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Anand Inguva updated BEAM-14337: -------------------------------- Description: Some models in Pytorch instantiating from torch.nn.Module, has extra parameters in the forward function call. These extra parameters can be passed as Dict or as positional arguments. Example of PyTorch models supported by Hugging Face -> [https://huggingface.co/bert-base-uncased] [Some torch models on Hugging face|https://github.com/huggingface/transformers/blob/main/src/transformers/models/bert/modeling_bert.py] Eg: [https://huggingface.co/docs/transformers/model_doc/bert#transformers.BertModel] {code:java} inputs = { input_ids: Tensor1, attention_mask: Tensor2, token_type_ids: Tensor3, } model = BertModel.from_pretrained("bert-base-uncased") # which is a #subclass of torch.nn.Module outputs = model(**inputs) # model forward method should be expecting the keys in the inputs as the positional arguments.{code} [Transformers|https://pytorch.org/hub/huggingface_pytorch-transformers/] integrated in Pytorch as supported by Hugging Face as well. was: Some models in Pytorch instantiating from torch.nn.Module, has extra parameters in the forward function call. These extra parameters can be passed as Dict or as positional arguments. Example of PyTorch models supported by Hugging Face -> [https://huggingface.co/bert-base-uncased] [Some torch models on Hugging face|https://github.com/huggingface/transformers/blob/main/src/transformers/models/bert/modeling_bert.py] Eg: [https://huggingface.co/docs/transformers/model_doc/bert#transformers.BertModel] {code:java} inputs = { input_ids: Tensor1, attention_mask: Tensor2, token_type_ids: Tensor3, } model = BertModel.from_pretrained("bert-base-uncased") # which is a #subclass of torch.nn.Module outputs = model(**inputs) # model forward method should be expecting the keys in the inputs as the positional arguments.{code} > Support **kwargs for PyTorch models. > ------------------------------------ > > Key: BEAM-14337 > URL: https://issues.apache.org/jira/browse/BEAM-14337 > Project: Beam > Issue Type: Sub-task > Components: sdk-py-core > Reporter: Anand Inguva > Priority: P2 > > Some models in Pytorch instantiating from torch.nn.Module, has extra > parameters in the forward function call. These extra parameters can be passed > as Dict or as positional arguments. > Example of PyTorch models supported by Hugging Face -> > [https://huggingface.co/bert-base-uncased] > [Some torch models on Hugging > face|https://github.com/huggingface/transformers/blob/main/src/transformers/models/bert/modeling_bert.py] > Eg: > [https://huggingface.co/docs/transformers/model_doc/bert#transformers.BertModel] > {code:java} > inputs = { > input_ids: Tensor1, > attention_mask: Tensor2, > token_type_ids: Tensor3, > } > model = BertModel.from_pretrained("bert-base-uncased") # which is a > #subclass of torch.nn.Module > outputs = model(**inputs) # model forward method should be expecting the keys > in the inputs as the positional arguments.{code} > > [Transformers|https://pytorch.org/hub/huggingface_pytorch-transformers/] > integrated in Pytorch as supported by Hugging Face as well. > -- This message was sent by Atlassian Jira (v8.20.7#820007)