Fix formatting error on 32-bits machines.

theano/tensor/nnet/Conv3D.py

@@ -201,7 +201,7 @@ class Conv3D(theano.Op):
 
             if (%(d)s->dimensions[0] != 3)
             {
-                PyErr_Format(PyExc_ValueError,"Conv3D: 3 stride length arguments expected (row, col, time) but %%li were given",%(d)s->dimensions[0]);
+                PyErr_Format(PyExc_ValueError,"Conv3D: 3 stride length arguments expected (row, col, time) but %%li were given", (long)%(d)s->dimensions[0]);
                 %(fail)s
             }
 
@@ -213,13 +213,13 @@ class Conv3D(theano.Op):
 
             if (%(W)s->dimensions[4] != inputChannels)
             {
-                PyErr_Format(PyExc_ValueError, "Conv3D: W operates on a %%ld channel image but the image has %%d channels. Overall shape of input: (%%ld,%%ld,%%ld,%%ld,%%ld)",%(W)s->dimensions[4],inputChannels, %(V)s->dimensions[0], %(V)s->dimensions[1], %(V)s->dimensions[2], %(V)s->dimensions[3], %(V)s->dimensions[4]);
+                PyErr_Format(PyExc_ValueError, "Conv3D: W operates on a %%ld channel image but the image has %%d channels. Overall shape of input: (%%ld,%%ld,%%ld,%%ld,%%ld)", (long)%(W)s->dimensions[4], inputChannels, (long)%(V)s->dimensions[0], (long)%(V)s->dimensions[1], (long)%(V)s->dimensions[2], (long)%(V)s->dimensions[3], (long)%(V)s->dimensions[4]);
                 %(fail)s
             }
 
             if (%(b)s->dimensions[0] != outputChannels)
             {
-                PyErr_Format(PyExc_ValueError, "Conv3D: b adds to a(n) %%ld channel output image but the output has %%d channels",%(b)s->dimensions[0],outputChannels);
+                PyErr_Format(PyExc_ValueError, "Conv3D: b adds to a(n) %%ld channel output image but the output has %%d channels", (long)%(b)s->dimensions[0], outputChannels);
                 %(fail)s
             }
 

theano/tensor/nnet/ConvGrad3D.py

@@ -121,7 +121,7 @@ class ConvGrad3D(theano.Op):
 
             if (%(d)s->dimensions[0] != 3)
             {
-                PyErr_Format(PyExc_ValueError,"ConvGrad3D: 3 stride length arguments expected (row, col, time) but %%li were given",%(d)s->dimensions[0]);
+                PyErr_Format(PyExc_ValueError,"ConvGrad3D: 3 stride length arguments expected (row, col, time) but %%li were given", (long)%(d)s->dimensions[0]);
                 %(fail)s
             }
 { //extra scope so that fail will not jump over declarations
@@ -197,7 +197,7 @@ class ConvGrad3D(theano.Op):
                 %(dCdH)s->dimensions[2] != outputWidth ||
                 %(dCdH)s->dimensions[3] != outputDur)
             {
-                PyErr_Format(PyExc_ValueError, "dCdH is the wrong size, expected (%%i,%%i,%%i,%%i,%%i), got (%%li,%%li,%%li,%%li,%%li)", batchSize,  outputHeight, outputWidth, outputDur, outputChannels, %(dCdH)s->dimensions[0], %(dCdH)s->dimensions[1], %(dCdH)s->dimensions[2] ,%(dCdH)s->dimensions[3], %(dCdH)s->dimensions[4] );
+                PyErr_Format(PyExc_ValueError, "dCdH is the wrong size, expected (%%i,%%i,%%i,%%i,%%i), got (%%li,%%li,%%li,%%li,%%li)", batchSize,  outputHeight, outputWidth, outputDur, outputChannels, (long)%(dCdH)s->dimensions[0], (long)%(dCdH)s->dimensions[1], (long)%(dCdH)s->dimensions[2], (long)%(dCdH)s->dimensions[3], (long)%(dCdH)s->dimensions[4]);
                 %(fail)s
             }
 { // extra scope for fail

theano/tensor/nnet/ConvTransp3D.py

@@ -125,7 +125,7 @@ class ConvTransp3D(theano.Op):
 		    //Read and check stride arguments
 		    if (%(d)s->dimensions[0] != 3)
 		    {
-		         PyErr_Format(PyExc_ValueError, "ConvTransp3D: 3 stride length arguments expected (for row, col, and time) but %%li were given", %(d)s->dimensions[0] );
+		         PyErr_Format(PyExc_ValueError, "ConvTransp3D: 3 stride length arguments expected (for row, col, and time) but %%li were given", (long)%(d)s->dimensions[0] );
 			 %(fail)s
 		    }
 
@@ -149,7 +149,7 @@ class ConvTransp3D(theano.Op):
 
 			    if (%(H)s->dimensions[4] != outputChannels)
 			    {
-                                PyErr_Format(PyExc_ValueError, "W produces a %%i channel image but the image has %%li channels. W.shape: (%%li, %%li, %%li,%%li, %%li) H.shape: (%%li, %%li, %%li, %%li, %%li)",outputChannels,%(H)s->dimensions[4], %(W)s->dimensions[0], %(W)s->dimensions[1], %(W)s->dimensions[2], %(W)s->dimensions[3], %(W)s->dimensions[4], %(H)s->dimensions[0], %(H)s->dimensions[1], %(H)s->dimensions[2], %(H)s->dimensions[3], %(H)s->dimensions[4]);
+                                PyErr_Format(PyExc_ValueError, "W produces a %%i channel image but the image has %%li channels. W.shape: (%%li, %%li, %%li, %%li, %%li) H.shape: (%%li, %%li, %%li, %%li, %%li)", outputChannels, (long)%(H)s->dimensions[4], (long)%(W)s->dimensions[0], (long)%(W)s->dimensions[1], (long)%(W)s->dimensions[2], (long)%(W)s->dimensions[3], (long)%(W)s->dimensions[4], (long)%(H)s->dimensions[0], (long)%(H)s->dimensions[1], (long)%(H)s->dimensions[2], (long)%(H)s->dimensions[3], (long)%(H)s->dimensions[4]);
                                 %(fail)s
 			    }
 
@@ -159,7 +159,7 @@ class ConvTransp3D(theano.Op):
 
 			        if (%(b)s->dimensions[0] != inputChannels)
 			        {
-                                    PyErr_Format(PyExc_ValueError, "ConvTransp3D: b operates on a %%li channel image but the image has %%i channels", %(b)s->dimensions[0], inputChannels );
+                                    PyErr_Format(PyExc_ValueError, "ConvTransp3D: b operates on a %%li channel image but the image has %%i channels", (long)%(b)s->dimensions[0], inputChannels );
 				    %(fail)s
 			        }