feat: 导入 IRSTD 研究代码与文档（小目标检测）

- 新增 irstd 核心包、scripts、tests、configs
- 新增研究文档：literature_review / mathematical_analysis / novelty_matrix / experiment_plan / research_decision / research_log / manuscript_outline
- 新增 evidence、results 数据与审计产物
- 新增 pyproject.toml、requirements、.gitignore

tests/test_torch.py

@@ -0,0 +1,18 @@
+import unittest,importlib.util
+AVAILABLE=importlib.util.find_spec('torch') is not None
+@unittest.skipUnless(AVAILABLE,'PyTorch is unavailable; gradient/training tests NOT executed')
+class TorchTests(unittest.TestCase):
+ def test_shapes_and_gradient(self):
+  import torch
+  from irstd.models import TinyUNet,segmentation_loss
+  model=TinyUNet();x=torch.randn(1,1,17,19);y=torch.zeros_like(x);y[:,:,8,9]=1
+  for name in ['bce','dice','bce_dice','focal','iou']:
+   model.zero_grad();z=model(x);self.assertEqual(z.shape,x.shape)
+   loss=segmentation_loss(z,y,name);loss.backward();self.assertTrue(torch.isfinite(loss))
+   self.assertTrue(all(torch.isfinite(p.grad).all() for p in model.parameters()))
+ def test_gate_gradients(self):
+  import torch
+  from irstd.models import gate_loss
+  s=torch.tensor([0.,0.],requires_grad=True)
+  loss,upper=gate_loss(s,torch.tensor([1.,0.]),torch.tensor([4.,1.]),1.,.1)
+  loss.backward();self.assertLess(s.grad[0],0);self.assertGreater(s.grad[1],0);self.assertAlmostEqual(upper.item(),1.)