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[jit][edge] Migrate to TypeFactory for jit types on mobile (#71516)

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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71516

Mobile should be able to contruct dynamic types by default.
ghstack-source-id: 147498365

Test Plan:
CI.

**-48KB** binary size reduction for igios BSB.
UMBEX link: https://www.internalfb.com/intern/unigraph/explorer/?jsgq_traversal_spec=%7B%22builds%22%3A[%22bsb%3A422553426218394%5Cu0040base%22%2C%22bsb%3A422553426218394%5Cu0040diff%22]%7D&unigraph_project=UnigraphProjectMbex&is_mbex_redirected

Reviewed By: iseeyuan

Differential Revision: D33673958

fbshipit-source-id: 8600c04ae929283681971aae264d3774188df9cd
(cherry picked from commit 64ebcec09e69d2eff64fdbf926fb43d3b67f99b2)
This commit is contained in:
Zhengxu Chen
2022-01-25 22:58:45 -08:00
committed by PyTorch MergeBot
parent e5794974cb
commit fe277b8717
20 changed files with 236 additions and 140 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
torch/csrc/jit/serialization/export_module.cpp
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@ -108,7 +108,11 @@ std::pair<IValue, IValue> getFunctionTuple(
static const std::string torch_prefix("__torch__");
static const std::string class_prefix("__torch__.torch.classes");
for (const TypePtr& t : mobile_code.types_) {
for (const TypePtr& ty : mobile_code.types_) {
auto t = ty;
if (auto dyn = t->castRaw<c10::DynamicType>()) {
t = dyn->fallback();
}
std::string type_str = t->annotation_str();
if (t->kind() == TypeKind::TupleType) {
TORCH_CHECK(
@ -216,9 +220,13 @@ std::pair<IValue, IValue> getFunctionTuple(
arg.type()->annotation_str(type_printer) => mangled unique name of the
module/submodule
*/
auto arg_type = arg.type();
if (auto dyn = arg_type->castRaw<c10::DynamicType>()) {
arg_type = dyn->fallback();
}
argTables.emplace_back(Table({
{"name", arg.name()},
{"type", arg.type()->annotation_str(type_printer)},
{"type", arg_type->annotation_str(type_printer)},
{"default_value", arg.default_value()},
}));
}