This repository refers to Chahal's blog
# in_channel for mnist is 1, and the input shape is (batch_size, 1, 28, 28), output shape is (batch_size, 20, 24, 24)
convolution_layer_1(in_channel=in_channel, out_channel=20, kernel_size=5, stride=1)
# output shape is (batch_size, 20, 12, 12)
max_pool(2, 2)
# output shape is (batch_size, 20, 8, 8)
convolution_layer_2(in_channel=20, out_channel=50, kernel_size=5, stride=1)
# output shape is (batch_size, 20, 4, 4)
max_pool(2, 2)
full_connection_layer_1(4*4*50, 500)
full_connection_layer_2(500, 10)使用aware quantization在mnist上进行4bit量化实验，运行代码：
python main.py对量化权重进行统计，运行代码：
python weight_plot.py统计结果见图 