Source code for tensorpack.callbacks.hooks

# -*- coding: utf-8 -*-
# File: hooks.py


""" Compatible layers between tf.train.SessionRunHook and Callback"""

import tensorflow as tf
from .base import Callback

__all__ = ['CallbackToHook', 'HookToCallback']


[docs]class CallbackToHook(tf.train.SessionRunHook): """ This is only for internal implementation of before_run/after_run callbacks. You shouldn't need to use this. """ def __init__(self, cb): self._cb = cb
[docs] def before_run(self, ctx): return self._cb.before_run(ctx)
[docs] def after_run(self, ctx, vals): self._cb.after_run(ctx, vals)
[docs]class HookToCallback(Callback): """ Make a ``tf.train.SessionRunHook`` into a callback. Note that when `SessionRunHook.after_create_session` is called, the `coord` argument will be None. """ _chief_only = False
[docs] def __init__(self, hook): """ Args: hook (tf.train.SessionRunHook): """ self._hook = hook
def _setup_graph(self): with tf.name_scope(None): # jump out of the name scope self._hook.begin() def _before_train(self): sess = tf.get_default_session() # coord is set to None when converting self._hook.after_create_session(sess, None) def _before_run(self, ctx): return self._hook.before_run(ctx) def _after_run(self, ctx, run_values): self._hook.after_run(ctx, run_values) def _after_train(self): self._hook.end(self.trainer.sess)