Logging with "self.log" in training_step does not create any outputs in progress bar or external Logger when loss isn't returned
🐛 Bug
I think the newly introduced log function function does not log properly while being used in the training_step. The same code in validation_step creates the desired results.
    def training_step(self, batch, batch_idx):
        output = self.layer(batch)
        loss = self.loss(batch, output)
        self.log("loss", loss, prog_bar=True, logger=True, on_step=True, on_epoch=True)
        self.log("my_metric_train", 1001, prog_bar=True, logger=True, on_step=True, on_epoch=True)
        ##### Doesn't Work #######


    def validation_step(self, batch, batch_idx):
        output = self.layer(batch)
        loss = self.loss(batch, output)
        self.log("val_loss", loss, prog_bar=True, logger=True, on_step=True, on_epoch=True)
        self.log("my_metric_val", 1001, prog_bar=True, logger=True, on_step=True, on_epoch=True)
        ##### Works #######

Please reproduce using
https://gist.github.com/tobiascz/bb2c6de83263eb38181052840062b5ac
Expected behavior
Logs created in training_step should show up in the prog_bar and loggers (such as tensorboard logger). Same code in the validation_step creates the desired results.
Environment

CUDA:

GPU:

Tesla T4


available:         True
version:           10.1


Packages:

numpy:             1.18.5
pyTorch_debug:     False
pyTorch_version:   1.6.0+cu101
pytorch-lightning: 0.10.0
tqdm:              4.41.1


System:

OS:                Linux
architecture:

64bit



processor:         x86_64
python:            3.6.9
version:           #1 SMP Thu Jul 23 08:00:38 PDT 2020
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