Change nb to num in ABCs, comments, and tqdm logging (#613)

* Change nb to num in ABCs, comments, and tqdm logging

* Fix warnings text

* Make warnings one line

* Change num to number in comments

pytorch_lightning/trainer/evaluation_loop.py

@@ -145,8 +145,8 @@ class TrainerEvaluationLoopMixin(ABC):
         self.single_gpu = None
         self.data_parallel_device_ids = None
         self.model = None
-        self.nb_test_batches = None
-        self.nb_val_batches = None
+        self.num_test_batches = None
+        self.num_val_batches = None
         self.fast_dev_run = None
         self.process_position = None
         self.show_progress_bar = None

pytorch_lightning/trainer/logging.py

@@ -177,7 +177,7 @@ class TrainerLoggingMixin(ABC):
             elif isinstance(output[k], torch.Tensor) and output[k].dim() == 0:
                 pass
 
-            # reduce only metrics that have the same nb of gpus
+            # reduce only metrics that have the same number of gpus
             elif output[k].size(0) == num_gpus:
                 reduced = torch.mean(output[k])
                 output[k] = reduced

pytorch_lightning/trainer/trainer.py

@@ -346,7 +346,7 @@ class Trainer(TrainerIOMixin,
             tqdm_dict['split_idx'] = self.split_idx
 
         if self.logger is not None and self.logger.version is not None:
-            tqdm_dict['v_nb'] = self.logger.version
+            tqdm_dict['v_num'] = self.logger.version
 
         tqdm_dict.update(self.tqdm_metrics)
 

pytorch_lightning/trainer/training_loop.py

@@ -151,6 +151,7 @@ When this flag is enabled each batch is split into sequences of size truncated_b
 
 import inspect
 from abc import ABC, abstractmethod
+import warnings
 
 import numpy as np
 
@@ -169,22 +170,22 @@ class TrainerTrainLoopMixin(ABC):
     def __init__(self):
         # this is just a summary on variables used in this abstract class,
         #  the proper values/initialisation should be done in child class
-        self.max_nb_epochs = None
+        self.max_epochs = None
+        self.min_epochs = None
         self.use_ddp = None
         self.use_dp = None
         self.use_ddp2 = None
         self.single_gpu = None
         self.data_parallel_device_ids = None
         self.check_val_every_n_epoch = None
-        self.nb_training_batches = None
+        self.num_training_batches = None
         self.val_check_batch = None
-        self.nb_val_batches = None
+        self.num_val_batches = None
         self.fast_dev_run = None
         self.is_iterable_train_dataloader = None
         self.main_progress_bar = None
         self.accumulation_scheduler = None
         self.lr_schedulers = None
-        self.min_nb_epochs = None
         self.enable_early_stop = None
         self.early_stop_callback = None
         self.callback_metrics = None
@@ -194,7 +195,7 @@ class TrainerTrainLoopMixin(ABC):
         self.log_save_interval = None
         self.proc_rank = None
         self.row_log_interval = None
-        self.total_batch_nb = None
+        self.total_batches = None
         self.truncated_bptt_steps = None
         self.optimizers = None
         self.accumulate_grad_batches = None
@@ -207,6 +208,24 @@ class TrainerTrainLoopMixin(ABC):
         self.get_train_dataloader = None
         self.reduce_lr_on_plateau_scheduler = None
 
+    @property
+    def max_nb_epochs(self):
+        """
+        .. warning:: `max_nb_epochs` is deprecated and will be removed in v0.8.0, use `max_epochs` instead.
+        """
+        warnings.warn("`max_nb_epochs` is deprecated and will be removed in "
+                      "v0.8.0, use `max_epochs` instead.", DeprecationWarning)
+        return self.max_epochs
+
+    @property
+    def min_nb_epochs(self):
+        """
+        .. warning:: `min_nb_epochs` is deprecated and will be removed in v0.8.0, use `min_epochs` instead.
+        """
+        warnings.warn("`min_nb_epochs` is deprecated and will be removed in "
+                      "v0.8.0, use `min_epochs` instead.", DeprecationWarning)
+        return self.min_epochs
+
     @abstractmethod
     def get_model(self):
         # this is just empty shell for code from other class
@@ -391,7 +410,7 @@ class TrainerTrainLoopMixin(ABC):
             if early_stop_epoch or self.fast_dev_run:
                 break
 
-            # stop epoch if we limited nb batches
+            # stop epoch if we limited the number of training batches
             met_batch_limit = batch_idx >= self.num_training_batches
             if met_batch_limit:
                 break