🚀 Feature request

In pipelines tests and documentation they are recurringly named nlp, the goal is to rename them to something more appropriate.

Motivation

nlp = pipeline(task='conversational', model='XXX')

This is a bit pre

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

🚀 Feature

See title

https://github.com/PyTorchLightning/pytorch-lightning/blob/9137b16068fe03e6db8df548235363e5f5476aac/pytorch_lightning/trainer/connectors/logger_connector/epoch_result_store.py#L25-L42

Motivation

No longer used after #5579

Pitch

Proper deprecation process

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_

more details at: allenai/allennlp#2264 (comment)

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)