Stops after 1000 steps

[GuusDeKroon]

Hi!
I've been having this issue where the program stops training at 1000 iters.
Everything else seems to be fine.

Here's the code output:

Another one bites the dust...

Traceback (most recent call last):
  File "main.py", line 852, in <module>
    trainer.test(model, data)
  File "C:\Users\Guus\miniconda3\envs\ldm\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 938, in test
    return self._call_and_handle_interrupt(self._test_impl, model, dataloaders, ckpt_path, verbose, datamodule)
  File "C:\Users\Guus\miniconda3\envs\ldm\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 723, in _call_and_handle_interrupt
    return trainer_fn(*args, **kwargs)
  File "C:\Users\Guus\miniconda3\envs\ldm\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 985, in _test_impl
    results = self._run(model, ckpt_path=self.ckpt_path)
  File "C:\Users\Guus\miniconda3\envs\ldm\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 1160, in _run
    verify_loop_configurations(self)
  File "C:\Users\Guus\miniconda3\envs\ldm\lib\site-packages\pytorch_lightning\trainer\configuration_validator.py", line 46, in verify_loop_configurations
    __verify_eval_loop_configuration(trainer, model, "test")
  File "C:\Users\Guus\miniconda3\envs\ldm\lib\site-packages\pytorch_lightning\trainer\configuration_validator.py", line 197, in __verify_eval_loop_configuration
    raise MisconfigurationException(f"No `{loader_name}()` method defined to run `Trainer.{trainer_method}`.")
pytorch_lightning.utilities.exceptions.MisconfigurationException: No `test_dataloader()` method defined to run `Trainer.test`.

[Kallamamran]

Do you have "max_training_steps = 1000"?
I don't get mine to run at all, so :/

[GuusDeKroon]

Nope, the max training steps is at 3000

[djbielejeski]

I've been seeing this too, looking into it right now.

[djbielejeski]

I tried removing the --no-test param, still get this error

Here comes the checkpoint...
Another one bites the dust...

Traceback (most recent call last):
  File "main.py", line 847, in <module>
    trainer.fit(model, data)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 771, in fit
    self._fit_impl, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 723, in _call_and_handle_interrupt
    return trainer_fn(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 811, in _fit_impl
    results = self._run(model, ckpt_path=self.ckpt_path)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1236, in _run
    results = self._run_stage()
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1323, in _run_stage
    return self._run_train()
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1353, in _run_train
    self.fit_loop.run()
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/base.py", line 204, in run
    self.advance(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/fit_loop.py", line 266, in advance
    self._outputs = self.epoch_loop.run(self._data_fetcher)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/base.py", line 205, in run
    self.on_advance_end()
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 255, in on_advance_end
    self._run_validation()
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 311, in _run_validation
    self.val_loop.run()
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/base.py", line 204, in run
    self.advance(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/dataloader/evaluation_loop.py", line 155, in advance
    dl_outputs = self.epoch_loop.run(self._data_fetcher, dl_max_batches, kwargs)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/base.py", line 204, in run
    self.advance(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 134, in advance
    self._on_evaluation_batch_end(output, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 267, in _on_evaluation_batch_end
    self.trainer._call_callback_hooks(hook_name, output, *kwargs.values())
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1636, in _call_callback_hooks
    fn(self, self.lightning_module, *args, **kwargs)
  File "/workspace/Dreambooth-Stable-Diffusion/main.py", line 470, in on_validation_batch_end
    self.log_img(pl_module, batch, batch_idx, split="val")
  File "/workspace/Dreambooth-Stable-Diffusion/main.py", line 434, in log_img
    images = pl_module.log_images(batch, split=split, **self.log_images_kwargs)
  File "/opt/conda/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/workspace/Dreambooth-Stable-Diffusion/ldm/models/diffusion/ddpm.py", line 1328, in log_images
    batch = batch[0]
KeyError: 0

[1blackbar]

Itsrunning fine here , past 1000 steps

[djbielejeski]

Pretty sure I found the issue. It is when writing an epoch, and the epoch size depends on your training_samples count and your regularization_images count. You can trigger this by going over 1 epoch. I think I found the spot in the code, testing it now.

[djbielejeski]

Fixed here

[djbielejeski]

At least my issue...