RuntimeError: Error(s) in loading state_dict for M2TR

[zhaoyuchen803]

We tried to load the corresponding weights for the model but found them to be inconsistent, including c23 and c40. We don't understand why, it looks like the keys are wrong.

RuntimeError: Error(s) in loading state_dict for M2TR:
Missing key(s) in state_dict: "layers.2.0.t.attention.query_embedding.weight", "layers.2.0.t.attention.query_embedding.bias", "layers.2.0.t.attention.value_embedding.weight", "layers.2.0.t.attention.value_embedding.bias", "layers.2.0.t.attention.key_embedding.weight", "layers.2.0.t.attention.key_embedding.bias", "layers.2.0.t.attention.output_linear.0.weight", "layers.2.0.t.attention.output_linear.0.bias", "layers.2.0.t.attention.output_linear.1.weight", "layers.2.0.t.attention.output_linear.1.bias", "layers.2.0.t.attention.output_linear.1.running_mean", "layers.2.0.t.attention.output_linear.1.running_var", "layers.2.0.t.feed_forward.conv.0.weight", "layers.2.0.t.feed_forward.conv.0.bias", "layers.2.0.t.feed_forward.conv.1.weight", "layers.2.0.t.feed_forward.conv.1.bias", "layers.2.0.t.feed_forward.conv.1.running_mean", "layers.2.0.t.feed_forward.conv.1.running_var", "layers.2.0.t.feed_forward.conv.3.weight", "layers.2.0.t.feed_forward.conv.3.bias", "layers.2.0.t.feed_forward.conv.4.weight", "layers.2.0.t.feed_forward.conv.4.bias", "layers.2.0.t.feed_forward.conv.4.running_mean", "layers.2.0.t.feed_forward.conv.4.running_var", "layers.2.1.filter.complex_weight", "layers.2.1.feed_forward.conv.0.weight", "layers.2.1.feed_forward.conv.0.bias", "layers.2.1.feed_forward.conv.1.weight", "layers.2.1.feed_forward.conv.1.bias", "layers.2.1.feed_forward.conv.1.running_mean", "layers.2.1.feed_forward.conv.1.running_var", "layers.2.1.feed_forward.conv.3.weight", "layers.2.1.feed_forward.conv.3.bias", "layers.2.1.feed_forward.conv.4.weight", "layers.2.1.feed_forward.conv.4.bias", "layers.2.1.feed_forward.conv.4.running_mean", "layers.2.1.feed_forward.conv.4.running_var", "layers.2.2.conv1.weight", "layers.2.2.conv1.bias", "layers.2.2.conv2.weight", "layers.2.2.conv2.bias", "layers.2.2.conv3.weight", "layers.2.2.conv3.bias", "layers.2.2.conv4.0.weight", "layers.2.2.conv4.0.bias", "layers.2.2.conv4.1.weight", "layers.2.2.conv4.1.bias", "layers.2.2.conv4.1.running_mean", "layers.2.2.conv4.1.running_var", "layers.3.0.t.attention.query_embedding.weight", "layers.3.0.t.attention.query_embedding.bias", "layers.3.0.t.attention.value_embedding.weight", "layers.3.0.t.attention.value_embedding.bias", "layers.3.0.t.attention.key_embedding.weight", "layers.3.0.t.attention.key_embedding.bias", "layers.3.0.t.attention.output_linear.0.weight", "layers.3.0.t.attention.output_linear.0.bias", "layers.3.0.t.attention.output_linear.1.weight", "layers.3.0.t.attention.output_linear.1.bias", "layers.3.0.t.attention.output_linear.1.running_mean", "layers.3.0.t.attention.output_linear.1.running_var", "layers.3.0.t.feed_forward.conv.0.weight", "layers.3.0.t.feed_forward.conv.0.bias", "layers.3.0.t.feed_forward.conv.1.weight", "layers.3.0.t.feed_forward.conv.1.bias", "layers.3.0.t.feed_forward.conv.1.running_mean", "layers.3.0.t.feed_forward.conv.1.running_var", "layers.3.0.t.feed_forward.conv.3.weight", "layers.3.0.t.feed_forward.conv.3.bias", "layers.3.0.t.feed_forward.conv.4.weight", "layers.3.0.t.feed_forward.conv.4.bias", "layers.3.0.t.feed_forward.conv.4.running_mean", "layers.3.0.t.feed_forward.conv.4.running_var", "layers.3.1.filter.complex_weight", "layers.3.1.feed_forward.conv.0.weight", "layers.3.1.feed_forward.conv.0.bias", "layers.3.1.feed_forward.conv.1.weight", "layers.3.1.feed_forward.conv.1.bias", "layers.3.1.feed_forward.conv.1.running_mean", "layers.3.1.feed_forward.conv.1.running_var", "layers.3.1.feed_forward.conv.3.weight", "layers.3.1.feed_forward.conv.3.bias", "layers.3.1.feed_forward.conv.4.weight", "layers.3.1.feed_forward.conv.4.bias", "layers.3.1.feed_forward.conv.4.running_mean", "layers.3.1.feed_forward.conv.4.running_var", "layers.3.2.conv1.weight", "layers.3.2.conv1.bias", "layers.3.2.conv2.weight", "layers.3.2.conv2.bias", "layers.3.2.conv3.weight", "layers.3.2.conv3.bias", "layers.3.2.conv4.0.weight", "layers.3.2.conv4.0.bias", "layers.3.2.conv4.1.weight", "layers.3.2.conv4.1.bias", "layers.3.2.conv4.1.running_mean", "layers.3.2.conv4.1.running_var", "classifier.projection.weight", "classifier.projection.bias".
Unexpected key(s) in state_dict: "classifier.weight", "classifier.bias".
size mismatch for model._fc.weight: copying a param with shape torch.Size([1, 1792]) from checkpoint, the shape in current model is torch.Size([2, 1792]).
size mismatch for model._fc.bias: copying a param with shape torch.Size([1]) from checkpoint, the shape in current model is torch.Size([2]).

Hope this can be fixed soon.

[AllenOris]

Thanks for pointing out. It was a fc layer problem. We have updated M2TR checkpoints.