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import os
import numpy as np
from huggingface_hub import snapshot_download
from transformers import AutoConfig, AutoTokenizer, PreTrainedTokenizer
from typing import Any, Callable, Dict, Generator, List, Optional, Tuple, Union
import time
from .base_engine import BaseEngine
from ..configs import (
MODEL_PATH,
)
FAKE_MODEL_PATH = os.environ.get("FAKE_MODEL_PATH", MODEL_PATH)
FAKE_RESPONSE = "Wow that's very very cool, please try again."
class DebugEngine(BaseEngine):
"""
It will always yield FAKE_RESPONSE
"""
def __init__(self, **kwargs) -> None:
super().__init__(**kwargs)
self._model = None
self._tokenizer = None
@property
def tokenizer(self) -> PreTrainedTokenizer:
if self._tokenizer is None:
self._tokenizer = AutoTokenizer.from_pretrained(FAKE_MODEL_PATH, trust_remote_code=True)
return self._tokenizer
def load_model(self):
print(f"Load fake model with tokenizer: {self.tokenizer}")
def generate_yield_string(self, prompt, temperature, max_tokens, stop_strings: Optional[Tuple[str]] = None, **kwargs):
num_tokens = len(self.tokenizer.encode(prompt))
response = FAKE_RESPONSE
for i in range(len(response)):
time.sleep(0.01)
yield response[:i], num_tokens
num_tokens = len(self.tokenizer.encode(prompt + response))
yield response, num_tokens
def batch_generate(self, prompts, temperature, max_tokens, stop_strings: Optional[Tuple[str]] = None, **kwargs):
return [p + " -- Test" for p in prompts]
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