Kill __main__

src/transformers/__main__.py

@@ -1,42 +0,0 @@
-# coding: utf8
-
-
-def main():
-    import sys
-
-    if len(sys.argv) < 2 or sys.argv[1] not in ["convert", "train", "predict", "serve"]:
-        print(
-            "First argument to `transformers` command line interface should be one of: \n"
-            ">> convert serve train predict"
-        )
-    if sys.argv[1] == "convert":
-        from transformers.commands import convert
-
-        convert(sys.argv)
-    elif sys.argv[1] == "train":
-        from transformers.commands import train
-
-        train(sys.argv)
-    elif sys.argv[1] == "serve":
-        pass
-        # from argparse import ArgumentParser
-        # from transformers.commands.serving import ServeCommand
-        # parser = ArgumentParser('Transformers CLI tool', usage='transformers serve <command> [<args>]')
-        # commands_parser = parser.add_subparsers(help='transformers-cli command helpers')
-
-        # # Register commands
-        # ServeCommand.register_subcommand(commands_parser)
-
-        # # Let's go
-        # args = parser.parse_args()
-
-        # if not hasattr(args, 'func'):
-        #     parser.print_help()
-        #     exit(1)
-        # # Run
-        # service = args.func(args)
-        # service.run()
-
-
-if __name__ == "__main__":
-    main()

templates/adding_a_new_model/README.md

@@ -56,7 +56,7 @@ You can then finish the addition step by adding imports for your classes in the
 - [ ] add your PyTorch and TF 2.0 model respectively in `modeling_auto.py` and `modeling_tf_auto.py`
 - [ ] add your tokenizer in `tokenization_auto.py`
 - [ ] add your models and tokenizer to `pipeline.py`
-- [ ] add a link to your conversion script in the main conversion utility (currently in `__main__` but will be moved to the `commands` subfolder in the near future)
+- [ ] add a link to your conversion script in the main conversion utility (in `commands/convert.py`)
 - [ ] edit the PyTorch to TF 2.0 conversion script to add your model in the `convert_pytorch_checkpoint_to_tf2.py` file
 - [ ] add a mention of your model in the doc: `README.md` and the documentation itself at `docs/source/pretrained_models.rst`.
 - [ ] upload the pretrained weigths, configurations and vocabulary files.