[perf] fix: modify the NPU profiler default configuration

[tardis-key]

What does this PR do?

Profiling in reinforcement learning generates a large volume of data, which impairs its ease of use. Based on optimization experience @mengchengTang , the default recommended parameters have been modified.
refer to https://www.hiascend.com/document/detail/zh/Pytorch/720/apiref/torchnpuCustomsapi/context/torch_npu-profiler-_ExperimentalConfig.md for detailed interface specifications.

The test results of tests/special_npu/run_qwen2_5_05b_grpo.sh are as follows:

• Before modification + analysis=True: 12.8GB
• Before modification + analysis=False: 3.25GB
• After modification + analysis=True: 3.48GB
• After modification + analysis=False: 1.92GB

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[gemini-code-assist]

Code Review

This pull request aims to reduce the data volume from the NPU profiler by changing the default profiling level from level1 to level0. The changes are consistently applied across various configuration files, examples, and the default configuration object. Additionally, the profiler configuration is updated to exclude communication data and switch to a database export format, which should further improve performance. I have one critical suggestion to improve the robustness of a runtime dependency check.

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