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```python | |
import torch.nn as nn | |
from transformers import AutoModelForCausalLM | |
class CodeGenerator(nn.Module): | |
""" | |
A PyTorch module that generates code using a pre-trained language model. | |
This class inherits from `nn.Module` and encapsulates a pre-trained language model | |
from the Hugging Face Transformers library. The model is used to generate code | |
based on the input sequence. | |
Attributes: | |
- model (transformers.AutoModelForCausalLM): The pre-trained language model | |
used for code generation. | |
""" | |
def __init__(self, model_name): | |
""" | |
Initializes a new instance of the `CodeGenerator` class. | |
Parameters: | |
- model_name (str): The name of the pre-trained language model to use. | |
This should be a valid model name from the Hugging Face | |
Transformers library. | |
""" | |
super().__init__() | |
self.model = AutoModelForCausalLM.from_pretrained(model_name) | |
def forward(self, input_ids): | |
""" | |
Generates code based on the input sequence. | |
Parameters: | |
- input_ids (torch.Tensor): A tensor of token IDs representing the input | |
sequence for the language model. | |
Returns: | |
torch.Tensor: The output tensor containing the generated code. | |
""" | |
return self.model(input_ids)[0] | |
``` |