diff --git a/topi/python/topi/arm_cpu/conv2d.py b/topi/python/topi/arm_cpu/conv2d.py
index c30ad496b24d..cfd423b584cf 100644
--- a/topi/python/topi/arm_cpu/conv2d.py
+++ b/topi/python/topi/arm_cpu/conv2d.py
@@ -2,6 +2,8 @@
 """Conv2D schedule for ARM CPU"""
 from __future__ import absolute_import as _abs
 
+import warnings
+
 import numpy as np
 
 import tvm
@@ -522,7 +524,10 @@ def _alter_conv2d_layout_arm(attrs, inputs, tinfos):
     out_dtype = attrs["out_dtype"]
     out_dtype = tinfos[0].dtype if out_dtype == "same" else out_dtype
 
-    if layout != 'NCHW' or groups != 1 or dilation != (1, 1):
+    if layout != 'NCHW' or groups != 1:
+        return None
+    if dilation != (1, 1):
+        warnings.warn("Does not support weight pre-transform for dilated convolution.")
         return None
 
     data, kernel = tinfos[0:2]
@@ -531,7 +536,7 @@ def _alter_conv2d_layout_arm(attrs, inputs, tinfos):
 
     # query config of this workload
     workload = autotvm.task.args_to_workload(
-        [data, kernel, strides, padding, layout, out_dtype], conv2d)
+        [data, kernel, strides, padding, dilation, layout, out_dtype], conv2d)
     target = tvm.target.current_target()
     dispatch_ctx = autotvm.DispatchContext.current
     cfg = dispatch_ctx.query(target, workload)
@@ -548,7 +553,7 @@ def _alter_conv2d_layout_arm(attrs, inputs, tinfos):
         new_data = data
         new_kernel = tvm.placeholder((CO // VC, CI, KH, KW, VC), dtype=kernel.dtype)
         new_workload = autotvm.task.args_to_workload(
-            [new_data, new_kernel, strides, padding, 'NCHW', out_dtype], conv2d)
+            [new_data, new_kernel, strides, padding, dilation, 'NCHW', out_dtype], conv2d)
         dispatch_ctx.update(target, new_workload, cfg)
 
         return sym.conv2d(*copy_inputs, **new_attrs)
@@ -574,7 +579,8 @@ def _alter_conv2d_layout_arm(attrs, inputs, tinfos):
         new_weight = tvm.placeholder((KH + tile_size - 1, KH + tile_size -1, CO // VC, CI, VC),
                                      kernel.dtype)
         new_workload = autotvm.task.args_to_workload(
-            [new_data, new_weight, strides, padding, new_attrs['layout'], out_dtype, tile_size],
+            [new_data, new_weight, strides, padding, dilation,
+             new_attrs['layout'], out_dtype, tile_size],
             conv2d_winograd_without_weight_transform)
         dispatch_ctx.update(target, new_workload, cfg)
 
diff --git a/topi/python/topi/cuda/conv2d_winograd.py b/topi/python/topi/cuda/conv2d_winograd.py
index fb30a4f9ad2e..1f2112979ee7 100644
--- a/topi/python/topi/cuda/conv2d_winograd.py
+++ b/topi/python/topi/cuda/conv2d_winograd.py
@@ -375,6 +375,8 @@ def _alter_conv2d_layout(attrs, inputs, tinfos):
             new_attrs['out_layout'] = new_layout
             new_attrs['kernel_layout'] = 'OIHW4o4i'
             ic_block_factor = oc_block_factor = 4
+
+            # Store the same config for the altered operator (workload)
             new_data = tvm.placeholder((N, CI // ic_block_factor, H, W, ic_block_factor),
                                        dtype=data.dtype)
             new_kernel = tvm.placeholder((CO // oc_block_factor, CI // ic_block_factor, KH, KW,\
@@ -387,7 +389,9 @@ def _alter_conv2d_layout(attrs, inputs, tinfos):
             return sym.conv2d(*copy_inputs, **new_attrs)
 
         if attrs.get_int_tuple("dilation") != (1, 1):
+            warnings.warn("Does not support weight pre-transform for dilated convolution.")
             return None
+
         # pre-compute weight transformation in winograd
         tile_size = _infer_tile_size(tinfos[0], tinfos[1])
 
@@ -397,6 +401,7 @@ def _alter_conv2d_layout(attrs, inputs, tinfos):
         copy_inputs[1] = weight
         new_attrs['tile_size'] = tile_size
 
+        # Store the same config for the altered operator (workload)
         new_data = data
         new_weight = tvm.placeholder((KH + tile_size - 1, KW + tile_size - 1, CI, CO),
                                      dtype=kernel.dtype)
diff --git a/topi/python/topi/mali/conv2d.py b/topi/python/topi/mali/conv2d.py
index 7c3b4a23cbc5..1ad58038abb1 100644
--- a/topi/python/topi/mali/conv2d.py
+++ b/topi/python/topi/mali/conv2d.py
@@ -440,7 +440,7 @@ def _schedule_winograd(cfg, s, op):
 
 ##### REGISTER TOPI COMPUTE / SCHEDULE FOR WINOGRAD WITH WEIGHT TRANSFORM #####
 @autotvm.register_topi_compute(conv2d_winograd_without_weight_transform, 'mali', ['winograd'])
-def conv2d_winograd_ww(cfg, data, kernel, strides, padding, layout, out_dtype, tile_size):
+def conv2d_winograd_ww(cfg, data, kernel, strides, padding, dilation, layout, out_dtype, tile_size):
     """TOPI compute callback"""
     return _decl_winograd(cfg, data, kernel, strides, padding, dilation, layout, out_dtype,
                           tile_size)