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# Copyright 2021,2022,2023 Sony Group Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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import pprint
from nnabla_rl.hook import Hook
from nnabla_rl.logger import logger
[docs]class IterationStateHook(Hook):
"""Hook which retrieves the iteration state to print/save the training
status through writer.
Args:
timing (int): Retriving interval. Defaults to 1000 iteration.
writer (nnabla_rl.writer.Writer, optional): Writer instance to save/print the iteration states.
Defaults to None.
"""
def __init__(self, writer=None, timing=1000):
self._timing = timing
self._writer = writer
[docs] def on_hook_called(self, algorithm):
logger.info('Iteration state at iteration {}'.format(
algorithm.iteration_num))
latest_iteration_state = algorithm.latest_iteration_state
if 'scalar' in latest_iteration_state:
logger.info(pprint.pformat(latest_iteration_state['scalar']))
if self._writer is not None:
for key, value in latest_iteration_state.items():
if key == 'scalar':
self._writer.write_scalar(algorithm.iteration_num, value)
if key == 'histogram':
self._writer.write_histogram(algorithm.iteration_num, value)
if key == 'image':
self._writer.write_image(algorithm.iteration_num, value)