ImageNet pretrained weights

Here are the latest pretrained weights on ImageNet dataset.
In this version, we fixed an unintentional bug in the model, where the 1x1 convs had paddings of 1,
this is now taken care of and new weightsand models are provided.

m2 variants:

Method	#Params	ImageNet	ImageNet-Real-Labels
simplenetv1_9m_m2(36.3 MB)	9.5m	74.23/91.748	81.22/94.756
simplenetv1_5m_m2(22 MB)	5.7m	72.03/90.324	79.328/93.714
simplenetv1_small_m2_075(12.6 MB)	3m	68.506/88.15	76.283/92.02
simplenetv1_small_m2_05(5.78 MB)	1.5m	61.67/83.488	69.31/ 88.195

m1 variants:

Method	#Params	ImageNet	ImageNet-Real-Labels
simplenetv1_9m_m1(36.3 MB)	9.5m	73.792/91.486	81.196/94.512
simplenetv1_5m_m1(22 MB)	5.7m	71.548/89.94	79.076/93.36
simplenetv1_small_m1_075(12.6 MB)	3m	67.784/87.718	75.448/91.69
simplenetv1_small_m1_05(5.78 MB)	1.5m	61.122/82.988	68.58/87.64

Note1:
some of these weights are achieved from finetuning the previous weights to shorten the training time
some others are trained from scratch.

imagenet pretrained weights with nopad in conv1x1 layers

These are the weights finetuned on previously trained weights, with the exception that the last 2 conv1x1 layers now have no padding
this allows for faster inference and I tried to improve the accuracy and here are the models so far.
the sample quantized weights are statically quantized, in order to get full accuracy like the one in full precision weights, they must be fintuned in QAT.

Initial ImageNet Models

Initial ImageNet pretrained weights are now available for download.

m2 variants:

Method	#Params	ImageNet	ImageNet-Real-Labels
simplenetv1_9m_m2(36.33 MB)	9.5m	74.17/91.61	81.24/94.63
simplenetv1_5m_m2(21.9 MB)	5.7m	71.94/90.3	79.12/93.68
simplenetv1_small_m2_075(12.58 MB)	3m	68.15/87.76	75.66/91.80
simplenetv1_small_m2_05(5.78 MB)	1.5m	61.53/83.43	69.11/88.10

m1 variants:

Method	#Params	ImageNet	ImageNet-Real-Labels
simplenetv1_9m_m1(36.33 MB)	9.5m	73.376/91.048	80.72/94.26
simplenetv1_5m_m1(21.9 MB)	5.7m	71.37/90.10	78.77/93.50
simplenetv1_small_m1_075(12.58 MB)	3m	67.764/87.66	75.48/91.66
simplenetv1_small_m1_05(5.78 MB)	1.5m	60.89/82.978	68.46/87.64

Initial ImageNet models

Initial ImageNet models that I trained recently