mshr-h commented on code in PR #17875:
URL: https://github.com/apache/tvm/pull/17875#discussion_r2055168695
##########
python/tvm/relax/frontend/torch/fx_translator.py:
##########
@@ -132,6 +132,54 @@ def convert(node: fx.Node) -> relax.Var:
return convert
+ ########## Binary Ops ##############
+
+ def _binary_op_inplace(self, relax_op: Callable, intrinsic_op: Callable)
-> Callable:
+ from torch import fx
+
+ def convert(node: fx.Node) -> relax.Var:
+ def promote_binary_op_args(lhs, rhs):
+ if isinstance(lhs, relax.Expr) and isinstance(rhs, relax.Expr):
+ return lhs, rhs
+ elif isinstance(lhs, relax.Expr):
+ assert isinstance(lhs.struct_info, relax.TensorStructInfo)
+ return lhs, relax.const(rhs, lhs.struct_info.dtype)
+ elif isinstance(rhs, relax.Expr):
+ assert isinstance(rhs.struct_info, relax.TensorStructInfo)
+ return relax.const(lhs, rhs.struct_info.dtype), rhs
+ else:
+ assert False
+
+ def call_binary_op(op, lhs, rhs):
+ lhs, rhs = promote_binary_op_args(lhs, rhs)
+ return self.block_builder.emit(op(lhs, rhs))
+
+ lhs, rhs = self.retrieve_args(node)
+ if isinstance(lhs, relax.Var) or isinstance(rhs, relax.Var):
Review Comment:
Can we avoid implementing separate converters for in-place and non-in-place
ops? I think the following logic should handle both cases. What do you think?
@kavin-sai-krishna
```python
if isinstance(lhs, relax.Var) or isinstance(rhs, relax.Var):
output = call_binary_op(relax_op, lhs, rhs)
elif isinstance(lhs, relax.expr.Constant):
output = call_binary_op(
relax_op, lhs, relax.const(rhs,
dtype=lhs.struct_info.dtype)
)
elif isinstance(rhs, relax.expr.Constant):
output = call_binary_op(
relax_op, relax.const(lhs, dtype=rhs.struct_info.dtype),
rhs
)
else:
output = intrinsic_op(lhs, rhs)
self.env[node.args[0]] = output
return output
```
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