* CI Lint fixes.

python/tvm/relay/frontend/tensorflow.py

@@ -17,13 +17,7 @@
 # pylint: disable=import-self, invalid-name, unused-argument, too-many-lines, len-as-condition, broad-except
 # pylint: disable=import-outside-toplevel, redefined-builtin
 """TF: Tensorflow frontend."""
-import warnings
-from collections import defaultdict
-
 # Numpy support
-import numpy as np
-import tvm
-
 from .tensorflow_parser import TFParser
 from .tf import tf_parser_v1 as v1
 
@@ -38,6 +32,7 @@
     "Merge",
 ]
 
+
 def from_tensorflow(tf_input, layout="NHWC", shape=None, outputs=None):
     """Load tensorflow graph which is a python tensorflow graph object into relay.
     The companion parameters will be handled automatically.

python/tvm/relay/frontend/tensorflow_parser.py

@@ -169,8 +169,8 @@ def _load_ckpt(self):
     def _build_signature_def(self, frozen_graph, input_nodes, output_nodes):
         try:
             from tensorflow.core.protobuf import meta_graph_pb2
-        except ImportError as e:
-            raise ImportError("Unable to import tensorflow which is required {}".format(e))
+        except ImportError as err:
+            raise ImportError("Unable to import tensorflow which is required {}".format(err))
         signature = meta_graph_pb2.SignatureDef()
         for input_tensor in input_nodes:
             op_name = input_tensor.name.split(":")[0]
@@ -198,18 +198,16 @@ def _build_signature_def(self, frozen_graph, input_nodes, output_nodes):
                 signature.outputs[output_tensor].name = output_tensor
         return signature
 
-
     def _run_grappler(self, config, graph_def, graph, signature_def):
         try:
             from tensorflow.python.grappler import tf_optimizer
             from tensorflow.python.training.saver import export_meta_graph
-        except ImportError as e:
-            raise ImportError("Unable to import tensorflow which is required {}".format(e))
+        except ImportError as err:
+            raise ImportError("Unable to import tensorflow which is required {}".format(err))
         meta_graph = export_meta_graph(graph_def=graph_def, graph=graph)
         meta_graph.signature_def["not_used_key"].CopyFrom(signature_def)
         return tf_optimizer.OptimizeGraph(config, meta_graph)
 
-
     def parse(self):
         """
         Parse tensorflow models: checkpoints, saved models, and single frozen pb file.
@@ -227,11 +225,13 @@ def parse(self):
             try:
                 from tensorflow.python.framework import convert_to_constants
                 from tensorflow.core.protobuf import config_pb2
-            except ImportError as e:
-                raise ImportError("Unable to import tensorflow which is required {}".format(e))
+            except ImportError as err:
+                raise ImportError("Unable to import tensorflow which is required {}".format(err))
             concrete_func = self._tf_input
             graph = convert_to_constants.convert_variables_to_constants_v2(concrete_func).graph
-            signature = self._build_signature_def(graph, concrete_func.inputs, concrete_func.outputs)
+            signature = self._build_signature_def(
+                graph, concrete_func.inputs, concrete_func.outputs
+            )
             graph_def = graph.as_graph_def()
 
             # Some optimization