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Fix default pytorch divide behaviour #10727

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Merged
masahi merged 1 commit into from
Mar 23, 2022
Merged

Fix default pytorch divide behaviour #10727

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14 changes: 14 additions & 0 deletions python/tvm/relay/frontend/pytorch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -254,6 +254,20 @@ def is_quantized_tensor(self, data):
# 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)

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