FM / core

/usr/local/lib64/python3.6/site-packages/torch/include/ATen/core/

/usr/local/lib64/python3.6/site-packages/torch/include/ATen/core

Name	Size	Mode	Actions
boxing/	-	0755	rm
dispatch/	-	0755	rm
op_registration/	-	0755	rm
alias_info.h	2986	0644	edit dl rm
Array.h	768	0644	edit dl rm
ATenGeneral.h	45	0644	edit dl rm
ATenOpList.h	246	0644	edit dl rm
aten_interned_strings.h	25389	0644	edit dl rm
Backtrace.h	59	0644	edit dl rm
blob.h	5422	0644	edit dl rm
builtin_function.h	3649	0644	edit dl rm
DeprecatedTypeProperties.h	3773	0644	edit dl rm
DeprecatedTypePropertiesRegistry.h	795	0644	edit dl rm
Dict.h	13195	0644	edit dl rm
Dict_inl.h	7996	0644	edit dl rm
Dimname.h	1188	0644	edit dl rm
DimVector.h	247	0644	edit dl rm
DistributionsHelper.h	12594	0644	edit dl rm
Formatting.h	959	0644	edit dl rm
function.h	2145	0644	edit dl rm
functional.h	1460	0644	edit dl rm
function_schema.h	13577	0644	edit dl rm
function_schema_inl.h	9319	0644	edit dl rm
Generator.h	4935	0644	edit dl rm
grad_mode.h	210	0644	edit dl rm
interned_strings.h	25332	0644	edit dl rm
interned_strings_class.h	770	0644	edit dl rm
ivalue.h	38823	0644	edit dl rm
ivalue_inl.h	59963	0644	edit dl rm
ivalue_to.h	756	0644	edit dl rm
jit_type.h	75971	0644	edit dl rm
jit_type_base.h	6508	0644	edit dl rm
LegacyTypeDispatch.h	4626	0644	edit dl rm
List.h	15667	0644	edit dl rm
List_inl.h	11012	0644	edit dl rm
Macros.h	44	0644	edit dl rm
MT19937RNGEngine.h	6410	0644	edit dl rm
NamedTensor.h	5050	0644	edit dl rm
operator_name.h	3018	0644	edit dl rm
PhiloxRNGEngine.h	6496	0644	edit dl rm
PythonModeTLS.h	403	0644	edit dl rm
qualified_name.h	4358	0644	edit dl rm
QuantizerBase.h	2443	0644	edit dl rm
Range.h	418	0644	edit dl rm
Reduction.h	461	0644	edit dl rm
rref_interface.h	1144	0644	edit dl rm
Scalar.h	29	0644	edit dl rm
ScalarType.h	33	0644	edit dl rm
stack.h	6034	0644	edit dl rm
Tensor.h	1756	0644	edit dl rm
TensorAccessor.h	10296	0644	edit dl rm
TensorBase.h	32767	0644	edit dl rm
TensorBody.h	247555	0644	edit dl rm
TransformationHelper.h	6911	0644	edit dl rm
typeid.h	29	0644	edit dl rm
UndefinedTensorImpl.h	42	0644	edit dl rm
UnsafeFromTH.h	708	0644	edit dl rm
VariableHooksInterface.h	3312	0644	edit dl rm
Variadic.h	2257	0644	edit dl rm
Vitals.h	2305	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/torch/include/ATen/core/function_schema.h (13577B)

#pragma once

#include <c10/util/StringUtil.h>
#include <c10/util/string_view.h>
#include <ATen/core/jit_type.h>
#include <ATen/core/interned_strings.h>
#include <ATen/core/ivalue.h>
#include <ATen/core/alias_info.h>
#include <ATen/core/operator_name.h>
#include <ATen/core/dispatch/OperatorOptions.h>
#include <unordered_map>

namespace c10 {

// schema as used in the compiler for resolving function calls and reporting
// errors. These objects should be constructed from C10 schema once those
// are available.

struct Argument;
struct FunctionSchema;

bool operator==(const Argument& lhs, const Argument& rhs);

struct Argument {
  Argument(
      std::string name = "",
      TypePtr type = nullptr,
      c10::optional<int32_t> N = c10::nullopt,
      c10::optional<IValue> default_value = c10::nullopt,
      bool kwarg_only = false,
      c10::optional<AliasInfo> alias_info = c10::nullopt)
      : name_(std::move(name)),
        type_(type ? std::move(type) : TensorType::get()),
        N_(std::move(N)),
        default_value_(std::move(default_value)),
        alias_info_(std::move(alias_info)),
        kwarg_only_(kwarg_only) {
    // this is an softly-enforced invariant for out arguments.
    bool is_alias = alias_info_.has_value() && alias_info_.value().isWrite();
    is_out_ = kwarg_only_ && is_alias;
  }
  const std::string& name() const {
    return name_;
  }
  const TypePtr& type() const {
    return type_;
  }
  c10::optional<int32_t> N() const {
    return N_;
  }
  const c10::optional<IValue>& default_value() const {
    return default_value_;
  }
  bool kwarg_only() const {
    return kwarg_only_;
  }

bool is_out() const {
    return is_out_;
  }

const c10::optional<AliasInfo>& alias_info() const {
    return alias_info_;
  }
  bool is_inferred_type() const {
    bool is_inferred_type = false;
    TORCH_INTERNAL_ASSERT(type_);
    if (auto pt = type_->cast<TensorType>()) {
      if (pt->isInferredType()) {
        is_inferred_type = true;
      }
    }
    return is_inferred_type;
  }

std::string formatTypeMismatchMsg(const std::string& actual_type) const {
    std::string inferred_type_hint;
    if (is_inferred_type()) {
      inferred_type_hint = c10::str(
          "Inferred '",
          name(),
          "' to be of type 'Tensor' ",
          "because it was not annotated with an explicit type.\n");
    }
    return c10::str(
        "Expected a value of type '",
        type()->repr_str(),
        "' for argument '",
        name(),
        "' but instead found type '",
        actual_type,
        "'.\n",
        inferred_type_hint);
  }

Argument cloneWithType(TypePtr new_type) const {
    return Argument(
        name_,
        std::move(new_type),
        N_,
        default_value_,
        kwarg_only_,
        alias_info_);
  }

// this function checks whether this Argument is backward compatible with
  // the old one. we consider the following cases are backward compatible:
  //   1) two arguments are equal
  //   2) this arg's type should be subtype of old
  //   3) this arg must provide the same default value if old arg has one,
  bool isBackwardCompatibleWith(
      const Argument& old,
      std::ostream* why_not=nullptr) const;

private:
  std::string name_;
  TypePtr type_;
  // for list types, an optional statically known length for the list
  // e.g. for int[3]: type = ListType::ofInts(), N = 3
  // If present, this will allow scalars to be broadcast to this length to
  // become a list.
  c10::optional<int32_t> N_;

c10::optional<IValue> default_value_;
  c10::optional<AliasInfo> alias_info_;
  // is this only specifiable as a keyword argument?
  bool kwarg_only_;
  // marks if the argument is out variant of the schema
  bool is_out_;
};

inline bool operator==(const Argument& lhs, const Argument& rhs) {
  return lhs.name() == rhs.name()
          && *lhs.type() == *rhs.type()
          && lhs.N() == rhs.N()
          && lhs.default_value() == rhs.default_value()
          && lhs.kwarg_only() == rhs.kwarg_only()
          && lhs.alias_info() == rhs.alias_info();
}

bool operator==(const FunctionSchema& lhs, const FunctionSchema& rhs);

struct FunctionSchema {
  FunctionSchema(
      std::string name,
      std::string overload_name,
      std::vector<Argument> arguments,
      std::vector<Argument> returns,
      bool is_vararg = false,
      bool is_varret = false)
      : name_({std::move(name), std::move(overload_name)}),
        arguments_(std::move(arguments)),
        returns_(std::move(returns)),
        is_vararg_(is_vararg),
        is_varret_(is_varret) {
    checkSchema();
  }

FunctionSchema(
      Symbol name,
      std::string overload_name,
      std::vector<Argument> arguments,
      std::vector<Argument> returns,
      bool is_vararg = false,
      bool is_varret = false)
      : FunctionSchema(
            name.toQualString(),
            std::move(overload_name),
            std::move(arguments),
            std::move(returns),
            is_vararg,
            is_varret) {
    checkSchema();
  }

// Checks whether this schema is backward compatible with the old one.
  // The following conditions must be true:
  // [Function structure] The new schema's name, overload-name, varargs, and
  //      return arity are the same.
  // [Output Narrowing] The new schema's output type must be the same class
  //      or inherit from the old schema's output type.
  // [Argument count] The new schema must have at least as many arguments as
  //      the old schema (considering the list of positional and kwargs).
  // [Arg Compatibility] Every argument in the old schema has a corresponding
  //      argument in the new schema that:
  //        * is at the same position.
  //        * has the same name.
  //        * is either positional, or kwarg and the old argument was kwarg.
  //        * has the same type, or the old argument's type inherits from the
  //          new argument's type.
  // [Default Values] Every new argument must have a default value.
  // E.g.
  //   OK    f_new(a, b, c=1) => f_old(a, b)
  //   NOK   f_new(a, c=1, *, b) => f_old(a, *, b)
  //   OK    f_new(a, b, *, c) => f_old(a, *, b, c)
  //   NOK   f_new(a, *, b, c) -> f_old(a, b, *, c)
  //   NOK   f_new(a, *, c, b) => f_old(a, *, b, c)
  //   OK    f_new(a, *, b, c, d=1) => f_old(a, *, b, c)
  bool isBackwardCompatibleWith(
      const FunctionSchema& old,
      std::ostream* why_not = nullptr) const;

private:
  OperatorName name_;
  std::vector<Argument> arguments_;
  std::vector<Argument> returns_;
  // if true then this schema takes an arbitrary number of additional arguments
  // after the argument specified in arguments
  // currently this is used primarily to represent 'primitive' operators whose
  // arguments are not checked by schema
  bool is_vararg_;
  bool is_varret_;

// if no alias information is directly specified, what kind of "default"
  // alias information should we infer?
  // NB: due to alias analysis kind merging, this may be nullopt.  Eventually
  // this should always be set no matter what
  c10::optional<AliasAnalysisKind> alias_kind_;

void checkArg(const IValue& value, const Argument& argument, optional<size_t> pos) const;

void checkSchema() const {
    bool seen_default_arg = false;
    for (const auto& arg : arguments()) {
      if (arg.default_value()) {
        seen_default_arg = true;
      } else {
        // we have historically serialized broadcasting lists wo/default values,
        // so to not break BC allow lists here
        if (arg.type()->kind() == ListType::Kind) {
          continue;
        }
        TORCH_INTERNAL_ASSERT(
            !seen_default_arg || arg.kwarg_only(),
            "Non-default positional argument follows default argument. Parameter ",
            arg.name(),
            " in ",
            *this);
      }
    }
  }

public:

void dump() const;

const OperatorName& operator_name() const {
    return name_;
  }
  const std::string& name() const {
    return name_.name;
  }
  const std::string& overload_name() const {
    return name_.overload_name;
  }
  const std::vector<Argument>& arguments() const {
    return arguments_;
  }
  const std::vector<Argument>& returns() const {
    return returns_;
  }
  bool is_vararg() const {
    return is_vararg_;
  }
  bool is_varret() const {
    return is_varret_;
  }
  bool is_mutable() const {
    return std::any_of(
        arguments_.cbegin(), arguments_.cend(), [](const Argument& arg) {
          const auto& aliasInfo = arg.alias_info();
          return aliasInfo && aliasInfo.value().isWrite();
        });
  }

c10::optional<int> argumentIndexWithName(c10::string_view name) const {
    for(size_t i = 0; i < arguments().size(); ++i) {
      if(name == arguments()[i].name())
        return i;
    }
    return c10::nullopt;
  }
  FunctionSchema cloneWithName(std::string name, std::string overload_name) const {
    return FunctionSchema(
        std::move(name),
        std::move(overload_name),
        arguments(),
        returns(),
        is_vararg(),
        is_varret()
        );
  }
  FunctionSchema cloneWithArguments(std::vector<Argument> new_arguments) const {
    return FunctionSchema(
        name(),
        overload_name(),
        std::move(new_arguments),
        returns(),
        is_vararg(),
        is_varret());
  }
  FunctionSchema cloneWithReturns(std::vector<Argument> new_returns) const {
    return FunctionSchema(
        name(),
        overload_name(),
        arguments(),
        std::move(new_returns),
        is_vararg(),
        is_varret());
  }

std::string formatTypeMismatchMsg(
      const Argument& expected,
      const std::string& actual_type,
      c10::optional<size_t> position = c10::nullopt,
      c10::optional<std::string> value = c10::nullopt) const;

FunctionSchema cloneWithRemappedTypes(
      const std::function<TypePtr(TypePtr)> type_map) const;

// Check that inputs have the correct types and appends any missing default
  // values.
  void checkAndNormalizeInputs(
      std::vector<IValue>& inputs,
      const std::unordered_map<std::string, IValue>& kwargs =
          std::unordered_map<std::string, IValue>{}) const;

std::string findErrorInKwargs(const std::vector<std::string>& kwargs) const;

bool hasAnyAliasInfo() const {
    for (const auto& arg : arguments_) {
      if (arg.alias_info().has_value()) {
        return true;
      }
    }
    for (const auto& ret : returns_) {
      if (ret.alias_info().has_value()) {
        return true;
      }
    }
    return false;
  }

// TODO remove the mutation here
  bool isDefaultAliasAnalysisKind() const {
    return !alias_kind_;
  }
  AliasAnalysisKind aliasAnalysis() const {
    return alias_kind_.value_or(AliasAnalysisKind::CONSERVATIVE);
  }
  void setAliasAnalysis(AliasAnalysisKind v) {
    alias_kind_ = v;
  }

c10::optional<c10::string_view> getNamespace() const {
    return name_.getNamespace();
  }

// Returns true if we successfully set the namespace (as there
  // was none set, and false otherwise)
  bool setNamespaceIfNotSet(const char* ns) {
    return name_.setNamespaceIfNotSet(ns);
  }

// can a function with this schema be substituted for a function of rhs's
  // schema and have the program typecheck?
  // as_method - if true, treat this schema as a method and ignore
  // the first argument, which will be the object in both cases
  bool isSubtypeOf(const FunctionSchema& rhs, bool as_method, std::ostream* why_not=nullptr) const;
};

inline bool operator==(const FunctionSchema& lhs, const FunctionSchema& rhs) {
  return lhs.name() == rhs.name()
     && lhs.overload_name() == rhs.overload_name()
     && lhs.arguments() == rhs.arguments()
     && lhs.returns() == rhs.returns()
     && lhs.is_vararg() == rhs.is_vararg()
     && lhs.is_varret() == rhs.is_varret();
}

inline bool operator!=(const FunctionSchema& lhs, const FunctionSchema& rhs) {
  return !(lhs == rhs);
}

// print out Argument, which is compatible with FunctionSchema parser
// full format: Type(alias)? name=default_value
inline std::ostream& operator<<(std::ostream& out, const Argument& arg) {

// for adjusting the ? position.
  // in schema, we have Tensor?(a!) input, and t(a!)?.
  // however, t?(a!) doesn't work with schema parser.
  // so we always use Type(alias)? format
  auto type = arg.type();
  bool is_opt = type->kind() == OptionalType::Kind;
  auto unopt_type = is_opt ? type->castRaw<OptionalType>()->getElementType() : type;

if (unopt_type->kind() == ListType::Kind && arg.N()) {
    // sized lists get size N from arg, not type
    auto list = unopt_type->cast<c10::ListType>();
    out << list->getElementType()->str() << "[" << *arg.N() << "]";
  } else {
    out << unopt_type->str();
  }

if (arg.alias_info()) {
    out << arg.alias_info().value();
  }

if (is_opt) {
    out << "?";
  }

if (!arg.name().empty()) {
    out << " " << arg.name();
  }

if (arg.default_value()) {
    out << "=";
    if (type->kind() == c10::TypeKind::StringType || (unopt_type->kind() == c10::TypeKind::StringType && !arg.default_value().value().isNone())) {
      printQuotedString(out, arg.default_value().value().toStringRef());
    } else {
      out << arg.default_value().value();
    }
  }

return out;
}

inline std::ostream& operator<<(std::ostream& out, const FunctionSchema& schema);

inline std::string toString(const FunctionSchema& schema) {
  std::ostringstream str;
  str << schema;
  return str.str();
}

} // namespace c10

#include <ATen/core/function_schema_inl.h>

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