T5 AttributeError: 'T5Encoder' object has no attribute 'main_input_name'

I trained a T5 model and when I ran the inference it gave me error as mentioned in title. I installed required package as shown below. It was working yesterday but now it returned me this attribute error.

!pip install sentencepiece==0.1.95
!pip install torch
!pip install transformers
!pip install pytorch_lightning==0.7.5

import torch
from transformers import T5ForConditionalGeneration,T5Tokenizer

def get_model_output(sentence,model):
    c_output = []
    text =  sentence + ' </s>'

    max_len = 256

    encoding = tokenizer.encode_plus(text,pad_to_max_length=True, return_tensors="pt")
    input_ids, attention_masks = encoding["input_ids"].to("cpu"), encoding["attention_mask"].to("cpu")


    # set top_k = 50 and set top_p = 0.95 and num_return_sequences = 3
    beam_outputs= model.generate(
          input_ids=input_ids, attention_mask=attention_masks,
          max_length=64,
          num_beams=10, 
          no_repeat_ngram_size=2, 
          do_sample = False,
          num_return_sequences=5, 
          early_stopping=True
      )
    final_outputs =[]
    for beam_output in beam_outputs:
        sent = tokenizer.decode(beam_output, skip_special_tokens=True,clean_up_tokenization_spaces=True)
        if sent.lower() != sentence.lower() and sent not in final_outputs:
            final_outputs.append(sent)

    for final_output in final_outputs:
        c_output.append(final_output)
    return `c_output[0]`

Here is the error message:

[/usr/local/lib/python3.7/dist-packages/transformers/generation_utils.py](https://localhost:8080/#) in generate(self, inputs, max_length, min_length, do_sample, early_stopping, num_beams, temperature, top_k, top_p, repetition_penalty, bad_words_ids, bos_token_id, pad_token_id, eos_token_id, length_penalty, no_repeat_ngram_size, encoder_no_repeat_ngram_size, num_return_sequences, max_time, max_new_tokens, decoder_start_token_id, use_cache, num_beam_groups, diversity_penalty, prefix_allowed_tokens_fn, logits_processor, stopping_criteria, output_attentions, output_hidden_states, output_scores, return_dict_in_generate, forced_bos_token_id, forced_eos_token_id, remove_invalid_values, synced_gpus, **model_kwargs)
   1067         # otherwise model_input_name is None
   1068         # all model-specific keyword inputs are removed from `model_kwargs`
-> 1069         inputs_tensor, model_input_name, model_kwargs = self._prepare_model_inputs(inputs, bos_token_id, model_kwargs)
   1070         batch_size = inputs_tensor.shape[0]
   1071 

[/usr/local/lib/python3.7/dist-packages/transformers/generation_utils.py](https://localhost:8080/#) in _prepare_model_inputs(self, inputs, bos_token_id, model_kwargs)
    392             self.config.is_encoder_decoder
    393             and hasattr(self, "encoder")
--> 394             and self.encoder.main_input_name != self.main_input_name
    395         ):
    396             input_name = self.encoder.main_input_name

[/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py](https://localhost:8080/#) in __getattr__(self, name)
   1176                 return modules[name]
   1177         raise AttributeError("'{}' object has no attribute '{}'".format(
-> 1178             type(self).__name__, name))
   1179 
   1180     def __setattr__(self, name: str, value: Union[Tensor, 'Module']) -> None:

AttributeError: 'T5Encoder' object has no attribute 'main_input_name'

Can anyone suggest? Thanks in advance!