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Unbreak optimum-executorch (#38646)

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* Unbreak optimum-executorch

* use static cache if has layer_types but no sliding_window

* revert view on kv_arange

---------

Co-authored-by: Guang Yang <guangyang@fb.com>
This commit is contained in:
Guang Yang
2025-06-13 02:13:32 -07:00
committed by GitHub
parent 5f59a9b439
commit 7f00b325f8
9 changed files with 64 additions and 39 deletions
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6
tests/models/gemma/test_modeling_gemma.py
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@@ -378,7 +378,6 @@ class GemmaIntegrationTest(unittest.TestCase):
from transformers.integrations.executorch import (
TorchExportableModuleWithStaticCache,
convert_and_export_with_cache,
)
tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b", pad_token="</s>", padding_side="right")
@@ -424,7 +423,10 @@ class GemmaIntegrationTest(unittest.TestCase):
self.assertEqual(EXPECTED_TEXT_COMPLETION, eager_generated_text)
# Static Cache + export
exported_program = convert_and_export_with_cache(model)
from transformers.integrations.executorch import TorchExportableModuleForDecoderOnlyLM
exportable_module = TorchExportableModuleForDecoderOnlyLM(model)
exported_program = exportable_module.export()
ep_generated_ids = TorchExportableModuleWithStaticCache.generate(
exported_program=exported_program, prompt_token_ids=prompt_token_ids, max_new_tokens=max_new_tokens
)

6
tests/models/gemma2/test_modeling_gemma2.py
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@@ -313,7 +313,6 @@ class Gemma2IntegrationTest(unittest.TestCase):
from transformers.integrations.executorch import (
TorchExportableModuleWithStaticCache,
convert_and_export_with_cache,
)
tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-2b", pad_token="</s>", padding_side="right")
@@ -363,7 +362,10 @@ class Gemma2IntegrationTest(unittest.TestCase):
max_new_tokens = max_generation_length - prompt_token_ids.shape[-1]
# Static Cache + export
exported_program = convert_and_export_with_cache(model)
from transformers.integrations.executorch import TorchExportableModuleForDecoderOnlyLM
exportable_module = TorchExportableModuleForDecoderOnlyLM(model)
exported_program = exportable_module.export()
ep_generated_ids = TorchExportableModuleWithStaticCache.generate(
exported_program=exported_program, prompt_token_ids=prompt_token_ids, max_new_tokens=max_new_tokens
)

6
tests/models/llama/test_modeling_llama.py
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@@ -306,7 +306,6 @@ class LlamaIntegrationTest(unittest.TestCase):
from transformers.integrations.executorch import (
TorchExportableModuleWithStaticCache,
convert_and_export_with_cache,
)
llama_models = {
@@ -352,7 +351,10 @@ class LlamaIntegrationTest(unittest.TestCase):
max_new_tokens = max_generation_length - prompt_token_ids.shape[-1]
# Static Cache + export
exported_program = convert_and_export_with_cache(model)
from transformers.integrations.executorch import TorchExportableModuleForDecoderOnlyLM
exportable_module = TorchExportableModuleForDecoderOnlyLM(model)
exported_program = exportable_module.export()
ep_generated_ids = TorchExportableModuleWithStaticCache.generate(
exported_program=exported_program, prompt_token_ids=prompt_token_ids, max_new_tokens=max_new_tokens
)

6
tests/models/olmo/test_modeling_olmo.py
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@@ -334,7 +334,6 @@ class OlmoIntegrationTest(unittest.TestCase):
from transformers.integrations.executorch import (
TorchExportableModuleWithStaticCache,
convert_and_export_with_cache,
)
olmo_model = "allenai/OLMo-1B-hf"
@@ -382,7 +381,10 @@ class OlmoIntegrationTest(unittest.TestCase):
self.assertEqual(EXPECTED_TEXT_COMPLETION, eager_generated_text)
# Static Cache + export
exported_program = convert_and_export_with_cache(model)
from transformers.integrations.executorch import TorchExportableModuleForDecoderOnlyLM
exportable_module = TorchExportableModuleForDecoderOnlyLM(model)
exported_program = exportable_module.export()
ep_generated_ids = TorchExportableModuleWithStaticCache.generate(
exported_program=exported_program, prompt_token_ids=prompt_token_ids, max_new_tokens=max_new_tokens
)

6
tests/models/phi3/test_modeling_phi3.py
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@@ -347,7 +347,6 @@ class Phi3IntegrationTest(unittest.TestCase):
from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
from transformers.integrations.executorch import (
TorchExportableModuleWithStaticCache,
convert_and_export_with_cache,
)
model_id = "microsoft/Phi-4-mini-instruct"
@@ -399,7 +398,10 @@ class Phi3IntegrationTest(unittest.TestCase):
max_new_tokens = max_generation_length - prompt_token_ids.shape[-1]
# Static Cache + export
exported_program = convert_and_export_with_cache(model)
from transformers.integrations.executorch import TorchExportableModuleForDecoderOnlyLM
exportable_module = TorchExportableModuleForDecoderOnlyLM(model)
exported_program = exportable_module.export()
ep_generated_ids = TorchExportableModuleWithStaticCache.generate(
exported_program=exported_program, prompt_token_ids=prompt_token_ids, max_new_tokens=max_new_tokens
)

11
tests/models/qwen2/test_modeling_qwen2.py
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@@ -31,7 +31,6 @@ from transformers.testing_utils import (
slow,
torch_device,
)
from transformers.utils.import_utils import is_torch_greater_or_equal
if is_torch_available():
@@ -246,7 +245,6 @@ class Qwen2IntegrationTest(unittest.TestCase):
from transformers.integrations.executorch import (
TorchExportableModuleWithStaticCache,
convert_and_export_with_cache,
)
qwen_model = "Qwen/Qwen2-0.5B"
@@ -287,8 +285,13 @@ class Qwen2IntegrationTest(unittest.TestCase):
max_new_tokens = max_generation_length - prompt_token_ids.shape[-1]
# Static Cache + export
strict = is_torch_greater_or_equal("2.7.0") # Due to https://github.com/pytorch/pytorch/issues/150994
exported_program = convert_and_export_with_cache(model, strict=strict)
from transformers.integrations.executorch import TorchExportableModuleForDecoderOnlyLM
exportable_module = TorchExportableModuleForDecoderOnlyLM(model)
strict = version.parse(torch.__version__) != version.parse(
"2.7.0"
) # Due to https://github.com/pytorch/pytorch/issues/150994
exported_program = exportable_module.export(strict=strict)
ep_generated_ids = TorchExportableModuleWithStaticCache.generate(
exported_program=exported_program, prompt_token_ids=prompt_token_ids, max_new_tokens=max_new_tokens
)

9
tests/models/qwen3/test_modeling_qwen3.py
View File

@@ -31,7 +31,6 @@ from transformers.testing_utils import (
slow,
torch_device,
)
from transformers.utils.import_utils import is_torch_greater_or_equal
if is_torch_available():
@@ -240,13 +239,12 @@ class Qwen3IntegrationTest(unittest.TestCase):
from transformers.integrations.executorch import (
TorchExportableModuleWithStaticCache,
convert_and_export_with_cache,
)
qwen_model = "Qwen/Qwen3-0.6B-Base"
tokenizer = AutoTokenizer.from_pretrained(qwen_model, pad_token="</s>", padding_side="right")
if is_torch_greater_or_equal("2.7.0"):
if version.parse(torch.__version__) == version.parse("2.7.0"):
strict = False # Due to https://github.com/pytorch/pytorch/issues/150994
EXPECTED_TEXT_COMPLETION = ["My favourite condiment is 100% plain, unflavoured, and unadulterated."]
else:
@@ -285,7 +283,10 @@ class Qwen3IntegrationTest(unittest.TestCase):
max_new_tokens = max_generation_length - prompt_token_ids.shape[-1]
# Static Cache + export
exported_program = convert_and_export_with_cache(model, strict=strict)
from transformers.integrations.executorch import TorchExportableModuleForDecoderOnlyLM
exportable_module = TorchExportableModuleForDecoderOnlyLM(model)
exported_program = exportable_module.export(strict=strict)
ep_generated_ids = TorchExportableModuleWithStaticCache.generate(
exported_program=exported_program, prompt_token_ids=prompt_token_ids, max_new_tokens=max_new_tokens
)