Intelegentny_Pszczelarz/.venv/Lib/site-packages/tensorflow/python/ops/signal/util_ops.py
2023-06-19 00:49:18 +02:00

70 lines
2.5 KiB
Python

# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Utility ops shared across tf.contrib.signal."""
import fractions # gcd is here for Python versions < 3
import math # Get gcd here for Python versions >= 3
import sys
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import math_ops
def gcd(a, b, name=None):
"""Returns the greatest common divisor via Euclid's algorithm.
Args:
a: The dividend. A scalar integer `Tensor`.
b: The divisor. A scalar integer `Tensor`.
name: An optional name for the operation.
Returns:
A scalar `Tensor` representing the greatest common divisor between `a` and
`b`.
Raises:
ValueError: If `a` or `b` are not scalar integers.
"""
with ops.name_scope(name, 'gcd', [a, b]):
a = ops.convert_to_tensor(a)
b = ops.convert_to_tensor(b)
a.shape.assert_has_rank(0)
b.shape.assert_has_rank(0)
if not a.dtype.is_integer:
raise ValueError('a must be an integer type. Got: %s' % a.dtype)
if not b.dtype.is_integer:
raise ValueError('b must be an integer type. Got: %s' % b.dtype)
# TPU requires static shape inference. GCD is used for subframe size
# computation, so we should prefer static computation where possible.
const_a = tensor_util.constant_value(a)
const_b = tensor_util.constant_value(b)
if const_a is not None and const_b is not None:
if sys.version_info.major < 3:
math_gcd = fractions.gcd
else:
math_gcd = math.gcd
return ops.convert_to_tensor(math_gcd(const_a, const_b))
cond = lambda _, b: math_ops.greater(b, array_ops.zeros_like(b))
body = lambda a, b: [b, math_ops.mod(a, b)]
a, b = control_flow_ops.while_loop(cond, body, [a, b], back_prop=False)
return a