masahi commented on a change in pull request #10773:
URL: https://github.com/apache/tvm/pull/10773#discussion_r834731807
##########
File path: python/tvm/relay/op/strategy/arm_cpu.py
##########
@@ -88,20 +88,21 @@ def conv2d_strategy_arm_cpu(attrs, inputs, out_type,
target):
if groups == 1:
if layout == "NCHW":
if kernel_layout == "OIHW":
- # ARM conv2d spatial pack schedule.
- strategy.add_implementation(
- wrap_compute_conv2d(topi.arm_cpu.conv2d_nchw_spatial_pack),
-
wrap_topi_schedule(topi.arm_cpu.schedule_conv2d_nchw_spatial_pack),
- name="conv2d_nchw_spatial_pack.arm_cpu",
- )
-
if topi.arm_cpu.is_int8_hw_support(data.dtype, kernel.dtype):
strategy.add_implementation(
wrap_compute_conv2d(topi.arm_cpu.conv2d_nchw_int8),
wrap_topi_schedule(topi.arm_cpu.schedule_conv2d_nchw_int8),
name="conv2d_nchw_int8.arm_cpu",
)
else:
+ # ARM conv2d spatial pack schedule.
+ strategy.add_implementation(
+
wrap_compute_conv2d(topi.arm_cpu.conv2d_nchw_spatial_pack),
+
wrap_topi_schedule(topi.arm_cpu.schedule_conv2d_nchw_spatial_pack),
+ name="conv2d_nchw_spatial_pack.arm_cpu",
+ plevel=10,
+ )
+
Review comment:
The annoying thing is this happens on only specific input or filter
sizes. It took me some time to figure out why the NCHWc schedule is not used
when the input shape is (56, 56) and filter size is 3x3. If I use (128, 128)
shape or 1x1 filter, I didn't see this issue.
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