Lint fixes

python/tvm/relax/frontend/nn/core.py

@@ -599,10 +599,10 @@ def wrap_nested(expr: rx.Expr, name: str) -> Union[Tensor, Sequence[Tensor]]:
             # struct info for a nested expression should be doable in
             # a free function, without requiring an active
             # BlockBuilder and an active scope.
-            bb = BlockBuilder()
-            with bb.function("dummy_scope", params=[]):
-                expr = bb.normalize(expr)
-                bb.emit_func_output([])
+            builder = BlockBuilder()
+            with builder.function("dummy_scope", params=[]):
+                expr = builder.normalize(expr)
+                builder.emit_func_output([])
         else:
             expr = BlockBuilder.current().emit(expr, name)
     if isinstance(expr.struct_info_, TensorStructInfo):

python/tvm/relax/frontend/nn/exporter.py

@@ -162,8 +162,6 @@ def _emit_method(  # pylint: disable=too-many-locals,too-many-branches,too-many-
     effects: typing.Optional[typing.List[typing.Tuple[str, core.Effect]]],
 ):
     # pylint: disable=protected-access
-    # symbolic shape's name mapping to its tir.Var for reuse
-    str2var_params: typing.Dict[str, tir.Var] = {}
 
     def _unwrap_ret(expr: typing.Any) -> typing.Any:
         if isinstance(expr, (core.Tensor, core.Object)):
@@ -189,14 +187,6 @@ def _convert_input(arg):
         raise TypeError(f"Unsupported input type: {type(arg)}")
 
     def _params(mode: str) -> typing.List[rx.Var]:
-        def _get_var(shape_var: tir.Var) -> tir.Var:
-            name = shape_var.name
-            if name in str2var_params:
-                return str2var_params[name]
-            var = tir.Var(name, "int64")
-            str2var_params[name] = var
-            return var
-
         param_vars: typing.List[rx.Var] = [
             rx.Var(name, rx.TensorStructInfo(param.shape, param.dtype)) for name, param in params
         ]

python/tvm/relax/frontend/nn/replace_implementation.py

@@ -14,6 +14,8 @@
 # KIND, either express or implied.  See the License for the
 # specific language governing permissions and limitations
 # under the License.
+"""Pattern matching in SLM"""
+
 
 import inspect
 from typing import Dict, Tuple, List
@@ -116,7 +118,7 @@ def transform(mod, _context):
     return transform
 
 
-def _no_op_init__(self):
+def _no_op_init__(self):  # pylint: ignore=unused-argument
     pass
 
 

python/tvm/relax/frontend/nn/spec.py

@@ -18,6 +18,8 @@
 import inspect
 import typing
 
+import tvm
+
 if typing.TYPE_CHECKING:
     from .core import Module as nn_module_class
 
@@ -26,8 +28,6 @@
 ModuleSpecType = typing.Union["ModuleSpec", typing.Dict[str, MethodSpecType]]
 SpecAny = typing.Union["Object", "Int", "Tensor", "Tuple"]
 
-import tvm
-
 
 class Int:  # pylint: disable=too-few-public-methods
     """An integer input"""