resolve conflict

Author: shiyang-weng

test/float8/test_compile.py

@@ -392,59 +392,5 @@ def test_dynamic_scale_numeric_parity(
     assert torch.equal(float8_eager._data, float8_compile._data)
 
 
-@pytest.mark.parametrize(
-    "float8_dtype",
-    [
-        torch.float8_e4m3fn,
-        torch.float8_e5m2,
-    ],
-)
-@pytest.mark.parametrize(
-    "hp_dtype",
-    [
-        torch.float32,
-        torch.float16,
-        torch.bfloat16,
-    ],
-)
-def test_quantize_dequantize_fp8_inductor(float8_dtype, hp_dtype):
-    quantize_affine_float8 = torch.ops.torchao.quantize_affine_float8
-    dequantize_affine_float8 = torch.ops.torchao.dequantize_affine_float8
-    input = torch.randn(10, 10)
-    with torch.no_grad():
-        torch._dynamo.reset()
-        expected_scale = torch.tensor(2.0)
-        expected_quantized = quantize_affine_float8(
-            input,
-            expected_scale,
-            float8_dtype=float8_dtype,
-        )
-        expected_dequantized = dequantize_affine_float8(
-            expected_quantized,
-            expected_scale,
-            output_dtype=hp_dtype,
-        )
-        test_q, (code_q,) = torch._inductor.utils.run_and_get_code(
-            torch.compile(quantize_affine_float8),
-            input,
-            expected_scale,
-            float8_dtype=float8_dtype,
-        )
-        torch.testing.FileCheck().check(
-            "torch.ops.torchao.quantize_affine_float8.default"
-        ).run(code_q)
-        test_dq, (code_dq,) = torch._inductor.utils.run_and_get_code(
-            torch.compile(dequantize_affine_float8),
-            test_q,
-            expected_scale,
-            hp_dtype,
-        )
-        torch.testing.FileCheck().check(
-            "torch.ops.torchao.dequantize_affine_float8.default"
-        ).run(code_dq)
-        torch.testing.assert_close(expected_quantized, test_q)
-        torch.testing.assert_close(expected_dequantized, test_dq)
-
-
 if __name__ == "__main__":
     pytest.main([__file__])