def test_shapes(self):
input_size = 20
n_classes = 5
layer_sizes = [5, 10]
network = network_dense.FullyConnectedClassifier(input_size=input_size,
n_classes=n_classes,
layer_sizes=layer_sizes,
model_path='temp',
verbose=False)
self.assertEqual(network.logits.get_shape().as_list(), [None, 5])
self.assertEqual(network.loss.get_shape().as_list(), [])
self.assertIsInstance(network.train_op, tf.Operation)
shapes = [[20, 5], [5, 10], [10, 5]]
for v, shape in zip(network.weight_matrices, shapes):
self.assertEqual(v.get_shape().as_list(), shape)
test_network_dense.py 文件源码
python
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