GitLab

* [doc] add minimum input size for alexnet builder

* [doc] add minimum input size for vgg builder

* [doc] add minimum input size for squeezenet builder

* [doc] add minimum input size for densenet builder

* [doc] add minimum input size for inception_v3 builder

* [doc] add minimum input size for googlenet builder
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update URLS of detection models

* Empty commit after setting  read permission on S3
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* fix: Fixed constructor typing in models._utils

* fix: Fixed constructor typing in models.alexnet

* fix: Fixed constructor typing in models.mnasnet

* fix: Fixed constructor typing in models.squeezenet

Fix the old flatten method which use the size(0) to caculate the batch size, the old method will intruduce Gather opertion in the onnx output, which will faild parsed by tensorRT 5.0 (#1134)

* added progress flag to model getters

* flake8

* bug fix

* backward commpability

The update allows Alexnet to process images larger or smaller than prescribed imagenet size using adaptive average pooling. Will be useful while finetuning or testing on different resolution images. Similar to https://github.com/pytorch/vision/pull/643 and https://github.com/pytorch/vision/pull/672. I did not include adaptive avg pool in features or classifier block so that these predefined blocks can be used as it is.

    git ls-files | grep '\.py$' | xargs -n1 -P`nproc` autopep8 -i

Also add pre-trained ResNet-152 model.

  ResNet-152: Prec@1 78.312 Prec@5 94.046