Add new test file for lightweight float to complex casting

Author: youge325

test/legacy_test/test_complex_cast.py

@@ -18,9 +18,6 @@
 
 import paddle
 
-# This test file covers casting operations between different data types,
-# including lightweight float formats (float8, float16, bfloat16) and complex types.
-
 
 class TestComplexCastOp(unittest.TestCase):
     def test_complex_to_real(self):
@@ -82,116 +79,6 @@ def test_complex64_complex128(self):
             c_128.cast('complex128').numpy(), c_64.numpy(), rtol=1e-05
         )
 
-    @unittest.skipIf(
-        not paddle.is_compiled_with_cuda(),
-        "float16/bfloat16/float8 test runs only on CUDA",
-    )
-    def test_float16_bfloat16_to_complex(self):
-        # Test float16 to complex64/complex128
-        r_fp16 = np.random.random(size=[10, 10]).astype('float16')
-        r_fp16_t = paddle.to_tensor(r_fp16, dtype='float16')
-
-        self.assertEqual(r_fp16_t.cast('complex64').dtype, paddle.complex64)
-        self.assertEqual(r_fp16_t.cast('complex128').dtype, paddle.complex128)
-
-        np.testing.assert_allclose(
-            r_fp16_t.cast('complex64').real().numpy(),
-            r_fp16.astype('float32'),
-            rtol=1e-03,
-        )
-        np.testing.assert_allclose(
-            r_fp16_t.cast('complex128').real().numpy(),
-            r_fp16.astype('float64'),
-            rtol=1e-03,
-        )
-
-        # Test bfloat16 to complex64/complex128
-        r_bf16 = np.random.random(size=[10, 10]).astype('float32')
-        r_bf16_t = paddle.to_tensor(r_bf16, dtype='bfloat16')
-
-        self.assertEqual(r_bf16_t.cast('complex64').dtype, paddle.complex64)
-        self.assertEqual(r_bf16_t.cast('complex128').dtype, paddle.complex128)
-
-        np.testing.assert_allclose(
-            r_bf16_t.cast('complex64').real().numpy(),
-            r_bf16_t.cast('float32').numpy(),
-            rtol=1e-02,
-        )
-        np.testing.assert_allclose(
-            r_bf16_t.cast('complex128').real().numpy(),
-            r_bf16_t.cast('float64').numpy(),
-            rtol=1e-02,
-        )
-
-    @unittest.skipIf(
-        not paddle.is_compiled_with_cuda(),
-        "float8 test runs only on CUDA",
-    )
-    def test_float8_to_complex(self):
-        # Test float8_e4m3fn to complex64/complex128
-        r_fp32 = np.random.uniform(1.0, 10.0, size=[10, 10]).astype('float32')
-        r_fp32_t = paddle.to_tensor(r_fp32)
-        r_fp8_e4m3fn_t = r_fp32_t.astype('float8_e4m3fn')
-
-        self.assertEqual(
-            r_fp8_e4m3fn_t.cast('complex64').dtype, paddle.complex64
-        )
-        self.assertEqual(
-            r_fp8_e4m3fn_t.cast('complex128').dtype, paddle.complex128
-        )
-
-        # Verify the real part matches the float32 version
-        np.testing.assert_allclose(
-            r_fp8_e4m3fn_t.cast('complex64').real().numpy(),
-            r_fp8_e4m3fn_t.cast('float32').numpy(),
-            rtol=1e-02,
-        )
-        np.testing.assert_allclose(
-            r_fp8_e4m3fn_t.cast('complex128').real().numpy(),
-            r_fp8_e4m3fn_t.cast('float64').numpy(),
-            rtol=1e-02,
-        )
-
-        # Verify the imaginary part is zero
-        np.testing.assert_array_equal(
-            r_fp8_e4m3fn_t.cast('complex64').imag().numpy(),
-            np.zeros([10, 10], dtype='float32'),
-        )
-        np.testing.assert_array_equal(
-            r_fp8_e4m3fn_t.cast('complex128').imag().numpy(),
-            np.zeros([10, 10], dtype='float64'),
-        )
-
-        # Test float8_e5m2 to complex64/complex128
-        r_fp8_e5m2_t = r_fp32_t.astype('float8_e5m2')
-
-        self.assertEqual(r_fp8_e5m2_t.cast('complex64').dtype, paddle.complex64)
-        self.assertEqual(
-            r_fp8_e5m2_t.cast('complex128').dtype, paddle.complex128
-        )
-
-        # Verify the real part matches the float32 version
-        np.testing.assert_allclose(
-            r_fp8_e5m2_t.cast('complex64').real().numpy(),
-            r_fp8_e5m2_t.cast('float32').numpy(),
-            rtol=1e-02,
-        )
-        np.testing.assert_allclose(
-            r_fp8_e5m2_t.cast('complex128').real().numpy(),
-            r_fp8_e5m2_t.cast('float64').numpy(),
-            rtol=1e-02,
-        )
-
-        # Verify the imaginary part is zero
-        np.testing.assert_array_equal(
-            r_fp8_e5m2_t.cast('complex64').imag().numpy(),
-            np.zeros([10, 10], dtype='float32'),
-        )
-        np.testing.assert_array_equal(
-            r_fp8_e5m2_t.cast('complex128').imag().numpy(),
-            np.zeros([10, 10], dtype='float64'),
-        )
-
 
 if __name__ == '__main__':
     unittest.main()