Lines Matching refs:num_classes
41 num_classes = 1000
44 logits, end_points = inception_v2.inception_v2(inputs, num_classes)
47 [batch_size, num_classes])
50 [batch_size, num_classes])
129 num_classes = 1000
132 _, end_points = inception_v2.inception_v2(inputs, num_classes)
140 inputs, num_classes, scope='depth_multiplied_net', depth_multiplier=0.5)
150 num_classes = 1000
153 _, end_points = inception_v2.inception_v2(inputs, num_classes)
161 inputs, num_classes, scope='depth_multiplied_net', depth_multiplier=2.0)
171 num_classes = 1000
175 _ = inception_v2.inception_v2(inputs, num_classes, depth_multiplier=-0.1)
177 _ = inception_v2.inception_v2(inputs, num_classes, depth_multiplier=0.0)
182 num_classes = 1000
185 logits, end_points = inception_v2.inception_v2(inputs, num_classes)
188 [batch_size, num_classes])
197 num_classes = 1000
202 logits, end_points = inception_v2.inception_v2(inputs, num_classes)
205 [batch_size, num_classes])
215 num_classes = 1000
218 logits, _ = inception_v2.inception_v2(inputs, num_classes)
220 self.assertListEqual(logits.get_shape().as_list(), [None, num_classes])
226 self.assertEquals(output.shape, (batch_size, num_classes))
231 num_classes = 1000
235 eval_inputs, num_classes, is_training=False)
247 num_classes = 1000
251 inception_v2.inception_v2(train_inputs, num_classes)
253 logits, _ = inception_v2.inception_v2(eval_inputs, num_classes, reuse=True)
262 num_classes = 25
265 images, num_classes=num_classes, spatial_squeeze=False)
270 self.assertListEqual(list(logits_out.shape), [1, 1, 1, num_classes])
