added lamblin's changes + flake8

theano/sandbox/cuda/cula.py

@@ -3,6 +3,7 @@ from theano.sandbox.cuda.type import CudaNdarrayType
 from theano.sandbox.cuda import GpuOp
 
 from theano.sandbox.cuda.basic_ops import as_cuda_ndarray_variable
+from theano.sandbox.cuda import cuda_ndarray
 
 dimshuffle = cuda_ndarray.cuda_ndarray.dimshuffle
 
@@ -19,19 +20,15 @@ class GpuSolve(GpuOp):
     """
     CULA GPU solver OP.
 
-    trans: Whether to take the transpose of the input matrix
+    :param trans: Whether to take the transpose of the input matrix
     or not.
     """
+    __props__ = ('trans')
+
     def __init__(self, trans='N'):
         self.trans = trans
         super(GpuSolve, self).__init__()
 
-    def __eq__(self, other):
-        return (type(other) == type(self))
-
-    def __hash__(self):
-        return hash(type(self))
-
     def output_type(self, inp):
         return CudaNdarrayType(broadcastable=[False] * inp.type.ndim)
 
@@ -39,8 +36,6 @@ class GpuSolve(GpuOp):
         inp1 = as_cuda_ndarray_variable(inp1)
         inp2 = as_cuda_ndarray_variable(inp2)
 
-        assert inp1.dtype == "float32"
-        assert inp2.dtype == "float32"
         assert inp1.ndim == 2
         assert inp2.ndim == 2
         return theano.Apply(self, [inp1, inp2], [self.output_type(inp1)()])
@@ -49,7 +44,6 @@ class GpuSolve(GpuOp):
                    node,
                    storage_map, _,
                    no_recycling=[]):
-        from theano.misc.pycuda_utils import to_gpuarray
 
         # Initialize CULA the first time it is needed
         global cula_initialized
@@ -85,9 +79,6 @@ class GpuSolve(GpuOp):
             A_cpy = A.copy()
             b_cpy = b_cpy.copy()
 
-            A_pycuda = to_gpuarray(A_cpy)
-            b_pycuda = to_gpuarray(b_cpy)
-
             def cula_gpu_solve(A_, b_, trans='T'):
 
                 A_shape = A_.shape
@@ -120,9 +111,9 @@ class GpuSolve(GpuOp):
                 cula.culaDeviceSgels(trans, n, l, m, A_ptr, lda, b_ptr, ldb)
                 return A_, b_
 
-            A_pycuda, b_pycuda = cula_gpu_solve(A_pycuda, b_pycuda, trans)
+            A_pycuda, b_pycuda = cula_gpu_solve(A_cpy, b_cpy, trans)
 
-            #Convert b to F-order from c-order and assign it to output:
+            # Convert b to F-order from c-order and assign it to output:
             b_cpy = b_cpy.reshape(b.shape[::-1])
             b_cpy = dimshuffle(b_cpy, (1, 0))
             z[0] = b_cpy