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  /external/tensorflow/tensorflow/python/keras/_impl/keras/
regularizers_test.py 27 NUM_CLASSES = 2
35 num_classes=NUM_CLASSES)
36 y_train = keras.utils.to_categorical(y_train, NUM_CLASSES)
37 y_test = keras.utils.to_categorical(y_test, NUM_CLASSES)
43 model.add(keras.layers.Dense(NUM_CLASSES,
callbacks_test.py 48 NUM_CLASSES = 2
71 num_classes=NUM_CLASSES)
83 model.add(keras.layers.Dense(NUM_CLASSES, activation='softmax'))
229 num_classes=NUM_CLASSES)
236 model.add(keras.layers.Dense(NUM_CLASSES, activation='softmax'))
301 num_classes=NUM_CLASSES)
308 model.add(keras.layers.Dense(NUM_CLASSES, activation='softmax')
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  /external/tensorflow/tensorflow/examples/android/src/org/tensorflow/demo/
TensorFlowYoloDetector.java 37 private static final int NUM_CLASSES = 20;
171 new float[gridWidth * gridHeight * (NUM_CLASSES + 5) * NUM_BOXES_PER_BLOCK];
191 (gridWidth * (NUM_BOXES_PER_BLOCK * (NUM_CLASSES + 5))) * y
192 + (NUM_BOXES_PER_BLOCK * (NUM_CLASSES + 5)) * x
193 + (NUM_CLASSES + 5) * b;
212 final float[] classes = new float[NUM_CLASSES];
213 for (int c = 0; c < NUM_CLASSES; ++c) {
218 for (int c = 0; c < NUM_CLASSES; ++c) {
  /external/tensorflow/tensorflow/examples/tutorials/mnist/
mnist.py 38 NUM_CLASSES = 10
77 tf.truncated_normal([hidden2_units, NUM_CLASSES],
80 biases = tf.Variable(tf.zeros([NUM_CLASSES]),
90 logits: Logits tensor, float - [batch_size, NUM_CLASSES].
133 logits: Logits tensor, float - [batch_size, NUM_CLASSES].
135 range [0, NUM_CLASSES).
  /external/tensorflow/tensorflow/python/keras/_impl/keras/wrappers/
scikit_learn_test.py 31 NUM_CLASSES = 2
42 model.add(keras.layers.Dense(NUM_CLASSES))
55 num_classes=NUM_CLASSES)
65 assert prediction in range(NUM_CLASSES)
68 assert proba.shape == (TEST_SAMPLES, NUM_CLASSES)
91 num_classes=NUM_CLASSES)
  /external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/
cifar10_pruning.py 50 NUM_CLASSES = cifar10_input.NUM_CLASSES
261 'weights', [192, NUM_CLASSES], stddev=1 / 192.0, wd=0.0)
262 biases = _variable_on_cpu('biases', [NUM_CLASSES],
cifar10_input.py 32 NUM_CLASSES = 10
  /external/tensorflow/tensorflow/contrib/factorization/examples/
mnist.py 45 NUM_CLASSES = 10
174 tf.truncated_normal([hidden2_units, NUM_CLASSES],
177 biases = tf.Variable(tf.zeros([NUM_CLASSES]),

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