reserved. Quantization Overview • Represent FP32 numbers with a lower-precision INT8 numbers • Integer number stands as a proxy for FP32 number (not a downcast) • Quantized tensor is represented with Calculations are different from FP32 Conv2D https://discuss.tvm.ai/t/tf-lite-quantized-conv2d-operator-conversion/2651/8 𝑟𝑒𝑎𝑙_𝑣𝑎𝑙𝑢𝑒 = 𝒔𝒄𝒂𝒍𝒆 ∗ (𝑞𝑢𝑎𝑛𝑡𝑖𝑧𝑒𝑑_𝑣𝑎𝑙𝑢𝑒 − 𝒛𝒆𝒓𝒐_𝒑𝒐𝒊𝒏𝒕)© Pre-quantized model support. Contributions are welcomed. • We need new/tuned TVM schedules using fast Integer operations like Intel VNNI, ARM Dot, Nvidia DP4A • Full pipeline is available. Please try it and

ee New Integer Analysis Infrastructure o_ Supports the ability to handle nested division and modulus o_ Improves the ability to reason about and optimize loops e Support for different integer division

him. Table 25 | An example of HellaSwag. PROMPT def starts_one_ends(n): """ Given a positive integer n, return the count of the numbers of n-digit positive integers that start or end with 1. """ Table