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about pretrain model convmae.pth #12

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lywang76 opened this issue Aug 7, 2022 · 5 comments
Open

about pretrain model convmae.pth #12

lywang76 opened this issue Aug 7, 2022 · 5 comments

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@lywang76
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lywang76 commented Aug 7, 2022

I downloaded your pretrained model. And when i tried to load it.
It gave me the following errors.

_IncompatibleKeys(missing_keys=['mask_token', 'decoder_pos_embed', 'stage1_output_decode.weight', 'stage1_output_decode.bias', 'stage2_output_decode.weight', 'stage2_output_decode.bias', 'decoder_embed.weight', 'decoder_embed.bias', 'decoder_blocks.0.norm1.weight', 'decoder_blocks.0.norm1.bias', 'decoder_blocks.0.attn.qkv.weight', 'decoder_blocks.0.attn.qkv.bias', 'decoder_blocks.0.attn.proj.weight', 'decoder_blocks.0.attn.proj.bias', 'decoder_blocks.0.norm2.weight', 'decoder_blocks.0.norm2.bias', 'decoder_blocks.0.mlp.fc1.weight', 'decoder_blocks.0.mlp.fc1.bias', 'decoder_blocks.0.mlp.fc2.weight', 'decoder_blocks.0.mlp.fc2.bias', 'decoder_blocks.1.norm1.weight', 'decoder_blocks.1.norm1.bias', 'decoder_blocks.1.attn.qkv.weight', 'decoder_blocks.1.attn.qkv.bias', 'decoder_blocks.1.attn.proj.weight', 'decoder_blocks.1.attn.proj.bias', 'decoder_blocks.1.norm2.weight', 'decoder_blocks.1.norm2.bias', 'decoder_blocks.1.mlp.fc1.weight', 'decoder_blocks.1.mlp.fc1.bias', 'decoder_blocks.1.mlp.fc2.weight', 'decoder_blocks.1.mlp.fc2.bias', 'decoder_blocks.2.norm1.weight', 'decoder_blocks.2.norm1.bias', 'decoder_blocks.2.attn.qkv.weight', 'decoder_blocks.2.attn.qkv.bias', 'decoder_blocks.2.attn.proj.weight', 'decoder_blocks.2.attn.proj.bias', 'decoder_blocks.2.norm2.weight', 'decoder_blocks.2.norm2.bias', 'decoder_blocks.2.mlp.fc1.weight', 'decoder_blocks.2.mlp.fc1.bias', 'decoder_blocks.2.mlp.fc2.weight', 'decoder_blocks.2.mlp.fc2.bias', 'decoder_blocks.3.norm1.weight', 'decoder_blocks.3.norm1.bias', 'decoder_blocks.3.attn.qkv.weight', 'decoder_blocks.3.attn.qkv.bias', 'decoder_blocks.3.attn.proj.weight', 'decoder_blocks.3.attn.proj.bias', 'decoder_blocks.3.norm2.weight', 'decoder_blocks.3.norm2.bias', 'decoder_blocks.3.mlp.fc1.weight', 'decoder_blocks.3.mlp.fc1.bias', 'decoder_blocks.3.mlp.fc2.weight', 'decoder_blocks.3.mlp.fc2.bias', 'decoder_blocks.4.norm1.weight', 'decoder_blocks.4.norm1.bias', 'decoder_blocks.4.attn.qkv.weight', 'decoder_blocks.4.attn.qkv.bias', 'decoder_blocks.4.attn.proj.weight', 'decoder_blocks.4.attn.proj.bias', 'decoder_blocks.4.norm2.weight', 'decoder_blocks.4.norm2.bias', 'decoder_blocks.4.mlp.fc1.weight', 'decoder_blocks.4.mlp.fc1.bias', 'decoder_blocks.4.mlp.fc2.weight', 'decoder_blocks.4.mlp.fc2.bias', 'decoder_blocks.5.norm1.weight', 'decoder_blocks.5.norm1.bias', 'decoder_blocks.5.attn.qkv.weight', 'decoder_blocks.5.attn.qkv.bias', 'decoder_blocks.5.attn.proj.weight', 'decoder_blocks.5.attn.proj.bias', 'decoder_blocks.5.norm2.weight', 'decoder_blocks.5.norm2.bias', 'decoder_blocks.5.mlp.fc1.weight', 'decoder_blocks.5.mlp.fc1.bias', 'decoder_blocks.5.mlp.fc2.weight', 'decoder_blocks.5.mlp.fc2.bias', 'decoder_blocks.6.norm1.weight', 'decoder_blocks.6.norm1.bias', 'decoder_blocks.6.attn.qkv.weight', 'decoder_blocks.6.attn.qkv.bias', 'decoder_blocks.6.attn.proj.weight', 'decoder_blocks.6.attn.proj.bias', 'decoder_blocks.6.norm2.weight', 'decoder_blocks.6.norm2.bias', 'decoder_blocks.6.mlp.fc1.weight', 'decoder_blocks.6.mlp.fc1.bias', 'decoder_blocks.6.mlp.fc2.weight', 'decoder_blocks.6.mlp.fc2.bias', 'decoder_blocks.7.norm1.weight', 'decoder_blocks.7.norm1.bias', 'decoder_blocks.7.attn.qkv.weight', 'decoder_blocks.7.attn.qkv.bias', 'decoder_blocks.7.attn.proj.weight', 'decoder_blocks.7.attn.proj.bias', 'decoder_blocks.7.norm2.weight', 'decoder_blocks.7.norm2.bias', 'decoder_blocks.7.mlp.fc1.weight', 'decoder_blocks.7.mlp.fc1.bias', 'decoder_blocks.7.mlp.fc2.weight', 'decoder_blocks.7.mlp.fc2.bias', 'decoder_norm.weight', 'decoder_norm.bias', 'decoder_pred.weight', 'decoder_pred.bias'], unexpected_keys=[])

@gaopengpjlab
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Thanks for your interest in ConvMAE.

The checkpoint only contain encoder weight as only encoder weight is required for downstream tasks.

@lywang76
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lywang76 commented Aug 8, 2022

can you provide a whole pretrained convmae, too?

Because we want to fine tune it for our data.

@gaopengpjlab
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We will find a way to share the full model. Stay tuned.

@wnismiddle
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Hi, has the full model been released? We want to fine tune it for our data too

@RominaZakerian
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hi.
excuse me. how can I learn just the encoder weights with my own dataset again?

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