I tried running pytest -s text_recognizer/evaluation/evaluate_paragraph_text_recognizer.py and I got the following error
> output_tokens[:, Sy : Sy + 1] = output[-1:] # Set the last output token
E RuntimeError: The expanded size of the tensor (1) must match the existing size (16) at non-singleton dimension 1. Target sizes: [16, 1]. Tensor sizes: [16]
That I fixed by changing the file /text_recognizer/models/resnet_transformer.py L176 to:
output_tokens[:, Sy : Sy + 1] = output[-1:].reshape((-1,1)) # Set the last output token
Though not quite sure of the larger ramifications of this fix.
The full traceback is:
(fsdl-text-recognizer-2021) ubuntu@pc:~/pytorch-lab/lab8_eds$ PYTHONPATH=. pytest -s text_recognizer/evaluation/evaluate_paragraph_text_recognizer.py
====================================================================================================== test session starts ======================================================================================================
platform linux -- Python 3.6.13, pytest-6.2.3, py-1.10.0, pluggy-0.13.1
rootdir: /home/ubuntu/pytorch-lab/lab8_eds, configfile: setup.cfg
plugins: anyio-2.2.0
collected 1 item
text_recognizer/evaluation/evaluate_paragraph_text_recognizer.py IAMParagraphs.setup(None): Loading IAM paragraph regions and lines...
Testing: 0it [00:00, ?it/s]F
=========================================================================================================== FAILURES ============================================================================================================
_______________________________________________________________________________________ TestEvaluateParagraphTextRecognizer.test_evaluate _______________________________________________________________________________________
self = <evaluate_paragraph_text_recognizer.TestEvaluateParagraphTextRecognizer testMethod=test_evaluate>
@torch.no_grad()
def test_evaluate(self):
dataset = IAMParagraphs(argparse.Namespace(batch_size=16, num_workers=10))
dataset.prepare_data()
dataset.setup()
text_recog = ParagraphTextRecognizer()
trainer = pl.Trainer(gpus=1)
start_time = time.time()
> metrics = trainer.test(text_recog.lit_model, datamodule=dataset)
text_recognizer/evaluation/evaluate_paragraph_text_recognizer.py:28:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py:910: in test
results = self.__test_given_model(model, test_dataloaders)
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py:970: in __test_given_model
results = self.fit(model)
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py:499: in fit
self.dispatch()
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py:540: in dispatch
self.accelerator.start_testing(self)
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/accelerators/accelerator.py:76: in start_testing
self.training_type_plugin.start_testing(trainer)
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py:118: in start_testing
self._results = trainer.run_test()
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py:786: in run_test
eval_loop_results, _ = self.run_evaluation()
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/trainer/trainer.py:725: in run_evaluation
output = self.evaluation_loop.evaluation_step(batch, batch_idx, dataloader_idx)
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/trainer/evaluation_loop.py:162: in evaluation_step
output = self.trainer.accelerator.test_step(args)
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/accelerators/accelerator.py:195: in test_step
return self.training_type_plugin.test_step(*args)
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py:134: in test_step
return self.lightning_module.test_step(*args, **kwargs)
text_recognizer/lit_models/transformer.py:63: in test_step
pred = self.model.predict(x)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = ResnetTransformer(
(resnet): Sequential(
(0): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), b... (dropout2): Dropout(p=0.4, inplace=False)
(dropout3): Dropout(p=0.4, inplace=False)
)
)
)
)
x = tensor([[[-0.9087, 1.0898, -0.4428, ..., -0.5195, -1.6015, 0.9281],
[-1.4115, 0.9965, -0.9382, ..., -0.8...49, -0.8971, 1.5430],
[-1.8523, -0.1957, -0.5435, ..., 0.7036, -0.6454, 0.3995]]],
device='cuda:0')
def predict(self, x: torch.Tensor) -> torch.Tensor:
"""
Parameters
----------
x
(B, H, W) image
Returns
-------
torch.Tensor
(B, Sy) with elements in [0, C-1] where C is num_classes
"""
B = x.shape[0]
S = self.max_output_length
x = self.encode(x) # (Sx, B, E)
output_tokens = (torch.ones((B, S)) * self.padding_token).type_as(x).long() # (B, S)
output_tokens[:, 0] = self.start_token # Set start token
for Sy in range(1, S):
y = output_tokens[:, :Sy] # (B, Sy)
output = self.decode(x, y) # (Sy, B, C)
output = torch.argmax(output, dim=-1) # (Sy, B)
> output_tokens[:, Sy : Sy + 1] = output[-1:] # Set the last output token
E RuntimeError: The expanded size of the tensor (1) must match the existing size (16) at non-singleton dimension 1. Target sizes: [16, 1]. Tensor sizes: [16]
text_recognizer/models/resnet_transformer.py:176: RuntimeError
------------------------------------------------------------------------------------------------------- Captured log call -------------------------------------------------------------------------------------------------------
INFO pytorch_lightning.utilities.distributed:distributed.py:56 GPU available: True, used: True
INFO pytorch_lightning.utilities.distributed:distributed.py:56 TPU available: False, using: 0 TPU cores
INFO pytorch_lightning.accelerators.gpu:gpu.py:51 LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
======================================================================================================= warnings summary ========================================================================================================
../../anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/fsspec/__init__.py:43
/home/ubuntu/anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/fsspec/__init__.py:43: DeprecationWarning: SelectableGroups dict interface is deprecated. Use select.
for spec in entry_points.get("fsspec.specs", []):
text_recognizer/evaluation/evaluate_paragraph_text_recognizer.py::TestEvaluateParagraphTextRecognizer::test_evaluate
text_recognizer/evaluation/evaluate_paragraph_text_recognizer.py::TestEvaluateParagraphTextRecognizer::test_evaluate
text_recognizer/evaluation/evaluate_paragraph_text_recognizer.py::TestEvaluateParagraphTextRecognizer::test_evaluate
text_recognizer/evaluation/evaluate_paragraph_text_recognizer.py::TestEvaluateParagraphTextRecognizer::test_evaluate
text_recognizer/evaluation/evaluate_paragraph_text_recognizer.py::TestEvaluateParagraphTextRecognizer::test_evaluate
/home/ubuntu/anaconda3/envs/fsdl-text-recognizer-2021/lib/python3.6/site-packages/pytorch_lightning/utilities/distributed.py:52: DeprecationWarning: This `Metric` was deprecated since v1.3.0 in favor of `torchmetrics.Metric`. It will be removed in v1.5.0
warnings.warn(*args, **kwargs)
-- Docs: https://docs.pytest.org/en/stable/warnings.html
==================================================================================================== short test summary info ====================================================================================================
FAILED text_recognizer/evaluation/evaluate_paragraph_text_recognizer.py::TestEvaluateParagraphTextRecognizer::test_evaluate - RuntimeError: The expanded size of the tensor (1) must match the existing size (16) at non-singl...
================================================================================================ 1 failed, 6 warnings in 45.72s =================================================================================================
Testing: 0%| | 0/15 [00:00<?, ?it/s]
I tried running
pytest -s text_recognizer/evaluation/evaluate_paragraph_text_recognizer.pyand I got the following errorThat I fixed by changing the file
/text_recognizer/models/resnet_transformer.pyL176 to:Though not quite sure of the larger ramifications of this fix.
The full traceback is: