37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
# The following switch allows the program runs locally and in the Agit environment without modifications.
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import os
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path = os.path.dirname(__file__)
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print(path)
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if 'CLOUD_PROVIDER' in os.environ and os.environ['CLOUD_PROVIDER'] == 'Agit':
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logdir = '/root/.agit'
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else:
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logdir = './runs'
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# setup tensorboard path
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import tensorflow as tf
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writer = tf.summary.create_file_writer(logdir)
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''' alternative tensorboards
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# pytorch tensorboard :
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from torch.utils.tensorboard import SummaryWriter
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writer = SummaryWriter(log_dir=logdir)
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# tensorboardX :
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from tensorboardX import SummaryWriter
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writer = SummaryWriter(logdir=logdir)
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'''
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import numpy as np
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import time
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# a 5 minutes running example, the realtime tensorboard can be viewed in the training page
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with writer.as_default():
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for n_iter in range(360):
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tf.summary.scalar('Loss/train', np.random.random(), n_iter)
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tf.summary.scalar('Loss/test', np.random.random(), n_iter)
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tf.summary.scalar('Accuracy/train', np.random.random(), n_iter)
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tf.summary.scalar('Accuracy/test', np.random.random(), n_iter)
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time.sleep(1) |