Exemplo n.º 1
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def test_long_transform():
    graph = ResNetGenerator(10, (28, 28, 1)).generate()
    graph.to_deeper_model(16, StubReLU())
    graph.to_deeper_model(16, StubReLU())
    graph.to_add_skip_model(13, 47)
    model = graph.produce_model()
    model(torch.Tensor(np.random.random((10, 1, 28, 28))))
Exemplo n.º 2
0
def test_long_transform():
    graph = ResNetGenerator(10, (28, 28, 1)).generate()
    graph.to_deeper_model(16, StubReLU())
    graph.to_deeper_model(16, StubReLU())
    graph.to_add_skip_model(13, 47)
    model = graph.produce_model()
    model(torch.Tensor(np.random.random((10, 1, 28, 28))))
Exemplo n.º 3
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 def _init_generator(self, n_output_node, input_shape):
     return ResNetGenerator(n_output_node, input_shape)
Exemplo n.º 4
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def test_long_transform5():
    graph = ResNetGenerator(10, (28, 28, 1)).generate()
    graph.to_concat_skip_model(19, 60)
    graph.to_wider_model(52, 256)
    model = graph.produce_model()
    model(torch.Tensor(np.random.random((10, 1, 28, 28))))
Exemplo n.º 5
0
 def _init_generator(self, n_output_node, input_shape):
     alex_gui = alexnet_gui()
     var = alex_gui.var
     return ResNetGenerator(n_output_node, input_shape)
Exemplo n.º 6
0
def test_long_transform5():
    graph = ResNetGenerator(10, (28, 28, 1)).generate()
    graph.to_concat_skip_model(19, 60)
    graph.to_wider_model(52, 256)
    model = graph.produce_model()
    model(torch.Tensor(np.random.random((10, 1, 28, 28))))