/
utils.py
46 lines (35 loc) · 1.36 KB
/
utils.py
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import cv2
import collections
import globals as glo
import torch
def load_model(model_file):
return torch.load(model_file)
def save_model(model, model_file):
torch.save(model.state_dict(), model_file)
def preprocess_frame(frame, device):
frame = torch.from_numpy(frame)
frame = frame.to(device, dtype=torch.float32)
frame = frame.unsqueeze(0)
return frame
def output_video(video_array, size, save_name, evaluate=False, eval_num=0):
if not evaluate:
out = cv2.VideoWriter(save_name + "{}.avi".format(glo.EPISODE), cv2.VideoWriter_fourcc(*'DIVX'), 15, size)
else:
out = cv2.VideoWriter(save_name + "{}.avi".format(eval_num), cv2.VideoWriter_fourcc(*'DIVX'), 15, size)
last_frame = video_array[len(video_array) - 1]
for x in range(5):
video_array.append(last_frame)
for x in range(len(video_array)):
out.write(video_array[x])
out.release()
'''
def debug_memory():
# https://forum.pyro.ai/t/a-clever-trick-to-debug-tensor-memory/556
print('maxrss = {}'.format(
resource.getrusage(resource.RUSAGE_SELF).ru_maxrss))
tensors = collections.Counter((str(o.device), o.dtype, tuple(o.shape))
for o in gc.get_objects()
if torch.is_tensor(o))
for line in sorted(tensors.items()):
print('{}\t{}'.format(*line))
'''