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
)