def test_reorganize_data_converter(self):
block_size = 2
input_dim = (3, 4 * block_size, 2 * block_size)
output_dim = (3 * block_size * block_size, 4, 2)
inputs = [('input', datatypes.Array(*input_dim))]
outputs = [('output', datatypes.Array(*output_dim))]
builder = NeuralNetworkBuilder(inputs, outputs)
builder.add_reorganize_data(name='Reorg', input_name='input', output_name='output', mode='SPACE_TO_DEPTH',
block_size=2)
model_onnx = convert_coreml(builder.spec)
self.assertTrue(model_onnx is not None)
def test_reorganize_data_converter(self):
block_size = 2
input_dim = (3, 4 * block_size, 2 * block_size)
output_dim = (3 * block_size * block_size, 4, 2)
inputs = [('input', datatypes.Array(*input_dim))]
outputs = [('output', datatypes.Array(*output_dim))]
builder = NeuralNetworkBuilder(inputs, outputs)
builder.add_reorganize_data(name='Reorg',
input_name='input',
output_name='output',
mode='SPACE_TO_DEPTH',
block_size=2)
context = ConvertContext()
node = ReorganizeDataLayerConverter.convert(
context, builder.spec.neuralNetwork.layers[0], ['input'],
['output'])
self.assertTrue(node is not None)
