npu的数据集和算法上传

npu/helloworld.py

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+import torch
+import moxing as mox
+import os
+import argparse
+import torch_npu  # 确保安装了 torch_npu
+
+# 创建参数解析器
+parser = argparse.ArgumentParser(description='Training script with output path option')
+parser.add_argument('--input', default=None, type=str, help='input, where the dataset is stored.')
+parser.add_argument('--output', type=str, default='', help='Output path for saving the result')
+args = parser.parse_args()
+
+# 检查 NPU 是否可用
+try:
+    import torch_npu
+
+    if torch_npu.npu.is_available():
+        device = torch.device('npu')
+        print("Using NPU for training.")
+    else:
+        device = torch.device('cpu')
+        print("NPU is not available, using CPU for training.")
+except ImportError:
+    device = torch.device('cpu')
+    print("torch_npu module not found, using CPU for training.")
+
+# 模拟一个简单的训练过程
+# 这里其实不涉及真正的模型训练，只是作为示例流程展示
+# 输出 Hello World
+result = "Hello World"
+print(result)
+
+# 将结果保存到本地文件
+local_result_path = 'hellworld.pth'
+with open(local_result_path, 'w') as f:
+    f.write(result)
+
+# 根据参数确定 OBS 路径
+obs_result_path = args.output if args.output else 'obs://nudt-cloudream2/cds/trainResult/model/hellworld.pth'
+# 如果传入的路径不是以斜杠结尾，则添加斜杠
+if obs_result_path and not obs_result_path.endswith('/'):
+    obs_result_path += '/'
+obs_result_path += 'hellworld.pth'
+
+try:
+    mox.file.copy(local_result_path, obs_result_path)
+    print(f"Result has been successfully saved to {obs_result_path}")
+except Exception as e:
+    print(f"Failed to save result to OBS: {e}")