LeakyReLU 算子 Kernel 未注册

#### 1.Describe the current behavior / 问题描述 (Mandatory / 必填) > `mindspore.mint.nn.functional.leaky_relu` 相关接口执行时报错 `The kernel LeakyReLUExt unregistered`，导致 LeakyReLU 计算失败。 #### 2.Environment / 环境信息 (Mandatory / 必填) - **Hardware Environment / 硬件环境(Mandatory / 必填)**: | 后端类型 | 硬件具体类别 | | --- | --- | | CPU | Mac CPU/Win CPU | - **Software Environment / 软件环境 (Mandatory / 必填)**: | Software | Version(根据实际修改，必填) | | --- | --- | | MindSpore | MindSpore 2.4.0 | | Python | Python 3.10 | | OS platform | Win Mac | 、 #### 3.Steps to reproduce the issue / 重现步骤 (Mandatory / 必填) > 1. 运行 `test_leaky_relu.py` 相关部分代码(已提交 PR) ```python def test_leaky_relu_fixed_dtype_output_equality(): """ (1b) 固定dtype=float32 随机输入，对比输出 """ print("===== LeakyReLU fixed dtype output equality test =====") x_np = np.random.randn(4,4).astype(np.float32) ms_in = Tensor(x_np, mstype.float32) torch_in = torch.tensor(x_np, dtype=torch.float32) out_ms = F_ms.leaky_relu(ms_in, 0.1).asnumpy() out_pt = F_torch.leaky_relu(torch_in, 0.1).numpy() diff = np.abs(out_ms - out_pt).max() print("Max diff:", diff) assert diff < 1e-3 def test_leaky_relu_fixed_shape_diff_params(): """ (1c) 测试 negative_slope 参数不同类型 """ print("===== LeakyReLU fixed shape diff params test =====") x = Tensor(np.array([-2., -1., 0., 1., 2.], np.float32)) out_slope_default = F_ms.leaky_relu(x) # default=0.01 out_slope_float = F_ms.leaky_relu(x, 0.2) out_slope_int = F_ms.leaky_relu(x, 1) out_slope_bool = F_ms.leaky_relu(x, True) # True => 1 print("default=0.01:", out_slope_default.asnumpy()) print("0.2:", out_slope_float.asnumpy()) print("1:", out_slope_int.asnumpy()) print("True(=1):", out_slope_bool.asnumpy()) # string slope => error try: F_ms.leaky_relu(x, negative_slope="0.1") except Exception as e: print("slope=string error:", e) def test_leaky_relu_network_forward_backward(): """ (2b,2c) 使用L…