DOC: Clarify DeviceStatsMonitor logged metrics

[MrAnayDongre]

What does this PR do?

This PR addresses issue #20807 by adding detailed documentation for the metrics logged by DeviceStatsMonitor.

The key clarifications include:

• The source of metrics (CPU via psutil, CUDA GPU via torch.cuda.memory_stats, and other accelerators via accelerator.get_device_stats()).
• The naming convention for logged keys: DeviceStatsMonitor.{hook_name}/{base_metric_name}.
• Explicitly states that GPU compute utilization is not logged by default for CUDA devices, with a pointer to torch.cuda.memory_stats() for the full list of memory metrics.
• Provides examples for common CPU, CUDA, and other accelerator (TPU, MPS) metrics.
• Includes a minor update to profiler_basic.rst to align with these clarifications and link to the API docs.

This documentation aims to help users understand what statistics to expect when using DeviceStatsMonitor with different hardware configurations.

Fixes #20807

No breaking changes are introduced by this documentation update.

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📚 Documentation preview 📚: https://pytorch-lightning--20895.org.readthedocs.build/en/20895/

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[Borda]

** really does not well represent the hierarchy in the headers, so let's rather use a nested lists