保持状态一致性:对于一些保存状态的模块(如批量归一化层),状态(例如运行均值和方差)需要在FP32中维护,以避免由于FP16较低的数值精度导致的数值不稳定问题。auto_fp16需要处理这些情况,确保状态不会被错误地转换为FP16。 对外接口:@auto_fp16可能提供参数来指定哪些输入或输出应该被转换。例如,可以指定apply_to=('...
Test name: test_autocast_methods_fp16 (__main__.TestCudaAutocast) Platforms for which to skip the test: linux Disabled by pytorch-bot[bot] Within ~15 minutes, test_autocast_methods_fp16 (__main__.TestCudaAutocast) will be disabled in PyTorch CI for these platforms: linux. Please veri...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - DISABLED test_autocast_methods_fp16 (__main__.TestCudaAutocast) · pytorch/pytorch@c0deec1
Questions about DL Workbench: FP16 Model auto-convert to FP32 / IR color space / Model parameters Subscribe More actions nat98 New Contributor I 11-25-2021 12:36 AM 2,783 Views Hello there, We have a few questions regarding DL Workbench. 1...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - DISABLED test_autocast_methods_fp16 (__main__.TestCudaAutocast) · pytorch/pytorch@8962610
Test name: test_autocast_torch_fp16 (__main__.TestCudaAutocast) Platforms for which to skip the test: linux Disabled by pytorch-bot[bot] Within ~15 minutes, test_autocast_torch_fp16 (__main__.TestCudaAutocast) will be disabled in PyTorch CI for these platforms: linux. Please verify...
_limit=5,no_cuda=False,seed=42,fp16=False,fp16_opt_level=O1,fp16_backend=auto,fp16_full_eval=False,local_rank=0,tpu_num_cores=None,tpu_metrics_debug=False,debug=[],dataloader_drop_last=False,eval_steps=10,dataloader_num_workers=0,past_index=-1,run_name=/data/dps_finetune_16_wiki...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - DISABLED test_autocast_linalg_fp16 (__main__.TestCudaAutocast) · pytorch/pytorch@8962610
Contributor wenhuach21 commented Nov 15, 2024 No description provided. wenhuach21 and others added 9 commits November 15, 2024 10:34 fix merge error 52ec561 fix fp_layers issues 7af3e8a Merge branch 'main' into bix_1115 Verified 40a72f2 Loosen the restrictions of lm-eval d44266a...
An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm. - Release v0.7.0: Marlin int4*fp16 kernel, AWQ checkpoints loading · AutoGPTQ/AutoGPTQ