Tangledup-ai/sam3_local
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apply Black 25.11.0 style in fbcode/deeplearning/projects (21/92)

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Summary:
Formats the covered files with pyfmt.

paintitblack

Reviewed By: itamaro

Differential Revision: D90476315

fbshipit-source-id: ee94c471788b8e7d067813d8b3e0311214d17f3f
This commit is contained in:
Bowie Chen
2026-01-11 23:16:49 -08:00
committed by meta-codesync[bot]
parent 7b89b8fc3f
commit 11dec2936d
69 changed files with 445 additions and 522 deletions
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25
sam3/train/matcher.py
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@@ -8,7 +8,6 @@ Modules to compute the matching cost and solve the corresponding LSAP.
import numpy as np
import torch
from sam3.model.box_ops import box_cxcywh_to_xyxy, box_iou, generalized_box_iou
from scipy.optimize import linear_sum_assignment
from torch import nn
@@ -60,9 +59,9 @@ class HungarianMatcher(nn.Module):
self.cost_bbox = cost_bbox
self.cost_giou = cost_giou
self.norm = nn.Sigmoid() if focal_loss else nn.Softmax(-1)
assert (
cost_class != 0 or cost_bbox != 0 or cost_giou != 0
), "all costs cant be 0"
assert cost_class != 0 or cost_bbox != 0 or cost_giou != 0, (
"all costs cant be 0"
)
self.focal_loss = focal_loss
self.focal_alpha = focal_alpha
self.focal_gamma = focal_gamma
@@ -197,9 +196,9 @@ class BinaryHungarianMatcher(nn.Module):
self.cost_bbox = cost_bbox
self.cost_giou = cost_giou
self.norm = nn.Sigmoid()
assert (
cost_class != 0 or cost_bbox != 0 or cost_giou != 0
), "all costs cant be 0"
assert cost_class != 0 or cost_bbox != 0 or cost_giou != 0, (
"all costs cant be 0"
)
@torch.no_grad()
def forward(self, outputs, batched_targets, repeats=0, repeat_batch=1):
@@ -322,9 +321,9 @@ class BinaryFocalHungarianMatcher(nn.Module):
self.alpha = alpha
self.gamma = gamma
self.stable = stable
assert (
cost_class != 0 or cost_bbox != 0 or cost_giou != 0
), "all costs cant be 0"
assert cost_class != 0 or cost_bbox != 0 or cost_giou != 0, (
"all costs cant be 0"
)
@torch.no_grad()
def forward(self, outputs, batched_targets, repeats=1, repeat_batch=1):
@@ -470,9 +469,9 @@ class BinaryHungarianMatcherV2(nn.Module):
self.cost_bbox = cost_bbox
self.cost_giou = cost_giou
self.norm = nn.Sigmoid()
assert (
cost_class != 0 or cost_bbox != 0 or cost_giou != 0
), "all costs cant be 0"
assert cost_class != 0 or cost_bbox != 0 or cost_giou != 0, (
"all costs cant be 0"
)
self.focal = focal
if focal:
self.alpha = alpha