Use realistic hyperparameter values

benchmarks/roman_pots/Snakefile

@@ -6,30 +6,30 @@ DETECTOR_VERSION = os.environ["DETECTOR_VERSION"]
 SUBSYSTEM = "roman_pots"
 BENCHMARK = "dense_neural_network"
 DETECTOR_CONFIG = ["epic_ip6"]
-NUM_TRAINING_INPUTS = [100,10]
-NUM_EPOCHS_PZ = [10, 100, 1000]
-LEARNING_RATE_PZ = [10,5]
-SIZE_INPUT_PZ = [10,4]
-SIZE_OUTPUT_PZ = [10,3]
-N_LAYERS_PZ = [10,2]
-SIZE_FIRST_HIDDEN_LAYER_PZ = [10]
-MULTIPLIER_PZ = [10]
+NUM_TRAINING_INPUTS = [10,100]
+NUM_EPOCHS_PZ = [1000,10000]
+LEARNING_RATE_PZ = [0.01]
+SIZE_INPUT_PZ = [4]
+SIZE_OUTPUT_PZ = [1]
+N_LAYERS_PZ = [3,6]
+SIZE_FIRST_HIDDEN_LAYER_PZ = [128]
+MULTIPLIER_PZ = [0.5]
 LEAK_RATE_PZ = [0.025]
-NUM_EPOCHS_PY = [10, 100, 1000]
-LEARNING_RATE_PY = [10]
-SIZE_INPUT_PY = [10]
-SIZE_OUTPUT_PY = [10]
-N_LAYERS_PY = [10]
-SIZE_FIRST_HIDDEN_LAYER_PY = [10]
-MULTIPLIER_PY = [10]
+NUM_EPOCHS_PY = [1000,10000]
+LEARNING_RATE_PY = [0.01]
+SIZE_INPUT_PY = [3]
+SIZE_OUTPUT_PY = [1]
+N_LAYERS_PY = [3,6]
+SIZE_FIRST_HIDDEN_LAYER_PY = [128]
+MULTIPLIER_PY = [0.5]
 LEAK_RATE_PY = [0.025]
-NUM_EPOCHS_PX = [10, 100, 1000]
-LEARNING_RATE_PX = [10]
-SIZE_INPUT_PX = [10]
-SIZE_OUTPUT_PX = [10]
-N_LAYERS_PX = [10]
-SIZE_FIRST_HIDDEN_LAYER_PX = [10]
-MULTIPLIER_PX = [10]
+NUM_EPOCHS_PX = [1000,10000]
+LEARNING_RATE_PX = [0.01]
+SIZE_INPUT_PX = [3]
+SIZE_OUTPUT_PX = [1]
+N_LAYERS_PX = [3,7]
+SIZE_FIRST_HIDDEN_LAYER_PX = [128]
+MULTIPLIER_PX = [0.5]
 LEAK_RATE_PX = [0.025]
 MAX_HASH = 6
 MODEL_VERSION = [