AndrewZhaoLuo commented on code in PR #13578:
URL: https://github.com/apache/tvm/pull/13578#discussion_r1043831311
##########
python/tvm/relay/transform/fake_quantization_to_integer.py:
##########
@@ -502,6 +502,33 @@ def register_binary_qnn(op_name, op):
def binary(expr, type_map):
left, right, left_t, right_t, out_t = get_binary_types(expr, type_map)
+
+ if (
+ approx_equal(left_t.scale, right_t.scale)
Review Comment:
Hmm I don't believe this work around is a good idea because it does not
handle overflow well where qnn ops will.
e.g. if we had 128 * 128 --> we will have issues.
Hmm the main problem we have if I understand correctly is dealing with
scales and zero points which are of shape [1] rather than be scalars.
Can we just unpack scales and zero points into scalars then?
##########
python/tvm/relay/frontend/onnx.py:
##########
@@ -1391,7 +1391,7 @@ def _impl_v1(cls, inputs, attr, params):
dtype = input0_state.checked_type.dtype
# Y = alpha * A * B + beta * C
alpha = float(attr.get("alpha", 1.0))
- beta = float(attr.get("beta", 1.0))
+ beta = float(attr.get("beta"))
Review Comment:
Though the change on L1409 might not be needed since if beta == 1, it can be
removed with constant folding.
##########
python/tvm/relay/frontend/onnx.py:
##########
@@ -1391,7 +1391,7 @@ def _impl_v1(cls, inputs, attr, params):
dtype = input0_state.checked_type.dtype
# Y = alpha * A * B + beta * C
alpha = float(attr.get("alpha", 1.0))
- beta = float(attr.get("beta", 1.0))
+ beta = float(attr.get("beta"))
Review Comment:
I would keep the original line of `.get('beta', 1.0)` since you cannot call
`float()` on `None` which `attr.get` can return.
Then below on L1409, you can just do `if beta is None` --> `if 'beta' not in
attr.keys()` or something.
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