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| # ------------------------------------------------------------------------ | |
| # Copyright (c) 2023-present, BAAI. 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. | |
| # ------------------------------------------------------------------------ | |
| """Tensorboard application.""" | |
| import time | |
| import numpy as np | |
| try: | |
| import tensorflow as tf | |
| except ImportError: | |
| tf = None | |
| class TensorBoard(object): | |
| """TensorBoard application.""" | |
| def __init__(self, log_dir=None): | |
| """Create a summary writer logging to log_dir.""" | |
| if tf is None: | |
| raise ImportError("Failed to import ``tensorflow`` package.") | |
| tf.config.set_visible_devices([], "GPU") | |
| if log_dir is None: | |
| log_dir = "./logs/" + time.strftime("%Y%m%d_%H%M%S", time.localtime(time.time())) | |
| self.writer = tf.summary.create_file_writer(log_dir) | |
| def is_available(): | |
| """Return if tensor board is available.""" | |
| return tf is not None | |
| def close(self): | |
| """Close board and apply all cached summaries.""" | |
| self.writer.close() | |
| def histogram_summary(self, tag, values, step, buckets=10): | |
| """Write a histogram of values.""" | |
| with self.writer.as_default(): | |
| tf.summary.histogram(tag, values, step, buckets=buckets) | |
| def image_summary(self, tag, images, step, order="BGR"): | |
| """Write a list of images.""" | |
| if isinstance(images, (tuple, list)): | |
| images = np.stack(images) | |
| if len(images.shape) != 4: | |
| raise ValueError("Images can not be packed to (N, H, W, C).") | |
| if order == "BGR": | |
| images = images[:, :, :, ::-1] | |
| with self.writer.as_default(): | |
| tf.summary.image(tag, images, step, max_outputs=images.shape[0]) | |
| def scalar_summary(self, tag, value, step): | |
| """Write a scalar.""" | |
| with self.writer.as_default(): | |
| tf.summary.scalar(tag, value, step) | |