2.4 EQ 量化 EQ 量化即 EasyQuant,是格灵深瞳开源的量化算法,在文章《EasyQuant: Post-training Quantization via Scale Optimization》中进行了介绍。EQ 量化方法的主要思想是:误差累计、整网决策变成单网决策、以余弦相似度为优化目标、交替优化权重缩放系数和激活值缩放系数。 假设量化公式如下(为了方便起见,采用对称量...
EQ 量化即 EasyQuant,是格灵深瞳开源的量化算法,在文章《EasyQuant: Post-training Quantization via Scale Optimization》中进行了介绍。EQ 量化方法的主要思想是:误差累计、整网决策变成单网决策、以余弦相似度为优化目标、交替优化权重缩放系数和激活值缩放系数。 假设量化公式如下(为了方便起见,采用对称量化...
Vector Quantization comprises of three different phases: Codebook Generation, Image Encoding and Image Decoding. The efficiency of VQ depends on the quality of the codebook. In this paper, we have proposed a novel idea for improving the quality of codebook. The codebook is populated with high ...
MINMAX Bit Allocation for Quantization-Based Video Coders level bit allocation for H.263, cast as a variation on the multiple-choice knapsack problem, and show how to solve it efficiently with dynamic ... G Shavit,RE Ladner,EA Riskin - Data Compression Conference 被引量: 12发表: 2005年 Opti...
torch/quantization/observer.py @@ -364,8 +371,8 @@ def __init__(self, dtype=torch.quint8, qscheme=torch.per_tensor_affine, reduce_range=reduce_range, quant_min=quant_min, quant_max=quant_max) self.register_buffer('min_val',torch.tensor([])) ...
Made changes totests/torch/ptq/test_min_max.pyto pass the functions that handle backend-specific layer attributes. Reason for changes For changes 2 and 3, only the node metatypes are required to test target point shape and weight quantization channel axes. ...
Superseded by explicit quantization.Extends the IInt8Calibrator class.To implement a custom calibrator, ensure that you explicitly instantiate the base class in __init__() :class MyCalibrator(trt.IInt8MinMaxCalibrator): def __init__(self): trt.IInt8MinMaxCalibrator.__init__(self) ...
EQ 量化即 EasyQuant,是格灵深瞳开源的量化算法,在文章《EasyQuant: Post-training Quantization via Scale Optimization》中进行了介绍。EQ 量化方法的主要思想是:误差累计、整网决策变成单网决策、以余弦相似度为优化目标、交替优化权重缩放系数和激活值缩放系数。
This paper examines the role of attacker's memory in Quantization Index Modulation (QIM) watermarking systems. First we derive the attacker's noise distribution that maximizes probability of error of the detector. Next, we derive QIM code parameters that are minmax optimal. The minmax optimal ...
Such compactly stored information enables the encoder to select quantization parameters in real-time during streaming process. Our results show that our algorithm obtains higher minimum PSNR values than the TM5 rate control while the average PSNR is similar. We also use the same technique to ...