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_pow.py
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_pow.py
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# Copyright 2020 The FastEstimator 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.
# ==============================================================================
from typing import TypeVar, Union
import numpy as np
import tensorflow as tf
import torch
Tensor = TypeVar('Tensor', tf.Tensor, torch.Tensor, np.ndarray)
def pow(tensor: Tensor, power: Union[int, float, Tensor] ) -> Tensor:
"""Raise a `tensor` to a given `power`.
This method can be used with Numpy data:
```python
n = np.array([-2, 7, -19])
b = fe.backend.pow(n, 2) # [4, 49, 361]
```
This method can be used with TensorFlow tensors:
```python
t = tf.constant([-2, 7, -19])
b = fe.backend.pow(t, 2) # [4, 49, 361]
```
This method can be used with PyTorch tensors:
```python
p = torch.tensor([-2, 7, -19])
b = fe.backend.pow(p, 2) # [4, 49, 361]
```
Args:
tensor: The input value.
power: The exponent to raise `tensor` by.
Returns:
The exponentiated `tensor`.
Raises:
ValueError: If `tensor` is an unacceptable data type.
"""
if tf.is_tensor(tensor):
return tf.pow(tensor, power)
elif isinstance(tensor, torch.Tensor):
return tensor.pow(power)
elif isinstance(tensor, np.ndarray):
return np.power(tensor, power)
else:
raise ValueError("Unrecognized tensor type {}".format(type(tensor)))