def test_default_input_fn_csv_bad_columns():
str_io = StringIO()
csv_writer = csv.writer(str_io, delimiter=',')
csv_writer.writerow([1, 2, 3])
csv_writer.writerow([1, 2, 3, 4])
with pytest.raises(ValueError):
default_input_fn(str_io.getvalue(), content_types.CSV)
def test_default_input_fn_npy(tensor):
stream = BytesIO()
np.save(stream, tensor.cpu().numpy())
deserialized_np_array = default_input_fn(stream.getvalue(), content_types.NPY)
assert deserialized_np_array.is_cuda == torch.cuda.is_available()
assert torch.equal(tensor, deserialized_np_array)
def test_default_input_fn_csv():
array = [[1, 2, 3], [4, 5, 6]]
str_io = StringIO()
csv.writer(str_io, delimiter=',').writerows(array)
deserialized_np_array = default_input_fn(str_io.getvalue(), content_types.CSV)
tensor = torch.FloatTensor(array).to(device)
assert torch.equal(tensor, deserialized_np_array)
assert deserialized_np_array.is_cuda == torch.cuda.is_available()
def test_default_input_fn_bad_content_type():
with pytest.raises(encoders.UnsupportedFormatError):
default_input_fn('', 'application/not_supported')
def test_default_input_fn_json(tensor):
json_data = json.dumps(tensor.cpu().numpy().tolist())
deserialized_np_array = default_input_fn(json_data, content_types.JSON)
assert deserialized_np_array.is_cuda == torch.cuda.is_available()
assert torch.equal(tensor, deserialized_np_array)
