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https://github.com/zebrajr/pytorch.git
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* Support list and tuple literals: Adds support for [a, b], (a, b) and "a, " * Allow non-tensors to reach emitBuiltinCall, each SugaredValue::call is now responsible for checking the types of its inputs. Add support for calling cat with a tuple to emitBuiltinOp
137 lines
4.9 KiB
C++
137 lines
4.9 KiB
C++
#pragma once
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#include <functional>
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#include <memory>
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#include <string>
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#include "torch/csrc/jit/ir.h"
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#include "torch/csrc/jit/script/error_report.h"
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#include "torch/csrc/jit/script/tree_views.h"
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#include "torch/csrc/jit/script/module.h"
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namespace torch {
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namespace jit {
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namespace script {
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struct CallsiteDescriptor {
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size_t n_outputs;
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bool allow_varargs;
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};
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// The AST can contain nodes like `self`, `self.b` or `python_fn` that
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// are not first-class values in the graph representation, but instead
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// will be desugared based on how they are used in the AST.
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// SugaredValue is used to temporarily represent these values in a way
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// that separates their behavior from the AST -> IR converter itself.
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// This allows us to keep dependencies on python minimal.
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struct SugaredValue : public std::enable_shared_from_this<SugaredValue> {
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// what is this node? for error reporting (e.g. Module, python function)
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virtual std::string kind() const = 0;
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// what can we do with this thing?
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// use it as a value e.g. `this + 4`
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virtual Value * asValue(SourceRange loc, Method & m) {
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throw ErrorReport(loc) << kind() << " cannot be used as a value";
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}
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// select an attribute on it, e.g. `this.field`
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virtual std::shared_ptr<SugaredValue> attr(SourceRange loc, Method & m, const std::string& field) {
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throw ErrorReport(loc) << "attribute lookup is not defined on " << kind();
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}
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// use it as a vector of values, e.g. a tuple of values as return value from
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// a method invocation
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virtual std::vector<std::shared_ptr<SugaredValue>> asTuple(SourceRange loc, Method& m) {
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throw ErrorReport(loc) << kind() << " cannot be used as a tuple";
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}
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// call it like a function, e.g. `outputs = this(inputs)`
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virtual std::shared_ptr<SugaredValue> call(
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SourceRange loc,
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Method & m,
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at::ArrayRef<Value*> inputs,
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List<Attribute> attributes,
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size_t n_binders) {
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// n_binders is always set to the number of variables an expression is
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// syntactically bound to:
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// a = foo() # 1 binder (note in this case the single binder might be a tuple)
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// a, * b = foo() # 1 binder
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// a, b = foo() # 2 binders
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// foo() # 0 binders
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//
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// In subexpressions, like bar() in foo(bar()), n_binders is always set to
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// 1. n_binders is used as a hint to subexpressions to determine how many
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// values they should return when that number is ambiguous statically. In
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// particular it is currently used to decide how many tensors a call to a
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// python function will return. It is only a hint, functions do not have to
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// check that n_binders match the number of things they are returning, the
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// assignment logic will do that anyway.
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throw ErrorReport(loc) << "cannot call a " << kind();
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}
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virtual ~SugaredValue() {}
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};
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// most things in the environment are just simple value types
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// and not special python syntax sugar types
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struct SimpleValue : public SugaredValue {
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SimpleValue(Value * value)
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: value(value) {}
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virtual std::string kind() const override {
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return "value";
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}
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virtual Value * asValue(SourceRange range, Method & m) override {
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return value;
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}
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virtual std::vector<std::shared_ptr<SugaredValue>> asTuple(SourceRange loc, Method& m) override;
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virtual std::shared_ptr<SugaredValue> attr(SourceRange loc, Method & m, const std::string& field) override;
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Value* getValue() const {
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return value;
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}
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private:
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Value* value;
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};
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struct BuiltinFunction : public SugaredValue {
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BuiltinFunction(const std::string& name, Value* value=nullptr)
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: name(name), value(value) {}
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std::string name;
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Value* value;
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virtual std::string kind() const override {
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return "builtin";
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}
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virtual std::shared_ptr<SugaredValue> call(
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SourceRange loc,
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Method & m,
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at::ArrayRef<Value*> inputs_,
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List<Attribute> attributes,
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size_t n_binders) override;
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};
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using Resolver = std::function<std::shared_ptr<SugaredValue>(const std::string& name)>;
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void defineMethodsInModule(
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Module & m,
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const std::vector<Def>& definitions,
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const std::vector<Resolver>& resolvers, /* determines how we handle free variables in each definition*/
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std::shared_ptr<SugaredValue> self /* if non-null, the first argument to each def, is bound to this value */
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);
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// same as above but parse the definitions from source
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void defineMethodsInModule(Module & m, const std::string& source, const Resolver& resolver, std::shared_ptr<SugaredValue> self);
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std::shared_ptr<Graph> compileFunction(Def def, const Resolver& resolver);
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// pack outputs of a function following python rules. If there is a single value return
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// a SimpleValue, otherwise pack all the values into a Tuple.
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std::shared_ptr<SugaredValue> packOutputs(Graph& g, at::ArrayRef<Value*> values);
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std::vector<Value*> inlineCallTo(Graph& g, Graph& callee, ArrayRef<Value*> inputs);
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void ensureSizeMatches(SourceRange loc, size_t expected, size_t actual, const std::string& what);
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void ensureTensors(const SourceRange& range, at::ArrayRef<Value*> values);
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} // namespace script
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} // namespace jit
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} // namespace torch
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