pytorch_lightning.utilities.exceptions.MisconfigurationException: The closure hasn't been executed

Question

I got an error message when I used pytorch-lightning Trainer module:

File "run.py", line 105, in <module>
    runner.fit(experiment)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 769, 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 721, in _call_and_handle_interrupt
    return trainer_fn(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 809, 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 1234, in _run
    results = self._run_stage()
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1321, in _run_stage
    return self._run_train()
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1351, 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 269, 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 204, in run
    self.advance(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 208, in advance
    batch_output = self.batch_loop.run(batch, batch_idx)
  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/batch/training_batch_loop.py", line 88, in advance
    outputs = self.optimizer_loop.run(split_batch, optimizers, batch_idx)
  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/optimization/optimizer_loop.py", line 207, in advance
    self.optimizer_idx,
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/optimization/optimizer_loop.py", line 258, in _run_optimization
    result = closure.consume_result()
  File "/opt/conda/lib/python3.7/site-packages/pytorch_lightning/loops/optimization/closure.py", line 52, in consume_result
    "The closure hasn't been executed."
pytorch_lightning.utilities.exceptions.MisconfigurationException: The closure hasn't been executed. HINT: did you call `optimizer_closure()` in your `optimizer_step` hook? It could also happen because the `optimizer.step(optimizer_closure)` call did not execute it internally.

I read the Pytorch Lightning 1.6.1 documentation. It seems that under the hood, the Lightning Trainer handles the training loop details for me. I don't know how to handle the "optimizer.step()" by myself...

The following is my code of calling Trainer:

runner = Trainer(checkpoint_callback=checkpoint_callback,
                 resume_from_checkpoint=model_path,
                 logger=tt_logger,
                 log_every_n_steps=100,
                 weights_summary='full',
                 # early_stop_callback = False,
                 **config['trainer_params'])

And I defined the following function in my model:

def forward(self, input: Tensor, **kwargs) -> Tensor
def training_step(self, batch, batch_idx, optimizer_idx)
def optimizer_step(self, epoch, batch_idx, optimizer, optimizer_idx, def optimizer_closure, on_tpu, using_native_amp, using_lbfgs)
on_load_checkpoint(self, checkpoint)
def training_epoch_end(self, outputs)
def configure_optimizers(self)
def train_dataloader(self)
def data_transforms(self)

This is my first time asking a question here. If there is something wrong, please forgive me. Thank you all for your help!