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模型预处理层介绍(2) - Hashing

来源:博客园

Hashing的方式本质上也是分桶,在上一篇我们提到过的bucket的方式进行分桶,而在Hashingd的方法中,所有的输入都会通过Hash映射进行转换成int,然后再进行分桶。

该层将分类输入转换为散列输出。它在元素上将一个 int型或字符串转换为固定范围内的int型。稳定哈希函数使用tensorflow::ops::Fingerprint在所有平台上产生一致的输出。


【资料图】

该层默认使用FarmHash64,它在不同的平台上提供一致的散列输出,并且通过彻底混合输入位,在不同的调用中都是稳定的,而不考虑设备和上下文。

如果您想混淆散列输出,还可以在构造函数中传递一个随机salt参数。在这种情况下,该层将使用SipHash64哈希函数,将salt值作为哈希函数的额外输入。

tf.keras.layers.Hashing(    num_bins,    mask_value=None,    salt=None,    output_mode="int",    sparse=False,    **kwargs)

举个例子来说

layer = tf.keras.layers.Hashing(num_bins=3)inp = [["A"], ["B"], ["C"], ["D"], ["E"]]layer(inp)

执行上述语句的结果是:

我们向Hashing层传入了一个字符串的list的嵌套list,尝试使用Hashing的方法进行分桶。从结果上我们可以看到,[A,C,D]被分到一个桶,[B] [E]被分成另外两个桶。

被分入哪个桶取决于输入的字符串或者int被HASH成什么样的数值。从下面的代码可以直观的看出,其实不管传入的int还是string,都会在 tf.as_string(values)统一处理成string,然后在tf.strings.to_hash_bucket_*中全部再进行分桶。

def call(self, inputs):        inputs = utils.ensure_tensor(inputs)        if isinstance(inputs, tf.SparseTensor):            indices = tf.SparseTensor(                indices=inputs.indices,                values=self._hash_values_to_bins(inputs.values),                dense_shape=inputs.dense_shape,            )        else:            indices = self._hash_values_to_bins(inputs)        return utils.encode_categorical_inputs(            indices,            output_mode=self.output_mode,            depth=self.num_bins,            sparse=self.sparse,            dtype=self.compute_dtype,        )    def _hash_values_to_bins(self, values):        """Converts a non-sparse tensor of values to bin indices."""        hash_bins = self.num_bins        mask = None        # If mask_value is set, the zeroth bin is reserved for it.        if self.mask_value is not None and hash_bins > 1:            hash_bins -= 1            mask = tf.equal(values, self.mask_value)        # Convert all values to strings before hashing.        if values.dtype.is_integer:            values = tf.as_string(values)        # Hash the strings.        if self.strong_hash:            values = tf.strings.to_hash_bucket_strong(                values, hash_bins, name="hash", key=self.salt            )        else:            values = tf.strings.to_hash_bucket_fast(                values, hash_bins, name="hash"            )        if mask is not None:            values = tf.add(values, tf.ones_like(values))            values = tf.where(mask, tf.zeros_like(values), values)        return values

Hash 的作用:

Hash :散列,通过关于键值(key)的函数,将数据映射到内存存储中一个位置来访问。这个过程叫做Hash,这个映射函数称做散列函数,存放记录的数组称做散列表(Hash Table)。

后面补充一下FarmHash64的处理代码,仅供参考:

FarmHash64

//Google FarmHash#include typedef std::pair uint128_t;inline uint64_t Uint128Low64(const uint128_t x) { return x.first; }inline uint64_t Uint128High64(const uint128_t x) { return x.second; }inline uint128_t Uint128(uint64_t lo, uint64_t hi) { return uint128_t(lo, hi); }#define STATIC_INLINE static inlineusing namespace std;using ui = unsigned int;using ul = unsigned long;using uc = unsigned char;using ull = unsigned long long;// Some primes between 2^63 and 2^64 for various uses.static const uint64_t k0 = 0xc3a5c85c97cb3127ULL;static const uint64_t k1 = 0xb492b66fbe98f273ULL;static const uint64_t k2 = 0x9ae16a3b2f90404fULL;#define uint32_in_expected_order(x) (x)#define uint64_in_expected_order(x) (x)STATIC_INLINE uint64_t Fetch64(const char *p) {  uint64_t result;  memcpy(&result, p, sizeof(result));  return uint64_in_expected_order(result);}STATIC_INLINE uint32_t Fetch32(const char *p) {  uint32_t result;  memcpy(&result, p, sizeof(result));  return uint32_in_expected_order(result);}STATIC_INLINE uint32_t bswap_32(const uint32_t x) {  uint32_t y = x;  for (size_t i = 0; i> 1; i++) {    uint32_t d = sizeof(uint32_t) - i - 1;    uint32_t mh = ((uint32_t)0xff) << (d << 3);    uint32_t ml = ((uint32_t)0xff) << (i << 3);    uint32_t h = x & mh;    uint32_t l = x & ml;    uint64_t t = (l << ((d - i) << 3)) | (h >> ((d - i) << 3));    y = t | (y & ~(mh | ml));  }  return y;}STATIC_INLINE uint64_t bswap_64(const uint64_t x) {  uint64_t y = x;  for (size_t i = 0; i> 1; i++) {    uint64_t d = sizeof(uint64_t) - i - 1;    uint64_t mh = ((uint64_t)0xff) << (d << 3);    uint64_t ml = ((uint64_t)0xff) << (i << 3);    uint64_t h = x & mh;    uint64_t l = x & ml;    uint64_t t = (l << ((d - i) << 3)) | (h >> ((d - i) << 3));    y = t | (y & ~(mh | ml));  }  return y;}STATIC_INLINE uint32_t Bswap32(uint32_t val) { return bswap_32(val); }STATIC_INLINE uint64_t Bswap64(uint64_t val) { return bswap_64(val); }// FARMHASH PORTABILITY LAYER: bitwise rotSTATIC_INLINE uint32_t BasicRotate32(uint32_t val, int shift) {  // Avoid shifting by 32: doing so yields an undefined result.  return shift == 0 ? val : ((val >> shift) | (val << (32 - shift)));}STATIC_INLINE uint64_t BasicRotate64(uint64_t val, int shift) {  // Avoid shifting by 64: doing so yields an undefined result.  return shift == 0 ? val : ((val >> shift) | (val << (64 - shift)));}STATIC_INLINE uint32_t Rotate32(uint32_t val, int shift) {  return BasicRotate32(val, shift);}STATIC_INLINE uint64_t Rotate64(uint64_t val, int shift) {  return BasicRotate64(val, shift);}// Hash 128 input bits down to 64 bits of output.// This is intended to be a reasonably good hash function.// May change from time to time, may differ on different platforms, may differ// depending on NDEBUG.STATIC_INLINE uint64_t Hash128to64(uint128_t x) {  // Murmur-inspired hashing.  const uint64_t kMul = 0x9ddfea08eb382d69ULL;  uint64_t a = (Uint128Low64(x) ^ Uint128High64(x)) * kMul;  a ^= (a >> 47);  uint64_t b = (Uint128High64(x) ^ a) * kMul;  b ^= (b >> 47);  b *= kMul;  return b;}STATIC_INLINE uint64_t ShiftMix(uint64_t val) {  return val ^ (val >> 47);}STATIC_INLINE uint64_t HashLen16(uint64_t u, uint64_t v) {  return Hash128to64(Uint128(u, v));}STATIC_INLINE uint64_t HashLen16(uint64_t u, uint64_t v, uint64_t mul) {  // Murmur-inspired hashing.  uint64_t a = (u ^ v) * mul;  a ^= (a >> 47);  uint64_t b = (v ^ a) * mul;  b ^= (b >> 47);  b *= mul;  return b;}STATIC_INLINE uint64_t HashLen0to16(const char *s, size_t len) {  if (len >= 8) {    uint64_t mul = k2 + len * 2;    uint64_t a = Fetch64(s) + k2;    uint64_t b = Fetch64(s + len - 8);    uint64_t c = Rotate64(b, 37) * mul + a;    uint64_t d = (Rotate64(a, 25) + b) * mul;    return HashLen16(c, d, mul);  }  if (len >= 4) {    uint64_t mul = k2 + len * 2;    uint64_t a = Fetch32(s);    return HashLen16(len + (a << 3), Fetch32(s + len - 4), mul);  }  if (len > 0) {    uint8_t a = s[0];    uint8_t b = s[len >> 1];    uint8_t c = s[len - 1];    uint32_t y = static_cast(a) + (static_cast(b) << 8);    uint32_t z = len + (static_cast(c) << 2);    return ShiftMix(y * k2 ^ z * k0) * k2;  }  return k2;}// This probably works well for 16-byte strings as well, but it may be overkill// in that case.STATIC_INLINE uint64_t HashLen17to32(const char *s, size_t len) {  uint64_t mul = k2 + len * 2;  uint64_t a = Fetch64(s) * k1;  uint64_t b = Fetch64(s + 8);  uint64_t c = Fetch64(s + len - 8) * mul;  uint64_t d = Fetch64(s + len - 16) * k2;  return HashLen16(Rotate64(a + b, 43) + Rotate64(c, 30) + d,                   a + Rotate64(b + k2, 18) + c, mul);}// Return a 16-byte hash for 48 bytes.  Quick and dirty.// Callers do best to use "random-looking" values for a and b.STATIC_INLINE pair WeakHashLen32WithSeeds(    uint64_t w, uint64_t x, uint64_t y, uint64_t z, uint64_t a, uint64_t b) {  a += w;  b = Rotate64(b + a + z, 21);  uint64_t c = a;  a += x;  a += y;  b += Rotate64(a, 44);  return make_pair(a + z, b + c);}// Return a 16-byte hash for s[0] ... s[31], a, and b.  Quick and dirty.STATIC_INLINE pair WeakHashLen32WithSeeds(    const char* s, uint64_t a, uint64_t b) {  return WeakHashLen32WithSeeds(Fetch64(s),                                Fetch64(s + 8),                                Fetch64(s + 16),                                Fetch64(s + 24),                                a,                                b);}// Return an 8-byte hash for 33 to 64 bytes.STATIC_INLINE uint64_t HashLen33to64(const char *s, size_t len) {  uint64_t mul = k2 + len * 2;  uint64_t a = Fetch64(s) * k2;  uint64_t b = Fetch64(s + 8);  uint64_t c = Fetch64(s + len - 8) * mul;  uint64_t d = Fetch64(s + len - 16) * k2;  uint64_t y = Rotate64(a + b, 43) + Rotate64(c, 30) + d;  uint64_t z = HashLen16(y, a + Rotate64(b + k2, 18) + c, mul);  uint64_t e = Fetch64(s + 16) * mul;  uint64_t f = Fetch64(s + 24);  uint64_t g = (y + Fetch64(s + len - 32)) * mul;  uint64_t h = (z + Fetch64(s + len - 24)) * mul;  return HashLen16(Rotate64(e + f, 43) + Rotate64(g, 30) + h,                   e + Rotate64(f + a, 18) + g, mul);}uint64_t FarmHash64(const char *s, size_t len) {  const uint64_t seed = 81;  if (len <= 32) {    if (len <= 16) {      return HashLen0to16(s, len);    } else {      return HashLen17to32(s, len);    }  } else if (len <= 64) {    return HashLen33to64(s, len);  }  // For strings over 64 bytes we loop.  Internal state consists of  // 56 bytes: v, w, x, y, and z.  uint64_t x = seed;  uint64_t y = seed * k1 + 113;  uint64_t z = ShiftMix(y * k2 + 113) * k2;  pair v = make_pair(0, 0);  pair w = make_pair(0, 0);  x = x * k2 + Fetch64(s);  // Set end so that after the loop we have 1 to 64 bytes left to process.  const char* end = s + ((len - 1) / 64) * 64;  const char* last64 = end + ((len - 1) & 63) - 63;  assert(s + len - 64 == last64);  do {    x = Rotate64(x + y + v.first + Fetch64(s + 8), 37) * k1;    y = Rotate64(y + v.second + Fetch64(s + 48), 42) * k1;    x ^= w.second;    y += v.first + Fetch64(s + 40);    z = Rotate64(z + w.first, 33) * k1;    v = WeakHashLen32WithSeeds(s, v.second * k1, x + w.first);    w = WeakHashLen32WithSeeds(s + 32, z + w.second, y + Fetch64(s + 16));    std::swap(z, x);    s += 64;  } while (s != end);  uint64_t mul = k1 + ((z & 0xff) << 1);  // Make s point to the last 64 bytes of input.  s = last64;  w.first += ((len - 1) & 63);  v.first += w.first;  w.first += v.first;  x = Rotate64(x + y + v.first + Fetch64(s + 8), 37) * mul;  y = Rotate64(y + v.second + Fetch64(s + 48), 42) * mul;  x ^= w.second * 9;  y += v.first * 9 + Fetch64(s + 40);  z = Rotate64(z + w.first, 33) * mul;  v = WeakHashLen32WithSeeds(s, v.second * mul, x + w.first);  w = WeakHashLen32WithSeeds(s + 32, z + w.second, y + Fetch64(s + 16));  std::swap(z, x);  return HashLen16(HashLen16(v.first, w.first, mul) + ShiftMix(y) * k0 + z,                   HashLen16(v.second, w.second, mul) + x,                   mul);}int main(int argc, char** argv){  string str = "最強|Hash #2";  uint64_t x = FarmHash64(str.c_str(), str.size());  cout<< x <

参考

https://blog.csdn.net/cyongxue/article/details/19544107

https://tensorflow.google.cn/api_docs/python/tf/keras/layers/Hashing

https://github.com/keras-team/keras/blob/v2.11.0/keras/layers/preprocessing/hashing.py#L35-L298

https://blog.csdn.net/qq_43561345/article/details/116612560

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