All rights reserved. Animesh Jain Amazon SageMaker Neo Compilation of Quantized Models in TVM AWS AI© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Quantization Overview • reserved. QNN Conv2D Operator • Calculations are different from FP32 Conv2D https://discuss.tvm.ai/t/tf-lite-quantized-conv2d-operator-conversion/2651/8 𝑟𝑒𝑎𝑙_𝑣𝑎𝑙𝑢𝑒 = 𝒔𝒄𝒂𝒍𝒆 ∗ (𝑞𝑢𝑎�

before putting its data on there. Like how a painter has a standard spot for their canvas, Krita also benefits from giving certain data it uses its place (a memory pool), so that it can find them easily, and 5, 0.5]. If a vector is used in a scalar context, only the first component is used. One of the benefits of this is that all the functions that are defined to work with scalars automatically extend to work on one of the coolest and fastest-growing open source painting programs out there. Krita also benefits from a modular architecture and the use of the KDE Frameworks and Qt libraries, which makes it easier

can be unset by prefixing ”no” set ignorecase ” :h ’ic set smartcase ” :h ’scs set autoindent ” :h ’ai set smartindent ” :h ’si set nowrap ” :h ’wrap ”set list ” :h ’list (default nolist) set noerrorbells