inference no working

[dezei547]

### when I training wav2lip384 ,and I start to test the model,it comes error blow:
RuntimeError: Error(s) in loading state_dict for Wav2Lip:
Missing key(s) in state_dict: "face_encoder_blocks.8.0.conv_block.0.weight", "face_encoder_blocks.8.0.conv_block.0.bias", "face_encoder_blocks.8.0.conv_block.1.weight", "face_encoder_blocks.8.0.conv_block.1.bias", "face_encoder_blocks.8.0.conv_block.1.running_mean", "face_encoder_blocks.8.0.conv_block.1.running_var", "face_encoder_blocks.8.1.conv_block.0.weight", "face_encoder_blocks.8.1.conv_block.0.bias", "face_encoder_blocks.8.1.conv_block.1.weight", "face_encoder_blocks.8.1.conv_block.1.bias", "face_encoder_blocks.8.1.conv_block.1.running_mean", "face_encoder_blocks.8.1.conv_block.1.running_var", "face_decoder_blocks.8.0.conv_block.0.weight", "face_decoder_blocks.8.0.conv_block.0.bias", "face_decoder_blocks.8.0.conv_block.1.weight", "face_decoder_blocks.8.0.conv_block.1.bias", "face_decoder_blocks.8.0.conv_block.1.running_mean", "face_decoder_blocks.8.0.conv_block.1.running_var", "face_decoder_blocks.8.1.conv_block.0.weight", "face_decoder_blocks.8.1.conv_block.0.bias", "face_decoder_blocks.8.1.conv_block.1.weight", "face_decoder_blocks.8.1.conv_block.1.bias", "face_decoder_blocks.8.1.conv_block.1.running_mean", "face_decoder_blocks.8.1.conv_block.1.running_var", "face_decoder_blocks.8.2.conv_block.0.weight", "face_decoder_blocks.8.2.conv_block.0.bias", "face_decoder_blocks.8.2.conv_block.1.weight", "face_decoder_blocks.8.2.conv_block.1.bias", "face_decoder_blocks.8.2.conv_block.1.running_mean", "face_decoder_blocks.8.2.conv_block.1.running_var".
Unexpected key(s) in state_dict: "sam.sa.conv1.weight", "face_encoder_blocks.0.1.conv_block.0.weight", "face_encoder_blocks.0.1.conv_block.0.bias", "face_encoder_blocks.0.1.conv_block.1.weight", "face_encoder_blocks.0.1.conv_block.1.bias", "face_encoder_blocks.0.1.conv_block.1.running_mean", "face_encoder_blocks.0.1.conv_block.1.running_var", "face_encoder_blocks.0.1.conv_block.1.num_batches_tracked", "face_encoder_blocks.0.2.conv_block.0.weight", "face_encoder_blocks.0.2.conv_block.0.bias", "face_encoder_blocks.0.2.conv_block.1.weight", "face_encoder_blocks.0.2.conv_block.1.bias", "face_encoder_blocks.0.2.conv_block.1.running_mean", "face_encoder_blocks.0.2.conv_block.1.running_var", "face_encoder_blocks.0.2.conv_block.1.num_batches_tracked", "face_encoder_blocks.0.3.conv_block.0.weight", "face_encoder_blocks.0.3.conv_block.0.bias", "face_encoder_blocks.0.3.conv_block.1.weight", "face_encoder_blocks.0.3.conv_block.1.bias", "face_encoder_blocks.0.3.conv_block.1.running_mean", "face_encoder_blocks.0.3.conv_block.1.running_var", "face_encoder_blocks.0.3.conv_block.1.num_batches_tracked", "face_encoder_blocks.1.3.conv_block.0.weight", "face_encoder_blocks.1.3.conv_block.0.bias", "face_encoder_blocks.1.3.conv_block.1.weight", "face_encoder_blocks.1.3.conv_block.1.bias", "face_encoder_blocks.1.3.conv_block.1.running_mean", "face_encoder_blocks.1.3.conv_block.1.running_var", "face_encoder_blocks.1.3.conv_block.1.num_batches_tracked", "face_encoder_blocks.2.3.conv_block.0.weight", "face_encoder_blocks.2.3.conv_block.0.bias", "face_encoder_blocks.2.3.conv_block.1.weight", "face_encoder_blocks.2.3.conv_block.1.bias", "face_encoder_blocks.2.3.conv_block.1.running_mean", "face_encoder_blocks.2.3.conv_block.1.running_var", "face_encoder_blocks.2.3.conv_block.1.num_batches_tracked", "face_encoder_blocks.4.3.conv_block.0.weight", "face_encoder_blocks.4.3.conv_block.0.bias", "face_encoder_blocks.4.3.conv_block.1.weight", "face_encoder_blocks.4.3.conv_block.1.bias", "face_encoder_blocks.4.3.conv_block.1.running_mean", "face_encoder_blocks.4.3.conv_block.1.running_var", "face_encoder_blocks.4.3.conv_block.1.num_batches_tracked", "face_encoder_blocks.5.3.conv_block.0.weight", "face_encoder_blocks.5.3.conv_block.0.bias", "face_encoder_blocks.5.3.conv_block.1.weight", "face_encoder_blocks.5.3.conv_block.1.bias", "face_encoder_blocks.5.3.conv_block.1.running_mean", "face_encoder_blocks.5.3.conv_block.1.running_var", "face_encoder_blocks.5.3.conv_block.1.num_batches_tracked", "face_encoder_blocks.6.3.conv_block.0.weight", "face_encoder_blocks.6.3.conv_block.0.bias", "face_encoder_blocks.6.3.conv_block.1.weight", "face_encoder_blocks.6.3.conv_block.1.bias", "face_encoder_blocks.6.3.conv_block.1.running_mean", "face_encoder_blocks.6.3.conv_block.1.running_var", "face_encoder_blocks.6.3.conv_block.1.num_batches_tracked".
size mismatch for face_encoder_blocks.0.0.conv_block.0.weight: copying a param with shape torch.Size([16, 6, 7, 7]) from checkpoint, the shape in current model is torch.Size([8, 6, 7, 7]).
size mismatch for face_encoder_blocks.0.0.conv_block.0.bias: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([8]).
size mismatch for face_encoder_blocks.0.0.conv_block.1.weight: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([8]).
size mismatch for face_encoder_blocks.0.0.conv_block.1.bias: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([8]).
size mismatch for face_encoder_blocks.0.0.conv_block.1.running_mean: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([8]).
size mismatch for face_encoder_blocks.0.0.conv_block.1.running_var: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([8]).
size mismatch for face_encoder_blocks.1.0.conv_block.0.weight: copying a param with shape torch.Size([32, 16, 3, 3]) from checkpoint, the shape in current model is torch.Size([16, 8, 3, 3]).
size mismatch for face_encoder_blocks.1.0.conv_block.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.0.conv_block.1.weight: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.0.conv_block.1.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.0.conv_block.1.running_mean: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.0.conv_block.1.running_var: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.1.conv_block.0.weight: copying a param with shape torch.Size([32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([16, 16, 3, 3]).
size mismatch for face_encoder_blocks.1.1.conv_block.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.1.conv_block.1.weight: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.1.conv_block.1.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.1.conv_block.1.running_mean: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.1.conv_block.1.running_var: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.2.conv_block.0.weight: copying a param with shape torch.Size([32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([16, 16, 3, 3]).
size mismatch for face_encoder_blocks.1.2.conv_block.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.2.conv_block.1.weight: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.2.conv_block.1.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.2.conv_block.1.running_mean: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.1.2.conv_block.1.running_var: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for face_encoder_blocks.2.0.conv_block.0.weight: copying a param with shape torch.Size([64, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 16, 3, 3]).
size mismatch for face_encoder_blocks.2.0.conv_block.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.0.conv_block.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.0.conv_block.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.0.conv_block.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.0.conv_block.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.1.conv_block.0.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]).
size mismatch for face_encoder_blocks.2.1.conv_block.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.1.conv_block.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.1.conv_block.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.1.conv_block.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.1.conv_block.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.2.conv_block.0.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]).
size mismatch for face_encoder_blocks.2.2.conv_block.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.2.conv_block.1.weight: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.2.conv_block.1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.2.conv_block.1.running_mean: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.2.2.conv_block.1.running_var: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([32]).
size mismatch for face_encoder_blocks.3.0.conv_block.0.weight: copying a param with shape torch.Size([128, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 32, 3, 3]).
size mismatch for face_encoder_blocks.3.0.conv_block.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.0.conv_block.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.0.conv_block.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.0.conv_block.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.0.conv_block.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.1.conv_block.0.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for face_encoder_blocks.3.1.conv_block.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.1.conv_block.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.1.conv_block.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.1.conv_block.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.1.conv_block.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.2.conv_block.0.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for face_encoder_blocks.3.2.conv_block.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.2.conv_block.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.2.conv_block.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.2.conv_block.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.2.conv_block.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.3.conv_block.0.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
size mismatch for face_encoder_blocks.3.3.conv_block.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.3.conv_block.1.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.3.conv_block.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.3.conv_block.1.running_mean: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.3.3.conv_block.1.running_var: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for face_encoder_blocks.4.0.conv_block.0.weight: copying a param with shape torch.Size([256, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 64, 3, 3]).
size mismatch for face_encoder_blocks.4.0.conv_block.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.0.conv_block.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.0.conv_block.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.0.conv_block.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.0.conv_block.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.1.conv_block.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for face_encoder_blocks.4.1.conv_block.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.1.conv_block.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.1.conv_block.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.1.conv_block.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.1.conv_block.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.2.conv_block.0.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for face_encoder_blocks.4.2.conv_block.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.2.conv_block.1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.2.conv_block.1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.2.conv_block.1.running_mean: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.4.2.conv_block.1.running_var: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for face_encoder_blocks.5.0.conv_block.0.weight: copying a param with shape torch.Size([512, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 128, 3, 3]).
size mismatch for face_encoder_blocks.5.0.conv_block.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.0.conv_block.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.0.conv_block.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.0.conv_block.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.0.conv_block.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.1.conv_block.0.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for face_encoder_blocks.5.1.conv_block.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.1.conv_block.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.1.conv_block.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.1.conv_block.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.1.conv_block.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.2.conv_block.0.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for face_encoder_blocks.5.2.conv_block.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.2.conv_block.1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.2.conv_block.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.2.conv_block.1.running_mean: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.5.2.conv_block.1.running_var: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for face_encoder_blocks.6.0.conv_block.0.weight: copying a param with shape torch.Size([1024, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 256, 3, 3]).
size mismatch for face_encoder_blocks.6.0.conv_block.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.0.conv_block.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.0.conv_block.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.0.conv_block.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.0.conv_block.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.1.conv_block.0.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
size mismatch for face_encoder_blocks.6.1.conv_block.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.1.conv_block.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.1.conv_block.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.1.conv_block.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.1.conv_block.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.2.conv_block.0.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 512, 3, 3]).
size mismatch for face_encoder_blocks.6.2.conv_block.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.2.conv_block.1.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.2.conv_block.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.2.conv_block.1.running_mean: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.6.2.conv_block.1.running_var: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([512]).
size mismatch for face_encoder_blocks.7.0.conv_block.0.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 512, 3, 3]).
size mismatch for face_encoder_blocks.7.1.conv_block.0.weight: copying a param with shape torch.Size([1024, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([1024, 1024, 3, 3]).
size mismatch for face_encoder_blocks.7.2.conv_block.0.weight: copying a param with shape torch.Size([1024, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([1024, 1024, 3, 3]).
size mismatch for output_block.0.conv_block.0.weight: copying a param with shape torch.Size([32, 80, 3, 3]) from checkpoint, the shape in current model is torch.Size([16, 40, 3, 3]).
size mismatch for output_block.0.conv_block.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for output_block.0.conv_block.1.weight: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for output_block.0.conv_block.1.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for output_block.0.conv_block.1.running_mean: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for output_block.0.conv_block.1.running_var: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([16]).
size mismatch for output_block.1.weight: copying a param with shape torch.Size([3, 32, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 16, 1, 1]).
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