def test_padding_converter(self):
input_dim = (1, 3, 4)
output_dim = (1, 5, 6)
input = [('input', datatypes.Array(*input_dim))]
output = [('output', datatypes.Array(*output_dim))]
builder = NeuralNetworkBuilder(input, output)
builder.add_padding(name='Pad', left=2, right=0, top=2, bottom=0, input_name='input', output_name='output',
padding_type='constant')
model_onnx = convert_coreml(builder.spec)
self.assertTrue(model_onnx is not None)
def test_padding_converter(self):
input_dim = (1, 3, 4)
output_dim = (1, 5, 6)
input = [('input', datatypes.Array(*input_dim))]
output = [('output', datatypes.Array(*output_dim))]
builder = NeuralNetworkBuilder(input, output)
builder.add_padding(name='Pad',
left=2,
right=0,
top=2,
bottom=0,
input_name='input',
output_name='output',
padding_type='constant')
context = ConvertContext()
node = PaddingLayerConverter.convert(
context, builder.spec.neuralNetwork.layers[0], ['input'],
['output'])
self.assertTrue(node is not None)
