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fix pixtral processor (#34486)

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* fix pixtral processor

* test out full length batches + remove undue ValueError

* fix up processing

* fix tests

* fix

* last fixup

* style

* [run-slow] pixtral

* [run-slow] pixtral

* fix config key

* skip torchscript tests

* [run-slow] pixtral

* add missing key

* [run-slow] pixtral

* fix docs

* [run-slow] pixtral

* fix wrong url for integration test

* [run-slow] pixtral

* pixtralVisionModel does not have a lm head

* [run-slow] pixtral
This commit is contained in:
Pablo Montalvo
2024-10-30 14:17:20 +01:00
committed by GitHub
parent 8a734ea2c3
commit 241d79026f
5 changed files with 35 additions and 48 deletions
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41
tests/models/pixtral/test_modeling_pixtral.py
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@@ -14,22 +14,16 @@
# limitations under the License.
"""Testing suite for the PyTorch Pixtral model."""
import gc
import unittest
import requests
from transformers import (
AutoProcessor,
PixtralVisionConfig,
PixtralVisionModel,
is_torch_available,
is_vision_available,
)
from transformers.testing_utils import (
require_bitsandbytes,
require_torch,
slow,
torch_device,
)
@@ -43,7 +37,7 @@ else:
is_torch_greater_or_equal_than_2_0 = False
if is_vision_available():
from PIL import Image
pass
class PixtralVisionModelTester:
@@ -148,6 +142,7 @@ class PixtralVisionModelModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (PixtralVisionModel,) if is_torch_available() else ()
test_pruning = False
test_head_masking = False
test_torchscript = False
def setUp(self):
self.model_tester = PixtralVisionModelTester(self)
@@ -258,35 +253,3 @@ class PixtralVisionModelModelTest(ModelTesterMixin, unittest.TestCase):
@unittest.skip(reason="Not supported yet")
def test_determinism(self):
pass
@require_torch
class PixtralVisionModelIntegrationTest(unittest.TestCase):
def setUp(self):
self.processor = AutoProcessor.from_pretrained("hf-internal-testing/pixtral-12b")
def tearDown(self):
gc.collect()
torch.cuda.empty_cache()
@slow
@require_bitsandbytes
def test_small_model_integration_test(self):
# Let' s make sure we test the preprocessing to replace what is used
model = PixtralVisionModel.from_pretrained("hf-internal-testing/pixtral-12b", load_in_4bit=True)
prompt = "<s>[INST][IMG]\nWhat are the things I should be cautious about when I visit this place?[/INST]"
image_file = "https://pixtral-vl.github.io/static/images/view.jpg"
raw_image = Image.open(requests.get(image_file, stream=True).raw)
inputs = self.processor(prompt, raw_image, return_tensors="pt")
EXPECTED_INPUT_IDS = torch.tensor([[1, 32000, 28705, 13, 11123, 28747, 1824, 460, 272, 1722,315, 1023, 347, 13831, 925, 684, 739, 315, 3251, 456,1633, 28804, 13, 4816, 8048, 12738, 28747]]) # fmt: skip
self.assertTrue(torch.equal(inputs["input_ids"], EXPECTED_INPUT_IDS))
output = model.generate(**inputs, max_new_tokens=20)
EXPECTED_DECODED_TEXT = "\nUSER: What are the things I should be cautious about when I visit this place?\nASSISTANT: When visiting this place, there are a few things one should be cautious about. Firstly," # fmt: skip
self.assertEqual(
self.processor.decode(output[0], skip_special_tokens=True),
EXPECTED_DECODED_TEXT,
)