1 files changed, 23 insertions, 5 deletions
diff --git a/tensorflow/contrib/lite/kernels/kernel_util.h b/tensorflow/contrib/lite/kernels/kernel_util.h
index 20058a5f69..c8ce3c917d 100644
--- a/tensorflow/contrib/lite/kernels/kernel_util.h
+++ b/tensorflow/contrib/lite/kernels/kernel_util.h
@@ -15,6 +15,8 @@ limitations under the License.
 #ifndef TENSORFLOW_CONTRIB_LITE_KERNELS_KERNEL_UTIL_H_
 #define TENSORFLOW_CONTRIB_LITE_KERNELS_KERNEL_UTIL_H_
 
+#include <algorithm>
+
 #include "tensorflow/contrib/lite/builtin_op_data.h"
 #include "tensorflow/contrib/lite/context.h"
 
@@ -86,8 +88,8 @@ TfLiteStatus GetQuantizedConvolutionMultipler(TfLiteContext* context,
                                               TfLiteTensor* output,
                                               double* multiplier);
 
-// Calculates the useful range of an activation layer given its activation
-// tensor.
+// Calculates the useful quantized range of an activation layer given its
+// activation tensor.
 TfLiteStatus CalculateActivationRangeQuantized(TfLiteContext* context,
                                                TfLiteFusedActivation activation,
                                                TfLiteTensor* output,
@@ -96,9 +98,25 @@ TfLiteStatus CalculateActivationRangeQuantized(TfLiteContext* context,
 void CalculateActivationRangeUint8(TfLiteFusedActivation activation,
                                    TfLiteTensor* output, int32_t* act_min,
                                    int32_t* act_max);
-void CalculateActivationRangeFloat(TfLiteFusedActivation activation,
-                                   float* activation_min,
-                                   float* activation_max);
+// Calculates the useful range of an activation layer given its activation
+// tensor.a
+template <typename T>
+void CalculateActivationRange(TfLiteFusedActivation activation,
+                              T* activation_min, T* activation_max) {
+  if (activation == kTfLiteActRelu) {
+    *activation_min = 0;
+    *activation_max = std::numeric_limits<T>::max();
+  } else if (activation == kTfLiteActRelu6) {
+    *activation_min = 0;
+    *activation_max = 6;
+  } else if (activation == kTfLiteActRelu1) {
+    *activation_min = -1;
+    *activation_max = 1;
+  } else {
+    *activation_min = std::numeric_limits<T>::lowest();
+    *activation_max = std::numeric_limits<T>::max();
+  }
+}
 
 // Return true if the given tensors have the same shape.
 bool HaveSameShapes(const TfLiteTensor* input1, const TfLiteTensor* input2);