/*
 * SPDX-License-Identifier: Apache-2.0
 */

// ATTENTION: The code in this file is highly EXPERIMENTAL.
// Adventurous users should note that the APIs will probably change.

#pragma once
#include <stdint.h>
#include <string>
#include <unordered_map>
#include <vector>

namespace ONNX_NAMESPACE {

#define FORALL_BUILTIN_SYMBOLS(_) \
  _(PythonOp)                     \
  _(CppOp)                        \
  _(Param)                        \
  _(Select)                       \
  _(Return)                       \
  _(Eval)                         \
  _(add)                          \
  _(Add)                          \
  _(Div)                          \
  _(Mul)                          \
  _(Neg)                          \
  _(Sub)                          \
  _(Pow)                          \
  _(Sigmoid)                      \
  _(ArgMax)                       \
  _(Concat)                       \
  _(Softmax)                      \
  _(LogSoftmax)                   \
  _(Dropout)                      \
  _(Tanh)                         \
  _(mul)                          \
  _(neg)                          \
  _(sigmoid)                      \
  _(tanh)                         \
  _(Constant)                     \
  _(cat)                          \
  _(Slice)                        \
  _(Squeeze)                      \
  _(Undefined)                    \
  _(FusionGroup)                  \
  _(MatMul)                       \
  _(Gemm)                         \
  _(Tile)                         \
  _(SubConstant)                  \
  _(Scale)                        \
  _(Transpose)                    \
  _(Pad)                          \
  _(Reshape)                      \
  _(split)                        \
  _(chunk)                        \
  _(Offset)                       \
  _(value)                        \
  _(Subgraph)                     \
  _(BatchNormalization)           \
  _(Conv)                         \
  _(ConvTranspose)                \
  _(is_test)                      \
  _(epsilon)                      \
  _(expand)                       \
  _(Expand)                       \
  _(order)                        \
  _(momentum)                     \
  _(consumed_inputs)              \
  _(kernels)                      \
  _(kernel_shape)                 \
  _(kernel)                       \
  _(scale)                        \
  _(strides)                      \
  _(stride)                       \
  _(pads)                         \
  _(pad)                          \
  _(beta)                         \
  _(alpha)                        \
  _(dilations)                    \
  _(dilation)                     \
  _(broadcast)                    \
  _(axis)                         \
  _(ratio)                        \
  _(size)                         \
  _(dim)                          \
  _(keepdims)                     \
  _(perm)                         \
  _(shape)                        \
  _(axes)                         \
  _(group)                        \
  _(inplace)                      \
  _(transA)                       \
  _(transB)                       \
  _(other)                        \
  _(__and__)                      \
  _(__lshift__)                   \
  _(__or__)                       \
  _(__rshift__)                   \
  _(__xor__)                      \
  _(abs)                          \
  _(acos)                         \
  _(asin)                         \
  _(atan)                         \
  _(atan2)                        \
  _(ceil)                         \
  _(clamp)                        \
  _(cos)                          \
  _(cosh)                         \
  _(div)                          \
  _(eq)                           \
  _(equal)                        \
  _(Exp)                          \
  _(ends)                         \
  _(expm1)                        \
  _(floor)                        \
  _(fmod)                         \
  _(frac)                         \
  _(ge)                           \
  _(gt)                           \
  _(le)                           \
  _(lerp)                         \
  _(lgamma)                       \
  _(Log)                          \
  _(log1p)                        \
  _(lt)                           \
  _(max)                          \
  _(min)                          \
  _(ne)                           \
  _(ones)                         \
  _(pow)                          \
  _(reciprocal)                   \
  _(remainder)                    \
  _(round)                        \
  _(rsqrt)                        \
  _(sin)                          \
  _(sinh)                         \
  _(Sqrt)                         \
  _(sub)                          \
  _(starts)                       \
  _(tan)                          \
  _(trunc)                        \
  _(zeros)                        \
  _(exponent)                     \
  _(device)                       \
  _(mode)                         \
  _(Identity)                     \
  _(Loop)                         \
  _(If)                           \
  _(body)                         \
  _(then_branch)                  \
  _(else_branch)                  \
  _(Captured)                     \
  _(__control_inputs)             \
  _(count_include_pad)            \
  _(storage_order)                \
  _(Unsqueeze)                    \
  _(ReduceL1)                     \
  _(ReduceL2)                     \
  _(ReduceLogSum)                 \
  _(ReduceLogSumExp)              \
  _(ReduceMax)                    \
  _(ReduceMean)                   \
  _(ReduceMin)                    \
  _(ReduceProd)                   \
  _(ReduceSum)                    \
  _(ReduceSumSquare)              \
  _(Cast)                         \
  _(to)                           \
  _(PRelu)                        \
  _(Greater)                      \
  _(Less)                         \
  _(scales)                       \
  _(Upsample)                     \
  _(RNN)                          \
  _(layout)                       \
  _(k)                            \
  _(Flatten)

enum BuiltinSymbol {
#define DEFINE_SYMBOL(s) k##s,
  FORALL_BUILTIN_SYMBOLS(DEFINE_SYMBOL)
#undef DEFINE_SYMBOL
      kLastSymbol, // where we start counting for new symbols
};

struct Symbol {
  Symbol() {}
  /*implicit*/ Symbol(BuiltinSymbol value) : value(value) {}
  explicit Symbol(const std::string& s);
  explicit Symbol(uint32_t value) : value(value) {}

  operator uint32_t() const {
    return value;
  }
  const char* toString() const;

 private:
  uint32_t value;
};

static inline bool operator==(Symbol lhs, Symbol rhs) {
  return static_cast<uint32_t>(lhs) == static_cast<uint32_t>(rhs);
}
// necessary to prevent ambiguous overload resolutions
static inline bool operator==(BuiltinSymbol lhs, Symbol rhs) {
  return static_cast<uint32_t>(lhs) == static_cast<uint32_t>(rhs);
}
static inline bool operator==(Symbol lhs, BuiltinSymbol rhs) {
  return static_cast<uint32_t>(lhs) == static_cast<uint32_t>(rhs);
}

inline Symbol operator"" _sym(const char* s, size_t) {
  return Symbol(s);
}

} // namespace ONNX_NAMESPACE

// make symbol behave like an integer in hash tables
namespace std {
template <>
struct hash<ONNX_NAMESPACE::Symbol> {
  std::size_t operator()(ONNX_NAMESPACE::Symbol s) const {
    return std::hash<uint32_t>()(static_cast<uint32_t>(s));
  }
};

} // namespace std
