plan.py 文件源码

def _setup_enqueuing(self, queues, **loom_kwargs):
    """Sets up enqueuing to the approx. smallest (least full) of `queues`."""
    self.compiler.init_loom(loom_input_tensor=None, **loom_kwargs)
    input_tensor = self.compiler.loom_input_tensor
    fns = [lambda r=q: r.enqueue_many([input_tensor]) for q in queues]
    self.train_op = _tf_nth(fns, tf.argmin(_noised_q_sizes(queues), axis=0))
    self.losses.clear()
    self.losses['dummy'] = tf.constant(0.0)
    self.save_summaries_secs = 0
    self.dev_examples = None
    self.train_feeds.clear()
    self.save_model_secs = 0
    self.exact_batch_sizes = True