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import json |
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import os |
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import pathlib |
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import time |
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import numpy as np |
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class Logger: |
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def __init__(self, step, outputs, multiplier=1): |
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self._step = step |
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self._outputs = outputs |
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self._multiplier = multiplier |
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self._last_step = None |
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self._last_time = None |
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self._metrics = [] |
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def add(self, mapping, prefix=None): |
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step = int(self._step) * self._multiplier |
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for name, value in dict(mapping).items(): |
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name = f'{prefix}_{name}' if prefix else name |
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value = np.array(value) |
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if len(value.shape) not in (0, 2, 3, 4): |
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raise ValueError( |
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f"Shape {value.shape} for name '{name}' cannot be " |
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"interpreted as scalar, image, or video.") |
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self._metrics.append((step, name, value)) |
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def scalar(self, name, value): |
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self.add({name: value}) |
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def image(self, name, value): |
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self.add({name: value}) |
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def video(self, name, value): |
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self.add({name: value}) |
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def write(self, fps=False): |
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fps and self.scalar('fps', self._compute_fps()) |
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if not self._metrics: |
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return |
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for output in self._outputs: |
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output(self._metrics) |
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self._metrics.clear() |
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def _compute_fps(self): |
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step = int(self._step) * self._multiplier |
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if self._last_step is None: |
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self._last_time = time.time() |
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self._last_step = step |
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return 0 |
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steps = step - self._last_step |
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duration = time.time() - self._last_time |
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self._last_time += duration |
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self._last_step = step |
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return steps / duration |
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class TerminalOutput: |
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def __call__(self, summaries): |
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step = max(s for s, _, _, in summaries) |
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scalars = {k: float(v) for _, k, v in summaries if len(v.shape) == 0} |
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formatted = {k: self._format_value(v) for k, v in scalars.items()} |
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print(f'[{step}]', ' / '.join(f'{k} {v}' for k, v in formatted.items())) |
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def _format_value(self, value): |
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if value == 0: |
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return '0' |
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elif 0.01 < abs(value) < 10000: |
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value = f'{value:.2f}' |
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value = value.rstrip('0') |
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value = value.rstrip('0') |
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value = value.rstrip('.') |
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return value |
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else: |
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value = f'{value:.1e}' |
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value = value.replace('.0e', 'e') |
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value = value.replace('+0', '') |
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value = value.replace('+', '') |
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value = value.replace('-0', '-') |
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return value |
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class JSONLOutput: |
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def __init__(self, logdir): |
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self._logdir = pathlib.Path(logdir).expanduser() |
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def __call__(self, summaries): |
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scalars = {k: float(v) for _, k, v in summaries if len(v.shape) == 0} |
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step = max(s for s, _, _, in summaries) |
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with (self._logdir / 'metrics.jsonl').open('a') as f: |
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f.write(json.dumps({'step': step, **scalars}) + '\n') |
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class TensorBoardOutput: |
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def __init__(self, logdir, fps=20): |
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self._logdir = os.path.expanduser(logdir) |
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self._writer = None |
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self._fps = fps |
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def __call__(self, summaries): |
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import tensorflow as tf |
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self._ensure_writer() |
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self._writer.set_as_default() |
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for step, name, value in summaries: |
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if len(value.shape) == 0: |
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tf.summary.scalar('scalars/' + name, value, step) |
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elif len(value.shape) == 2: |
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tf.summary.image(name, value, step) |
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elif len(value.shape) == 3: |
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tf.summary.image(name, value, step) |
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elif len(value.shape) == 4: |
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self._video_summary(name, value, step) |
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self._writer.flush() |
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def _ensure_writer(self): |
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if not self._writer: |
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import tensorflow as tf |
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self._writer = tf.summary.create_file_writer( |
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self._logdir, max_queue=1000) |
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def _video_summary(self, name, video, step): |
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import tensorflow as tf |
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import tensorflow.compat.v1 as tf1 |
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name = name if isinstance(name, str) else name.decode('utf-8') |
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if np.issubdtype(video.dtype, np.floating): |
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video = np.clip(255 * video, 0, 255).astype(np.uint8) |
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try: |
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T, H, W, C = video.shape |
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summary = tf1.Summary() |
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image = tf1.Summary.Image(height=H, width=W, colorspace=C) |
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image.encoded_image_string = encode_gif(video, self._fps) |
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summary.value.add(tag=name, image=image) |
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tf.summary.experimental.write_raw_pb(summary.SerializeToString(), step) |
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except (IOError, OSError) as e: |
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print('GIF summaries require ffmpeg in $PATH.', e) |
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tf.summary.image(name, video, step) |
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def encode_gif(frames, fps): |
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from subprocess import Popen, PIPE |
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h, w, c = frames[0].shape |
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pxfmt = {1: 'gray', 3: 'rgb24'}[c] |
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cmd = ' '.join([ |
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'ffmpeg -y -f rawvideo -vcodec rawvideo', |
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f'-r {fps:.02f} -s {w}x{h} -pix_fmt {pxfmt} -i - -filter_complex', |
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'[0:v]split[x][z];[z]palettegen[y];[x]fifo[x];[x][y]paletteuse', |
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f'-r {fps:.02f} -f gif -']) |
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proc = Popen(cmd.split(' '), stdin=PIPE, stdout=PIPE, stderr=PIPE) |
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for image in frames: |
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proc.stdin.write(image.tobytes()) |
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out, err = proc.communicate() |
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if proc.returncode: |
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raise IOError('\n'.join([' '.join(cmd), err.decode('utf8')])) |
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del proc |
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return out |
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