Update tvm, fix lint due to pylint update (#423)

nnvm/python/nnvm/frontend/coreml.py

 # pylint: disable=invalid-name, unused-argument
 """CoreML frontend."""
 from __future__ import absolute_import as _abs
-import tvm
 import numpy as np
+
+import tvm
 from .. import symbol as _sym
 from .common import SymbolTable
 
@@ -77,6 +78,7 @@ def ConvolutionLayerParams(op, insym, symtab):
     return ret
 
 def BatchnormLayerParams(op, insym, symtab):
+    """Get layer of batchnorm parameter"""
     # this changes the symbol
     if op.instanceNormalization:
         raise NotImplementedError("instance normalization not implemented")
@@ -89,6 +91,7 @@ def BatchnormLayerParams(op, insym, symtab):
         return _sym.batch_norm(data=insym, **params)
 
 def ActivationParams(op, insym, symtab):
+    """Get activation parameters"""
     whichActivation = op.WhichOneof('NonlinearityType')
     par = getattr(op, whichActivation)
     if whichActivation == 'linear':
@@ -129,6 +132,8 @@ def ActivationParams(op, insym, symtab):
         betasym = symtab.new_const(beta)
         return _sym.broadcast_mul(_sym.log(_sym.broadcast_add(
             _sym.exp(insym), betasym)), alphasym)
+    else:
+        raise NotImplementedError('%s not implemented' % whichActivation)
 
 def ScaleLayerParams(op, insym, symtab):
     """Scale layer params."""
@@ -144,6 +149,7 @@ def ScaleLayerParams(op, insym, symtab):
     return ret
 
 def PoolingLayerParams(op, insym, symtab):
+    """get pooling parameters"""
     if op.globalPooling:
         if op.type == 0:
             return _sym.global_max_pool2d(insym)

nnvm/tests/python/compiler/test_top_level2.py

@@ -3,6 +3,7 @@ import numpy as np
 import tvm
 from tvm.contrib import graph_runtime
 import topi
+import topi.testing
 import nnvm.symbol as sym
 import nnvm.compiler
 from nnvm.testing.config import ctx_list