Lianmin/simplify memory pool #7202
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Summary of Changes
Hello @merrymercy, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request aims to simplify the memory pool implementation by removing specific compiled helper functions that were potentially problematic or underperforming. It also adjusts the logic for retrieving KV cache buffer information to correctly handle layer indexing based on a starting layer offset.
Highlights
- Remove Compiled Functions: Removed the
@torch.compiledecorated functionsfused_downcastandcopy_two_arrayfrom the memory pool implementation. A comment indicatedcopy_two_arraywas slower in unit tests. - Adjust Layer Indexing: Modified the
get_contiguous_buf_infosmethod to iterate over layers usingrange(self.start_layer, self.start_layer + self.layer_num)instead of justrange(self.layer_num). This change affects how KV cache buffer information is retrieved, likely to support models with a specific range of layers or handle layer offsets. - Add Debug Method: Added an empty
debug_printmethod to theMemoryPoolclass.
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Code Review
This pull request simplifies the memory pool by removing @torch.compiled functions that were reportedly underperforming. It updates import statements, adds a debug_print method (currently a stub), and corrects the loop logic in KVCache.get_contiguous_buf_infos to properly handle layer indexing based on start_layer. My main feedback is to implement the debug_print method to provide useful state information. A more detailed PR description would also improve clarity.
| self.get_key_buffer(i).data_ptr() | ||
| for i in range(self.start_layer, self.start_layer + self.layer_num) |
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Using range(self.start_layer, self.start_layer + self.layer_num) correctly accounts for the possibility that this KVCache instance manages a subset of layers starting from self.start_layer, ensuring the correct buffers are accessed.
| @@ -182,6 +182,9 @@ def __init__( | |||
| def available_size(self): | |||
| return len(self.free_slots) | |||
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| def debug_print(self) -> str: | |||
| return "" | |||
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The new debug_print method is a helpful addition for diagnostics. Currently, it returns an empty string. To make it immediately useful, you might consider having it return some basic information about the allocator's state. For example, it could include details like the total number of slots, the number of free slots, and the page size.
| return "" | |
| return f"TokenToKVPoolAllocator(size={self.size}, free_slots={len(self.free_slots)}, page_size={self.page_size})" |
No description provided.