def resnet34_qfi(pretrained=False, **kwargs): """Constructs a ResNet-34 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = ResNetQFI(BasicBlockQ, [3, 4, 6, 3], **kwargs) if pretrained: load_fake_quantized_state_dict(model, model_zoo.load_url(model_urls['resnet34']), 'resnet34_qfi_map.json') return model
def resnet50_qfn(pretrained=False, **kwargs): """Constructs a ResNet-50 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = ResNetQFN(BottleneckQ, [3, 4, 6, 3], **kwargs) if pretrained: load_fake_quantized_state_dict(model, model_zoo.load_url(model_urls['resnet50']), 'resnet50_qfn_map.json') return model
def resnet18_qfn(pretrained=False, **kwargs): """Constructs a ResNet-18 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = ResNetQFN(BasicBlockQ, [2, 2, 2, 2], **kwargs) if pretrained: load_fake_quantized_state_dict(model, model_zoo.load_url(model_urls['resnet18']), 'resnet18_qfn_map.json') return model
def mobilenetv2_qfnv2(pretrained=False, **kwargs): r"""MobileNetV2 model architecture from the Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = MobileNetV2QFNv2(**kwargs) if pretrained: load_fake_quantized_state_dict( model, model_zoo.load_url(model_urls['mobilenetv2'], map_location='cpu'), 'mobilenetv2_qfnv2_map.json') return model
def alexnet_bp_no_fc_v2(pretrained=False, **kwargs): r"""AlexNet model architecture from the `"One weird trick..." <https://arxiv.org/abs/1404.5997>`_ paper. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet """ model = AlexNetBPNOFCv2(**kwargs) if pretrained: load_fake_quantized_state_dict( model, model_zoo.load_url(model_urls['alexnet'], map_location='cpu'), 'alexnet_bp_no_fc_v2_map.json') return model