【Hackathon 7th No.40】为 Paddle 代码转换工具新增 API 转换规则（第 7 组）-Part

docs/guides/model_convert/convert_from_pytorch/api_difference/cuda/torch.cuda.comm.gather.md

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+## [组合替代实现] torch.cuda.comm.gather
+
+### [torch.cuda.comm.gather](https://pytorch.org/docs/stable/generated/torch.cuda.comm.gather.html)
+```python
+torch.cuda.comm.gather(tensors, dim=0, destination=None, *, out=None)
+```
+
+将多个设备的张量集中起来，Paddle 无此 API，需要组合替代实现。
+
+### 转写示例
+```python
+# PyTorch 写法
+destination = 'cuda:0'
+gathered_tensor = torch.cuda.comm.gather(tensors, destination=destination)
+
+# Paddle 写法
+def paddle_comm_gather(tensors, dim=0, destination=None, *, out=None):
+    if destination is None:
+        destination = paddle.CPUPlace()
+    elif 'cuda' in destination:
+        destination = paddle.CUDAPlace(int(destination.split(':')[-1]))
+
+    gathered_tensors = [t.cuda(destination) if 'cuda' in t.place.__str__() else t.cpu() for t in tensors]
+
+    gathered_tensor = paddle.concat(gathered_tensors, axis=dim)
+
+    if out is not None:
+        out.copy_(gathered_tensor)
+        return out
+
+    return gathered_tensor
+
+destination = 'gpu:0'
+gathered_tensor = paddle_comm_gather(tensors, dim=dim, destination=destination)
+```

docs/guides/model_convert/convert_from_pytorch/api_difference/cuda/torch.cuda.comm.scatter.md

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+## [组合替代实现] torch.cuda.comm.scatter
+
+### [torch.cuda.comm.scatter](https://pytorch.org/docs/stable/generated/torch.cuda.comm.scatter.html)
+
+```python
+torch.cuda.comm.scatter(tensor, devices=None, chunk_sizes=None, dim=0, streams=None, *, out=None)
+```
+
+将张量分散到多个设备上，Paddle 无此 API，需要组合替代实现
+
+### 转写示例
+```python
+# torch 写法
+devices = [torch.device('cuda:0'), torch.device('cuda:1')]
+torch.cuda.comm.scatter(inputs, devices=devices)
+
+# paddle 写法
+def paddle_comm_scatter(tensor, devices=None, chunk_sizes=None, dim=0, streams=None, out=None):
+    if devices is None:
+        devices = ['cpu'] * len(tensor)
+
+    if chunk_sizes is not None:
+        chunks = paddle.split(tensor, num_or_sections=chunk_sizes, dim=dim)
+    else:
+        chunks = tensor if isinstance(tensor, list) else [tensor]
+
+    scattered_tensors = out if out is not None else []
+
+    for idx, (chunk, device) in enumerate(zip(chunks, devices)):
+        place = paddle.CUDAPlace(int(device.split(':')[-1])) if 'cuda' in device else paddle.CPUPlace()
+
+        tensor_on_device = chunk.cuda(place) if 'cuda' in device else chunk.cpu()
+
+        if streams is not None:
+            stream = streams[idx]
+            tensor_on_device = tensor_on_device.cuda(place, non_blocking=True)
+            tensor_on_device = tensor_on_device.cuda_stream(stream)
+
+        if out is not None:
+            out[idx].copy_(tensor_on_device)
+        else:
+            scattered_tensors.append(tensor_on_device)
+
+    if out is None:
+        return scattered_tensors
+
+devices = ['gpu:0', 'gpu:1']
+chunk_sizes = [5, 5]
+scattered_tensors = paddle_comm_scatter(tensor, devices=devices, chunk_sizes=chunk_sizes)
+```

docs/guides/model_convert/convert_from_pytorch/api_difference/cuda/torch.cuda.device_of.md

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+## [组合替代实现] torch.cuda.device_of
+
+### [torch.cuda.device_of](https://pytorch.org/docs/stable/generated/torch.cuda.device_of.html#torch.cuda.device_of)
+```python
+torch.cuda.device_of(obj)
+```
+
+获取张量所在的设备，Paddle 无此 api，需要组合实现
+可以通过`tensor.place`来获取张量所在的设备信息
+
+### 转写示例
+```python
+# torch 写法
+device = torch.cuda.device_of(tensor)
+
+# paddle 写法
+device = tensor.place
+```

docs/guides/model_convert/convert_from_pytorch/api_difference/cuda/torch.cuda.is_initialized.md

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+## [ 组合替代实现 ]torch.cuda.is_initialized
+
+### [torch.cuda.is_initialized](xly.bce.baidu.com/paddlepaddle/fluid-doc/newipipe/detail/11746629/job/27824342/realTimeLog/479)
+
+```python
+torch.cuda.is_initialized()
+```
+
+判断 cuda 是否初始化，Paddle 无此 API，需要组合实现。
+Paddle 可以通过检查是否支持 cuda，并且尝试创建一个张量来判断初始化是否成功。
+
+### 转写示例
+
+```python
+# torch 写法
+torch.cuda.is_initialized()
+
+# paddle 写法
+def paddle_cuda_is_initialized():
+    if not paddle.is_compiled_with_cuda():
+        return False
+    try:
+        cuda_tensor = paddle.rand([1], place=paddle.CUDAPlace(0))
+        return True
+    except Exception as e:
+        return False
+paddle_cuda_is_initialized()
+```

docs/guides/model_convert/convert_from_pytorch/api_difference/torch/torch.get_default_device.md

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+## [组合替代实现] torch.get_default_device
+
+### [torch.get_default_device](https://pytorch.org/docs/stable/generated/torch.get_default_device.html)
+```python
+torch.get_default_device()
+```
+
+获取默认的设备，Paddle 无此 api， 需要组合实现
+
+### 转写示例
+```python
+# torch 写法
+device = torch.get_default_device()
+
+# paddle 写法
+device = paddle.device.get_device()
+```

docs/guides/model_convert/convert_from_pytorch/api_difference/torch/torch.set_default_device.md

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+## [组合替代实现] torch.set_default_device
+### [torch.set_default_device](https://pytorch.org/docs/stable/generated/torch.set_default_device.html#torch.set_default_device)
+```python
+torch.set_default_device(device)
+```
+
+设置默认设备，Paddle 无此 api，需要组合替代实现。
+
+### 转写示例
+
+```python
+# torch 写法
+torch.set_default_device(device)
+
+# paddle 写法
+paddle.device.set_device(device)
+```