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Description
evaluate.predictions_sequence_module(
... best_model,
... sdata=sd_test,
... seq_var="ohe_seq",
... target_vars="qseqid_x",
... batch_size=128,
... gpus=1,
... in_memory=True,
... name="LTRidentity",
... version="0.75",
... file_label="test",
... prefix=f"LTRidentity_",
... transforms={"ohe_seq": lambda x: x.swapaxes(1, 2)},
... num_workers=63
... )
Loading ohe_seq and ['qseqid_x'] into memory
GPU available: False, used: False
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
Predicting DataLoader 0: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 18/18 [00:00<00:00, 70.29it/s]Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/eugene/evaluate/_predict.py", line 146, in predictions_sequence_module
preds = predictions(
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/eugene/evaluate/_predict.py", line 62, in predictions
ps = np.concatenate(predictor.predict(model, dataloader), axis=0)
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 864, in predict
return call._call_and_handle_interrupt(
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/trainer/call.py", line 44, in _call_and_handle_interrupt
return trainer_fn(*args, **kwargs)
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 903, in _predict_impl
results = self._run(model, ckpt_path=ckpt_path)
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 989, in _run
results = self._run_stage()
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py", line 1030, in _run_stage
return self.predict_loop.run()
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/loops/utilities.py", line 182, in _decorator
return loop_run(self, *args, **kwargs)
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/loops/prediction_loop.py", line 128, in run
return self.on_run_end()
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/loops/prediction_loop.py", line 200, in on_run_end
results = self._on_predict_epoch_end()
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/loops/prediction_loop.py", line 357, in _on_predict_epoch_end
call._call_callback_hooks(trainer, "on_predict_epoch_end")
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/trainer/call.py", line 208, in _call_callback_hooks
fn(trainer, trainer.lightning_module, *args, **kwargs)
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pytorch_lightning/callbacks/prediction_writer.py", line 156, in on_predict_epoch_end
self.write_on_epoch_end(trainer, pl_module, trainer.predict_loop.predictions, epoch_batch_indices)
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/eugene/evaluate/_utils.py", line 20, in write_on_epoch_end
pred_df = pd.DataFrame(data=outputs, columns=pred_cols + target_cols)
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pandas/core/frame.py", line 721, in __init__
mgr = ndarray_to_mgr(
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pandas/core/internals/construction.py", line 349, in ndarray_to_mgr
_check_values_indices_shape_match(values, index, columns)
File "/home/xiongzx/.conda/envs/eugene/lib/python3.9/site-packages/pandas/core/internals/construction.py", line 420, in _check_values_indices_shape_match
**raise ValueError(f"Shape of passed values is {passed}, indices imply {implied}")
ValueError: Shape of passed values is (2274, 10), indices imply (2274, 18)**my output_dim is 9
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