Introduce type variables to implement generic list operators #12040
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| if(it == type_map.end()) { | ||
| if(text.size() > 0 && islower(text[0])) { | ||
| // lower case identifiers that are not otherwise valid types | ||
| // are treated as type variables |
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| : Type(TypeKind::ListType), elem(std::move(elem)) {} | ||
| : Type(TypeKind::ListType) | ||
| , elem(std::move(elem)) | ||
| , has_free_variables_(getElementType()->hasFreeVariables()) {} |
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| return StringType::get(); | ||
| } else if (kind.find("TypeVar:") == 0) { | ||
| return VarType::create(kind.substr(strlen("TypeVar:"))); |
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torch/csrc/jit/script/compiler.cpp
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| @@ -616,7 +630,10 @@ at::optional<std::vector<Value*>> tryMatchSchema( | |||
| return at::nullopt; | |||
| } | |||
| } | |||
| return positional_inputs; | |||
| auto return_type = fmap(schema.returns, [&](const Argument& r) { | |||
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torch/csrc/jit/script/compiler.cpp
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| @@ -791,7 +808,7 @@ struct to_ir { | |||
| // Record the type for the schema and set the Type on the Value* | |||
| arguments.push_back(schema.arguments.at(arg_annotation_idx++)); | |||
| new_input->setType(arguments.back().type); | |||
| ensureLegalType((*it).ident().range(), arguments.back().type); | |||
| // ensureLegalType((*it).ident().range(), arguments.back().type); | |||
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torch/csrc/jit/type.h
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| }; | ||
|
|
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| TORCH_API TypePtr matchTypeVariables(TypePtr formal, TypePtr actual, std::unordered_map<std::string, TypePtr>& type_env); | ||
| TORCH_API TypePtr evalTypeVariables(TypePtr type, std::unordered_map<std::string, TypePtr>& type_env); |
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torch/csrc/jit/type.cpp
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| AT_ERROR("unhandled free variable container: ", formal->str()); | ||
| } | ||
|
|
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| // change return types like List[List[int]] into List[List[int]] |
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Summary: We generate specialized list operations for int, float, and Tensor lists so that small lists of integers like the arguments to conv do not involve tons of boxing code. This PR adds a fallback GenericList for List types that contain any other type. It does so by adding type variables to `jit::Type`, and machinery for matching/replacing the type variables during `tryMatchSchema` and operator lookup. It also modifies the builtin list ops to include a fallback that works on a GenericList object that simply holds IValues. This is distinguished from IValue's tuple type so that conversion to/from Python still happens losslessly. Pull Request resolved: pytorch/pytorch#12040 Differential Revision: D10037098 Pulled By: zdevito fbshipit-source-id: 0c5f2864d12e7d33554bf34cc29e5fb700dde150
We generate specialized list operations for int, float, and Tensor lists so that small lists of integers like the arguments to conv do not involve tons of boxing code.
This PR adds a fallback GenericList for List types that contain any other type. It does so by adding type variables to
jit::Type, and machinery for matching/replacing the type variables duringtryMatchSchemaand operator lookup.It also modifies the builtin list ops to include a fallback that works on a GenericList object that simply holds IValues. This is distinguished from IValue's tuple type so that conversion to/from Python still happens losslessly.