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"""minicpm.py.
File for providing the MiniCPM model implementation.
"""
import logging
import torch
from PIL import Image
from transformers import AutoModel, AutoTokenizer
from transformers.feature_extraction_utils import BatchFeature
from src.models.base import ModelBase
from src.models.config import Config
class MiniCPMModel(ModelBase):
"""MiniCPM model implementation."""
def __init__(self, config: Config) -> None:
"""Initialization of the MiniCPM model.
Args:
config (Config): Parsed config
"""
# initialize the parent class
super().__init__(config)
def _load_specific_model(self) -> None:
"""Overridden function to populate self.model."""
self.model = AutoModel.from_pretrained(
self.model_path, **getattr(self.config, 'model', {})
)
def _generate_prompt(self, prompt: str) -> str:
"""Generates the MiniCPM model prompt which will not use the chat template.
Args:
prompt (str): The prompt content.
Returns:
str: The prompt to return, set by the config.
"""
return prompt
def _init_processor(self) -> None:
"""Initialize the MiniCPM tokenizer."""
self.processor = None # no intended processor here
self.tokenizer = AutoTokenizer.from_pretrained(self.model_path, trust_remote_code=True)
def _generate_processor_output(self, prompt: str, img_path: str) -> dict:
"""Generate the processor outputs from the prompt and image path.
Args:
prompt (str): The generated prompt string with the input text and
the image labels.
img_path (str): The specified image path.
Returns:
dict: The corresponding processor output per image and prompt.
"""
msgs = [{'role': 'user', 'content': prompt}]
image = Image.open(img_path).convert('RGB')
return {'msgs': msgs, 'image': image}
def _forward(self, data: BatchFeature) -> None:
"""Given some input data, performs a single forward pass.
This function itself can be overriden, while _hook_and_eval
should be left in tact.
Args:
data (BatchFeature): The given data tensor.
"""
with torch.no_grad():
_ = self.model.chat(**data, context=None, tokenizer=self.tokenizer, **self.config.forward)
logging.debug('Completed forward pass...')
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