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sugared_value.h
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#pragma once
#include <functional>
#include <memory>
#include <string>
#include <torch/csrc/jit/ir.h>
#include <torch/csrc/jit/script/error_report.h>
#include <torch/csrc/jit/script/module.h>
#include <torch/csrc/jit/script/tree_views.h>
namespace torch {
namespace jit {
namespace script {
// The AST can contain nodes like `self`, `self.b` or `python_fn` that
// are not first-class values in the graph representation, but instead
// will be desugared based on how they are used in the AST.
// SugaredValue is used to temporarily represent these values in a way
// that separates their behavior from the AST -> IR converter itself.
// This allows us to keep dependencies on python minimal.
enum NoneStatus { ALWAYS, MAYBE, NEVER };
struct SugaredValue : public std::enable_shared_from_this<SugaredValue> {
// what is this node? for error reporting (e.g. Module, python function)
virtual std::string kind() const = 0;
// what can we do with this thing?
// use it as a value e.g. `this + 4`
virtual Value* asValue(const SourceRange& loc, Method& m) {
throw ErrorReport(loc) << kind() << " cannot be used as a value";
}
// select an attribute on it, e.g. `this.field`
virtual std::shared_ptr<SugaredValue> attr(
const SourceRange& loc,
Method& m,
const std::string& field) {
throw ErrorReport(loc) << "attribute lookup is not defined on " << kind();
}
virtual NoneStatus isNone() {
return NEVER;
}
// use it as a vector of values, e.g. a tuple of values as return value from
// a method invocation
virtual std::vector<std::shared_ptr<SugaredValue>> asTuple(
const SourceRange& loc,
Method& m,
const c10::optional<size_t>& size_hint = {}) {
throw ErrorReport(loc) << kind() << " cannot be used as a tuple";
}
// call it like a function, e.g. `outputs = this(inputs)`
virtual std::shared_ptr<SugaredValue> call(
const SourceRange& loc,
Method& m,
// note: names for args will be 'argument 0', 'argument 1', etc..
at::ArrayRef<NamedValue> inputs_,
at::ArrayRef<NamedValue> attributes,
size_t n_binders) {
// n_binders is always set to the number of variables an expression is
// syntactically bound to:
// a = foo() # 1 binder (note in this case the single binder might be a
// tuple) a, * b = foo() # 1 binder a, b = foo() # 2 binders foo() # 0
// binders
//
// In subexpressions, like bar() in foo(bar()), n_binders is always set to
// 1. n_binders is used as a hint to subexpressions to determine how many
// values they should return when that number is ambiguous statically. In
// particular it is currently used to decide how many tensors a call to a
// python function will return. It is only a hint, functions do not have to
// check that n_binders match the number of things they are returning, the
// assignment logic will do that anyway.
throw ErrorReport(loc) << "cannot call a " << kind();
}
virtual ~SugaredValue() = default;
};
// most things in the environment are just simple value types
// and not special python syntax sugar types
struct TORCH_API SimpleValue : public SugaredValue {
SimpleValue(Value* value) : value(value) {}
std::string kind() const override {
return "value";
}
Value* asValue(const SourceRange& range, Method& m) override {
return value;
}
NoneStatus isNone() override {
if (value->mustBeNone())
return ALWAYS;
else if (value->type()->cast<OptionalType>())
return MAYBE;
else
return NEVER;
}
std::vector<std::shared_ptr<SugaredValue>> asTuple(
const SourceRange& loc,
Method& m,
const c10::optional<size_t>& size_hint = {}) override;
std::shared_ptr<SugaredValue> attr(
const SourceRange& loc,
Method& m,
const std::string& field) override;
Value* getValue() const {
return value;
}
private:
Value* value;
};
struct TORCH_API BuiltinFunction : public SugaredValue {
BuiltinFunction(Symbol symbol, c10::optional<NamedValue> self)
: symbol(symbol), self(std::move(self)) {}
// The symbol of the function (e.g. `aten::relu`).
Symbol symbol;
// if this is method, then this is the self argument.
c10::optional<NamedValue> self;
std::string kind() const override {
return "builtin";
}
std::shared_ptr<SugaredValue> call(
const SourceRange& loc,
Method& m,
at::ArrayRef<NamedValue> attributes,
at::ArrayRef<NamedValue> inputs,
size_t n_binders) override;
};
struct TORCH_API BuiltinModule : public SugaredValue {
BuiltinModule(std::string name, c10::optional<int64_t> version = at::nullopt)
: name(std::move(name)), version(std::move(version)) {}
std::string kind() const override {
return "builtin module";
}
std::shared_ptr<SugaredValue> attr(
const SourceRange& loc,
Method& m,
const std::string& field) override {
return std::make_shared<BuiltinFunction>(
Symbol::fromQualString(name + "::" + field), c10::nullopt);
}
private:
std::string name;
// when we add operator versioning, emit this op as it exising at 'version'
// if not set, use the latest version
c10::optional<int64_t> version;
};
// defines how a method obtained from a module behaves in script
struct MethodValue : public SugaredValue {
MethodValue(std::shared_ptr<Module> module, Method& method)
: module(std::move(module)) // insurance that method stays alive
,
method(method) {}
std::string kind() const override {
return "method";
}
std::shared_ptr<SugaredValue> call(
const SourceRange& loc,
Method& caller,
at::ArrayRef<NamedValue> inputs,
at::ArrayRef<NamedValue> attributes,
size_t n_binders) override {
return std::make_shared<SimpleValue>(
caller.emit_call_to(loc, method, inputs, attributes));
}
private:
std::shared_ptr<Module> module;
Method& method;
};
struct TORCH_API PrintValue : public SugaredValue {
std::string kind() const override {
return "print";
}
std::shared_ptr<SugaredValue> call(
const SourceRange& loc,
Method& m,
at::ArrayRef<NamedValue> inputs,
at::ArrayRef<NamedValue> attributes,
size_t n_binders) override;
};
// expressions like int(x)
// these are the same as call prim::Int or equivalent except it
// is a noop when the input is a subtype of 'type'
struct TORCH_API CastValue : public BuiltinFunction {
CastValue(TypePtr type, c10::Symbol method)
: BuiltinFunction(method, c10::nullopt), type_(std::move(type)) {}
std::shared_ptr<SugaredValue> call(
const SourceRange& loc,
Method& m,
at::ArrayRef<NamedValue> inputs,
at::ArrayRef<NamedValue> attributes,
size_t n_binders) override {
if (inputs.size() == 1 && attributes.size() == 0) {
auto v = inputs[0].value(*m.graph());
if (v->type()->isSubtypeOf(type_)) {
return std::make_shared<SimpleValue>(v);
}
}
return BuiltinFunction::call(loc, m, inputs, attributes, n_binders);
}
private:
TypePtr type_;
};
// These SugaredValues have special handling in the compiler because they
// change the normal evalution order of the expression they participate in.
// They are exposed here so that the python frontend can inject them
// when it sees the equivalent thing in python
struct TORCH_API ForkValue : public SugaredValue {
ForkValue() = default;
std::string kind() const override {
return "fork";
}
};
struct TORCH_API AnnotateValue : public SugaredValue {
AnnotateValue() = default;
std::string kind() const override {
return "annotate";
}
};
// matched against for special handling of getattr expressions
struct TORCH_API GetAttrValue : SugaredValue {
GetAttrValue() = default;
std::string kind() const override {
return "getattr";
}
};
// matched against for special handling of isinstance expressions
struct TORCH_API IsInstanceValue : SugaredValue {
IsInstanceValue() = default;
std::string kind() const override {
return "isinstance";
}
};
static inline std::vector<Value*> toValues(
Graph& g,
at::ArrayRef<NamedValue> nvs) {
return fmap(nvs, [&](const NamedValue& v) { return v.value(g); });
}
} // namespace script
} // namespace jit
} // namespace torch