Add a CUDNNDataType wrapper to handle all the libraries and other such stuff.

theano/gpuarray/dnn.py

@@ -224,6 +224,31 @@ def dnn_available(context_name):
 dnn_available.msg = None
 
 
+def CUDNNDataType(name, freefunc=None):
+    hdirs = []
+    if config.dnn.include_path:
+        hdirs.append(config.dnn.include_path)
+    if config.cuda.include_path:
+        hdirs.append(config.cuda.include_path)
+    ldirs = []
+    if config.dnn.library_path:
+        ldirs.append(config.dnn.library_path)
+    cargs = []
+    if config.dnn.bin_path:
+        if sys.platform == 'darwin':
+            cargs.append('-Wl,-rpath,' + config.dnn.bin_path)
+        else:
+            cargs.append('-Wl,-rpath,"' + config.dnn.bin_path + '"')
+
+    return CDataType(name, freefunc,
+                     headers=['cudnn.h'],
+                     header_dirs=hdirs,
+                     libraries=['cudnn'],
+                     lib_dirs=ldirs,
+                     compile_args=cargs,
+                     version=version(raises=False))
+
+
 class DnnVersion(Op):
     __props__ = ()
 
@@ -311,12 +336,7 @@ def version(raises=True):
     return version.v
 version.v = None
 
-handle_type = CDataType('cudnnHandle_t', 'cudnnDestroy',
-                        headers=['cudnn.h'],
-                        header_dirs=[config.dnn.include_path],
-                        libraries=['cudnn'],
-                        lib_dirs=[config.dnn.library_path],
-                        version=version(raises=False))
+handle_type = CUDNNDataType('cudnnHandle_t', 'cudnnDestroy')
 
 # Get cuDNN definitions to be used.
 cudnn = cudnn_defs.get_definitions(version(raises=False))
@@ -489,9 +509,8 @@ class GpuDnnConvDesc(COp):
         kern_shape = theano.tensor.basic.cast(kern_shape, 'int64')
 
         node = Apply(self, [kern_shape],
-                     [CDataType("cudnnConvolutionDescriptor_t",
-                                freefunc="cudnnDestroyConvolutionDescriptor",
-                                version=version(raises=False))()])
+                     [CUDNNDataType("cudnnConvolutionDescriptor_t",
+                                    freefunc="cudnnDestroyConvolutionDescriptor")()])
         # DebugMode cannot compare the values of CDataType variables, so by
         # default it returns False all the time. To prevent DebugMode from
         # complaining because of the MergeOptimizer, we make this variable
@@ -1301,9 +1320,8 @@ class GpuDnnPoolDesc(Op):
 
     def make_node(self):
         node = Apply(self, [],
-                     [CDataType("cudnnPoolingDescriptor_t",
-                                freefunc="cudnnDestroyPoolingDescriptor",
-                                version=version(raises=False))()])
+                     [CUDNNDataType("cudnnPoolingDescriptor_t",
+                                    freefunc="cudnnDestroyPoolingDescriptor")()])
         # DebugMode cannot compare the values of CDataType variables, so by
         # default it returns False all the time. To prevent DebugMode from
         # complaining because of the MergeOptimizer, we make this variable
@@ -1961,9 +1979,8 @@ class GpuDnnBatchNormGrad(DnnBase):
         return [shape[0], shape[2], shape[2]]
 
 gpudata_type = CDataType('gpudata *', 'gpudata_release')
-dropoutdesc_type = CDataType('cudnnDropoutDescriptor_t',
-                             'cudnnDestroyDropoutDescriptor',
-                             version=version(raises=False))
+dropoutdesc_type = CUDNNDataType('cudnnDropoutDescriptor_t',
+                                 'cudnnDestroyDropoutDescriptor')
 
 
 class GpuDnnDropoutOp(DnnBase):
@@ -2031,9 +2048,8 @@ def dropout(x, dropout=0.0, seed=4242):
     y, odesc = GpuDnnDropoutOp()(x, desc)
     return y, desc, odesc, states
 
-rnndesc_type = CDataType('cudnnRNNDescriptor_t',
-                         'cudnnDestroyRNNDescriptor',
-                         version=version(raises=False))
+rnndesc_type = CUDNNDataType('cudnnRNNDescriptor_t',
+                             'cudnnDestroyRNNDescriptor')
 
 
 def as_i32(v):