| # Copyright 2023 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 functions.""" | |
| import numpy as np | |
| def generate_fake_input(batch_size=1, seq_len=5, vocab_size=10000, seed=0): | |
| """Generate consistent fake integer input sequences.""" | |
| np.random.seed(seed) | |
| fake_input = [] | |
| for _ in range(batch_size): | |
| fake_input.append([]) | |
| for _ in range(seq_len): | |
| fake_input[-1].append(np.random.randint(0, vocab_size)) | |
| fake_input = np.asarray(fake_input) | |
| return fake_input | |