19feb08bf8b7c9ab8b2cf2c4d5ec74541b84b103,autokeras/generator.py,RandomConvClassifierGenerator,_get_shape,#RandomConvClassifierGenerator#Any#,33

Before Change

        raise ValueError("The input dimension is too high.")

    def _get_shape(self, dim_size):
        if len(self.input_shape) == 1:
            return dim_size,
        elif len(self.input_shape) == 2:
            return dim_size, dim_size
        elif len(self.input_shape) == 3:
            return dim_size, dim_size, dim_size
        raise ValueError("The input dimension is too high.")

    def generate(self):
        conv_num = randint(1, 10)
        dense_num = randint(1, 10)

After Change

        return pool_funcs[len(self.input_shape) - 2]

    def _get_shape(self, dim_size):
        temp_list = [(dim_size,), (dim_size, dim_size), (dim_size, dim_size, dim_size)]
        return temp_list[len(self.input_shape) - 2]

    def generate(self):
        conv_num = randint(1, 10)
        dense_num = randint(1, 10)

Instances