Llama3 and Llama2 are ExecuTorch compatible (#34101)

Llama3_1b and Llama2_7b are ExecuTorch compatible

Co-authored-by: Guang Yang <guangyang@fb.com>
This commit is contained in:
Guang Yang
2024-10-17 08:33:19 -07:00
committed by GitHub
parent 7f5088503f
commit 9470c00042

View File

@@ -23,6 +23,7 @@ from packaging import version
from parameterized import parameterized
from transformers import AutoTokenizer, LlamaConfig, StaticCache, is_torch_available, set_seed
from transformers.generation.configuration_utils import GenerationConfig
from transformers.testing_utils import (
backend_empty_cache,
require_bitsandbytes,
@@ -916,6 +917,74 @@ class LlamaIntegrationTest(unittest.TestCase):
static_compiled_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
self.assertEqual(EXPECTED_TEXT_COMPLETION, static_compiled_text)
@slow
@require_read_token
def test_export_static_cache(self):
if version.parse(torch.__version__) < version.parse("2.4.0"):
self.skipTest(reason="This test requires torch >= 2.4 to run.")
from transformers.integrations.executorch import (
TorchExportableModuleWithStaticCache,
convert_and_export_with_cache,
)
llama_models = {
"meta-llama/Llama-3.2-1B": [
"Simply put, the theory of relativity states that 1) the speed of light is the same for all "
"observers, regardless of their location, and 2) the laws of physics are the same for all observers"
],
"meta-llama/Llama-3.2-3B": [
"Simply put, the theory of relativity states that 1. the speed of light is constant, and 2. "
"the speed of light is the fastest speed possible"
],
"meta-llama/Llama-2-7b-hf": [
"Simply put, the theory of relativity states that 1) the speed of light is a constant, and 2) "
"the laws of physics are the same for all",
],
}
for llama_model_ckp, EXPECTED_TEXT_COMPLETION in llama_models.items():
# Load tokenizer
tokenizer = AutoTokenizer.from_pretrained(llama_model_ckp, pad_token="</s>", padding_side="right")
max_generation_length = tokenizer(EXPECTED_TEXT_COMPLETION, return_tensors="pt", padding=True)[
"input_ids"
].shape[-1]
# Load model
device = "cpu"
dtype = torch.bfloat16
cache_implementation = "static"
attn_implementation = "sdpa"
batch_size = 1
model = LlamaForCausalLM.from_pretrained(
llama_model_ckp,
device_map=device,
torch_dtype=dtype,
attn_implementation=attn_implementation,
generation_config=GenerationConfig(
use_cache=True,
cache_implementation=cache_implementation,
max_length=max_generation_length,
cache_config={
"batch_size": batch_size,
"max_cache_len": max_generation_length,
},
),
)
prompts = ["Simply put, the theory of relativity states that "]
prompt_tokens = tokenizer(prompts, return_tensors="pt", padding=True).to(model.device)
prompt_token_ids = prompt_tokens["input_ids"]
max_new_tokens = max_generation_length - prompt_token_ids.shape[-1]
# Static Cache + export
exported_program = convert_and_export_with_cache(model)
ep_generated_ids = TorchExportableModuleWithStaticCache.generate(
exported_program=exported_program, prompt_token_ids=prompt_token_ids, max_new_tokens=max_new_tokens
)
ep_generated_text = tokenizer.batch_decode(ep_generated_ids, skip_special_tokens=True)
self.assertEqual(EXPECTED_TEXT_COMPLETION, ep_generated_text)
@slow
@require_torch_accelerator