As a part of an effort to make all examples have the same look and feel this issue requests to sync the support for these 3 cl args in run_seq2seq.py:

--max_train_samples 5 --max_val_samples 5 --max_test_samples 5

into:

1. all other examples/*/run_*.py
2. templates/adding_a_new_example_script

Part B. the metrics should be now updated to include the actual number of samples t

some recordings have low volume so the output can be sometimes really quiet. how about we add a volume bar so we can make the output louder/quieter?

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Similar to ModelCheckpoint(verbose=true), we can add verbose_progress_bar trainer flag, to print the logs to the screen after every epoch

Change tensor.data to tensor.detach() due to
pytorch/pytorch#6990 (comment)
tensor.detach() is more robust than tensor.data.

Add a new API for converting a model to external data. Today the conversion happens in 2 steps
external_data_helper.convert_model_to_external_data(<model>, <all_tensors_to_one_file>, <size_threshold>) save_model(model, output_path)
We want to add another api which combines the 2 steps
`
save_model_to_external_data(, <output_

While setting train_parameters to False very often we also may consider disabling dropout/batchnorm, in other words, to run the pretrained model in eval mode.
We've done a little modification to PretrainedTransformerEmbedder that allows providing whether the token embedder should be forced to eval mode during the training phase.

Do you this feature might be handy? Should I open a PR?

I'm using mxnet to do some work, but there is nothing when I search the mxnet trial and example.

Current pytorch implementation ignores the argument split_f in the function train_batch_ch13 as shown below.

def train_batch_ch13(net, X, y, loss, trainer, devices):
    if isinstance(X, list):
        # Required for BERT Fine-tuning (to be covered later)
        X = [x.to(devices[0]) for x in X]
    else:
        X = X.to(devices[0])
...

Todo: Define the argument `

Is it possible to run this on a (recent) Mac, which does not support CUDA? I would have guessed setting --GPU 0 would not attempt to call CUDA, but it fails.

File "/Users/../Desktop/bopbtl/venv/lib/python3.7/site-packages/torch/cuda/__init__.py", line 61, in _check_driver
    raise AssertionError("Torch not compiled with CUDA enabled")
AssertionError: Torch not compiled with CUDA enable

Please can you train ghostnet.
(i don't have the imagenet dataset)