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interned_strings.h
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interned_strings.h
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#pragma once
#include <vector>
#include <cstdint>
#include <string>
#include <unordered_map>
#include <algorithm>
#include <c10/macros/Macros.h>
#include <ATen/core/aten_interned_strings.h>
#include <ATen/core/symbol.h>
namespace c10 {
#define FORALL_NS_SYMBOLS(_) \
_(namespaces, prim) \
_(namespaces, aten) \
_(namespaces, cuda) \
_(namespaces, onnx) \
_(namespaces, attr) \
_(namespaces, scope) \
_(namespaces, user) \
_(namespaces, _caffe2) \
_(namespaces, dimname) \
_(namespaces, namespaces) \
_(prim, Assign) \
_(prim, BroadcastingChunk) \
_(prim, BroadcastSizes) \
_(prim, ReductionSizes) \
_(prim, Constant) \
_(prim, ChunkSizes) \
_(prim, ConstantMKLDNNTensor) \
_(prim, BroadcastMKLDNNTensors) \
_(prim, MKLDNNGroup) \
_(prim, MKLDNNHardSwish) \
_(prim, MKLDNNHardSigmoid) \
_(prim, MKLDNNHardTanh) \
_(prim, MKLDNNClamp) \
_(prim, StaticRuntimeCopyOuts) \
_(prim, Drop) \
_(prim, Eval) \
_(prim, Expand) /* onnx */ \
_(prim, FusionGroup) \
_(prim, CudaFusionGroup) \
_(prim, CudaFusionGuard) \
_(prim, FunctionalGraph) \
_(prim, add_optional) \
_(prim, view_copy) \
_(prim, reshape_copy) \
_(prim, squeeze_copy) \
_(prim, unsqueeze_copy) \
_(prim, DifferentiableGraph) \
_(prim, TensorExprGroup) \
_(prim, TensorExprDynamicGroup) \
_(prim, StaticSubgraph) \
_(prim, If) \
_(prim, Jump) /* debug */ \
_(prim, JumpNZ) /* debug */ \
_(prim, JumpZ) /* debug */ \
_(prim, Load) \
_(prim, Loop) \
_(prim, Param) \
_(prim, PackPadded) /* onnx */ \
_(prim, PadPacked) /* onnx */ \
_(prim, Placeholder) /* debug */ \
_(prim, Print) \
_(prim, EmptyListLiteral) \
_(prim, LegacyTypedConstructor) \
_(prim, PythonOp) \
_(prim, IgnoredPythonOp) \
_(prim, Reverse) \
_(prim, Return) \
_(prim, ReturnStmt) \
_(prim, BreakStmt) \
_(prim, ContinueStmt) \
_(prim, ComprehensionScope) \
_(prim, Store) \
_(prim, AutogradZero) \
_(prim, AutogradAnyNonZero) \
_(prim, AutogradAllNonZero) \
_(prim, AutogradAllZero) \
_(prim, Starred) \
_(prim, TupleConstruct) \
_(prim, TupleUnpack) \
_(prim, TupleIndex) \
_(prim, TupleSlice) \
_(prim, ListConstruct) \
_(prim, ListUnpack) \
_(prim, DictConstruct) \
_(prim, ModuleContainerIndex) \
_(prim, EnumName) \
_(prim, EnumValue) \
_(prim, StringIndex) \
_(prim, NumToTensor) \
_(prim, Uninitialized) \
_(prim, VarConcat) \
_(prim, VarStack) \
_(prim, With) \
_(prim, Enter) \
_(prim, Exit) \
_(prim, IfThenElse) \
_(aten, Bool) \
_(aten, Int) \
_(aten, FloatImplicit) \
_(aten, ComplexImplicit) \
_(aten, IntImplicit) \
_(aten, ScalarImplicit) \
_(aten, Float) \
_(aten, Complex) \
_(aten, str) \
_(aten, Delete) \
_(aten, gelu_) \
_(prim, device) \
_(prim, dtype) \
_(prim, layout) \
_(prim, id) \
_(prim, requires_grad) \
_(prim, MakeTestTensor) /* test */ \
_(prim, AutogradAdd) \
_(prim, GradOf) \
_(aten, grad) \
_(aten, backward) \
_(prim, Guard) \
_(prim, BailOut) \
_(prim, TypeCheck) \
_(prim, RequiresGradCheck) \
_(prim, FallbackGraph) \
_(prim, FusedConcat) \
_(prim, ConstantChunk) \
_(prim, MMTreeReduce) \
_(prim, MMBatchSide) \
_(prim, list) \
_(prim, dict) \
_(prim, min) \
_(prim, max) \
_(prim, abs) \
_(aten, divmod) \
_(prim, zip) \
_(prim, enumerate) \
_(prim, range) \
_(prim, rangelist) \
_(prim, isinstance) \
_(prim, tolist) \
_(prim, unchecked_cast) \
_(aten, _grad_sum_to_size) \
_(aten, _size_if_not_equal) \
_(aten, _ncf_unsqueeze) \
_(aten, warn) \
_(aten, sorted) \
_(aten, floordiv) \
_(aten, __range_length) \
_(aten, __derive_index) \
_(aten, __round_to_zero_floordiv) \
_(aten, is_scripting) \
_(aten, _unwrap_optional) \
_(prim, fork) \
_(prim, forkClosure) \
_(prim, RaiseException) \
_(prim, Closure) \
_(prim, CreateObject) \
_(prim, SetAttr) \
_(prim, GetAttr) \
_(prim, HasAttr) \
_(prim, profile) \
_(prim, profile_ivalue) \
_(prim, AddStatValue) \
_(prim, TimePoint) \
_(prim, CallFunction) \
_(prim, CallMethod) \
_(prim, LoopContinuation) \
_(prim, annotate) \
_(prim, TracedModuleForward) \
_(prim, TracedFork) \
_(prim, TracedAttr) \
_(prim, rpc_async) \
_(prim, rpc_sync) \
_(prim, rpc_remote) \
_(prim, is_cuda) \
_(aten, append) \
_(aten, as_tensor) \
_(aten, adaptive_avg_pool2d_backward) \
_(aten, dim) \
_(aten, format) \
_(aten, percentFormat) \
_(aten, __not__) \
_(aten, __is__) \
_(aten, __isnot__) \
_(aten, _ger) \
_(aten, __getitem__) \
_(aten, _set_item) \
_(aten, manual_seed) \
_(aten, device) \
_(aten, hash) \
_(aten, len) \
_(aten, list) \
_(aten, dict) \
_(aten, wait) \
_(aten, save) \
_(aten, keys) \
_(aten, ord) \
_(aten, chr) \
_(aten, hex) \
_(aten, oct) \
_(aten, clear) \
_(aten, setdefault) \
_(aten, bin) \
_(aten, pop) \
_(aten, insert) \
_(aten, tensor) \
_(prim, unchecked_unwrap_optional) \
_(aten, __contains__) \
_(prim, BailoutTemplate) \
_(prim, grad) \
_(cuda, _set_device) \
_(cuda, set_stream) \
_(cuda, _current_device) \
_(cuda, synchronize) \
_(aten, has_torch_function) \
FORALL_ATEN_BASE_SYMBOLS(_) \
_(onnx, Add) \
_(onnx, Concat) \
_(onnx, Constant) \
_(onnx, ConstantFill) \
_(onnx, Div) \
_(onnx, GRU) \
_(onnx, Gather) \
_(onnx, Gemm) \
_(onnx, LSTM) \
_(onnx, MatMul) \
_(onnx, Mul) \
_(onnx, Pow) \
_(onnx, RNN) \
_(onnx, Shape) \
_(onnx, Size) \
_(onnx, Slice) \
_(onnx, Softmax) \
_(onnx, Squeeze) \
_(onnx, Sub) \
_(onnx, Transpose) \
_(onnx, Unsqueeze) \
_(onnx, Loop) \
_(onnx, If) \
_(onnx, Reshape) \
_(onnx, Expand) \
_(onnx, Equal) \
_(onnx, Greater) \
_(onnx, GreaterOrEqual) \
_(onnx, Less) \
_(onnx, LessOrEqual) \
_(onnx, Not) \
_(onnx, ATen) \
_(onnx, Split) \
_(onnx, ConstantOfShape) \
_(onnx, Cast) \
_(onnx, Mod) \
_(onnx, Sqrt) \
_(onnx, SplitToSequence) \
_(onnx, SequenceAt) \
_(onnx, SequenceConstruct) \
_(onnx, SequenceEmpty) \
_(onnx, SequenceInsert) \
_(onnx, SequenceErase) \
_(onnx, ConcatFromSequence) \
_(onnx, Identity) \
_(onnx, SoftmaxCrossEntropyLoss) \
_(onnx, NegativeLogLikelihoodLoss) \
_(onnx, LogSoftmax) \
_(onnx, ReduceL1) \
_(onnx, ReduceL2) \
_(onnx, Conv) \
_(onnx, BatchNormalization) \
_(onnx, ReduceMean) \
_(onnx, ReduceProd) \
_(onnx, Relu) \
_(onnx, Neg) \
_(onnx, NonZero) \
_(onnx, Range) \
_(onnx, Tile) \
_(onnx, Where) \
FORALL_ATTR_BASE_SYMBOLS(_) \
_(attr, Subgraph) \
_(attr, ReverseSubgraph) \
_(attr, f_real_outputs) \
_(attr, df_input_vjps) \
_(attr, df_input_captured_inputs) \
_(attr, df_input_captured_outputs) \
_(attr, df_output_vjps) \
_(attr, axes) \
_(attr, symbolic_shape_inputs) \
_(attr, allow_stack_outputs) \
_(attr, striding_inputs_desc) \
_(attr, striding_outputs_desc) \
_(attr, broadcast) \
_(attr, direction) \
_(attr, ends) \
_(attr, inplace) \
_(attr, input_as_shape) \
_(attr, is_zero) \
_(attr, num_none) \
_(attr, num_present) \
_(attr, perm) \
_(attr, starts) \
_(attr, profiled_type) \
_(attr, transA) \
_(attr, transB) \
_(attr, name) \
_(attr, module) \
_(attr, beg) \
_(attr, idx) \
_(attr, split) \
_(attr, slot) \
_(attr, kinds) \
_(attr, types) \
_(attr, scope) \
_(attr, keepdims) \
_(attr, cache_id) \
_(attr, new_axis) \
_(attr, warn_id) \
_(attr, allowzero) \
_(attr, seen_none)
enum class _keys : unique_t {
#define DEFINE_KEY(ns, s) ns##_##s,
FORALL_NS_SYMBOLS(DEFINE_KEY)
#undef DEFINE_KEY
num_symbols
};
#define DEFINE_SYMBOL(ns, s) \
namespace ns { constexpr Symbol s(static_cast<unique_t>(_keys::ns##_##s)); }
FORALL_NS_SYMBOLS(DEFINE_SYMBOL)
#undef DEFINE_SYMBOL
} // namespace c10