Fix compile problems.

theano/gpuarray/__init__.py

@@ -69,9 +69,6 @@ def init_dev(dev, name=None):
             pcibusid = context.pcibusid
         except pygpu.gpuarray.UnsupportedException:
             pcibusid = '(unsupported for device %s)' % dev
-        except Exception:
-            warnings.warn('Unable to get PCI Bus ID. Please consider updating libgpuarray and pygpu.')
-            pcibusid = 'unknown'
 
         print("Mapped name %s to device %s: %s" %
               (name, dev, context.devname),
@@ -99,10 +96,11 @@ def init_dev(dev, name=None):
     if need_preallocate:
         MB = (1024 * 1024)
         if config.gpuarray.preallocate <= 1:
-            gmem = min(config.gpuarray.preallocate, 0.95) * ctx.total_gmem
+            gmem = min(config.gpuarray.preallocate, 0.95) * context.total_gmem
         else:
             gmem = config.gpuarray.preallocate * MB
-        gmem = min(ctx.free_gmem - 50 * MB, gmem)
+        if gmem > context.free_gmem - 50 * MB:
+            print ("WARNING: Preallocating too much memory can prevent cudnn and cublas from working properly")
 
         # This will allocate and immediatly free an object of size gmem
         # which will reserve that amount of memory on the GPU.

theano/gpuarray/dnn_fwd.c

@@ -100,7 +100,7 @@ APPLY_SPECIFIC(conv_fwd)(PyGpuArrayObject *input, PyGpuArrayObject *kerns,
   if (!reuse_algo) {
     size_t free;
 
-    int err2 = gpucontext_property(ctx, GA_CTX_PROP_LARGEST_MEMBLOCK, &free);
+    int err2 = gpucontext_property(c->ctx, GA_CTX_PROP_LARGEST_MEMBLOCK, &free);
     if (err2 != GA_NO_ERROR) {
       PyErr_Format(PyExc_RuntimeError, "Error when trying to find the "
                    "memory information on the GPU");
@@ -116,7 +116,7 @@ APPLY_SPECIFIC(conv_fwd)(PyGpuArrayObject *input, PyGpuArrayObject *kerns,
     cudnnConvolutionFwdAlgoPerf_t choice;
     gpudata *tmpmem;
 
-    tmpmem = gpudata_alloc(ctx, free, NULL, 0, NULL);
+    tmpmem = gpudata_alloc(c->ctx, free, NULL, 0, NULL);
     if (tmpmem == NULL) {
       PyErr_SetString(PyExc_MemoryError, "Could not allocate working GPU memory");
       return -1;

theano/gpuarray/dnn_gi.c

@@ -155,7 +155,7 @@ APPLY_SPECIFIC(conv_gi)(PyGpuArrayObject *kerns, PyGpuArrayObject *output,
     cudnnConvolutionBwdDataAlgoPerf_t choice;
     gpudata *tmpmem;
 
-    tmpmem = gpudata_alloc(ctx, mem_sz, NULL, 0, NULL);
+    tmpmem = gpudata_alloc(c->ctx, mem_sz, NULL, 0, NULL);
     if (tmpmem == NULL) {
       PyErr_SetString(PyExc_MemoryError, "Could not allocate working GPU memory");
       return -1;

theano/gpuarray/dnn_gw.c

@@ -142,7 +142,7 @@ APPLY_SPECIFIC(conv_gw)(PyGpuArrayObject *input, PyGpuArrayObject *output,
   if (!reuse_algo) {
     size_t free;
 
-    int err2 = gpucontext_property(ctx, GA_CTX_PROP_LARGEST_MEMBLOCK, &free);
+    int err2 = gpucontext_property(c->ctx, GA_CTX_PROP_LARGEST_MEMBLOCK, &free);
     if (err2 != GA_NO_ERROR) {
       PyErr_Format(PyExc_RuntimeError, "Error when trying to find the "
                    "memory information on the GPU");
@@ -158,7 +158,7 @@ APPLY_SPECIFIC(conv_gw)(PyGpuArrayObject *input, PyGpuArrayObject *output,
     cudnnConvolutionBwdFilterAlgoPerf_t choice;
     gpudata *tmpmem;
 
-    tmpmem = gpudata_alloc(ctx, free, NULL, 0, NULL);
+    tmpmem = gpudata_alloc(c->ctx, free, NULL, 0, NULL);
     if (tmpmem == NULL) {
       PyErr_SetString(PyExc_MemoryError, "Could not allocate working GPU memory");
       return -1;