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fix 3 failed test cases for video_llama_3 model on Intel XPU #41931

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Merged
merged 6 commits into from
Nov 3, 2025
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fix 3 failed test cases for video_llama_3 model on Intel XPU #41931

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be6a37d
fix 3 failed test cases for video_llama_3 model on Intel XPU
kaixuanliu Oct 29, 2025
1051ccf
update
kaixuanliu Oct 30, 2025
4ddc86f
adjust format
kaixuanliu Oct 31, 2025
52c2754
Merge branch 'main' into video_llama_3
kaixuanliu Oct 31, 2025
f15e9ce
update code
kaixuanliu Nov 3, 2025
cf51ff3
Merge branch 'video_llama_3' of https://github.com/kaixuanliu/transfo…
kaixuanliu Nov 3, 2025
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2 changes: 1 addition & 1 deletion src/transformers/utils/import_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,7 @@ def _is_package_available(pkg_name: str, return_version: bool = False) -> tuple[
# pick the first item of the list as best guess (it's almost always a list of length 1 anyway)
distribution_name = pkg_name if pkg_name in distributions else distributions[0]
package_version = importlib.metadata.version(distribution_name)
except importlib.metadata.PackageNotFoundError:
except (importlib.metadata.PackageNotFoundError, KeyError):
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@ydshieh ydshieh Oct 29, 2025

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Could you explain what is the issue here that requires this new KeyError?

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@yao-matrix yao-matrix Oct 29, 2025

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same question.

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@kaixuanliu kaixuanliu Oct 30, 2025

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When i run pytest -rA tests/models/video_llama_3/test_modeling_video_llama_3.py::VideoLlama3ModelTest::test_generate_with_quant_cache, it will fail and return error:

pkg_name = 'optimum.quanto', return_version = True

    def _is_package_available(pkg_name: str, return_version: bool = False) -> tuple[bool, str] | bool:
        """Check if `pkg_name` exist, and optionally try to get its version"""
        spec = importlib.util.find_spec(pkg_name)
        package_exists = spec is not None
        package_version = "N/A"
        if package_exists and return_version:
            try:
                # importlib.metadata works with the distribution package, which may be different from the import
                # name (e.g. `PIL` is the import name, but `pillow` is the distribution name)
>               distributions = PACKAGE_DISTRIBUTION_MAPPING[pkg_name]
E               KeyError: 'optimum.quanto'

src/transformers/utils/import_utils.py:56: KeyError

Here is to fix this.

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@yao-matrix yao-matrix Oct 30, 2025

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@kaixuanliu it shows 'optimum': ['optimum-quanto', 'optimum-onnx', 'optimum'], in PACKAGE_DISTRIBUTION_MAPPING, so we may need another logic to search optimum-quanto distribution in optimum package, rather than using your current logic, because the package actually there, just we find it in a wrong way in this case. @ydshieh , WDYT?

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@ydshieh ydshieh Oct 30, 2025

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Let me check ,thank you for explaining the issue.

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@kaixuanliu kaixuanliu Oct 31, 2025

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In this PR, when we catch the keyError exception, it will load optimum-quanto in package = importlib.import_module(pkg_name), where pkg_name is optimum.quanto, and it can be imported properly.

# If we cannot find the metadata (because of editable install for example), try to import directly.
# Note that this branch will almost never be run, so we do not import packages for nothing here
package = importlib.import_module(pkg_name)
Expand Down
28 changes: 23 additions & 5 deletions tests/models/video_llama_3/test_modeling_video_llama_3.py
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Expand Up @@ -36,6 +36,7 @@
is_torch_available,
)
from transformers.testing_utils import (
Expectations,
backend_empty_cache,
require_flash_attn,
require_torch,
Expand Down Expand Up @@ -831,7 +832,14 @@ def test_small_model_integration_test(self):
torch.testing.assert_close(expected_pixel_slice, inputs.pixel_values[:6, :3], atol=1e-4, rtol=1e-4)

output = model.generate(**inputs, max_new_tokens=20, do_sample=False, repetition_penalty=None)
EXPECTED_DECODED_TEXT = "user\n\nDescribe the image.\nassistant\nThe image captures a vibrant nighttime scene on a bustling city street. A woman in a striking red dress"
# fmt: off
EXPECTED_DECODED_TEXT = Expectations(
{
("cuda", None): "user\n\nDescribe the image.\nassistant\nThe image captures a vibrant nighttime scene on a bustling city street. A woman in a striking red dress",
("xpu", None): "user\n\nDescribe the image.\nassistant\nThe image captures a vibrant night scene in a bustling Japanese city. A woman in a striking red dress",
}
).get_expectation()
# fmt: on

self.assertEqual(
self.processor.decode(output[0], skip_special_tokens=True),
Expand Down Expand Up @@ -874,11 +882,21 @@ def test_small_model_integration_test_batch_wo_image(self):

# it should not matter whether two images are the same size or not
output = model.generate(**inputs, max_new_tokens=20, do_sample=False, repetition_penalty=None)
# fmt: off
EXPECTED_DECODED_TEXT = Expectations(
{
("cuda", None): [
"user\n\nDescribe the image.\nassistant\nThe image captures a vibrant nighttime scene on a bustling city street. A woman in a striking red dress",
"user\nWhat is relativity?\nassistant\nRelativity is a scientific theory that describes the relationship between space and time. It was first proposed by",
],
("xpu", None): [
"user\n\nDescribe the image.\nassistant\nThe image captures a vibrant night scene in a bustling Japanese city. A woman in a striking red dress",
"user\nWhat is relativity?\nassistant\nRelativity is a scientific theory that describes the relationship between space and time. It was first proposed by",
],
}
).get_expectation()
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@yao-matrix yao-matrix Oct 29, 2025

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as above

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@kaixuanliu kaixuanliu Oct 30, 2025

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Done

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@yao-matrix yao-matrix Oct 30, 2025

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as above

# fmt: on

EXPECTED_DECODED_TEXT = [
"user\n\nDescribe the image.\nassistant\nThe image captures a vibrant nighttime scene on a bustling city street. A woman in a striking red dress",
"user\nWhat is relativity?\nassistant\nRelativity is a scientific theory that describes the relationship between space and time. It was first proposed by",
] # fmt: skip
self.assertEqual(
self.processor.batch_decode(output, skip_special_tokens=True),
EXPECTED_DECODED_TEXT,
Expand Down