , out_type , name ) elif side == "left" : output = gen_array_ops . lower_bound ( sorted_sequence_2d , values_2d , out_type , name ) else : raise ValueError ( "side must be either 'right' or 'left'.  Saw: %s." % side ) return reshape ( output , shape_internal ( values ) )