tng and val steps now have batch nbs
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@ -163,7 +163,7 @@ class Trainer(TrainerIO):
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outputs = []
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# run training
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for i, data_batch in enumerate(dataloader):
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for batch_i, data_batch in enumerate(dataloader):
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if data_batch is None:
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continue
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@ -175,7 +175,7 @@ class Trainer(TrainerIO):
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# -----------------
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# RUN VALIDATION STEP
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# -----------------
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output = model.validation_step(data_batch)
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output = model.validation_step(data_batch, batch_i)
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outputs.append(output)
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# batch done
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@ -290,7 +290,7 @@ class Trainer(TrainerIO):
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# ---------------
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# RUN TRAIN STEP
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# ---------------
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batch_result = self.__run_tng_batch(data_batch)
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batch_result = self.__run_tng_batch(data_batch, batch_nb)
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early_stop_epoch = batch_result == -1
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# ---------------
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@ -348,7 +348,7 @@ class Trainer(TrainerIO):
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return
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def __run_tng_batch(self, data_batch):
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def __run_tng_batch(self, data_batch, batch_nb):
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if data_batch is None:
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return 0
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@ -363,7 +363,7 @@ class Trainer(TrainerIO):
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# forward pass
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# return a scalar value and a dic with tqdm metrics
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loss, model_specific_tqdm_metrics_dic = self.model.training_step(data_batch)
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loss, model_specific_tqdm_metrics_dic = self.model.training_step(data_batch, batch_nb)
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self.__add_tqdm_metrics(model_specific_tqdm_metrics_dic)
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# backward pass
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2
setup.py
2
setup.py
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@ -7,7 +7,7 @@ from setuptools import setup, find_packages
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# http://blog.ionelmc.ro/2014/05/25/python-packaging/
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setup(
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name="pytorch-lightning",
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version='0.1.dev1821',
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version='0.1.dev1822',
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description="The Keras for ML researchers using PyTorch",
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author="William Falcon",
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author_email="waf2107@columbia.edu",
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