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jacobbieker · Feb 10, 2019 · 13985d4 · 13985d4
1 parent 9b4a7fa
commit 13985d4
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Showing 2 changed files with 13 additions and 13 deletions.
diff --git a/examples/talos_3d_classification.py b/examples/talos_3d_classification.py
@@ -29,10 +29,10 @@
 
           'neuron_1': [8, 16, 64],
           'kernel_1': [1, 3, 5],
-          'stride_1': [1, 2, 3],
+          'stride_1': [1, 2],
           'layer_drop': [0.0, 0.8, 4],
           'layers': [2,3,4],
-          'pool': [0,1]
+          'pool': [0]
 
           }
 '''
@@ -124,8 +124,7 @@ def input_model(x_train, y_train, x_val, y_val, params):
 
 x, y = get_chunk_of_data(directory=gamma_dir, proton_directory=proton_dir, indicies=(30, 129, 10), rebin=100,
                          chunk_size=args['size'], as_channels=True)
-
-x = x.reshape(100,100,10,1)
+x = x.reshape(-1, 100,100,10,1)
 
 print("Got data")
 print("X Shape", x.shape)

diff --git a/examples/talos_time_classification.py b/examples/talos_time_classification.py
@@ -16,9 +16,9 @@
 
 params = {'lr': (1, 10, 10),
           'first_neuron': [4, 16, 32],
-          'last_neuron': [4, 8, 16],
-          'hidden_layers': [2, 3, 4],
-          'batch_size': [2, 8, 32],
+          'last_neuron': [4, 16],
+          'hidden_layers': [2, 4],
+          'batch_size': [2, 8],
           'epochs': [500],
           'dropout': (0, 0.80, 4),
           'weight_regulizer': [None],
@@ -33,11 +33,12 @@
           'rec_dropout': [0.0, 0.8, 4],
           'rec_act': [hard_sigmoid, tanh],
           'layer_drop': [0.0, 0.8, 4],
-          'layers': [1,2,3,4]
+          'layers': [2,3,4],
+          'pool': [0, 1],
 
           }
 '''
-'pool': [0, 1],
+
 'neuron_2': [4, 8, 16, 32, 64],
 'kernel_2': [1, 2, 3],
 'stride_2': [1, 2],
@@ -68,8 +69,8 @@ def input_model(x_train, y_train, x_val, y_val, params):
                              recurrent_activation=params['rec_act'],
                              return_sequences=True,
                              stateful=False))
-        if params['pool']:
-            model.add(MaxPooling3D())
+        #if params['pool']:
+        #    model.add(MaxPooling3D())
 
     if params['layers'] >= 3:
         model.add(ConvLSTM2D(params['neuron_1'], kernel_size=params['kernel_1'], strides=params['stride_1'],
@@ -89,8 +90,8 @@ def input_model(x_train, y_train, x_val, y_val, params):
                              recurrent_activation=params['rec_act'],
                              return_sequences=True,
                              stateful=False))
-        if params['pool']:
-            model.add(MaxPooling3D())
+        #if params['pool']:
+        #    model.add(MaxPooling3D())
 
     '''
     if params['pool']: