[0-size Tensor No.256] Add 0-size Tensor support for paddle.sgn API

paddle/phi/kernels/stride/as_complex_kernel.cc

@@ -31,6 +31,21 @@ void AsComplexStridedKernel(const Context& dev_ctx,
         "FLAGS_use_stride_kernel is closed. Strided kernel "
         "be called, something wrong has happened!"));
   }
+  if (out && out->numel() == 0) {
+    if (x.dtype() == DataType::FLOAT32) {
+      out->set_type(DataType::COMPLEX64);
+    } else if (x.dtype() == DataType::FLOAT64) {
+      out->set_type(DataType::COMPLEX128);
+    } else {
+      PADDLE_THROW(common::errors::Unimplemented(
+          "as_complex is not supported data type (%s).",
+          DataTypeToString(x.dtype())));
+    }
+    out->set_offset(x.offset());
+    out->ResetHolder(x.Holder());
+    out->ShareInplaceVersionCounterWith(x);
+    return;
+  }
 
   PADDLE_ENFORCE_EQ(
       x.strides()[x.strides().size() - 1],

test/legacy_test/test_sgn.py

@@ -143,6 +143,37 @@ def test_float_static_and_pir(self):
                 z_expected = np_sgn(np_x)
                 np.testing.assert_allclose(z, z_expected, rtol=1e-05)
 
+    def test_zero_size_complex_dynamic(self):
+        for dtype in ['complex64', 'complex128']:
+            np_x = np.empty((0, 4), dtype=dtype)  # 空张量 shape=[0, 4]
+            x = paddle.to_tensor(np_x)
+            z = paddle.sgn(x)
+            np_z = z.numpy()
+            z_expected = np_sgn(np_x)
+            np.testing.assert_allclose(np_z, z_expected, rtol=1e-05)
+            np.testing.assert_equal(np_z.shape, (0, 4))
+
+    def test_zero_size_complex_static_and_pir(self):
+        with static_guard():
+            for dtype in ['complex64', 'complex128']:
+                exe = paddle.static.Executor()
+                train_program = paddle.static.Program()
+                startup_program = paddle.static.Program()
+                with paddle.static.program_guard(
+                    train_program, startup_program
+                ):
+                    x = paddle.static.data(name='X', shape=[0, 4], dtype=dtype)
+                    z = paddle.sgn(x)
+
+                exe.run(startup_program)
+                x_np = np.empty((0, 4), dtype=dtype)
+                (z_out,) = exe.run(
+                    train_program, feed={"X": x_np}, fetch_list=[z]
+                )
+                z_expected = np_sgn(x_np)
+                np.testing.assert_allclose(z_out, z_expected, rtol=1e-05)
+                np.testing.assert_equal(z_out.shape, (0, 4))
+
 
 if __name__ == "__main__":
     unittest.main()