AndrewZhaoLuo commented on a change in pull request #8907:
URL: https://github.com/apache/tvm/pull/8907#discussion_r701330456
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File path: python/tvm/relay/frontend/onnx.py
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@@ -3306,6 +3290,32 @@ def get_scalar(x, dtype="float32"):
return _qnn.op.quantize(out, y_scale, y_zero_point, out_dtype=dtype)
+class QLinearConcat(OnnxOpConverter):
+ """Operator converter for QLinearConcat from Microsoft onnxruntime contrib
opset."""
+
+ @classmethod
+ def _impl_v1(cls, inputs, attr, params):
+ # which axis to concat on
+ axis = attr["axis"]
+
+ y_scale = fold_constant(get_scalar(inputs[0], params))
+ y_zero_point = get_scalar(inputs[1], params, "int32")
+
+ # input tensors, scales, zero_points
+ assert (
+ len(inputs) % 3 == 2
+ ), "Additional input count must be a multiple of 3 --
tensor/scale/zero_point tuples"
+ tensors = []
+ scales = []
+ zero_points = []
+ for i in range(2, len(inputs), 3):
Review comment:
Cool, documentation is wrong then. Not the first time :P
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