README.md
1# Test models for testing quantization 2 3This directory contains test models for testing quantization. 4 5## Models 6 7* `single_conv_weights_min_0_max_plus_10.bin` \ 8 A floating point model with single convolution where all weights are 9 integers between [0, 10] weights are randomly distributed. It is not 10 guaranteed that min max for weights are going to appear in each channel. 11 All activations have min maxes and activations are in range [0,10]. 12* `single_conv_weights_min_minus_127_max_plus_127.bin` \ 13 A floating point model with a single convolution where weights of the model 14 are all integers that lie in range[-127, 127]. The weights have been put in 15 such a way that each channel has at least one weight as -127 and one weight 16 as 127. The activations are all in range: [-128, 127]. 17 This means all bias computations should result in 1.0 scale. 18* `single_softmax_min_minus_5_max_5.bin` \ 19 A floating point model with a single softmax. The input tensor has min 20 and max in range [-5, 5], not necessarily -5 or +5. 21* `single_avg_pool_input_min_minus_5_max_5.bin` \ 22 A floating point model with a single average pool. The input tensor has min 23 and max in range [-5, 5], not necessarily -5 or +5. 24* `weight_shared_between_convs.bin` \ 25 A floating point model with two convs that have a use the same weight tensor. 26* `multi_input_add_reshape.bin` \ 27 A floating point model with two inputs with an add followed by a reshape. 28* `quantized_with_gather.bin` \ 29 A floating point model with an input with a gather, modeling a situation 30 of mapping categorical input to embeddings. 31