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// #status: RECOMMENDED
// #category: operations on strings
// #summary: Merges strings or numbers with no delimiter.
//
#ifndef TENSORFLOW_LIB_STRINGS_STRCAT_H_
#define TENSORFLOW_LIB_STRINGS_STRCAT_H_
#include <string>
#include "tensorflow/core/lib/core/stringpiece.h"
#include "tensorflow/core/lib/strings/numbers.h"
#include "tensorflow/core/platform/port.h"
// The AlphaNum type was designed to be used as the parameter type for StrCat().
// Any routine accepting either a string or a number may accept it.
// The basic idea is that by accepting a "const AlphaNum &" as an argument
// to your function, your callers will automagically convert bools, integers,
// and floating point values to strings for you.
//
// NOTE: Use of AlphaNum outside of the //strings package is unsupported except
// for the specific case of function parameters of type "AlphaNum" or "const
// AlphaNum &". In particular, instantiating AlphaNum directly as a stack
// variable is not supported.
//
// Conversion from 8-bit values is not accepted because if it were, then an
// attempt to pass ':' instead of ":" might result in a 58 ending up in your
// result.
//
// Bools convert to "0" or "1".
//
// Floating point values are converted to a string which, if passed to strtod(),
// would produce the exact same original double (except in case of NaN; all NaNs
// are considered the same value). We try to keep the string short but it's not
// guaranteed to be as short as possible.
//
// You can convert to Hexadecimal output rather than Decimal output using Hex.
// To do this, pass strings::Hex(my_int) as a parameter to StrCat. You may
// specify a minimum field width using a separate parameter, so the equivalent
// of Printf("%04x", my_int) is StrCat(Hex(my_int, strings::ZERO_PAD_4))
//
// This class has implicit constructors.
namespace tensorflow {
namespace strings {
enum PadSpec {
NO_PAD = 1,
ZERO_PAD_2,
ZERO_PAD_3,
ZERO_PAD_4,
ZERO_PAD_5,
ZERO_PAD_6,
ZERO_PAD_7,
ZERO_PAD_8,
ZERO_PAD_9,
ZERO_PAD_10,
ZERO_PAD_11,
ZERO_PAD_12,
ZERO_PAD_13,
ZERO_PAD_14,
ZERO_PAD_15,
ZERO_PAD_16,
};
struct Hex {
uint64 value;
enum PadSpec spec;
template <class Int>
explicit Hex(Int v, PadSpec s = NO_PAD)
: spec(s) {
// Prevent sign-extension by casting integers to
// their unsigned counterparts.
static_assert(
sizeof(v) == 1 || sizeof(v) == 2 || sizeof(v) == 4 || sizeof(v) == 8,
"Unknown integer type");
value = sizeof(v) == 1
? static_cast<uint8>(v)
: sizeof(v) == 2 ? static_cast<uint16>(v)
: sizeof(v) == 4 ? static_cast<uint32>(v)
: static_cast<uint64>(v);
}
};
class AlphaNum {
public:
// No bool ctor -- bools convert to an integral type.
// A bool ctor would also convert incoming pointers (bletch).
AlphaNum(int i32) // NOLINT(runtime/explicit)
: piece_(digits_, FastInt32ToBufferLeft(i32, digits_) - &digits_[0]) {}
AlphaNum(unsigned int u32) // NOLINT(runtime/explicit)
: piece_(digits_, FastUInt32ToBufferLeft(u32, digits_) - &digits_[0]) {}
AlphaNum(long x) // NOLINT(runtime/explicit)
: piece_(digits_, FastInt64ToBufferLeft(x, digits_) - &digits_[0]) {}
AlphaNum(unsigned long x) // NOLINT(runtime/explicit)
: piece_(digits_, FastUInt64ToBufferLeft(x, digits_) - &digits_[0]) {}
AlphaNum(long long int i64) // NOLINT(runtime/explicit)
: piece_(digits_, FastInt64ToBufferLeft(i64, digits_) - &digits_[0]) {}
AlphaNum(unsigned long long int u64) // NOLINT(runtime/explicit)
: piece_(digits_, FastUInt64ToBufferLeft(u64, digits_) - &digits_[0]) {}
AlphaNum(float f) // NOLINT(runtime/explicit)
: piece_(digits_, strlen(FloatToBuffer(f, digits_))) {}
AlphaNum(double f) // NOLINT(runtime/explicit)
: piece_(digits_, strlen(DoubleToBuffer(f, digits_))) {}
AlphaNum(Hex hex); // NOLINT(runtime/explicit)
AlphaNum(const char *c_str) : piece_(c_str) {} // NOLINT(runtime/explicit)
AlphaNum(const StringPiece &pc) : piece_(pc) {} // NOLINT(runtime/explicit)
AlphaNum(const tensorflow::string &str) // NOLINT(runtime/explicit)
: piece_(str) {}
StringPiece::size_type size() const { return piece_.size(); }
const char *data() const { return piece_.data(); }
StringPiece Piece() const { return piece_; }
private:
StringPiece piece_;
char digits_[kFastToBufferSize];
// Use ":" not ':'
AlphaNum(char c); // NOLINT(runtime/explicit)
TF_DISALLOW_COPY_AND_ASSIGN(AlphaNum);
};
extern AlphaNum gEmptyAlphaNum;
using strings::AlphaNum;
using strings::gEmptyAlphaNum;
// ----------------------------------------------------------------------
// StrCat()
// This merges the given strings or numbers, with no delimiter. This
// is designed to be the fastest possible way to construct a string out
// of a mix of raw C strings, StringPieces, strings, bool values,
// and numeric values.
//
// Don't use this for user-visible strings. The localization process
// works poorly on strings built up out of fragments.
//
// For clarity and performance, don't use StrCat when appending to a
// string. In particular, avoid using any of these (anti-)patterns:
// str.append(StrCat(...))
// str += StrCat(...)
// str = StrCat(str, ...)
// where the last is the worse, with the potential to change a loop
// from a linear time operation with O(1) dynamic allocations into a
// quadratic time operation with O(n) dynamic allocations. StrAppend
// is a better choice than any of the above, subject to the restriction
// of StrAppend(&str, a, b, c, ...) that none of the a, b, c, ... may
// be a reference into str.
// ----------------------------------------------------------------------
// For performance reasons, we have specializations for <= 4 args.
string StrCat(const AlphaNum &a) TF_MUST_USE_RESULT;
string StrCat(const AlphaNum &a, const AlphaNum &b) TF_MUST_USE_RESULT;
string StrCat(const AlphaNum &a, const AlphaNum &b,
const AlphaNum &c) TF_MUST_USE_RESULT;
string StrCat(const AlphaNum &a, const AlphaNum &b, const AlphaNum &c,
const AlphaNum &d) TF_MUST_USE_RESULT;
// inline definitions must be duplicated due to TF_MUST_USE_RESULT
inline string StrCat(const AlphaNum &a) { return string(a.data(), a.size()); }
namespace internal {
// Do not call directly - this is not part of the public API.
string CatPieces(std::initializer_list<StringPiece> pieces);
void AppendPieces(string *dest, std::initializer_list<StringPiece> pieces);
} // namespace internal
// Support 5 or more arguments
template <typename... AV>
string StrCat(const AlphaNum &a, const AlphaNum &b, const AlphaNum &c,
const AlphaNum &d, const AlphaNum &e,
const AV &... args) TF_MUST_USE_RESULT;
template <typename... AV>
inline string StrCat(const AlphaNum &a, const AlphaNum &b, const AlphaNum &c,
const AlphaNum &d, const AlphaNum &e, const AV &... args) {
return internal::CatPieces({a.Piece(), b.Piece(), c.Piece(), d.Piece(),
e.Piece(),
static_cast<const AlphaNum &>(args).Piece()...});
}
// ----------------------------------------------------------------------
// StrAppend()
// Same as above, but adds the output to the given string.
// WARNING: For speed, StrAppend does not try to check each of its input
// arguments to be sure that they are not a subset of the string being
// appended to. That is, while this will work:
//
// string s = "foo";
// s += s;
//
// This will not (necessarily) work:
//
// string s = "foo";
// StrAppend(&s, s);
//
// Note: while StrCat supports appending up to 26 arguments, StrAppend
// is currently limited to 9. That's rarely an issue except when
// automatically transforming StrCat to StrAppend, and can easily be
// worked around as consecutive calls to StrAppend are quite efficient.
// ----------------------------------------------------------------------
void StrAppend(string *dest, const AlphaNum &a);
void StrAppend(string *dest, const AlphaNum &a, const AlphaNum &b);
void StrAppend(string *dest, const AlphaNum &a, const AlphaNum &b,
const AlphaNum &c);
void StrAppend(string *dest, const AlphaNum &a, const AlphaNum &b,
const AlphaNum &c, const AlphaNum &d);
// Support 5 or more arguments
template <typename... AV>
inline void StrAppend(string *dest, const AlphaNum &a, const AlphaNum &b,
const AlphaNum &c, const AlphaNum &d, const AlphaNum &e,
const AV &... args) {
internal::AppendPieces(dest,
{a.Piece(), b.Piece(), c.Piece(), d.Piece(), e.Piece(),
static_cast<const AlphaNum &>(args).Piece()...});
}
} // namespace strings
} // namespace tensorflow
#endif // TENSORFLOW_LIB_STRINGS_STRCAT_H_
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