issue/890 - 为nn.module添加to函数

python/infinicore/nn/modules/module.py

@@ -32,6 +32,7 @@
 
 import infinicore
 
+from ...device import device as InfiniCoreDevice
 from ...tensor import Tensor
 from ..parameter import InfiniCoreParameter as Parameter
 
@@ -481,15 +482,14 @@ def _load_from_state_dict(
                         f"While copying the parameter named {key}, expected Tensor from checkpoint but received {type(input_param)}"
                     )
 
-                if (
-                    (param.shape == input_param.shape)
-                    and (param.dtype == input_param.dtype)
-                    and (param.device == input_param.device)
+                if (param.shape == input_param.shape) and (
+                    param.dtype == input_param.dtype
                 ):
                     param.copy_(input_param)
                 else:
-                    print(f"param '{name}' don't match input_param '{key}'")
-                    setattr(self, name, input_param)
+                    raise KeyError(
+                        f"param '{name}' don't match input_param '{key}' with shape or dtype"
+                    )
 
             elif strict:
                 missing_keys.append(key)
@@ -848,10 +848,29 @@ def eval(self: T) -> T:
         Returns:
             Module: self
         """
-        pass
+        raise KeyError("not support")
 
     def _apply(self, fn, recurse=True):
-        raise KeyError("not support")
+        if recurse:
+            for module in self.children():
+                module._apply(fn)
 
-    def to(self, *args, **kwargs):
-        raise KeyError("not support")
+        for key, param in self._parameters.items():
+            if param is not None:
+                setattr(self, key, fn(param))
+
+        for key, buf in self._buffers.items():
+            if buf is not None:
+                setattr(self, key, fn(buf))
+
+        return self
+
+    def to(self, device: str | InfiniCoreDevice):
+        if device is None:
+            raise ValueError("device cannot be None")
+        device = InfiniCoreDevice(device)
+
+        def convert(t):
+            return t.to(device)
+
+        return self._apply(convert)

test/infinicore/nn/module.py

@@ -44,6 +44,7 @@ def __init__(self):
     def forward(self):
         return infinicore.add(self.a, self.b)
 
+
 infinicore_model_infer = InfiniCoreNet()
 # ============================================================
 # 2. 加载权重
@@ -75,6 +76,91 @@ def forward(self):
 
 
 # ============================================================
-# 5. to测试，buffer测试
+# 5. to测试 - 测试模型在不同设备间的转换
 # ============================================================
-# 等待添加
+print("\n" + "=" * 60)
+print("5. to测试 - 设备转换测试")
+print("=" * 60)
+
+
+def print_model_state(model, title="状态"):
+    """打印模型的参数状态"""
+    print(f"\n{title}:")
+    print("-" * 40)
+    print("Parameters:")
+    for name, param in model.named_parameters():
+        print(
+            f"  {name}: shape={param.shape}, dtype={param.dtype}, device={param.device}"
+        )
+
+
+def verify_device_conversion(model, target_device, use_type_check=False):
+    """验证模型参数的设备转换"""
+    print("转换后的Parameters:")
+    for name, param in model.named_parameters():
+        print(
+            f"  {name}: shape={param.shape}, dtype={param.dtype}, device={param.device}"
+        )
+        if use_type_check:
+            # 当使用字符串参数时，只检查设备类型
+            expected_type = (
+                target_device if isinstance(target_device, str) else target_device.type
+            )
+            assert param.device.type == expected_type, (
+                f"参数 {name} 的设备转换失败: 期望类型 {expected_type}, 实际 {param.device.type}"
+            )
+        else:
+            # 使用device对象时，进行完整比较
+            assert param.device == target_device, (
+                f"参数 {name} 的设备转换失败: 期望 {target_device}, 实际 {param.device}"
+            )
+
+
+# 5.1 打印初始状态
+print_model_state(infinicore_model_infer, "5.1 初始状态")
+
+# 定义设备转换测试用例列表
+device_conversion_cases = [
+    {
+        "name": "5.2 转换到CUDA设备",
+        "description": "使用 infinicore.device('cuda', 0)",
+        "target": infinicore.device("cuda", 0),
+        "use_type_check": False,
+        "success_msg": "✓ CUDA设备转换验证通过",
+    },
+    {
+        "name": "5.3 转换到CPU设备",
+        "description": "使用 infinicore.device('cpu', 0)",
+        "target": infinicore.device("cpu", 0),
+        "use_type_check": False,
+        "success_msg": "✓ CPU设备转换验证通过",
+    },
+    {
+        "name": "5.4 转换到CUDA设备",
+        "description": "使用字符串 'cuda'",
+        "target": "cuda",
+        "use_type_check": True,
+        "success_msg": "✓ 字符串参数设备转换验证通过",
+    },
+]
+
+# 循环测试每个设备转换用例
+for case in device_conversion_cases:
+    print(f"\n{case['name']} ({case['description']}):")
+    print("-" * 40)
+    infinicore_model_infer.to(case["target"])
+    verify_device_conversion(
+        infinicore_model_infer, case["target"], use_type_check=case["use_type_check"]
+    )
+    print(case["success_msg"])
+
+# 5.5 验证to方法返回self（链式调用支持）
+print("\n5.5 测试to方法的返回值（链式调用）:")
+print("-" * 40)
+result = infinicore_model_infer.to(infinicore.device("cpu", 0))
+assert result is infinicore_model_infer, "to方法应该返回self以支持链式调用"
+print("✓ to方法返回值验证通过")
+
+print("\n" + "=" * 60)
+print("所有to测试通过！")
+print("=" * 60 + "\n")