Merge commit '429699bb20596e1c8bc87ab37e4597b700eff8f6'

torch/lib/THNN/generic/LogSigmoid.c

@@ -10,11 +10,12 @@ void THNN_(LogSigmoid_updateOutput)(
 {
   THTensor_(resizeAs)(output, input);
   THTensor_(resizeAs)(buffer, input);
-
+  //Use the LogSumExp trick to make this stable against overflow
   TH_TENSOR_APPLY3(real, output, real, input, real, buffer,
-    real z = exp(-*input_data);
+    real max_elem = fmax(0, -*input_data);
+    real z = exp(-max_elem) + exp(-*input_data - max_elem);
     *buffer_data = z;
-    *output_data = -log(1. + z);
+    *output_data = -(max_elem + log(z));
   );
 }
 
@@ -27,10 +28,24 @@ void THNN_(LogSigmoid_updateGradInput)(
 {
   THNN_CHECK_NELEMENT(input, gradOutput);
   THTensor_(resizeAs)(gradInput, buffer);
-  TH_TENSOR_APPLY3(real, gradInput, real, gradOutput, real, buffer,
+/* deriv of -max(0,-x) - log(e(0 - max(0,-x)) + e(-x - max(0,-x)) is
+ * -max_deriv - (-max_deriv*e(0-max(0,-x)) + (-1 - max_deriv)*e(-x - max(0,-x)))/z
+ * where z = e(0 - max(0,-x)) + e(-x - max(0,-x))
+ * which simplifies to 
+ *  -max_deriv - (z-1)/z if x is >= 0 or
+ *  -max_deriv + (z-1)/z if x is < 0
+ */
+  TH_TENSOR_APPLY3(real, input, real, gradInput, real, buffer,
     real z = *buffer_data;
-    *gradInput_data = *gradOutput_data * z / (1. + z);
-  );
+    real max_deriv = 0.0;
+    real sign = -1.0;
+    if (*input_data < 0){
+        max_deriv = -1.0;
+        sign = 1.0;
+    }
+    *gradInput_data = -max_deriv - sign*((z - 1.0)/ z);
+    );
+    THTensor_(cmul)(gradInput, gradOutput, gradInput);
 }
 
 #endif