problem_unittests.py 文件源码

def test_generator(generator, tf_module):
    with TmpMock(tf_module, 'variable_scope') as mock_variable_scope:
        z = tf.placeholder(tf.float32, [None, 100])
        out_channel_dim = 5

        output = generator(z, out_channel_dim)
        _assert_tensor_shape(output, [None, 28, 28, out_channel_dim], 'Generator output (is_train=True)')
        assert mock_variable_scope.called, \
            'tf.variable_scope not called in Generator Training(reuse=false)'
        assert mock_variable_scope.call_args == mock.call('generator', reuse=False), \
            'tf.variable_scope called with wrong arguments in Generator Training(reuse=false)'

        mock_variable_scope.reset_mock()
        output = generator(z, out_channel_dim, False)
        _assert_tensor_shape(output, [None, 28, 28, out_channel_dim], 'Generator output (is_train=False)')
        assert mock_variable_scope.called, \
            'tf.variable_scope not called in Generator Inference(reuse=True)'
        assert mock_variable_scope.call_args == mock.call('generator', reuse=True), \
            'tf.variable_scope called with wrong arguments in Generator Inference(reuse=True)'