| /external/tensorflow/tensorflow/examples/android/src/org/tensorflow/demo/ |
| D | TensorFlowYoloDetector.java | 37 private static final int NUM_CLASSES = 20; field in TensorFlowYoloDetector
171 new float[gridWidth * gridHeight * (NUM_CLASSES + 5) * NUM_BOXES_PER_BLOCK]; in recognizeImage()
191 (gridWidth * (NUM_BOXES_PER_BLOCK * (NUM_CLASSES + 5))) * y in recognizeImage()
192 + (NUM_BOXES_PER_BLOCK * (NUM_CLASSES + 5)) * x in recognizeImage()
193 + (NUM_CLASSES + 5) * b; in recognizeImage()
212 final float[] classes = new float[NUM_CLASSES]; in recognizeImage()
213 for (int c = 0; c < NUM_CLASSES; ++c) { in recognizeImage()
218 for (int c = 0; c < NUM_CLASSES; ++c) { in recognizeImage()
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| /external/tensorflow/tensorflow/python/keras/ |
| D | regularizers_test.py | 30 NUM_CLASSES = 2 variable
37 model.add(keras.layers.Dense(NUM_CLASSES,
48 num_classes=NUM_CLASSES)
49 y_train = keras.utils.to_categorical(y_train, NUM_CLASSES)
50 y_test = keras.utils.to_categorical(y_test, NUM_CLASSES)
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| D | callbacks_v1_test.py | 38 NUM_CLASSES = 2 variable
57 num_classes=NUM_CLASSES)
85 model.add(keras.layers.Dense(NUM_CLASSES, activation='softmax'))
166 num_classes=NUM_CLASSES)
192 output1 = keras.layers.Dense(NUM_CLASSES, activation='softmax')(hidden)
193 output2 = keras.layers.Dense(NUM_CLASSES, activation='softmax')(hidden)
270 num_classes=NUM_CLASSES)
281 model.add(keras.layers.Dense(NUM_CLASSES, activation='softmax'))
366 num_classes=NUM_CLASSES)
371 num_hidden=NUM_HIDDEN, num_classes=NUM_CLASSES, input_dim=INPUT_DIM)
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| D | callbacks_test.py | 57 NUM_CLASSES = 2 variable
273 keras.layers.Dense(NUM_CLASSES, activation='softmax')
287 num_classes=NUM_CLASSES)
299 model.add(keras.layers.Dense(NUM_CLASSES, activation='softmax'))
443 num_classes=NUM_CLASSES)
447 num_hidden=NUM_HIDDEN, num_classes=NUM_CLASSES, input_dim=INPUT_DIM)
503 num_classes=NUM_CLASSES)
572 num_classes=NUM_CLASSES)
576 num_hidden=NUM_HIDDEN, num_classes=NUM_CLASSES, input_dim=INPUT_DIM)
619 num_classes=NUM_CLASSES)
[all …]
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| /external/tensorflow/tensorflow/python/keras/wrappers/ |
| D | scikit_learn_test.py | 31 NUM_CLASSES = 2 variable
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)
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| /external/tensorflow/tensorflow/contrib/distribute/python/examples/ |
| D | keras_mnist.py | 27 NUM_CLASSES = 10 variable
62 y_train = tf.keras.utils.to_categorical(y_train, NUM_CLASSES)
63 y_test = tf.keras.utils.to_categorical(y_test, NUM_CLASSES)
101 model.add(tf.keras.layers.Dense(NUM_CLASSES, activation='softmax'))
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| /external/tensorflow/tensorflow/examples/tutorials/mnist/ |
| D | mnist.py | 38 NUM_CLASSES = 10 variable
77 tf.truncated_normal([hidden2_units, NUM_CLASSES],
80 biases = tf.Variable(tf.zeros([NUM_CLASSES]),
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| /external/tensorflow/tensorflow/examples/saved_model/integration_tests/ |
| D | mnist_util.py | 25 NUM_CLASSES = 10 variable
49 return tf.keras.utils.to_categorical(y, NUM_CLASSES)
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| D | use_mnist_cnn.py | 68 net = tf.keras.layers.Dense(mnist_util.NUM_CLASSES, activation='softmax',
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| D | export_mnist_cnn.py | 77 net = tf.keras.layers.Dense(mnist_util.NUM_CLASSES, activation='softmax',
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| /external/tensorflow/tensorflow/contrib/model_pruning/examples/cifar10/ |
| D | cifar10_pruning.py | 50 NUM_CLASSES = cifar10_input.NUM_CLASSES variable
261 'weights', [192, NUM_CLASSES], stddev=1 / 192.0, wd=0.0)
262 biases = _variable_on_cpu('biases', [NUM_CLASSES],
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| D | cifar10_input.py | 32 NUM_CLASSES = 10 variable
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| /external/tensorflow/tensorflow/contrib/factorization/examples/ |
| D | mnist.py | 45 NUM_CLASSES = 10 variable
174 tf.truncated_normal([hidden2_units, NUM_CLASSES],
177 biases = tf.Variable(tf.zeros([NUM_CLASSES]),
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| /external/tensorflow/tensorflow/compiler/xla/g3doc/tutorials/ |
| D | xla_compile.ipynb | 130 "NUM_CLASSES = 10\n",
183 " y = tf.keras.layers.Dense(NUM_CLASSES).apply(x)\n",
|