diff --git a/tensorflow/lite/kernels/internal/tensor_utils.h b/tensorflow/lite/kernels/internal/tensor_utils.h
index 33163027ca3..b515949bb29 100644
--- a/tensorflow/lite/kernels/internal/tensor_utils.h
+++ b/tensorflow/lite/kernels/internal/tensor_utils.h
@@ -186,7 +186,7 @@ void ApplyLayerNorm(const int16_t* input, const int16_t* layer_norm_weights,
                     int32_t layer_norm_scale_b, int32_t variance_limit,
                     int n_batch, int n_input, int16_t* output);
 
-// Apply Sigmoid to a Quantized vector.
+// Apply Sigmoid to a quantized vector.
 // Parameters:
 //     - input: batch vector of size n_batch * n_input; 16 bit.
 //     - n_batch: the number of batch.
@@ -196,7 +196,7 @@ void ApplyLayerNorm(const int16_t* input, const int16_t* layer_norm_weights,
 void ApplySigmoid(const int16_t* input, int32_t n_batch, int32_t n_input,
                   int16_t* output);
 
-// Apply Tanh to a Quantized vector.
+// Apply Tanh to a quantized vector.
 // Parameters:
 //     - input: batch vector of size n_batch * n_input; 16 bit.
 //     - n_batch: the number of batch.
@@ -206,6 +206,13 @@ void ApplySigmoid(const int16_t* input, int32_t n_batch, int32_t n_input,
 void ApplyTanh0(const int16_t* input, int32_t n_batch, int32_t n_input,
                 int16_t* output);
 
+// Apply Tanh to a quantized vector.
+// Parameters:
+//     - input: batch vector of size n_batch * n_input; 16 bit.
+//     - n_batch: the number of batch.
+//     - n_input: the size for input and output.
+//     - output: the 16 bit output
+// The input is in Q3.12 format and the output is in Q0.15 format.
 void ApplyTanh3(const int16_t* input, int32_t n_batch, int32_t n_input,
                 int16_t* output);