minor: cleanup sgl-kernel (#3143)

sgl-kernel/tests/test_sampling_scaling_penalties.py

@@ -1,39 +0,0 @@
-import pytest
-import torch
-from sgl_kernel import sampling_scaling_penalties
-
-batch_sizes = [1, 2, 4, 8, 16, 32, 64, 65]
-vocab_sizes = [2048, 4096, 8192, 16384, 32768, 32767]
-dtypes = [torch.float32, torch.half, torch.bfloat16]
-
-
-@pytest.mark.parametrize("batch_size", batch_sizes)
-@pytest.mark.parametrize("vocab_size", vocab_sizes)
-@pytest.mark.parametrize("dtype", dtypes)
-def test_sampling_scaling_penalties(batch_size, vocab_size, dtype):
-    device = torch.device("cuda")
-    rtol = 1e-3
-    atol = 1e-3
-
-    logits = torch.randn(batch_size, vocab_size, device=device, dtype=dtype)
-    scaling_penalties = (
-        torch.rand(batch_size, vocab_size, device=device, dtype=dtype) + 0.5
-    )
-
-    ref_output = torch.where(
-        logits > 0, logits / scaling_penalties, logits * scaling_penalties
-    )
-
-    kernel_output = sampling_scaling_penalties(logits, scaling_penalties)
-
-    torch.testing.assert_close(
-        kernel_output,
-        ref_output,
-        rtol=rtol,
-        atol=atol,
-        msg=f"Failed for batch_size={batch_size}, vocab_size={vocab_size}, dtype={dtype}",
-    )
-
-
-if __name__ == "__main__":
-    pytest.main([__file__])