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On-device AI across mobile, embedded and edge for PyTorch
* Add legalization from aten.mm to TOSA MatMul for FP32 & INT8 types * Add tests for main and base inference * Add an annotator for aten.mm in the quantizer
- Use single rounding at rescale to int8 - Minor refactor of op_addmm to use shared functions
hello, now I want to realize the sliding window of kv cache, so dynamic allocation and reclamation of memory needs to be realized. could you please teach me how to...
Summary: And use std lib to compute it. Differential Revision: D60854860
Summary: Refactoring partitioner-based delegation to prepare for allowing buffer mutations in the delegate (following diff). Differential Revision: D60813405
Change-Id: I15f8a37fe88ba6c7d1e357c9ab897069c3c912b2
Testing baseline full CI run for XNNPACK upgrade.