zhiics commented on a change in pull request #5324: [Runtime][Relay][Cleanup]
Clean up for memory pass to enable heterogenous execution support.
URL: https://github.com/apache/incubator-tvm/pull/5324#discussion_r407796820
##########
File path: python/tvm/relay/op/memory/memory.py
##########
@@ -96,3 +100,53 @@ def shape_func(func, inputs, outputs, dependent=False):
The shape function expression.
"""
return _make.shape_func(func, inputs, outputs, dependent)
+
+def flatten_tuple_type(ty):
+ """Return a sequence of the types contained in the tuple type in order.
+
+ Parameters
+ ----------
+ ty: tvm.Type
+ The type to flatten.
+
+ Returns
+ -------
+ result: List[tvm.Type]
+ The types in their linear order.
+ """
+ return _make.FlattenTupleType(ty)
+
+def from_tuple_type(ty, expr):
+ """Convert an expression with the given type into a sequence of
expressions.
+ Each expressions maps to a field of the tuple or nested tuples in linear
+ order.
+
+ Parameters
+ ----------
+ ty: tvm.Type
+ The type to unpack.
+ expr: The expression from which to extract each sub-field.
+
+ Returns
+ -------
+ result: List[tvm.relay.Expr]
+ The list of sub-expressions.
+ """
+ return _make.FromTupleType(ty, expr)
+
+def to_tuple_type(ty, exprs):
+ """Pack the sequence of expressions into the nested tuple type.
+
+ Parameters
+ ----------
+ ty: tvm.Type
+ The type to pack with.
+
+ exprs: The expressions to pack back into the nested tuple type.
Review comment:
```suggestion
exprs: tvm.relay.Expr
The expressions to pack back into the nested tuple type.
```
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