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jh 2021-03-17 12:03:04 -07:00
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models/Model_SAEHD/Model.py
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@ -455,8 +455,9 @@ Examples: df, liae, df-d, df-ud, liae-ud, ...
print('abs_loss.shape: ', abs_loss.shape) print('abs_loss.shape: ', abs_loss.shape)
abs_mean_loss = tf.reduce_mean(300 * abs_loss, axis=[1,2,3]) abs_mean_loss = tf.reduce_mean(300 * abs_loss, axis=[1,2,3])
print('abs_mean_loss.shape: ', abs_mean_loss.shape) print('abs_mean_loss.shape: ', abs_mean_loss.shape)
gpu_src_loss += 300*nn.MsSsim(resolution, kernel_size=5)(gpu_target_src*gpu_target_part_mask, gpu_pred_src_src*gpu_target_part_mask, max_val=1.0)
gpu_src_loss += tf.reduce_mean ( 300*nn.MsSsim(resolution, kernel_size=5)(gpu_target_src*gpu_target_part_mask, gpu_pred_src_src*gpu_target_part_mask, max_val=1.0)) # gpu_src_loss += tf.reduce_mean ( 300*nn.MsSsim(resolution, kernel_size=5)(gpu_target_src*gpu_target_part_mask, gpu_pred_src_src*gpu_target_part_mask, max_val=1.0))
else: else:
gpu_src_loss += tf.reduce_mean ( 300*tf.abs ( gpu_target_src*gpu_target_part_mask - gpu_pred_src_src*gpu_target_part_mask ), axis=[1,2,3]) gpu_src_loss += tf.reduce_mean ( 300*tf.abs ( gpu_target_src*gpu_target_part_mask - gpu_pred_src_src*gpu_target_part_mask ), axis=[1,2,3])