def setup_REINFORCE_train_algo_generator_with_FAILING_spec():
nb_of_try = 2
env_max_return = 200.000
epoch_generator, exp_spec, consol_print_learning_stats, reinforce_agent = init_spec_and_REINFORCEagent(
hparam=CARTPOLE_HPARAM_FAIL)
this_run_dir = setup_commented_run_dir_str(exp_spec, AGENT_ROOT_DIR)
writer = tf_cv1.summary.FileWriter(this_run_dir,
tf_cv1.get_default_graph())
reinforce_agent.this_run_dir = this_run_dir
reinforce_agent.writer = writer
yield epoch_generator, nb_of_try, env_max_return, exp_spec
consol_print_learning_stats.print_experiment_stats(
print_plot=exp_spec.show_plot)
reinforce_agent.writer.close()
def train(self, render_env: bool = False) -> None:
"""
Train a REINFORCE agent
:param render_env: Control over trajectory rendering
:type render_env: bool
"""
print(":: Environment rendering autorised: {}".format(render_env))
consol_print_learning_stats = ConsolPrintLearningStats(
self.exp_spec, self.exp_spec.print_metric_every_what_epoch)
""" ---- Setup run dir name ---- """
self.this_run_dir = setup_commented_run_dir_str(
self.exp_spec, self.agent_root_dir)
""" ---- Create run dir & setup file writer for TensorBoard ---- """
self.writer = tf_cv1.summary.FileWriter(self.this_run_dir,
tf_cv1.get_default_graph())
""" ---- Log experiment spec in run directory ---- """
try:
with open("{}/config.txt".format(self.this_run_dir), "w") as f:
f.write(self.exp_spec.__repr__())
except IOError as e:
raise IOError(
"The config file cannot be saved in the run directory!") from e
""" ---- Start training agent ---- """
for epoch in self._training_epoch_generator(
consol_print_learning_stats, render_env):
(epoch, epoch_loss, batch_average_trjs_return,
batch_average_trjs_lenght) = epoch
""" ---- Teardown ---- """
consol_print_learning_stats.print_experiment_stats(
print_plot=self.exp_spec.show_plot)
self.writer.close()
return None