34 void MatrixBatchVectorMultiplyAccumulate(const int8_t* input, const int32_t* bias,  in MatrixBatchVectorMultiplyAccumulate()  argument
44                 int8_t input_val = input[batch * n_input + col];  in MatrixBatchVectorMultiplyAccumulate()
82 inline bool GetInvSqrtQuantizedMultiplierExp(int32_t input, int reverse_shift,  in GetInvSqrtQuantizedMultiplierExp()  argument
84     NN_RET_CHECK_GE(input, 0);  in GetInvSqrtQuantizedMultiplierExp()
85     if (input <= 1) {  in GetInvSqrtQuantizedMultiplierExp()
97     while (input >= (1 << 29)) {  in GetInvSqrtQuantizedMultiplierExp()
98         input /= 4;  in GetInvSqrtQuantizedMultiplierExp()
101     const unsigned max_left_shift_bits = CountLeadingZeros(static_cast<uint32_t>(input)) - 1;  in GetInvSqrtQuantizedMultiplierExp()
105     input <<= 2 * left_shift_bit_pairs;  in GetInvSqrtQuantizedMultiplierExp()
106     NN_RET_CHECK_GE(input, (1 << 27));  in GetInvSqrtQuantizedMultiplierExp()
107     NN_RET_CHECK_LT(input, (1 << 29));  in GetInvSqrtQuantizedMultiplierExp()
115     const F3 fixedpoint_input = F3::FromRaw(input >> 1);  in GetInvSqrtQuantizedMultiplierExp()
140 void ApplyLayerNorm(const int16_t* input, const int16_t* layer_norm_weights, const int32_t* bias,
151 void ApplySigmoid(const int16_t* input, int32_t n_batch, int32_t n_input, int16_t* output);
154 void ApplyTanh(const int16_t* input, int32_t n_batch, int32_t n_input, int16_t* output) {  in ApplyTanh()  argument
160             FX tanh_input = FX::FromRaw(input[index]);  in ApplyTanh()
167 inline void ApplyTanh(int32_t integer_bits, const int16_t* input, int32_t n_batch, int32_t n_input,  in ApplyTanh()  argument
172         ApplyTanh<i>(input, n_batch, n_input, output); \  in ApplyTanh()
205 void CwiseClipping(int16_t* input, const int16_t clipping_value, int32_t n_batch, int32_t n_input);
207 void CwiseClipping(int8_t* input, const int8_t clipping_value, int32_t n_batch, int32_t n_input);