Initial project scaffold

tasks/02_row_softmax/test_task.py

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+from __future__ import annotations
+
+import pytest
+import torch
+
+from kernels.triton.row_softmax import triton_row_softmax
+from reference.torch_row_softmax import torch_row_softmax
+
+
+def _run_impl_or_skip(fn, *args):
+    try:
+        return fn(*args)
+    except NotImplementedError:
+        pytest.skip("implementation is still TODO")
+    except RuntimeError as exc:
+        pytest.skip(str(exc))
+
+
+@pytest.mark.reference
+def test_row_softmax_reference_matches_torch():
+    x = torch.randn(8, 17)
+    out = torch_row_softmax(x)
+    torch.testing.assert_close(out, torch.softmax(x, dim=1))
+
+
+@pytest.mark.reference
+def test_row_softmax_reference_is_numerically_stable():
+    x = torch.tensor([[1000.0, 1001.0, 1002.0], [-1000.0, -999.0, -998.0]])
+    out = torch_row_softmax(x)
+    torch.testing.assert_close(out.sum(dim=1), torch.ones(2), atol=1e-6, rtol=1e-6)
+
+
+@pytest.mark.triton_required
+@pytest.mark.skeleton
+def test_triton_row_softmax_if_available():
+    if not torch.cuda.is_available():
+        pytest.skip("CUDA is not available")
+    x = torch.randn(16, 63, device="cuda")
+    out = _run_impl_or_skip(triton_row_softmax, x)
+    torch.testing.assert_close(out, torch.softmax(x, dim=1), atol=1e-4, rtol=1e-4)