message: More linter fixings.
diff: # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  +"""This file contains an implementation of dual_net.py for Google's EdgeTPU. It can only be used for inference and requires a specially quantized and compiled model file.
  -"""
  -This file contains an implementation of dual_net.py for Google's EdgeTPU.
  -It can only be used for inference and requires a specially quantized and
  -compiled model file. For more information see https://coral.withgoogle.com
  +For more information see https://coral.withgoogle.com
  """
  import numpy as np
  import features as features_lib
  import go
  -from edgetpu.basic.basic_engine import BasicEngine
  +from edgetpu.basic.basic_engine import BasicEngine # pylint: disable=import-error
  +
  class DualNetworkEdgeTpu():
  +
  def __init__(self, save_file):
  self.engine = BasicEngine(save_file)
  self.board_size = go.N
  @@ -37,7 +37,8 @@ class DualNetworkEdgeTpu():
  input_tensor_shape, expected_input_shape))
  output_tensors_sizes = self.engine.get_all_output_tensors_sizes()
  expected_output_tensor_sizes = [self.output_policy_size, 1]
  - if not np.array_equal(output_tensors_sizes, expected_output_tensor_sizes):
  + if not np.array_equal(output_tensors_sizes,
  + expected_output_tensor_sizes):
  raise RuntimeError(
  'Invalid output tensor sizes {}. Expected: {}'.format(
  output_tensors_sizes, expected_output_tensor_sizes))
  @@ -51,7 +52,8 @@ class DualNetworkEdgeTpu():
  probabilities = []
  values = []
  for state in processed:
  - assert state.shape == (self.board_size, self.board_size, 17), str(state.shape)
  + assert state.shape == (self.board_size, self.board_size,
  + 17), str(state.shape)
  result = self.engine.RunInference(state.flatten())
  # If needed you can get the raw inference time from the result object.
  # inference_time = result[0] # ms
  