inference error when predicting multimer sequence

[ssn1771]

when i try to inference multimer sequence，i met the error after finishing running alignment and searching for templates：
Traceback (most recent call last):
File "inference.py", line 513, in
main(args)
File "inference.py", line 148, in main
inference_multimer_model(args)
File "inference.py", line 268, in inference_multimer_model
processed_feature_dict = feature_processor.process_features(
File "/home/FastFold/fastfold/data/feature_pipeline.py", line 124, in process_features
return np_example_to_features(
File "/home/FastFold/fastfold/data/feature_pipeline.py", line 96, in np_example_to_features
features = input_pipeline_multimer.process_tensors_from_config(
File "/home/FastFold/fastfold/data/input_pipeline_multimer.py", line 107, in process_tensors_from_config
tensors = compose(nonensembled)(tensors)
File "/home/FastFold/fastfold/data/data_transforms.py", line 76, in
return lambda x: f(x, *args, **kwargs)
File "/home/FastFold/fastfold/data/input_pipeline_multimer.py", line 124, in compose
x = f(x)
File "/home/FastFold/fastfold/data/data_transforms_multimer.py", line 298, in make_msa_profile
batch['msa_mask'][..., None],
KeyError: 'msa_mask'

i’ve tried several sequences，but met the same error . The sequence is

7M5F_1|Chain A|CdiI|Serratia marcescens (615)
MKEIKLMADYHCYPLWGTTPDDFGDISPDELPISLGLKNSLEAWAKRYDAILNTDDPALSGFKSVEEEKLFIDDGYKLAELLQEELGSAYKVIYHADY
7M5F_2|Chain B[auth C]|Toxin CdiA|Serratia marcescens (615)
MHHHHHHENLYFQSNAAKNSLTTKSLFKEMTIQGIKFTPENVVGAAKDNSGKIIFLEKGNSKSGLQHIVEEHGDQFAQIGVSEARIPDVVMKAVTDGKIVGYQGAGAGRPIYETMIDGKKYNIAVTVGSNGYVVGANLRGSVK

[Shenggan]

I think it may be a problem with the input format, try using this fasta file as input.
target.fasta.txt

[ssn1771]

I tried the target fasta which you provided and met the same error ><

Traceback (most recent call last):
File "inference.py", line 513, in
main(args)
File "inference.py", line 148, in main
inference_multimer_model(args)
File "inference.py", line 268, in inference_multimer_model
processed_feature_dict = feature_processor.process_features(
File "/home/FastFold/fastfold/data/feature_pipeline.py", line 124, in process_features
return np_example_to_features(
File "/home/FastFold/fastfold/data/feature_pipeline.py", line 96, in np_example_to_features
features = input_pipeline_multimer.process_tensors_from_config(
File "/home/FastFold/fastfold/data/input_pipeline_multimer.py", line 107, in process_tensors_from_config
tensors = compose(nonensembled)(tensors)
File "/home/FastFold/fastfold/data/data_transforms.py", line 76, in
return lambda x: f(x, *args, **kwargs)
File "/home/FastFold/fastfold/data/input_pipeline_multimer.py", line 124, in compose
x = f(x)
File "/home/FastFold/fastfold/data/data_transforms_multimer.py", line 298, in make_msa_profile
batch['msa_mask'][..., None],
KeyError: 'msa_mask'

[Shenggan]

Are you using the latest main branch? I can inference this fasta file successfully.

[ssn1771]

ok, I pull the latest code and it works. Thanks a lot !

[Shenggan]

Thanks, feel free to contact us if you have ant further question.