So we categorize TensorFlow operators that are supported by MKL backend in BFloat16 type into 1) if they are always numerically stable, and 2) if they are always numerically unstable, and 3) if their stability could depend on the context. Auto Mixed Precision pass uses a specific Allow, De...
MARLIN是一个matmul kernel,一个在FP16(activation) x INT4(weight)精度上做了极致优化的matmul kernel,一个在大规模LLM推理、投机解码中广泛应用的matmul kernel。其推理性能超过了exllamav2、bitsandbytes等著名kernel实现,目前已被vLLM、TGI等流行推理框架集成。最近开发团队发表了相关论文,趁此机会也来学习下它的...
AutoMPQ introduces an innovative evaluation mechanism based on a few-shot quantization adapter strategy. This approach significantly reduces the evaluation cost by efficiently tuning the meta-parameters of batch normalization (BN), mixed-precision convolution (MPConv), and mixed-precision ReLU (MPReLU)...
torch.autocast#523 Merged michaelbenayoun merged 22 commits into main from mixed_precision Apr 3, 2024 Merged Mixed-precision training with both torch_xla or torch.autocast #523 michaelbenayoun merged 22 commits into main from mixed_precision Apr 3, 2024 ...
if self.autocast_handler is not None: self.autocast_handler.cache_enabled = True else: self.autocast_handler = AutocastKwargs(cache_enabled=True) if autocast_handler is None: # By default `self.autocast_handler` enables autocast if: # - `self.state.mixed_precision == "bf16"` # -...
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