fix pylint

python/tvm/relay/transform/fake_quantization_to_integer.py

@@ -56,7 +56,7 @@ def quantize(expr, type_map):
     return [out, TensorAffineType(expr.args[1], expr.args[2], expr.attrs.out_dtype)]
 
 
-def register_unary_identity(op_name, op):
+def register_unary_identity(op_name):
     def identity(expr, type_map):
         assert len(expr.args) == 1
         arg = expr.args[0]
@@ -66,13 +66,13 @@ def identity(expr, type_map):
     return register_fake_quantization_to_integer(op_name, identity)
 
 
-register_unary_identity("reshape", relay.op.reshape)
-register_unary_identity("squeeze", relay.op.squeeze)
-register_unary_identity("strided_slice", relay.op.strided_slice)
-register_unary_identity("transpose", relay.op.transpose)
-register_unary_identity("expand_dims", relay.op.expand_dims)
-register_unary_identity("nn.max_pool2d", relay.op.nn.max_pool2d)
-register_unary_identity("nn.batch_flatten", relay.op.nn.batch_flatten)
+register_unary_identity("reshape")
+register_unary_identity("squeeze")
+register_unary_identity("strided_slice")
+register_unary_identity("transpose")
+register_unary_identity("expand_dims")
+register_unary_identity("nn.max_pool2d")
+register_unary_identity("nn.batch_flatten")
 
 
 @register_fake_quantization_to_integer("nn.avg_pool2d")
@@ -201,6 +201,7 @@ def clip(expr, type_map):
 
 @register_fake_quantization_to_integer("nn.pad")
 def pad(expr, type_map):
+    """Rewite an nn.pad op"""
     arg = expr.args[0]
     t = type_map[arg]
     pad_value = expr.args[1]
@@ -219,12 +220,12 @@ def pad(expr, type_map):
         assert isinstance(pad_value, relay.expr.Constant)
         pad_value = relay.qnn.op.quantize(pad_value, t.scale, t.zero_point)
 
-    z_p = fold_constant(t.zero_point)
     out = relay.op.nn.pad(arg, pad_value=pad_value, **expr.attrs)
     return [out, t]
 
 
 def get_binary_types(expr, type_map):
+    """Get Affine types of a binary op's inputs and unify them"""
     ##Support the case where one input is quantized and the other is a constant float
     left = expr.args[0]
     right = expr.args[1]
@@ -262,6 +263,7 @@ def get_binary_types(expr, type_map):
 
 
 def register_binary_qnn(op_name, op):
+    """Register a Binary Op that converts to QNN"""
     def binary(expr, type_map):
         left, right, left_t, right_t, out_t = get_binary_types(expr, type_map)
         out = op(
@@ -280,12 +282,13 @@ def binary(expr, type_map):
 
 
 # Use lambdas here to avoid a circular import problem
-register_binary_qnn("add", lambda *args: relay.qnn.op.add(*args))
-register_binary_qnn("multiply", lambda *args: relay.qnn.op.mul(*args))
-register_binary_qnn("subtract", lambda *args: relay.qnn.op.subtract(*args))
+register_binary_qnn("add", lambda *args: relay.qnn.op.add(*args)) # pylint: disable=unnecessary-lambda
+register_binary_qnn("multiply", lambda *args: relay.qnn.op.mul(*args)) # pylint: disable=unnecessary-lambda
+register_binary_qnn("subtract", lambda *args: relay.qnn.op.subtract(*args)) # pylint: disable=unnecessary-lambda
 
 
 def register_binary_identity(op_name, op):
+    """Register a binary op that works directly on int8"""
     def binary(expr, type_map):
         left, right, left_t, right_t, out_t = get_binary_types(expr, type_map)
         if left_t != out_t: