Delete single-GPU Keras runner; comment out hyperopt driver for it

felker · felker · commit b11d7596526d · 2019-12-07T17:10:49.000-05:00
diff --git a/examples/hyper_learn.py b/examples/hyper_learn.py
@@ -1,47 +1,48 @@
-from plasma.models import runner
-from plasma.models.loader import Loader
-
-import numpy as np
-from hyperopt import Trials, tpe
-
-from plasma.conf import conf
-from pprint import pprint
-pprint(conf)
-# from plasma.primitives.shots import Shot, ShotList
-# from plasma.models.runner import train, make_predictions,make_predictions_gpu
-
-if conf['data']['normalizer'] == 'minmax':
-    from plasma.preprocessor.normalize import MinMaxNormalizer as Normalizer
-elif conf['data']['normalizer'] == 'meanvar':
-    from plasma.preprocessor.normalize import MeanVarNormalizer as Normalizer
-elif conf['data']['normalizer'] == 'var':
-    # performs !much better than minmaxnormalizer
-    from plasma.preprocessor.normalize import VarNormalizer as Normalizer
-elif conf['data']['normalizer'] == 'averagevar':
-    # performs !much better than minmaxnormalizer
-    from plasma.preprocessor.normalize import (
-        AveragingVarNormalizer as Normalizer
-    )
-else:
-    print('unkown normalizer. exiting')
-    exit(1)
-
-np.random.seed(1)
-
-print("normalization", end='')
-nn = Normalizer(conf)
-nn.train()
-loader = Loader(conf, nn)
-shot_list_train, shot_list_validate, shot_list_test = loader.load_shotlists(
-    conf)
-print("...done")
-
-print('Training on {} shots, testing on {} shots'.format(
-    len(shot_list_train), len(shot_list_test)))
-
-specific_runner = runner.HyperRunner(conf, loader, shot_list_train)
-
-best_run, best_model = specific_runner.frnn_minimize(
-    algo=tpe.suggest, max_evals=2, trials=Trials())
-print(best_run)
-print(best_model)
+# from plasma.models import runner
+# from plasma.models.loader import Loader
+
+# import numpy as np
+# from hyperopt import Trials, tpe
+
+# from plasma.conf import conf
+# from pprint import pprint
+# pprint(conf)
+#  #from plasma.primitives.shots import Shot, ShotList
+#  #from plasma.models.runner import train, make_predictions
+#  ,make_predictions_gpu
+
+# if conf['data']['normalizer'] == 'minmax':
+#     from plasma.preprocessor.normalize import MinMaxNormalizer as Normalizer
+# elif conf['data']['normalizer'] == 'meanvar':
+#     from plasma.preprocessor.normalize import MeanVarNormalizer as Normalizer
+# elif conf['data']['normalizer'] == 'var':
+#     # performs !much better than minmaxnormalizer
+#     from plasma.preprocessor.normalize import VarNormalizer as Normalizer
+# elif conf['data']['normalizer'] == 'averagevar':
+#     # performs !much better than minmaxnormalizer
+#     from plasma.preprocessor.normalize import (
+#         AveragingVarNormalizer as Normalizer
+#     )
+# else:
+#     print('unkown normalizer. exiting')
+#     exit(1)
+
+# np.random.seed(1)
+
+# print("normalization", end='')
+# nn = Normalizer(conf)
+# nn.train()
+# loader = Loader(conf, nn)
+# shot_list_train, shot_list_validate, shot_list_test = loader.load_shotlists(
+#     conf)
+# print("...done")
+
+# print('Training on {} shots, testing on {} shots'.format(
+#     len(shot_list_train), len(shot_list_test)))
+
+# specific_runner = runner.HyperRunner(conf, loader, shot_list_train)
+
+# best_run, best_model = specific_runner.frnn_minimize(
+#     algo=tpe.suggest, max_evals=2, trials=Trials())
+# print(best_run)
+# print(best_model)
diff --git a/examples/learn.py b/examples/learn.py
@@ -39,7 +39,9 @@
         train, make_predictions_and_evaluate_gpu
         )
 else:
-    from plasma.models.runner import train, make_predictions_and_evaluate_gpu
+    print('unknown driver. exiting')
+    exit(1)
+    # from plasma.models.runner import train, make_predictions_and_evaluate_gpu
 
 if conf['data']['normalizer'] == 'minmax':
     from plasma.preprocessor.normalize import MinMaxNormalizer as Normalizer
diff --git a/plasma/models/runner.py b/plasma/models/runner.py
