mirror of
https://github.com/huggingface/trl.git
synced 2025-10-20 18:43:52 +08:00
78 lines
2.5 KiB
Python
78 lines
2.5 KiB
Python
# Copyright 2020-2025 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.
|
|
|
|
import config
|
|
import torch
|
|
from torch.utils import benchmark
|
|
from transformers import AutoModelForCausalLM, AutoTokenizer
|
|
|
|
|
|
def generate_tokens(model, inputs):
|
|
outputs = model.generate(
|
|
**inputs,
|
|
do_sample=False,
|
|
max_new_tokens=64,
|
|
)
|
|
return outputs
|
|
|
|
|
|
def generate_tokens_with_assistance(model, inputs, assistant_early_exit):
|
|
outputs = model.generate(
|
|
**inputs,
|
|
assistant_early_exit=assistant_early_exit,
|
|
do_sample=False,
|
|
max_new_tokens=64,
|
|
)
|
|
return outputs
|
|
|
|
|
|
if __name__ == "__main__":
|
|
ckpt = config.hub_model_id
|
|
|
|
model = AutoModelForCausalLM.from_pretrained(ckpt, device_map="auto", torch_dtype=torch.bfloat16)
|
|
tokenizer = AutoTokenizer.from_pretrained(ckpt)
|
|
|
|
prompt = "### Instruction: What are my alarms for the rest of the day?\n ### Response: "
|
|
|
|
results = []
|
|
label = "Generation Times"
|
|
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
|
|
|
|
results.append(
|
|
benchmark.Timer(
|
|
stmt="generate_tokens(model, inputs)",
|
|
setup="from __main__ import generate_tokens",
|
|
globals={"model": model, "inputs": inputs},
|
|
num_threads=torch.get_num_threads(),
|
|
label=label,
|
|
sub_label="no layer skip",
|
|
description="generation",
|
|
).blocked_autorange()
|
|
)
|
|
|
|
for i in range(1, model.config.num_hidden_layers):
|
|
results.append(
|
|
benchmark.Timer(
|
|
stmt="generate_tokens_with_assistance(model, inputs, assistant_early_exit)",
|
|
setup="from __main__ import generate_assistant_tokens",
|
|
globals={"model": model, "assistant_early_exit": i, "inputs": inputs},
|
|
num_threads=torch.get_num_threads(),
|
|
label=label,
|
|
sub_label=f"layer skip {i}",
|
|
description="generation",
|
|
).blocked_autorange()
|
|
)
|
|
|
|
benchmark.Compare(results).print()
|