MLBEDSW-7315: Add support for AvgPool with stride_width > 3

* Convert AvgPool with stride_width > 3 and Valid padding to Conv2D to
  optimize it to run on NPU.

Change-Id: I06ab412357f0b09b1498f9019a9d1963a324ad34
Signed-off-by: Raul Farkas <raul.farkas@arm.com>

1 files changed, 8 insertions, 0 deletions

diff --git a/ethosu/vela/high_level_command_to_npu_op.py b/ethosu/vela/high_level_command_to_npu_op.py
index 9526bd50..79ac3929 100644
--- a/ethosu/vela/high_level_command_to_npu_op.py
+++ b/ethosu/vela/high_level_command_to_npu_op.py
@@ -308,6 +308,14 @@ def use_zero_point_0(ps, tens: Tensor, is_ifm_tensor: bool) -> bool:
     if tens.dtype == DataType.int32 and is_ifm_tensor:
         return True
     if ps.primary_op.rounding_mode == RoundingMode.AwayZero:
+        if (
+            ps.primary_op.original_type == Op.AvgPool
+            and ps.primary_op.type == Op.Conv2DBias
+            and ps.primary_op.attrs.get("padding", None) == Padding.VALID
+        ):
+            # Force zero point to 0 for AveragePool operators converted to a Conv2DBias with rounding away from
+            # zero.
+            return True
         if ps.primary_op.original_type == Op.ResizeBilinear and ps.primary_op.type == Op.DepthwiseConv2DBias:
             # Force zero point to 0 for ResizeBilinear operators converted to a DepthwiseConv with rounding away from
             # zero. This is because the reference kernel ignores the zero points.