From 0d9a4a50c9253b032a41ad114c41aa82d370d102 Mon Sep 17 00:00:00 2001
From: Ronan Collobert <ronan@collobert.com>
Date: Wed, 25 Jul 2012 13:50:37 +0200
Subject: added temporal max pooling

---
 generic/TemporalMaxPooling.c | 127 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 127 insertions(+)
 create mode 100644 generic/TemporalMaxPooling.c

(limited to 'generic')

diff --git a/generic/TemporalMaxPooling.c b/generic/TemporalMaxPooling.c
new file mode 100644
index 0000000..56d0ef6
--- /dev/null
+++ b/generic/TemporalMaxPooling.c
@@ -0,0 +1,127 @@
+#ifndef TH_GENERIC_FILE
+#define TH_GENERIC_FILE "generic/TemporalMaxPooling.c"
+#else
+
+static int nn_(TemporalMaxPooling_updateOutput)(lua_State *L)
+{
+  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  int kW = luaT_getfieldcheckint(L, 1, "kW");
+  int dW = luaT_getfieldcheckint(L, 1, "dW");
+  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
+  THTensor *output = luaT_getfieldcheckudata(L, 1, "output", torch_(Tensor_id));
+
+  luaL_argcheck(L, input->nDimension == 2, 2, "2D tensor expected");
+  luaL_argcheck(L, input->size[0] >= kW, 2, "input sequence smaller than kernel size");
+
+  // sizes
+  long niframe = input->size[0];
+  long framesize = input->size[1];
+  long noframe = (niframe - kW) / dW + 1;
+
+  // get contiguous input
+  input = THTensor_(newContiguous)(input);
+
+  // resize output
+  THTensor_(resize2d)(output, noframe, framesize);
+
+  // indices will contain index locations for each output point
+  THTensor_(resize2d)(indices, noframe, framesize);
+
+  // get raw pointers
+  real *input_data = THTensor_(data)(input);
+  real *output_data = THTensor_(data)(output);
+  real *indices_data = THTensor_(data)(indices);
+
+  long t, x, y;
+  for(t = 0; t < noframe; t++)
+  {
+    real *ip = input_data + t*framesize*dW;
+    real *op = output_data + t*framesize;
+    real *xp = indices_data + t*framesize;
+#pragma omp parallel for private(y)
+    for(y = 0; y < framesize; y++)
+    {
+      // compute local max:
+      long maxindex = -1;
+      real maxval = -THInf;
+      for(x = 0; x < kW; x++)
+      {
+        real val = ip[x*framesize+y];
+        if (val > maxval)
+        {
+          maxval = val;
+          maxindex = x;
+        }
+      }
+
+      // set output to local max
+      op[y] = maxval;
+      xp[y] = (real)maxindex;
+    }
+  }
+
+  // cleanup
+  THTensor_(free)(input);
+
+  return 1;
+}
+
+static int nn_(TemporalMaxPooling_updateGradInput)(lua_State *L)
+{
+  THTensor *input = luaT_checkudata(L, 2, torch_(Tensor_id));
+  THTensor *gradOutput = luaT_checkudata(L, 3, torch_(Tensor_id));
+  int dW = luaT_getfieldcheckint(L, 1, "dW");
+  THTensor *indices = luaT_getfieldcheckudata(L, 1, "indices", torch_(Tensor_id));
+  THTensor *gradInput = luaT_getfieldcheckudata(L, 1, "gradInput", torch_(Tensor_id));
+
+  // get contiguous gradOutput
+  gradOutput = THTensor_(newContiguous)(gradOutput);
+
+  // resize and zero
+  THTensor_(resizeAs)(gradInput, input);
+  THTensor_(zero)(gradInput);
+
+  // sizes
+  int noframe = gradOutput->size[0];
+  long framesize = gradOutput->size[1];
+
+  // get raw pointers
+  real *gradInput_data = THTensor_(data)(gradInput);
+  real *gradOutput_data = THTensor_(data)(gradOutput);
+  real *indices_data = THTensor_(data)(indices);
+
+  long t, y;
+  for(t = 0; t < noframe; t++)
+  {
+    real *gip = gradInput_data + t*framesize*dW;
+    real *gop = gradOutput_data + t*framesize;
+    real *xp = indices_data + t*framesize;
+#pragma omp parallel for private(y)
+    for(y = 0; y < framesize; y++)
+    {
+      // compute local max:
+      long maxindex = (long)xp[y];
+      gip[maxindex*framesize+y] += gop[y];
+    }
+  }
+
+  // cleanup
+  THTensor_(free)(gradOutput);
+
+  return 1;
+}
+
+static const struct luaL_Reg nn_(TemporalMaxPooling__) [] = {
+  {"TemporalMaxPooling_updateOutput", nn_(TemporalMaxPooling_updateOutput)},
+  {"TemporalMaxPooling_updateGradInput", nn_(TemporalMaxPooling_updateGradInput)},
+  {NULL, NULL}
+};
+
+static void nn_(TemporalMaxPooling_init)(lua_State *L)
+{
+  luaT_pushmetaclass(L, torch_(Tensor_id));
+  luaT_registeratname(L, nn_(TemporalMaxPooling__), "nn");
+  lua_pop(L,1);
+}
+
+#endif
-- 
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