text-generation-inference/server/text_generation_server/jetstream_pt_support/compatibility.py (24 lines of code) (raw):

# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from typing import Any from transformers import AutoConfig from optimum.tpu import jetstream_pt_available def model_can_use_jetstream_pt(model_path: str) -> bool: """Checks if the model is supported by Jetstream Pytorch on Optimum TPU and if the required dependencies to provide the engine are installed. """ config = AutoConfig.from_pretrained(model_path) # For now few models are supported supported_models = ["llama", "gemma", "mixtral"] if config.model_type not in supported_models: return False if jetstream_pt_available(): return True return False def create_engine( model_path: str, batch_size: int, sequence_length: int, max_input_tokens: int, max_output_tokens: int, ) -> Any: if not model_can_use_jetstream_pt(model_path): # The model is not compatible with Jetstream PyTorch, just exit return None # Now import engine_loader to prevent importing it at the top when not supported from .engine_loader import create_engine return create_engine( model_path, batch_size, sequence_length, max_input_tokens, max_output_tokens )