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Modify ProcessorTesterMixin for better generalization #32637

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merged 3 commits into from
Aug 13, 2024
Merged

Modify ProcessorTesterMixin for better generalization #32637

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dc5e360
Add padding="max_length" to tokenizer kwargs and change crop_size to …
yonigozlan Aug 12, 2024
e8064ef
remove crop_size argument in align processor tests to be coherent wit…
yonigozlan Aug 12, 2024
3c85fcb
Add pad_token when loading tokenizer if needed, change test override …
yonigozlan Aug 13, 2024
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2 changes: 0 additions & 2 deletions tests/models/align/test_processor_align.py
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Original file line number Diff line number Diff line change
Expand Up @@ -66,8 +66,6 @@ def setUp(self):
image_processor_map = {
"do_resize": True,
"size": 20,
"do_center_crop": True,
"crop_size": 18,
"do_normalize": True,
"image_mean": [0.48145466, 0.4578275, 0.40821073],
"image_std": [0.26862954, 0.26130258, 0.27577711],
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42 changes: 28 additions & 14 deletions tests/test_processing_common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -126,7 +126,9 @@ def test_tokenizer_defaults_preserved_by_kwargs(self):
if "image_processor" not in self.processor_class.attributes:
self.skipTest(f"image_processor attribute not present in {self.processor_class}")
image_processor = self.get_component("image_processor")
tokenizer = self.get_component("tokenizer", max_length=117)
tokenizer = self.get_component("tokenizer", max_length=117, padding="max_length")
if not tokenizer.pad_token:
tokenizer.pad_token = "[TEST_PAD]"

processor = self.processor_class(tokenizer=tokenizer, image_processor=image_processor)
self.skip_processor_without_typed_kwargs(processor)
Expand All @@ -141,8 +143,10 @@ def test_tokenizer_defaults_preserved_by_kwargs(self):
def test_image_processor_defaults_preserved_by_image_kwargs(self):
if "image_processor" not in self.processor_class.attributes:
self.skipTest(f"image_processor attribute not present in {self.processor_class}")
image_processor = self.get_component("image_processor", crop_size=(234, 234))
tokenizer = self.get_component("tokenizer", max_length=117)
image_processor = self.get_component("image_processor", size=(234, 234))
tokenizer = self.get_component("tokenizer", max_length=117, padding="max_length")
if not tokenizer.pad_token:
tokenizer.pad_token = "[TEST_PAD]"

processor = self.processor_class(tokenizer=tokenizer, image_processor=image_processor)
self.skip_processor_without_typed_kwargs(processor)
Expand All @@ -159,31 +163,37 @@ def test_kwargs_overrides_default_tokenizer_kwargs(self):
if "image_processor" not in self.processor_class.attributes:
self.skipTest(f"image_processor attribute not present in {self.processor_class}")
image_processor = self.get_component("image_processor")
tokenizer = self.get_component("tokenizer", max_length=117)
tokenizer = self.get_component("tokenizer", max_length=117, padding="max_length")
if not tokenizer.pad_token:
tokenizer.pad_token = "[TEST_PAD]"

processor = self.processor_class(tokenizer=tokenizer, image_processor=image_processor)
self.skip_processor_without_typed_kwargs(processor)
input_str = "lower newer"
image_input = self.prepare_image_inputs()

inputs = processor(text=input_str, images=image_input, return_tensors="pt", max_length=112)
inputs = processor(
text=input_str, images=image_input, return_tensors="pt", max_length=112, padding="max_length"
)
Comment on lines +171 to +173
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nit: a bit redundant to indicate max-length when init tokenizer and when calling. IMO we can remove it from init because we're testing kwargs at call

Or we can even explicitly init with a padding=longest and test if kwargs overrides defaults, as the test name suggests

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+1 on removing from the init.

Checking the kwargs overrides is also a good idea - we should add a new test to isolate and check this behaviour

self.assertEqual(len(inputs["input_ids"][0]), 112)

@require_torch
@require_vision
def test_kwargs_overrides_default_image_processor_kwargs(self):
if "image_processor" not in self.processor_class.attributes:
self.skipTest(f"image_processor attribute not present in {self.processor_class}")
image_processor = self.get_component("image_processor", crop_size=(234, 234))
tokenizer = self.get_component("tokenizer", max_length=117)
image_processor = self.get_component("image_processor", size=(234, 234))
tokenizer = self.get_component("tokenizer", max_length=117, padding="max_length")
if not tokenizer.pad_token:
tokenizer.pad_token = "[TEST_PAD]"
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I see this recurring in all tests, maybe we should add pad token when saving dummy tokenizer, so it's loaded with a pad id

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+1


processor = self.processor_class(tokenizer=tokenizer, image_processor=image_processor)
self.skip_processor_without_typed_kwargs(processor)

input_str = "lower newer"
image_input = self.prepare_image_inputs()

inputs = processor(text=input_str, images=image_input, crop_size=[224, 224])
inputs = processor(text=input_str, images=image_input, size=[224, 224])
self.assertEqual(len(inputs["pixel_values"][0][0]), 224)

@require_torch
Expand All @@ -193,6 +203,8 @@ def test_unstructured_kwargs(self):
self.skipTest(f"image_processor attribute not present in {self.processor_class}")
image_processor = self.get_component("image_processor")
tokenizer = self.get_component("tokenizer")
if not tokenizer.pad_token:
tokenizer.pad_token = "[TEST_PAD]"

processor = self.processor_class(tokenizer=tokenizer, image_processor=image_processor)
self.skip_processor_without_typed_kwargs(processor)
Expand All @@ -203,7 +215,7 @@ def test_unstructured_kwargs(self):
text=input_str,
images=image_input,
return_tensors="pt",
crop_size={"height": 214, "width": 214},
size={"height": 214, "width": 214},
padding="max_length",
max_length=76,
)
Expand All @@ -218,6 +230,8 @@ def test_unstructured_kwargs_batched(self):
self.skipTest(f"image_processor attribute not present in {self.processor_class}")
image_processor = self.get_component("image_processor")
tokenizer = self.get_component("tokenizer")
if not tokenizer.pad_token:
tokenizer.pad_token = "[TEST_PAD]"

processor = self.processor_class(tokenizer=tokenizer, image_processor=image_processor)
self.skip_processor_without_typed_kwargs(processor)
Expand All @@ -228,7 +242,7 @@ def test_unstructured_kwargs_batched(self):
text=input_str,
images=image_input,
return_tensors="pt",
crop_size={"height": 214, "width": 214},
size={"height": 214, "width": 214},
padding="longest",
max_length=76,
)
Expand All @@ -254,8 +268,8 @@ def test_doubly_passed_kwargs(self):
_ = processor(
text=input_str,
images=image_input,
images_kwargs={"crop_size": {"height": 222, "width": 222}},
crop_size={"height": 214, "width": 214},
images_kwargs={"size": {"height": 222, "width": 222}},
size={"height": 214, "width": 214},
)

@require_torch
Expand All @@ -275,7 +289,7 @@ def test_structured_kwargs_nested(self):
# Define the kwargs for each modality
all_kwargs = {
"common_kwargs": {"return_tensors": "pt"},
"images_kwargs": {"crop_size": {"height": 214, "width": 214}},
"images_kwargs": {"size": {"height": 214, "width": 214}},
"text_kwargs": {"padding": "max_length", "max_length": 76},
}

Expand Down Expand Up @@ -303,7 +317,7 @@ def test_structured_kwargs_nested_from_dict(self):
# Define the kwargs for each modality
all_kwargs = {
"common_kwargs": {"return_tensors": "pt"},
"images_kwargs": {"crop_size": {"height": 214, "width": 214}},
"images_kwargs": {"size": {"height": 214, "width": 214}},
"text_kwargs": {"padding": "max_length", "max_length": 76},
}

Expand Down
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