GitLab

* partially enable mypy for .models

* fix existing errors

* ignore error instead of using Union

* remove sys.version_info == 2

* remove sys.version_info < 3

* remove from __future__ imports

* quantizable googlenet

* Minor improvements

* Rename basic_conv2d with conv_block plus additional fixes

* More renamings and fixes

* Bugfix

* Fix missing import for mypy

* Add pretrained weights

* make googlnet scriptable

* Remove typing import in favor of torch.jit.annotations

* add inceptionnet

* flake fixes

* fix asssert true

* add import division for torchscript

* fix script compilation

* fix flake, py2 division error

* fix py2 division error

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)

I grepped the repo for Ouputs and these were the only occurences

* added progress flag to model getters

* flake8

* bug fix

* backward commpability

* add aux_logits support to inception

it is related to pytorch/pytorch#18668

* instantiate InceptionAux only when requested

it is related to pytorch/pytorch#18668

* revert googlenet

* support and aux_logits in pretrained models

* return namedtuple when aux_logit is True

Including the `transform_input` argument in the docs of inceptionV3

* flake_fixes

* flake_fixes2

* Modifying the comments of inceptionV3 dimensions

Modifying the comments of inceptionV3 dimensions to match the pytorch convention. Relevant (https://github.com/pytorch/vision/pull/719#pullrequestreview-203194302)

* Added Batch size in comment

* Update inception.py

* Updated inceptionV3 to accept different sized images (Adaptive avg pool)

The update allows inceptionV3 to process images larger or smaller than prescribed image size (299x299) using adaptive average pooling. Will be useful while finetuning or testing on different resolution images.

* Update inception.py

* Added size information for inception v3

Since inception v3 expects in contrast to the other models a size
of 299x299x3 I added a small note in the docstring to point that out
(addresses #560)

* inception size info in note box; fixed line length

* removed trailing whitespace

* Fix inception v3 input transform for trace & onnx

* Input transform are in-place updates, which produce issues for tracing
and exporting to onnx.

* nit

* fix for PyTorch v0.4 (remove .data and add _ for the initializations in nn.init)

* fix m.**.**() style to nn.init.**(**) style

* remove .idea

* fix lines and indents

* fix lines and indents

* change to use `kaming_normal_`

* add `.data` for safety

* add nonlinearity='relu' for sure

* fix indents

First dimension is batch size, channel is the second