def floordiv(x, y, name=None):
"""Divides `x / y` elementwise, rounding down for floating point.
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`.
Note that for efficiency, `floordiv` uses C semantics for negative numbers
(unlike Python and Numpy).
`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 (except possibly towards zero for negative integers).
Raises:
TypeError: If the inputs are complex.
"""
with ops.op_scope([x, y], name, "floordiv") as name:
x = ops.convert_to_tensor(x, name="x")
dtype = x.dtype
if dtype.is_floating:
return gen_math_ops.floor(gen_math_ops.div(x, y), name=name)
else:
if not dtype.is_integer:
raise TypeError("Expected floating point or integer, got %r" % dtype)
return gen_math_ops.div(x, y, name=name)
def round(x, name=None):
"""Rounds the values of a tensor to the nearest integer, element-wise.
For example:
```python
# 'a' is [0.9, 2.5, 2.3, -4.4]
tf.round(a) ==> [ 1.0, 3.0, 2.0, -4.0 ]
```
Args:
x: A `Tensor` of type `float` or `double`.
name: A name for the operation (optional).
Returns:
A `Tensor` of same shape and type as `x`.
"""
x = ops.convert_to_tensor(x, name="x")
if x.dtype.is_integer:
return x
else:
return gen_math_ops.floor(x + 0.5, name=name)
