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new 375566b Fix default pytorch divide behaviour (#10727)
375566b is described below
commit 375566b6e2d3c4a01844efbc7e6bff35bf28822c
Author: AleksKnezevic <[email protected]>
AuthorDate: Wed Mar 23 19:46:07 2022 -0400
Fix default pytorch divide behaviour (#10727)
Co-authored-by: Aleks Knezevic <[email protected]>
---
python/tvm/relay/frontend/pytorch.py | 14 ++++++++++++++
1 file changed, 14 insertions(+)
diff --git a/python/tvm/relay/frontend/pytorch.py
b/python/tvm/relay/frontend/pytorch.py
index 37a8e45..8d37d48 100644
--- a/python/tvm/relay/frontend/pytorch.py
+++ b/python/tvm/relay/frontend/pytorch.py
@@ -254,6 +254,20 @@ class PyTorchOpConverter:
# Operator implementations
def make_elemwise(self, name):
def elemwise(inputs, input_types):
+ if name == "divide":
+ #
https://pytorch.org/docs/stable/generated/torch.div.html#torch.div
+ # None - default behavior. Performs no rounding and, if both
input and
+ # other are integer types, promotes the inputs to the default
scalar type.
+ if all(["int" in input_type for input_type in
input_types[:2]]):
+ input_types[:2] = ["float32"] * 2
+ cast_inputs = []
+ for inp in inputs[:2]:
+ if np.isscalar(inp):
+ cast_inputs.append(_expr.const(inp,
dtype="float32"))
+ else:
+ cast_inputs.append(_op.cast(inp, "float32"))
+ inputs[:2] = cast_inputs
+
data0, data1 = self.pytorch_promote_types(inputs[:2],
input_types[:2])
return get_relay_op(name)(data0, data1)
