| # coding=utf-8 | |
| # Copyright 2021 The Deeplab2 Authors. | |
| # | |
| # 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. | |
| """This file contains utility functions for the model tests.""" | |
| import numpy as np | |
| import tensorflow as tf | |
| def create_test_input(batch, height, width, channels): | |
| """Creates test input tensor.""" | |
| input_tensor = np.tile( | |
| np.reshape( | |
| np.reshape(np.arange(height), [height, 1]) + | |
| np.reshape(np.arange(width), [1, width]), | |
| [1, height, width, 1]), | |
| [batch, 1, 1, channels]) | |
| # Normalize the input tensor so that the outputs are not too large. | |
| input_tensor = (input_tensor * 2 / np.max(input_tensor)) - 1 | |
| return tf.cast(input_tensor, tf.float32) | |