Merge pull request #133 from justusschock/predictor_caching_patch

Fix predictor caching behavior
delira-dev · Jun 12, 2019 · 4e9643b · 4e9643b
2 parents 9d25a68 + d60e964
commit 4e9643b
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Showing 3 changed files with 9 additions and 8 deletions.
diff --git a/delira/training/base_trainer.py b/delira/training/base_trainer.py
@@ -303,7 +303,7 @@ def _train_single_epoch(self, batchgen: Augmenter, epoch,
                 unit=' batch',
                 total=n_batches,
                 desc='Epoch %d' %
-                epoch)
+                     epoch)
         else:
             iterable = enumerate(batchgen)
 
@@ -438,10 +438,11 @@ def reduce_fn(batch):
                 # next must be called here because self.predict_data_mgr
                 # returns a generator (of size 1) and we want to get the first
                 # (and only) item
-                val_predictions, val_metrics = next(self.predict_data_mgr(
-                    datamgr_valid, datamgr_valid.batch_size,
-                    metrics=val_metric_fns, metric_keys=val_metric_keys,
-                    verbose=verbose, lazy_gen=False))
+                val_metrics = next(
+                    self.predict_data_mgr_cache_metrics_only(
+                        datamgr_valid, datamgr_valid.batch_size,
+                        metrics=val_metric_fns, metric_keys=val_metric_keys,
+                        verbose=verbose))
 
                 total_metrics.update(val_metrics)
 

diff --git a/delira/training/experiment.py b/delira/training/experiment.py
@@ -395,9 +395,8 @@ def test(self, network, test_data: BaseDataManager,
                                prepare_batch_fn=prepare_batch, **kwargs)
 
         # return first item of generator
-        return next(predictor.predict_data_mgr(test_data, 1, metrics,
-                                               metric_keys, verbose,
-                                               lazy_gen=False))
+        return next(predictor.predict_data_mgr_cache_all(test_data, 1, metrics,
+                                                         metric_keys, verbose))
 
     def kfold(self, data: BaseDataManager, metrics: dict, num_epochs=None,
               num_splits=None, shuffle=False, random_seed=None,

diff --git a/delira/training/predictor.py b/delira/training/predictor.py
@@ -183,6 +183,7 @@ def predict_data_mgr(self, datamgr, batchsize=None, metrics={},
 
         n_batches = batchgen.num_batches
 
+
         if verbose:
             iterable = tqdm(enumerate(batchgen), unit=' sample',
                             total=n_batches, desc=self._tqdm_desc)