Author: dligach Date: Wed Sep 21 19:21:06 2016 New Revision: 1761798 URL: http://svn.apache.org/viewvc?rev=1761798&view=rev Log: minor cosmetic fixes
Modified: ctakes/trunk/ctakes-temporal/scripts/nn/predict.py ctakes/trunk/ctakes-temporal/scripts/nn/train_and_package.py Modified: ctakes/trunk/ctakes-temporal/scripts/nn/predict.py URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-temporal/scripts/nn/predict.py?rev=1761798&r1=1761797&r2=1761798&view=diff ============================================================================== --- ctakes/trunk/ctakes-temporal/scripts/nn/predict.py (original) +++ ctakes/trunk/ctakes-temporal/scripts/nn/predict.py Wed Sep 21 19:21:06 2016 @@ -34,22 +34,22 @@ def main(args): feats=[] for unigram in line.rstrip().split(): - if(word2int.has_key(unigram)): + if(unigram in word2int): feats.append(word2int[unigram]) else: - feats.append(word2int["none"]) + feats.append(word2int['oov_word']) - if(len(feats) > maxlen): + if len(feats) > maxlen: feats=feats[0:maxlen] test_x = pad_sequences([feats], maxlen=maxlen) - X_dup = [] - X_dup.append(test_x) - X_dup.append(test_x) - X_dup.append(test_x) - X_dup.append(test_x) + test_xs = [] + test_xs.append(test_x) + test_xs.append(test_x) + test_xs.append(test_x) + test_xs.append(test_x) - out = model.predict(X_dup, batch_size=50)[0] + out = model.predict(test_xs, batch_size=50)[0] except KeyboardInterrupt: sys.stderr.write("Caught keyboard interrupt\n") @@ -60,7 +60,7 @@ def main(args): break out_str = int2label[out.argmax()] - print(out_str) + print out_str sys.stdout.flush() sys.exit(0) Modified: ctakes/trunk/ctakes-temporal/scripts/nn/train_and_package.py URL: http://svn.apache.org/viewvc/ctakes/trunk/ctakes-temporal/scripts/nn/train_and_package.py?rev=1761798&r1=1761797&r2=1761798&view=diff ============================================================================== --- ctakes/trunk/ctakes-temporal/scripts/nn/train_and_package.py (original) +++ ctakes/trunk/ctakes-temporal/scripts/nn/train_and_package.py Wed Sep 21 19:21:06 2016 @@ -32,8 +32,7 @@ def main(args): train_x, train_y = provider.load(data_file) # turn x and y into numpy array among other things maxlen = max([len(seq) for seq in train_x]) - outcomes = set(train_y) - classes = len(outcomes) + classes = len(set(train_y)) train_x = pad_sequences(train_x, maxlen=maxlen) train_y = to_categorical(np.array(train_y), classes) @@ -49,7 +48,6 @@ def main(args): train_xs = [] # train x for each branch for filter_len in '2,3,4,5'.split(','): - branch = Sequential() branch.add(Embedding(len(provider.word2int), 300, @@ -77,8 +75,7 @@ def main(args): model.add(Dense(classes)) model.add(Activation('softmax')) - optimizer = RMSprop(lr=0.0001, - rho=0.9, epsilon=1e-08) + optimizer = RMSprop(lr=0.0001, rho=0.9, epsilon=1e-08) model.compile(loss='categorical_crossentropy', optimizer=optimizer, metrics=['accuracy']) @@ -87,8 +84,7 @@ def main(args): nb_epoch=3, batch_size=50, verbose=1, - validation_split=0.1, - class_weight=None) + validation_split=0.1) json_string = model.to_json() open(os.path.join(working_dir, 'model_0.json'), 'w').write(json_string)