Moved some things

workbench.py

@@ -0,0 +1,72 @@
+
+# coding: utf-8
+
+# In[1]:
+
+
+# -*- coding: utf-8 -*-
+from __future__ import unicode_literals
+# text in Western (Windows 1252)
+
+import numpy as np
+# import StringIO
+import math
+from keras.models import Sequential
+from keras.layers import Dense, Dropout, Merge
+from keras.layers.merge import concatenate
+from keras import regularizers
+from keras.layers.convolutional import Conv1D
+from keras.layers.convolutional import MaxPooling1D
+from keras.constraints import maxnorm
+from keras.layers import Flatten
+from keras.optimizers import SGD
+from keras.models import load_model
+np.random.seed(7)
+
+# get_ipython().magic('run ../../../prepare_data.py')
+
+# import sys
+# # sys.path.insert(0, '../../../')
+# sys.path.insert(0, '/home/luka/Developement/accetuation/')
+from prepare_data import *
+
+
+# X_train, X_other_features_train, y_train, X_validate, X_other_features_validate, y_validate = generate_full_matrix_inputs()
+# save_inputs('../../internal_representations/inputs/shuffeled_matrix_train_inputs_other_features_output_11.h5', X_train, y_train, other_features = X_other_features_train)
+# save_inputs('../../internal_representations/inputs/shuffeled_matrix_validate_inputs_other_features_output_11.h5', X_validate, y_validate,  other_features = X_other_features_validate)
+X_train, X_other_features_train, y_train = load_inputs('cnn/internal_representations/inputs/shuffeled_matrix_train_inputs_other_features_output_11.h5', other_features=True)
+X_validate, X_other_features_validate, y_validate = load_inputs('cnn/internal_representations/inputs/shuffeled_matrix_validate_inputs_other_features_output_11.h5', other_features=True)
+
+num_examples = len(X_train)  # training set size
+nn_output_dim = 11
+nn_hdim = 516
+
+word_processor = Sequential()
+word_processor.add(Conv1D(43, (3), input_shape=(23, 43), padding='same', activation='relu'))
+word_processor.add(Conv1D(43, (3), padding='same', activation='relu'))
+word_processor.add(MaxPooling1D(pool_size=2))
+word_processor.add(Flatten())
+word_processor.add(Dense(516, activation='relu', kernel_constraint=maxnorm(3)))
+
+metadata_processor = Sequential()
+metadata_processor.add(Dense(256, input_dim=167, activation='relu'))
+
+model = Sequential()
+model.add(Merge([word_processor, metadata_processor], mode='concat'))  # Merge is your sensor fusion buddy
+model.add(Dense(1024, input_dim=(516 + 256), activation='relu'))
+model.add(Dropout(0.3))
+model.add(Dense(1024, input_dim=(516 + 256), activation='relu'))
+model.add(Dropout(0.2))
+model.add(Dense(nn_output_dim, activation='sigmoid'))
+
+
+# In[10]:
+
+
+# epochs = 5
+# lrate = 0.1
+# decay = lrate/epochs
+# sgd = SGD(lr=lrate, momentum=0.9, decay=decay, nesterov=False)
+model.compile(loss='mean_squared_error', optimizer='adam', metrics=['accuracy'])
+model.fit([X_train, X_other_features_train], y_train, validation_data=([X_validate, X_other_features_validate], y_validate), epochs=10, batch_size=10)
+model.save('v1_1.h5')