test_keras2_numeric.py 文件源码

def test_tiny_deconv_random(self):
        # In Keras 2, deconvolution auto computes the output shape.
        np.random.seed(1988)
        input_dim = 13
        input_shape = (input_dim, input_dim, 5)
        num_kernels = 16
        kernel_height = 3
        kernel_width = 3

        # Define a model
        model = Sequential()
        model.add(Conv2DTranspose(filters = num_kernels, kernel_size=(kernel_height, kernel_width), 
            input_shape = input_shape, padding = 'valid', strides = (2,2)))

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

        # Test the keras model
        self._test_keras_model(model)