NVIDIA
feat: Run PyExecutor's inference flow to estimate max_num_tokens for kv_cache_manager
model_engine's forward was ran to perform memory usage testing before which is not accurate because memory used in decoding not counted in. In this change, PyExecutor is ran to perform the memory usage. Note: CacheTransceiver will hang on the second time of creation. Then, one API to update kv_cache_manager for it is added.
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/bot run --stage-list="A100X-1,A100X-2,A30-7,B200_PCIe-1" --disable-fail-fast
PR_Github #634 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #533 completed with status: 'FAILURE'
PR_Github #1262 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #953 completed with status: 'FAILURE'
/bot run --stage-list="A100X-TensorRT-1,L40S-PyTorch-1" --disable-fail-fast
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/LLM/main/L0_MergeRequest_PR pipeline #991 (Partly Tested) completed with status: 'SUCCESS'
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/LLM/main/L0_MergeRequest_PR pipeline #998 completed with status: 'FAILURE'
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PR_Github #1408 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #1056 completed with status: 'FAILURE'
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