def _define_loop(graph, logdir, train_steps, eval_steps):
"""Create and configure a training loop with training and evaluation phases.
Args:
graph: Object providing graph elements via attributes.
logdir: Log directory for storing checkpoints and summaries.
train_steps: Number of training steps per epoch.
eval_steps: Number of evaluation steps per epoch.
Returns:
Loop object.
"""
loop = tools.Loop(logdir, graph.step, graph.should_log, graph.do_report,
graph.force_reset)
loop.add_phase('train',
graph.done,
graph.score,
graph.summary,
train_steps,
report_every=None,
log_every=train_steps // 2,
checkpoint_every=None,
feed={graph.is_training: True})
loop.add_phase('eval',
graph.done,
graph.score,
graph.summary,
eval_steps,
report_every=eval_steps,
log_every=eval_steps // 2,
checkpoint_every=10 * eval_steps,
feed={graph.is_training: False})
return loop
def _define_loop(graph, eval_steps):
"""Create and configure an evaluation loop.
Args:
graph: Object providing graph elements via attributes.
eval_steps: Number of evaluation steps per epoch.
Returns:
Loop object.
"""
loop = tools.Loop(
None, graph.step, graph.should_log, graph.do_report, graph.force_reset)
loop.add_phase(
'eval', graph.done, graph.score, graph.summary, eval_steps,
report_every=eval_steps,
log_every=None,
checkpoint_every=None,
feed={graph.is_training: False})
return loop