fixed pylint formating issues

This commit is contained in:
Harsh188 2020-08-29 11:36:21 +05:30
parent b65191ffd1
commit eb234e5b7c

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@ -535,7 +535,7 @@ _mul.__doc__ = (
def subtract(x, y, name=None):
"""Returns x - y element-wise.
*Note*: Subtract supports broadcasting. More about broadcasting
*Note*: Subtract supports broadcasting. More about broadcasting
[here](https://numpy.org/doc/stable/user/basics.broadcasting.html)
Both input and output have a range `(-inf, inf)`.
@ -549,9 +549,9 @@ def subtract(x, y, name=None):
array([-4. , -2. , 1.3, 17.9, -inf], dtype=float32)>
Args:
x: A `Tensor`. Must be one of the following types: `bfloat16`, `half`,
`float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`,
`complex128`, `string`.
x: A `Tensor`. Must be one of the following types: `bfloat16`, `half`,
`float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`,
`complex64`, `complex128`, `string`.
y: A `Tensor`. Must have the same type as x.
name: A name for the operation (optional).
Returns:
@ -4953,17 +4953,18 @@ def rsqrt(x, name=None):
return gen_math_ops.rsqrt(x, name)
@tf_export("math.add", v1=["math.add","add"])
@tf_export("math.add", v1=["math.add", "add"])
@deprecation.deprecated_endpoints("add")
@dispatch.add_dispatch_support
def add(x,y,name=None):
def add(x, y, name=None):
"""Returns x + y element-wise.
*NOTE*: `Add` supports broadcasting. `AddN` does not. More about broadcasting
[here](http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html)
Given two input tensors, the `tf.add` operation computes the sum for every element in the tensor.
Given two input tensors, the `tf.add` operation computes the sum
for every element in the tensor.
Both input and output have a range `(-inf, inf)`.
For example:
@ -4973,10 +4974,11 @@ def add(x,y,name=None):
>>> tf.add(x,y)
<tf.Tensor: shape=(5,), dtype=float32, numpy=
array([ 6. , 0. , 8.7, -21.9, inf], dtype=float32)>
Args:
x: A `Tensor`. Must be one of the following types: `bfloat16`, `half`,
`float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`,
x: A `Tensor`. Must be one of the following types:
`bfloat16`, `half`, `float32`, `float64`, `uint8`, `int8`,
`int16`, `int32`, `int64`, `complex64`,
`complex128`, `string`.
y: A `Tensor`. Must have the same type as x.
name: A name for the operation (optional).
@ -4986,14 +4988,15 @@ def add(x,y,name=None):
return gen_math_ops.add(x,y,name)
@tf_export("math.acos", v1=["math.acos","acos"])
@tf_export("math.acos", v1=["math.acos", "acos"])
@deprecation.deprecated_endpoints("acos")
@dispatch.add_dispatch_support
def acos(x,name=None):
def acos(x, name=None):
"""Computes acos of x element-wise.
Provided an input tensor, the `tf.math.acos` operation returns the inverse cosine of
each element of the tensor. If `y = tf.math.cos(x)` then, `x = tf.math.acos(y)`.
Provided an input tensor, the `tf.math.acos` operation
returns the inverse cosine of each element of the tensor.
If `y = tf.math.cos(x)` then, `x = tf.math.acos(y)`.
Input range is `[-1, 1]` and the output has a range of `[0, pi]`.
@ -5006,9 +5009,9 @@ def acos(x,name=None):
dtype=float32)>
Args:
x: A `Tensor`. Must be one of the following types: `bfloat16`, `half`,
`float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`,
`complex128`, `string`.
x: A `Tensor`. Must be one of the following types: `bfloat16`, `half`,
`float32`, `float64`, `uint8`, `int8`, `int16`, `int32`,
`int64`, `complex64`, `complex128`, `string`.
name: A name for the operation (optional).
Returns:
A `Tensor`. Has the same type as x.
@ -5016,25 +5019,27 @@ def acos(x,name=None):
return gen_math_ops.acos(x,name)
@tf_export("math.floor", v1=["math.floor","floor"])
@tf_export("math.floor", v1=["math.floor", "floor"])
@deprecation.deprecated_endpoints("floor")
@dispatch.add_dispatch_support
def floor(x,name=None):
def floor(x, name=None):
"""Returns element-wise largest integer not greater than x.
Both input range is `(-inf,inf)` and the ouput range consists of all integer values.
Both input range is `(-inf, inf)` and the
ouput range consists of all integer values.
For example:
>>> x = tf.constant([1.3324, -1.5, 5.555, -2.532, 0.99, float("inf")])
>>> x = tf.constant([1.3324, -1.5, 5.555, -2.532, 0.99, float("inf")])
>>> tf.floor(x)
<tf.Tensor: shape=(6,), dtype=float32, numpy=
array([ 1., -2., 5., -3., 0., inf], dtype=float32)>
Args:
x: A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`.
x: A `Tensor`. Must be one of the following types:
`bfloat16`, `half`, `float32`, `float64`.
name: A name for the operation (optional).
Returns:
A `Tensor`. Has the same type as x.
"""
return gen_math_ops.floor(x,name)
return gen_math_ops.floor(x,name)