feat: Free gpu space after each inference run

[hh-space-invader]

This PR introduces two improvements to memory management in ONNX Runtime:

• Mitigating Memory Fragmentation:

  • When running a high volume of inferences, the ONNX Runtime memory arena can become fragmented, leading to inefficient memory usage.
  • Enabling memory.enable_memory_arena_shrinkage forces cleanup of the memory arena after each run, reducing fragmentation at the cost of some performance.

• Optimizing Memory Allocation Strategy:

  • By default, ONNX Runtime’s arena allocator expands memory aggressively using kNextPowerOfTwo, which can lead to excessive memory consumption (e.g., 1GB → 2GB → 4GB, etc.).
  • Switching to kSameAsRequested ensures that only the necessary memory is allocated, preventing unnecessary over-allocation.

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