@tf_export('math.floordiv', v1=['math.floordiv', 'floordiv'])
@dispatch.add_dispatch_support
@deprecation.deprecated_endpoints('floordiv')
def floordiv(x, y, name=None):
    'Divides `x / y` elementwise, rounding toward the most negative integer.\n\n  The same as `tf.div(x,y)` for integers, but uses `tf.floor(tf.div(x,y))` for\n  floating point arguments so that the result is always an integer (though\n  possibly an integer represented as floating point).  This op is generated by\n  `x // y` floor division in Python 3 and in Python 2.7 with\n  `from __future__ import division`.\n\n  `x` and `y` must have the same type, and the result will have the same type\n  as well.\n\n  Args:\n    x: `Tensor` numerator of real numeric type.\n    y: `Tensor` denominator of real numeric type.\n    name: A name for the operation (optional).\n\n  Returns:\n    `x / y` rounded down.\n\n  Raises:\n    TypeError: If the inputs are complex.\n  '
    with ops.name_scope(name, 'floordiv', [x, y]) as name:
        return gen_math_ops.floor_div(x, y, name=name)
Divides `x / y` elementwise, rounding toward the most negative integer.

The same as `tf.div(x,y)` for integers, but uses `tf.floor(tf.div(x,y))` for
floating point arguments so that the result is always an integer (though
possibly an integer represented as floating point).  This op is generated by
`x // y` floor division in Python 3 and in Python 2.7 with
`from __future__ import division`.

`x` and `y` must have the same type, and the result will have the same type
as well.

Args:
  x: `Tensor` numerator of real numeric type.
  y: `Tensor` denominator of real numeric type.
  name: A name for the operation (optional).

Returns:
  `x / y` rounded down.

Raises:
  TypeError: If the inputs are complex.
@tf_export('math.floordiv', v1=['math.floordiv', 'floordiv'])
@dispatch.add_dispatch_support
@deprecation.deprecated_endpoints('floordiv')
def floordiv(x, y, name=None):
    'Divides `x / y` elementwise, rounding toward the most negative integer.\n\n  The same as `tf.div(x,y)` for integers, but uses `tf.floor(tf.div(x,y))` for\n  floating point arguments so that the result is always an integer (though\n  possibly an integer represented as floating point).  This op is generated by\n  `x // y` floor division in Python 3 and in Python 2.7 with\n  `from __future__ import division`.\n\n  `x` and `y` must have the same type, and the result will have the same type\n  as well.\n\n  Args:\n    x: `Tensor` numerator of real numeric type.\n    y: `Tensor` denominator of real numeric type.\n    name: A name for the operation (optional).\n\n  Returns:\n    `x / y` rounded down.\n\n  Raises:\n    TypeError: If the inputs are complex.\n  '
    with ops.name_scope(name, 'floordiv', [x, y]) as name:
        return gen_math_ops.floor_div(x, y, name=name)