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minor fixes #60

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Merged
clemsgrs merged 1 commit into from
Feb 25, 2026
Merged

minor fixes #60

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2 changes: 1 addition & 1 deletion slide2vec/configs/default_model.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,7 @@ model:
arch: # architecture of custom model
pretrained_weights: # path to the pretrained weights when using a custom model
batch_size: 256
tile_size: ${tiling.params.tile_size}
input_size: ${tiling.params.tile_size}
restrict_to_tissue: false # whether to restrict tile content to tissue pixels only when feeding tile through encoder
patch_size: 256 # if level is "region", size used to unroll the region into patches
token_size: 16 # size of the tokens used model is a custom pretrained ViT
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10 changes: 3 additions & 7 deletions slide2vec/main.py
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Expand Up @@ -93,8 +93,7 @@ def run_feature_extraction(config_file, output_dir, run_on_cpu: False):
"torch.distributed.run",
f"--master_port={free_port}",
"--nproc_per_node=gpu",
"-m",
"slide2vec.embed",
"slide2vec/embed.py",
"--config-file",
os.path.abspath(config_file),
"--output-dir",
Expand All @@ -103,8 +102,7 @@ def run_feature_extraction(config_file, output_dir, run_on_cpu: False):
if run_on_cpu:
cmd = [
sys.executable,
"-m",
"slide2vec.embed",
"slide2vec/embed.py",
"--config-file",
os.path.abspath(config_file),
"--output-dir",
Expand All @@ -127,11 +125,9 @@ def run_feature_extraction(config_file, output_dir, run_on_cpu: False):

def run_feature_aggregation(config_file, output_dir, run_on_cpu: False):
print("Running aggregate.py...")
# find a free port
cmd = [
sys.executable,
"-m",
"slide2vec.aggregate",
"slide2vec/aggregate.py",
"--config-file",
os.path.abspath(config_file),
"--output-dir",
Expand Down
14 changes: 7 additions & 7 deletions slide2vec/models/models.py
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Original file line number Diff line number Diff line change
Expand Up @@ -63,7 +63,7 @@ def __init__(
model = PathoJEPA(
pretrained_weights=options.pretrained_weights,
arch=options.arch,
input_size=options.tile_size,
input_size=options.input_size,
patch_size=options.token_size,
normalize_embeddings=options.normalize_embeddings,
)
Expand All @@ -77,13 +77,13 @@ def __init__(
model = PandaViT(
arch="vit_small",
pretrained_weights=options.pretrained_weights,
input_size=options.tile_size,
input_size=options.input_size,
)
elif options.name == "dino" and options.arch:
model = DINOViT(
arch=options.arch,
pretrained_weights=options.pretrained_weights,
input_size=options.tile_size,
input_size=options.input_size,
patch_size=options.token_size,
)
elif options.level == "region":
Expand Down Expand Up @@ -117,7 +117,7 @@ def __init__(
tile_encoder = PathoJEPA(
pretrained_weights=options.pretrained_weights,
arch=options.arch,
input_size=options.patch_size,
input_size=options.input_size,
patch_size=options.token_size,
normalize_embeddings=options.normalize_embeddings,
)
Expand All @@ -131,13 +131,13 @@ def __init__(
tile_encoder = PandaViT(
arch="vit_small",
pretrained_weights=options.pretrained_weights,
input_size=options.tile_size,
input_size=options.input_size,
)
elif options.name is None and options.arch:
tile_encoder = DINOViT(
arch=options.arch,
pretrained_weights=options.pretrained_weights,
input_size=options.patch_size,
input_size=options.input_size,
patch_size=options.token_size,
)
model = RegionFeatureExtractor(tile_encoder, tile_size=options.patch_size)
Expand Down Expand Up @@ -861,7 +861,7 @@ class RegionFeatureExtractor(nn.Module):
def __init__(
self,
tile_encoder: nn.Module,
tile_size: int = 256,
tile_size: int,
):
super(RegionFeatureExtractor, self).__init__()
self.tile_encoder = tile_encoder
Expand Down
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