Intelegentny_Pszczelarz/.venv/Lib/site-packages/keras/layers/merging/maximum.py

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# Copyright 2015 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.
# ==============================================================================
"""Layer that computes the maximum (element-wise) of several inputs."""
import tensorflow.compat.v2 as tf
from keras.layers.merging.base_merge import _Merge
# isort: off
from tensorflow.python.util.tf_export import keras_export
@keras_export("keras.layers.Maximum")
class Maximum(_Merge):
"""Layer that computes the maximum (element-wise) a list of inputs.
It takes as input a list of tensors, all of the same shape, and returns
a single tensor (also of the same shape).
>>> tf.keras.layers.Maximum()([np.arange(5).reshape(5, 1),
... np.arange(5, 10).reshape(5, 1)])
<tf.Tensor: shape=(5, 1), dtype=int64, numpy=
array([[5],
[6],
[7],
[8],
[9]])>
>>> x1 = tf.keras.layers.Dense(8)(np.arange(10).reshape(5, 2))
>>> x2 = tf.keras.layers.Dense(8)(np.arange(10, 20).reshape(5, 2))
>>> maxed = tf.keras.layers.Maximum()([x1, x2])
>>> maxed.shape
TensorShape([5, 8])
"""
def _merge_function(self, inputs):
output = inputs[0]
for i in range(1, len(inputs)):
output = tf.maximum(output, inputs[i])
return output
@keras_export("keras.layers.maximum")
def maximum(inputs, **kwargs):
"""Functional interface to compute maximum (element-wise) list of `inputs`.
This is equivalent to the `tf.keras.layers.Maximum` layer.
For example:
```python
input1 = tf.keras.layers.Input(shape=(16,))
x1 = tf.keras.layers.Dense(8, activation='relu')(input1) #shape=(None, 8)
input2 = tf.keras.layers.Input(shape=(32,))
x2 = tf.keras.layers.Dense(8, activation='relu')(input2) #shape=(None, 8)
max_inp=tf.keras.layers.maximum([x1,x2]) #shape=(None, 8)
out = tf.keras.layers.Dense(4)(max_inp)
model = tf.keras.models.Model(inputs=[input1, input2], outputs=out)
```
Args:
inputs: A list of input tensors of same shape.
**kwargs: Standard layer keyword arguments.
Returns:
A tensor (of same shape as input tensor) with the element-wise
maximum of the inputs.
Raises:
ValueError: If input tensors are of different shape.
"""
return Maximum(**kwargs)(inputs)