test_keras2_numeric.py 文件源码

 复制代码def test_tiny_conv_dense_random(self):
        np.random.seed(1988)
        num_samples = 1
        input_dim = 8
        input_shape = (input_dim, input_dim, 3)
        num_kernels = 2
        kernel_height = 5
        kernel_width = 5
        hidden_dim = 4

        # Define a model
        model = Sequential()
        model.add(Conv2D(input_shape = input_shape,
            filters = num_kernels, kernel_size=(kernel_height, kernel_width)))
        model.add(Dropout(0.5))
        model.add(Flatten())
        model.add(Dense(hidden_dim))

        # Set some random weights
        model.set_weights([np.random.rand(*w.shape) for w in model.get_weights()])

        # Get the coreml model
        self._test_keras_model(model)