Shut up coreml version incompatibility warnings

We don't use any of the functionality they pertain to

kraken/lib/layers.py

@@ -10,11 +10,11 @@
 from torch.nn import functional as F
 from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
 
-logger = logging.getLogger('coremltools')
-logger.setLevel(logging.ERROR)
+root_logger = logging.getLogger()
+level = root_logger.getEffectiveLevel()
+root_logger.setLevel(logging.ERROR)
 from coremltools.proto import NeuralNetwork_pb2  # NOQA
-
-logger.setLevel(logging.WARNING)
+root_logger.setLevel(level)
 
 # all tensors are ordered NCHW, the "feature" dimension is C, so the output of
 # an LSTM will be put into C same as the filters of a CNN.

kraken/lib/vgsl.py

@@ -9,15 +9,20 @@
                     Tuple, Union)
 
 import torch
-from coremltools.models import MLModel, datatypes
-from coremltools.models.neural_network import NeuralNetworkBuilder
 from google.protobuf.message import DecodeError
 from torch import nn
 
 from kraken.lib import layers
 from kraken.lib.codec import PytorchCodec
 from kraken.lib.exceptions import KrakenInvalidModelException
 
+root_logger = logging.getLogger()
+level = root_logger.getEffectiveLevel()
+root_logger.setLevel(logging.ERROR)
+from coremltools.models import MLModel, datatypes
+from coremltools.models.neural_network import NeuralNetworkBuilder
+root_logger.setLevel(level)
+
 # all tensors are ordered NCHW, the "feature" dimension is C, so the output of
 # an LSTM will be put into C same as the filters of a CNN.