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I noticed a significant increase in CPU usage in the following part of demo_EDTalk_A_using_predefined_exp_weights.py
I suspect that the function test_EDTalk_A_use_exp_weight in generator.py is causing this spike in CPU usage. I am planning to modify this function to utilize GPU (CUDA) more efficiently in order to reduce the load on the CPU and improve the calculation speed, anyone here?
img_target_lip = self.lip_vid_target[i:i+1]
if i >= len_pose:
img_target_pose = self.pose_vid_target[:, -1, :, :, :]
else:
img_target_pose = self.pose_vid_target[:, i, :, :, :]
img_recon = self.gen.test_EDTalk_A_use_exp_weight(self.img_source, img_target_lip, img_target_pose, self.exp_vid_target, h_start)
vid_target_recon.append(img_recon.unsqueeze(2))
The text was updated successfully, but these errors were encountered:
I noticed a significant increase in CPU usage in the following part of demo_EDTalk_A_using_predefined_exp_weights.py
I suspect that the function test_EDTalk_A_use_exp_weight in generator.py is causing this spike in CPU usage. I am planning to modify this function to utilize GPU (CUDA) more efficiently in order to reduce the load on the CPU and improve the calculation speed, anyone here?
img_target_lip = self.lip_vid_target[i:i+1]
if i >= len_pose:
img_target_pose = self.pose_vid_target[:, -1, :, :, :]
else:
img_target_pose = self.pose_vid_target[:, i, :, :, :]
img_recon = self.gen.test_EDTalk_A_use_exp_weight(self.img_source, img_target_lip, img_target_pose, self.exp_vid_target, h_start)
vid_target_recon.append(img_recon.unsqueeze(2))
I have checked the codes, and the current models and function calculation are on GPU. I think only loading data depends on CPU.
I noticed a significant increase in CPU usage in the following part of demo_EDTalk_A_using_predefined_exp_weights.py
I suspect that the function test_EDTalk_A_use_exp_weight in generator.py is causing this spike in CPU usage. I am planning to modify this function to utilize GPU (CUDA) more efficiently in order to reduce the load on the CPU and improve the calculation speed, anyone here?
The text was updated successfully, but these errors were encountered: