GitHub

quantization_aware_training.py

# SPDX-License-Identifier: BSD-3-Clause """ This file demonstrates the use of quantization using AIMET quantization aware training. """ import argparse import logging import os from datetime import ...
GitHub

custom_quantization_int8_example.py

self.register_buffer("weight", torch.zeros((out_features, in_features), dtype=torch.int8)) self.register_buffer("weight_scale", torch.zeros((out_features, 1), dtype ...
Techopedia

What is Quantization?

Quantization is a process aimed at simplifying data representation by reducing precision – the number of bits used. This process involves approximating a continuous range of values with a smaller set ...
IEEE

Data Quality-Aware Mixed-Precision Quantization via Hybrid Reinforcement Learning

Abstract: Mixed-precision quantization mostly predetermines the model bit-width settings before actual training due to the non-differential bit-width sampling process, obtaining suboptimal performance ...
IEEE

Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering

Abstract: TinyML enables the deployment of Machine Learning (ML) models on resource-constrained devices, addressing a growing need for efficient, low-power AI solutions. However, significant ...
INSPIRE

Frozen formalism and canonical quantization in group field theory

Canonical quantization of gravitational systems is obstructed by the problem of time. Due to diffeomorphism symmetry the Hamiltonian vanishes: dynamics with respect to a background time parameter ...
INSPIRE

Note on canonical quantization and unitary (in)equivalence in field theory

The problem of defining and constructing representations of the Canonical Commutation Relations can be systematically approached via the technique of {\it algebraic quantization}. In particular, when ...