ashutosh-arm commented on code in PR #12353:
URL: https://github.com/apache/tvm/pull/12353#discussion_r942622944
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python/tvm/relay/op/contrib/cmsisnn.py:
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@@ -122,6 +130,25 @@ def check_qnn_conv2d(pattern):
conv2d_input = conv2d.args[0]
conv2d_weight = conv2d.args[1]
+ # check if sum of paddings from pad() and conv2d() satisfies CMSIS-NN
constraints
+ can_pad_be_fused = True
+ if isinstance(conv2d_input, tvm.relay.expr.Call) and
str(conv2d_input.op.name) == "nn.pad":
+ data_layout = conv2d.attrs.data_layout
+ conv2d_padding = conv2d.attrs.padding # (top, left, bottom, right)
+ pad = conv2d_input
+ pad_width = pad.attrs.pad_width
+ pad_width_w = pad_width[data_layout.find("W")] # (left, right)
+ pad_width_h = pad_width[data_layout.find("H")] # (top, bottom)
+ # calculate effective padding post pad fusion
+ pad_top = pad_width_h[0] + conv2d_padding[0]
+ pad_bottom = pad_width_h[1] + conv2d_padding[2]
+ pad_left = pad_width_w[0] + conv2d_padding[1]
+ pad_right = pad_width_w[1] + conv2d_padding[3]
+ # check if difference in the side paddings is 1 along each
dimension
+ pad_w_diff = int(pad_right - pad_left)
Review Comment:
No worries :+1:
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