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[Unity]Lazy transform param now only work on non-dataflow block #14864

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Merged
tqchen merged 1 commit into from
May 17, 2023
Merged

[Unity]Lazy transform param now only work on non-dataflow block #14864

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4 changes: 2 additions & 2 deletions python/tvm/relax/transform/lazy_transform_params.py
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Original file line number Diff line number Diff line change
Expand Up @@ -85,11 +85,11 @@ def __init__(self, out_tuple_var: relax.Var, input_params: set) -> None:
self.input_params = input_params
self.var_liveness_end = {}

def visit_dataflow_block_(self, block: relax.DataflowBlock) -> None:
def visit_binding_block_(self, block: relax.BindingBlock) -> None:
for binding in reversed(block.bindings):
self.visit_binding(binding)

def visit_dataflow_var_(self, op: relax.DataflowVar) -> None:
def visit_var_(self, op: relax.Var) -> None:
if op in self.input_params:
self.last_appear_in_var_binding.append(op)
self.input_params.remove(op)
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54 changes: 23 additions & 31 deletions tests/python/relax/test_transform_lazy_transform_params.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,19 +45,17 @@ def main_transform_params(
R.Tensor((16, 16, 3, 3), dtype="float32"), R.Tensor((16, 3, 3, 3), dtype="float32")
):
cls = Before
with R.dataflow():
lv: R.Tensor((16, 16, 3, 3), dtype="float32") = params[1]
lv1: R.Tensor((3, 16, 3, 3), dtype="float32") = params[0]
lv2 = R.call_tir(
cls.transform_layout_IOHW_to_OIHW,
(lv1,),
out_sinfo=R.Tensor((16, 3, 3, 3), dtype="float32"),
)
gv: R.Tuple(
R.Tensor((16, 16, 3, 3), dtype="float32"),
R.Tensor((16, 3, 3, 3), dtype="float32"),
) = (lv, lv2)
R.output(gv)
lv: R.Tensor((16, 16, 3, 3), dtype="float32") = params[1]
lv1: R.Tensor((3, 16, 3, 3), dtype="float32") = params[0]
lv2 = R.call_tir(
cls.transform_layout_IOHW_to_OIHW,
(lv1,),
out_sinfo=R.Tensor((16, 3, 3, 3), dtype="float32"),
)
gv: R.Tuple(
R.Tensor((16, 16, 3, 3), dtype="float32"),
R.Tensor((16, 3, 3, 3), dtype="float32"),
) = (lv, lv2)
return gv

@I.ir_module
Expand All @@ -77,24 +75,18 @@ def transform_layout_IOHW_to_OIHW(
@R.function
def main_transform_params() -> R.Tuple(R.Object, R.Object):
cls = Expected
with R.dataflow():
lv: R.Object = R.call_packed("get_item", R.prim_value(1), sinfo_args=(R.Object,))
lv1: R.Object = R.call_packed(
"set_item", R.prim_value(0), lv, sinfo_args=(R.Object,)
)
lv2: R.Tuple = R.vm.kill_object(lv)
lv1_1: R.Object = R.call_packed("get_item", R.prim_value(0), sinfo_args=(R.Object,))
lv3 = R.call_tir(
cls.transform_layout_IOHW_to_OIHW,
(lv1_1,),
out_sinfo=R.Tensor((16, 3, 3, 3), dtype="float32"),
)
lv4: R.Object = R.call_packed(
"set_item", R.prim_value(1), lv3, sinfo_args=(R.Object,)
)
lv5: R.Tuple = R.vm.kill_object(lv1_1)
gv: R.Tuple(R.Object, R.Object) = (lv1, lv4)
R.output(gv)
lv: R.Object = R.call_packed("get_item", R.prim_value(1), sinfo_args=(R.Object,))
lv1: R.Object = R.call_packed("set_item", R.prim_value(0), lv, sinfo_args=(R.Object,))
lv2: R.Tuple = R.vm.kill_object(lv)
lv1_1: R.Object = R.call_packed("get_item", R.prim_value(0), sinfo_args=(R.Object,))
lv3 = R.call_tir(
cls.transform_layout_IOHW_to_OIHW,
(lv1_1,),
out_sinfo=R.Tensor((16, 3, 3, 3), dtype="float32"),
)
lv4: R.Object = R.call_packed("set_item", R.prim_value(1), lv3, sinfo_args=(R.Object,))
lv5: R.Tuple = R.vm.kill_object(lv1_1)
gv: R.Tuple(R.Object, R.Object) = (lv1, lv4)
return gv

after = LazyTransformParams()(Before)
Expand Down