30 void MatrixBatchVectorMultiplyAccumulate(const int8_t* input, const int32_t* bias,  in MatrixBatchVectorMultiplyAccumulate()  argument
40                 int8_t input_val = input[batch * n_input + col];  in MatrixBatchVectorMultiplyAccumulate()
78 inline bool GetInvSqrtQuantizedMultiplierExp(int32_t input, int reverse_shift,  in GetInvSqrtQuantizedMultiplierExp()  argument
80     NN_RET_CHECK_GE(input, 0);  in GetInvSqrtQuantizedMultiplierExp()
81     if (input <= 1) {  in GetInvSqrtQuantizedMultiplierExp()
93     while (input >= (1 << 29)) {  in GetInvSqrtQuantizedMultiplierExp()
94         input /= 4;  in GetInvSqrtQuantizedMultiplierExp()
97     const unsigned max_left_shift_bits = CountLeadingZeros(static_cast<uint32_t>(input)) - 1;  in GetInvSqrtQuantizedMultiplierExp()
101     input <<= 2 * left_shift_bit_pairs;  in GetInvSqrtQuantizedMultiplierExp()
102     NN_RET_CHECK_GE(input, (1 << 27));  in GetInvSqrtQuantizedMultiplierExp()
103     NN_RET_CHECK_LT(input, (1 << 29));  in GetInvSqrtQuantizedMultiplierExp()
111     const F3 fixedpoint_input = F3::FromRaw(input >> 1);  in GetInvSqrtQuantizedMultiplierExp()
136 void ApplyLayerNorm(const int16_t* input, const int16_t* layer_norm_weights, const int32_t* bias,
147 void ApplySigmoid(const int16_t* input, int32_t n_batch, int32_t n_input, int16_t* output);
150 void ApplyTanh(const int16_t* input, int32_t n_batch, int32_t n_input, int16_t* output) {  in ApplyTanh()  argument
156             FX tanh_input = FX::FromRaw(input[index]);  in ApplyTanh()
163 inline void ApplyTanh(int32_t integer_bits, const int16_t* input, int32_t n_batch, int32_t n_input,  in ApplyTanh()  argument
168         ApplyTanh<i>(input, n_batch, n_input, output); \  in ApplyTanh()
201 void CwiseClipping(int16_t* input, const int16_t clipping_value, int32_t n_batch, int32_t n_input);
203 void CwiseClipping(int8_t* input, const int8_t clipping_value, int32_t n_batch, int32_t n_input);