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Update ppo.save to include iteration in "current" save file content. #46

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Update ppo.save to include iteration in "current" save file content. #46

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9 changes: 5 additions & 4 deletions rocket_learn/ppo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -171,7 +171,7 @@ def _iter():
iteration += 1

if save_dir:
self.save(os.path.join(save_dir, self.logger.project + "_" + "latest"), -1, save_jit)
self.save(os.path.join(save_dir, self.logger.project + "_" + "latest"), iteration, save_actor_jit=save_jit, is_latest=True)
if iteration % iterations_per_save == 0:
self.save(current_run_dir, iteration, save_jit) # noqa

Expand Down Expand Up @@ -485,18 +485,19 @@ def load(self, load_location, continue_iterations=True):
self.total_steps = checkpoint["total_steps"]
print("Continuing training at iteration " + str(self.starting_iteration))

def save(self, save_location, current_step, save_actor_jit=False):
def save(self, save_location, current_step, save_actor_jit=False, is_latest=False,):
"""
Save the model weights, optimizer values, and metadata
:param save_location: where to save
:param current_step: the current iteration when saved. Use to later continue training
:param save_actor_jit: save the policy network as a torch jit file for rlbot use
:param is_latest: if this file is the "latest" checkpoint, used to decide if real checkpoint number should be used in filename
"""

version_str = str(self.logger.project) + "_" + str(current_step)
version_str = str(self.logger.project) + "_" + (str(current_step) if not is_latest else "c")
version_dir = save_location + "\\" + version_str

os.makedirs(version_dir, exist_ok=current_step == -1)
os.makedirs(version_dir, exist_ok=is_latest)

torch.save({
'epoch': current_step,
Expand Down