sfvaroglu commented on code in PR #10952:
URL: https://github.com/apache/tvm/pull/10952#discussion_r852397609
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python/tvm/relay/qnn/op/legalizations.py:
##########
@@ -91,12 +91,30 @@ def qnn_conv2d_transpose_legalize(attrs, inputs, types):
# Collect the input exprs.
data, kernel, input_zero_point, kernel_zero_point, _, _ = inputs
- shift_data = relay.subtract(
Review Comment:
Without this change, the model I'm looking at fails with `Incompatible
broadcast type TensorType([32, 32, 3, 3], int16) and TensorType([32], int16)`.
Here is the op for more info:
```
%2181 = qnn.conv2d_transpose(%2180, meta[relay.Constant][1003] /*
ty=Tensor[(32, 32, 3, 3), int8] */, -26 /* ty=int32 */,
meta[relay.Constant][1004] /* ty=Tensor[(32), int32] */, 0.196949f /*
ty=float32 */, meta[relay.Constant][1005] /* ty=Tensor[(32), float32] */,
channels=32, kernel_size=[3, 3], strides=[2, 2], padding=[0, 0, 1, 1],
kernel_layout="IOHW", out_dtype="int32") /* ty=Tensor[(1, 32, 100, 100), int32]
*/;
```
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