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Fixing mixtral runner #258

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merged 1 commit into from
Aug 5, 2024
Merged

Fixing mixtral runner #258

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15 changes: 12 additions & 3 deletions natural_language_processing/text_generation/mixtral/run.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,11 +18,12 @@
sys.exit(1)


def run_pytorch(num_runs, timeout, dataset_path, disable_jit_freeze=False, **kwargs):
def run_pytorch(num_runs, timeout, dataset_path, use_torch_fp16=False):
from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
from utils.nlp.alpaca_instruct import AlpacaInstruct
from utils.pytorch import PyTorchRunnerV2, apply_compile
from utils.benchmark import run_model
import torch

def run_single_pass(pytorch_runner, dataset):
input_array = [{"role": "user", "content": dataset.get_input_string()}]
Expand All @@ -33,8 +34,12 @@ def run_single_pass(pytorch_runner, dataset):
response = decode(outputs[:, inputs.shape[1]:])[0]
dataset.submit_prediction(response)

# This is needed for TorchDynamo to correctly capture where op
torch._dynamo.config.capture_dynamic_output_shape_ops = True
model = AutoModelForCausalLM.from_pretrained("mistralai/Mixtral-8x7B-Instruct-v0.1")
model.eval()
if use_torch_fp16:
model = model.half()
model.forward = apply_compile(model.forward)

tokenizer = AutoTokenizer.from_pretrained("mistralai/Mixtral-8x7B-Instruct-v0.1")
Expand All @@ -51,8 +56,12 @@ def run_single_pass(pytorch_runner, dataset):
return run_model(run_single_pass, runner, dataset, 1, num_runs, timeout)


def run_pytorch_fp32(num_runs, timeout, dataset_path, disable_jit_freeze=False, **kwargs):
return run_pytorch(num_runs, timeout, dataset_path, disable_jit_freeze, **kwargs)
def run_pytorch_fp32(num_runs, timeout, dataset_path, **kwargs):
return run_pytorch(num_runs, timeout, dataset_path)


def run_pytorch_fp16(num_runs, timeout, dataset_path, **kwargs):
return run_pytorch(num_runs, timeout, dataset_path, use_torch_fp16=True, **kwargs)


def main():
Expand Down