tensorflow保存和加载训练进度
tf.train.Checkpoint : 用于创建checkpoint
tf.train.Checkpoint:
tf.train.Checkpoint(
root=None, **kwargs
)
TensorFlow objects may contain trackable state, such as tf.Variables, tf.keras.optimizers.Optimizer implementations, tf.data.Dataset iterators, tf.keras.Layer implementations, or tf.keras.Model implementations. These are called trackable objects.
# 例子
model = tf.keras.Model(...)
checkpoint = tf.train.Checkpoint(model)
# Save a checkpoint to /tmp/training_checkpoints-{save_counter}. Every time
# checkpoint.save is called, the save counter is increased.
save_path = checkpoint.save('/tmp/training_checkpoints')
# Restore the checkpointed values to the `model` object.
checkpoint.restore(save_path)
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