Skip to content

Remove pad_max_tiles from preprocess #6295

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

Remove pad_max_tiles from preprocess #6295

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 4 additions & 4 deletions examples/models/llama3_2_vision/preprocess/export_preprocess.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,17 +13,17 @@


def main():
# Export
ep = export_preprocess()

# ExecuTorch
et = lower_to_executorch_preprocess(ep)
ep_et = export_preprocess()
et = lower_to_executorch_preprocess(ep_et)
with open("preprocess_et.pte", "wb") as file:
et.write_to_file(file)

# AOTInductor
ep_aoti = export_preprocess()
torch._inductor.aot_compile(
ep.module(),
ep_aoti.module(),
get_example_inputs(),
options={"aot_inductor.output_path": "preprocess_aoti.so"},
)
Expand Down
2 changes: 0 additions & 2 deletions examples/models/llama3_2_vision/preprocess/export_preprocess_lib.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,6 @@ def export_preprocess(
max_num_tiles: int = 4,
tile_size: int = 224,
antialias: bool = False,
pad_max_tiles: bool = True,
) -> ExportedProgram:

# Instantiate eager model.
Expand All @@ -54,7 +53,6 @@ def export_preprocess(
max_num_tiles=max_num_tiles,
tile_size=tile_size,
antialias=antialias,
pad_max_tiles=pad_max_tiles,
)

# Replace non-exportable ops with custom ops.
Expand Down
51 changes: 8 additions & 43 deletions examples/models/llama3_2_vision/preprocess/test_preprocess.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,11 @@

from executorch.extension.pybindings import portable_lib # noqa # usort: skip
from executorch.extension.llm.custom_ops import sdpa_with_kv_cache # noqa # usort: skip
from executorch.examples.models.llama3_2_vision.preprocess.export_preprocess_lib import (
export_preprocess,
get_example_inputs,
lower_to_executorch_preprocess,
)
from executorch.extension.pybindings.portable_lib import (
_load_for_executorch_from_buffer,
)
Expand All @@ -37,12 +42,6 @@
)
from torchvision.transforms.v2 import functional as F

from .export_preprocess_lib import (
export_preprocess,
get_example_inputs,
lower_to_executorch_preprocess,
)


@dataclass
class PreprocessConfig:
Expand All @@ -54,7 +53,6 @@ class PreprocessConfig:
tile_size: int = 224
max_num_tiles: int = 4
possible_resolutions = None
pad_max_tiles: bool = True


class TestImageTransform(unittest.TestCase):
Expand Down Expand Up @@ -137,17 +135,6 @@ def prepare_inputs(
[1.0, 1.0], # expected_tile_max
[0.0, 0.0], # expected_tile_min
[1, 2], # expected_aspect_ratio
False, # pad_max_tiles
),
(
(100, 400, 3), # image_size
torch.Size([4, 3, 224, 224]), # expected shape
False, # resize_to_max_canvas
[0.2230, 0.1763, 0.0, 0.0], # expected_tile_means
[1.0, 1.0, 0.0, 0.0], # expected_tile_max
[0.0, 0.0, 0.0, 0.0], # expected_tile_min
[1, 2], # expected_aspect_ratio
True, # pad_max_tiles
),
(
(1000, 300, 3), # image_size
Expand All @@ -157,7 +144,6 @@ def prepare_inputs(
[0.9976, 0.9940, 0.9936, 0.9906], # expected_tile_max
[0.0037, 0.0047, 0.0039, 0.0], # expected_tile_min
[4, 1], # expected_aspect_ratio
False, # pad_max_tiles
),
(
(200, 200, 3), # image_size
Expand All @@ -167,7 +153,6 @@ def prepare_inputs(
[0.9921, 0.9925, 0.9969, 0.9908], # expected_tile_max
[0.0056, 0.0069, 0.0059, 0.0032], # expected_tile_min
[2, 2], # expected_aspect_ratio
False, # pad_max_tiles
),
(
(600, 200, 3), # image_size
Expand All @@ -177,17 +162,6 @@ def prepare_inputs(
[1.0, 1.0, 1.0], # expected_tile_max
[0.0, 0.0, 0.0], # expected_tile_min
[3, 1], # expected_aspect_ratio
False, # pad_max_tiles
),
(
(600, 200, 3), # image_size
torch.Size([4, 3, 224, 224]), # expected shape
False, # resize_to_max_canvas
[0.4472, 0.4468, 0.3031, 0.0], # expected_tile_means
[1.0, 1.0, 1.0, 0.0], # expected_tile_max
[0.0, 0.0, 0.0, 0.0], # expected_tile_min
[3, 1], # expected_aspect_ratio
True, # pad_max_tiles
),
]
)
Expand All @@ -200,11 +174,8 @@ def test_preprocess(
expected_tile_max: List[float],
expected_tile_min: List[float],
expected_ar: List[int],
pad_max_tiles: bool,
) -> None:
config = PreprocessConfig(
resize_to_max_canvas=resize_to_max_canvas, pad_max_tiles=pad_max_tiles
)
config = PreprocessConfig(resize_to_max_canvas=resize_to_max_canvas)

reference_model = CLIPImageTransform(
image_mean=config.image_mean,
Expand All @@ -215,7 +186,6 @@ def test_preprocess(
tile_size=config.tile_size,
max_num_tiles=config.max_num_tiles,
possible_resolutions=None,
pad_max_tiles=config.pad_max_tiles,
)

eager_model = _CLIPImageTransform(
Expand All @@ -225,7 +195,6 @@ def test_preprocess(
antialias=config.antialias,
tile_size=config.tile_size,
max_num_tiles=config.max_num_tiles,
pad_max_tiles=config.pad_max_tiles,
)

exported_model = export_preprocess(
Expand All @@ -235,7 +204,6 @@ def test_preprocess(
antialias=config.antialias,
tile_size=config.tile_size,
max_num_tiles=config.max_num_tiles,
pad_max_tiles=config.pad_max_tiles,
)

executorch_model = lower_to_executorch_preprocess(exported_model)
Expand Down Expand Up @@ -275,11 +243,8 @@ def test_preprocess(
self.assertAlmostEqual(tile.min().item(), expected_tile_min[i], delta=1e-4)

# Check num tiles matches the product of the aspect ratio.
if pad_max_tiles:
self.assertEqual(config.max_num_tiles, reference_image.shape[0])
else:
expected_num_tiles = reference_ar[0] * reference_ar[1]
self.assertEqual(expected_num_tiles, reference_image.shape[0])
expected_num_tiles = reference_ar[0] * reference_ar[1]
self.assertEqual(expected_num_tiles, reference_image.shape[0])

# Pre-work for eager and exported models. The reference model performs these
# calculations and passes the result to _CLIPImageTransform, the exportable model.
Expand Down
Loading