ibsidorenko commented on code in PR #13734:
URL: https://github.com/apache/tvm/pull/13734#discussion_r1066638617
##########
python/tvm/relay/qnn/op/legalizations.py:
##########
@@ -483,3 +488,68 @@ def _qnn_dense_legalize_cuda(attrs, inputs, types):
# CUDA prefers both datatypes to be the int8.
return helper_change_dtypes_to_int8(attrs, inputs, types,
relay.qnn.op.dense)
return None
+
+
+########################
+# Hexagon legalizations.
+########################
+
+IN_CHANNEL_VECTOR_LENGTH = 4
+OUT_CHANNEL_VECTOR_LENGTH = 32
+
+
+@qnn_conv2d_legalize.register("hexagon")
+def _qnn_conv2d_legalize_hexagon(attrs, inputs, types):
+ """Legalize qnn.conv2d op for vrmpy tensorization.
+
+ If the inputs are signed or unsigned int8 and data/kernel layouts are
NCHW/OIHW, then the input
+ and output channels are padded to be a multiple of 4 and 32 respectively.
Review Comment:
agree... dtype legalization will be the next step here.
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