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update eager runner to use same options for loading the model #6257

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update eager runner to use same options for loading the model #6257

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58 changes: 15 additions & 43 deletions examples/models/llama2/runner/eager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,9 +11,12 @@
import torch

from examples.models.llama2.llama_transformer import ModelArgs
from executorch.examples.models.model_factory import EagerModelFactory

from .generation import LlamaRunner
from executorch.examples.models.llama2.export_llama_lib import (
_prepare_for_llama_export,
build_args_parser as _build_args_parser,
)
from executorch.examples.models.llama2.runner.generation import LlamaRunner
from executorch.extension.llm.export import LLMEdgeManager


class EagerLlamaRunner(LlamaRunner):
Expand All @@ -25,21 +28,17 @@ def __init__(self, args):
with open(args.params, "r") as f:
params = json.loads(f.read())
model_args: ModelArgs = ModelArgs(
max_seq_len=args.max_len,
max_seq_len=args.max_seq_length,
max_batch_size=1,
use_kv_cache=True,
use_kv_cache=args.use_kv_cache,
**params,
)
super().__init__(tokenizer_path=args.tokenizer, model_args=model_args)
self.model, _, _, _ = EagerModelFactory.create_model(
"llama2",
"Llama2Model",
checkpoint=args.checkpoint,
params=args.params,
use_kv_cache=True,
fairseq2=False,
max_seq_len=args.max_len,
enable_dynamic_shape=True,
super().__init__(tokenizer_path=args.tokenizer_path, model_args=model_args)
manager: LLMEdgeManager = _prepare_for_llama_export("llama", args)
self.model = (
manager.model.eval().to(device="cuda")
if torch.cuda.is_available()
else manager.model.eval().to(device="cpu")
)

def forward(
Expand All @@ -51,34 +50,7 @@ def forward(


def build_args_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser()

parser.add_argument(
"--checkpoint",
type=str,
default=None,
help="path to model checkpoint file",
)

parser.add_argument(
"--params",
type=str,
default=None,
help="model params file",
)

parser.add_argument(
"--max_len",
type=int,
default=128,
help="Maximum length of the generated response sequence.",
)

parser.add_argument(
"--tokenizer",
type=str,
default=None,
)
parser = _build_args_parser()

parser.add_argument(
"--prompt",
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