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Searched
refs:NUM_CLASSES
(Results
1 - 8
of
8
) sorted by null
/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')
[
all
...]
/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
]),
Completed in 306 milliseconds