Fixes found from test_basic_ops.py

theano/sandbox/gpuarray/__init__.py

@@ -54,7 +54,7 @@ if pygpu:
 
         from .basic_ops import (GpuAlloc, GpuContiguous, GpuEye, GpuFromHost,
                                 GpuJoin, GpuReshape, GpuSplit, HostFromGpu)
-        from .basic_ops import host_from_gpu, gpu_from_host
+        from .basic_ops import host_from_gpu, GpuFromHost
         from .elemwise import GpuElemwise
         from .subtensor import (GpuSubtensor, GpuIncSubtensor,
                                 GpuAdvancedIncSubtensor1)

theano/sandbox/gpuarray/basic_ops.py

@@ -181,7 +181,7 @@ class GpuKernelBase(object):
                 dict(cname=k.codevar, code=code))
 
     def _generate_kernel_vars(self, k):
-        return """static GpuKernel %(kname)s;""" % dict(kname=k.objvar)
+        return """GpuKernel %(kname)s;""" % dict(kname=k.objvar)
 
     def c_support_code(self):
         return """
@@ -215,11 +215,11 @@ class GpuKernelBase(object):
   if (GpuKernel_init(&%(ovar)s, %(ctx)s->ops, %(ctx)s->ctx, 1, &bcode, &sz,
                      "%(kname)s", %(numargs)u, types, GA_USE_BINARY, NULL)
       != GA_NO_ERROR) {
-    if ((%(err)s = GpuKernel_init(&%(ovar)s, %(ctx)s->ops, %(ctx)s->ctx, 1,
-                                  &%(cname)s, NULL, "%(kname)s", %(numargs)u,
-                                  types, %(flags)s, NULL)) != GA_NO_ERROR) {
+    if ((err = GpuKernel_init(&%(ovar)s, %(ctx)s->ops, %(ctx)s->ctx, 1,
+                              &%(cname)s, NULL, "%(kname)s", %(numargs)u,
+                              types, %(flags)s, NULL)) != GA_NO_ERROR) {
       PyErr_Format(PyExc_RuntimeError, "GpuKernel_init error %%d: %%s",
-                   %(err)s, Gpu_error(%(ctx)s->ops, %(ctx)s->ctx, %(err)s));
+                   err, Gpu_error(%(ctx)s->ops, %(ctx)s->ctx, err));
       %(fail)s
     }
   }
@@ -371,7 +371,7 @@ class GpuFromHost(Op):
 
     def c_code(self, node, name, inputs, outputs, sub):
         return """
-        PyGpuArrayObject *%(name)s_tmp;
+        PyArrayObject *%(name)s_tmp;
         %(name)s_tmp = PyArray_GETCONTIGUOUS(%(inp)s);
         if (%(name)s_tmp == NULL)
           %(fail)s
@@ -551,9 +551,9 @@ class GpuAlloc(HideC, Alloc):
                 if (err != GA_NO_ERROR)
                 {
                     PyErr_Format(PyExc_MemoryError,
-                                 "GpuAlloc: Error memsetting %%d"
+                                 "GpuAlloc: Error memsetting %%llu"
                                  " element of device memory to 0.",
-                                 PyGpuArray_SIZE(%(zz)s));
+                                 (unsigned long long)PyGpuArray_SIZE(%(zz)s));
                     %(fail)s;
                 }
             }

theano/sandbox/gpuarray/elemwise.py

@@ -173,7 +173,8 @@ class GpuElemwise(GpuKernelBase, HideC, Elemwise):
                         ("npy_float64", "ga_double"),
                         ]:
             kop = kop.replace(npy, ga)
-        return ElemwiseKernel(None, inps + outs, kop, preamble=support_code)
+        return ElemwiseKernel(self.get_context(node), inps + outs, kop,
+                              preamble=support_code)
 
     def c_headers(self):
         return ['<numpy_compat.h>', '<gpuarray/types.h>']
@@ -269,7 +270,7 @@ class GpuElemwise(GpuKernelBase, HideC, Elemwise):
         if (%(nd)s != PyGpuArray_NDIM(%(iname)s))
         {
             PyErr_Format(PyExc_TypeError,
-                         "need %(nd)s dims, not %%i",
+                         "need %(nd)s dims, not %%u",
                          PyGpuArray_NDIM(%(iname)s));
             %(fail)s;
         }
@@ -282,11 +283,11 @@ class GpuElemwise(GpuKernelBase, HideC, Elemwise):
             {
                 PyErr_Format(PyExc_ValueError,
                              "GpuElemwise. Input dimension mis-match. Input"
-                             " %(idx)d (indices start at 0) has shape[%%i] == %%i"
-                             ", but the output's size on that axis is %%i.",
+                             " %(idx)d (indices start at 0) has shape[%%d] == %%llu"
+                             ", but the output's size on that axis is %%llu.",
                              i,
-                             PyGpuArray_DIMS(%(iname)s)[i],
-                             dims[i]
+                             (unsigned long long)PyGpuArray_DIMS(%(iname)s)[i],
+                             (unsigned long long)dims[i]
                             );
                 %(fail)s;
             }
@@ -333,11 +334,11 @@ class GpuElemwise(GpuKernelBase, HideC, Elemwise):
                 PyErr_Format(PyExc_ValueError,
                              "GpuElemwise. Output dimension mis-match. Output"
                              " %(idx)d (indices start at 0), working inplace"
-                             " on input %(input_idx)s, has shape[%%i] == %%i"
-                             ", but the output's size on that axis is %%i.",
+                             " on input %(input_idx)s, has shape[%%i] == %%llu"
+                             ", but the output's size on that axis is %%llu.",
                              i,
-                             PyGpuArray_DIMS(%(oname)s)[i],
-                             dims[i]
+                             (unsigned long long)PyGpuArray_DIMS(%(oname)s)[i],
+                             (unsigned long long)dims[i]
                             );
                 Py_DECREF(%(oname)s);
                 %(oname)s = NULL;
@@ -446,10 +447,12 @@ class GpuDimShuffle(HideC, DimShuffle):
     _f16_ok = True
 
     def make_node(self, input):
+        ctx_name = infer_context_name(input)
         res = DimShuffle.make_node(self, input)
         otype = GpuArrayType(dtype=res.outputs[0].type.dtype,
-                             broadcastable=res.outputs[0].type.broadcastable)
-        input = as_gpuarray_variable(input)
+                             broadcastable=res.outputs[0].type.broadcastable,
+                             context_name=ctx_name)
+        input = as_gpuarray_variable(input, ctx_name)
         return Apply(self, [input], [otype()])
 
     def __str__(self):
@@ -650,7 +653,7 @@ class GpuCAReduceCuda(GpuKernelBase, HideC, CAReduceDtype):
     def get_context(self, node):
         return node.inputs[0].type.context
 
-    def perform(self, node, inp, out):
+    def perform(self, node, inp, out, ctx):
         raise MethodNotDefined("")
 
     def supports_c_code(self, inputs):
@@ -680,7 +683,7 @@ class GpuCAReduceCuda(GpuKernelBase, HideC, CAReduceDtype):
         inp = ['fake_input_name_%d' % i for i in xrange(len(inputs))]
         out = ['fake_output_name_%d' % i for i in xrange(len(node.outputs))]
 
-        sub = {'fail': 'fake failure code'}
+        sub = {'fail': 'fake failure code', 'context': 'fake context'}
 
         try:
             self.c_code(node, name, inp, out, sub)
@@ -715,7 +718,7 @@ class GpuCAReduceCuda(GpuKernelBase, HideC, CAReduceDtype):
         if (PyGpuArray_NDIM(%(x)s) != %(nd_in)s)
         {
             PyErr_Format(PyExc_TypeError,
-                         "required nd=%(nd_in)s, got nd=%%i", PyGpuArray_NDIM(%(x)s));
+                         "required nd=%(nd_in)s, got nd=%%u", PyGpuArray_NDIM(%(x)s));
             %(fail)s;
         }
         """ % locals(), file=sio)
@@ -1320,8 +1323,8 @@ class GpuCAReduceCuda(GpuKernelBase, HideC, CAReduceDtype):
                                      (void *)%(z)s->ga.data,
                                      (void *)&%(z)s->ga.offset};
             if (verbose) printf("running kernel_reduce_ccontig_%(name)s"
-                                " n_threads=%%lu, size=%%lu, ndim=%%d\\n",
-                                n_threads,numEls,
+                                " n_threads=%%llu, size=%%llu, ndim=%%u\\n",
+                                n_threads, numEls,
                                 PyGpuArray_NDIM(%(x)s));
             size_t n_shared = sizeof(%(acc_dtype)s) * n_threads;
             int err = GpuKernel_call(&%(k_var)s, 1, &n_threads, &n_blocks, n_shared, kernel_params);
@@ -1503,9 +1506,9 @@ class GpuCAReduceCuda(GpuKernelBase, HideC, CAReduceDtype):
             size_t n_blocks[3] = {1, std::min(PyGpuArray_DIMS(%(x)s)[1], (size_t) 4096), 1};
             if (verbose) {
               fprintf(stderr,
-                "running kernel_reduce_10_%(name)s n_blocks=(%%i,%%i)\\n",
-                n_blocks[0],
-                n_blocks[1]);
+                "running kernel_reduce_10_%(name)s n_blocks=(%%llu,%%llu)\\n",
+                (unsigned long long)n_blocks[0],
+                (unsigned long long)n_blocks[1]);
             }
             assert(PyGpuArray_DIMS(%(x)s)[1] == PyGpuArray_DIMS(%(z)s)[0]);
             size_t n_shared = sizeof(%(acc_dtype)s) * n_threads[0];

theano/sandbox/gpuarray/subtensor.py

@@ -215,7 +215,7 @@ class GpuIncSubtensor(GpuKernelBase, IncSubtensor):
         iadd_node = gop(xview, y).owner
         self.iadd_node = iadd_node
 
-    def perform(self, node, inputs, out_):
+    def perform(self, node, inputs, out_, ctx):
         out, = out_
         x, y = inputs[:2]
         indices = list(reversed(inputs[2:]))
@@ -326,7 +326,7 @@ class GpuIncSubtensor(GpuKernelBase, IncSubtensor):
                                   %(view_ndim)s,
                                   dims,
                                   xview_strides,
-                                  %(x)s->ctx,
+                                  %(x)s->context,
                                   1,
                                   (PyObject *)%(x)s,
                                   (PyObject *)&PyGpuArrayType);
@@ -360,10 +360,10 @@ class GpuIncSubtensor(GpuKernelBase, IncSubtensor):
         """
         return """GpuArray_setarray(&%(view)s->ga, &%(source)s->ga)""" % locals()
 
-    def c_support_code_apply(self, node, nodename):
+    def c_support_code_struct(self, node, nodename):
         gop = self.iadd_node.op
         sub_name = nodename + "_add_to_zview"
-        ret = gop.c_support_code_apply(self.iadd_node, sub_name)
+        ret = gop.c_support_code_struct(self.iadd_node, sub_name)
         ret += """
         PyGpuArrayObject* inc_sub_iadd_%(nodename)s(PyGpuArrayObject* dst,
                                                     PyGpuArrayObject* src){
@@ -371,10 +371,11 @@ class GpuIncSubtensor(GpuKernelBase, IncSubtensor):
         """ % locals()
         inputs = ["dst", "src"]
         outputs = ["ret"]
-        sub = {"fail": "return NULL;", "context": "dst->ctx"}
+        sub = {"fail": "return NULL;", "context": "dst->context"}
         ret += gop.c_code(self.iadd_node, sub_name, inputs, outputs, sub)
         ret += """
             return ret;
+
         }
         """
         return ret
@@ -608,7 +609,7 @@ class GpuAdvancedIncSubtensor1_dev20(GpuKernelBase, GpuAdvancedIncSubtensor1):
         return gof.Apply(self, [x_, y_, ilist_], [x_.type()])
 
     def get_context(self, node):
-        return self.node.outputs[0].type.context
+        return node.outputs[0].type.context
 
     def c_code_cache_version(self):
         return (6,)
@@ -617,6 +618,9 @@ class GpuAdvancedIncSubtensor1_dev20(GpuKernelBase, GpuAdvancedIncSubtensor1):
         return ['<numpy_compat.h>', '<gpuarray_helper.h>',
                 '<gpuarray/types.h>']
 
+    def c_header_dirs(self):
+        return [os.path.dirname(__file__)]
+
     def c_code(self, node, name, inputs, outputs, sub):
         ctx = self.get_context(node)
         if ctx.kind != 'cuda':
@@ -754,7 +758,7 @@ __device__ ga_half atomicAdd(ga_half *addr, ga_half val) {
         return [Kernel(code=code, name=kname, params=params,
                        flags=flags, objvar=k_var)]
 
-    def c_support_code_apply(self, node, nodename):
+    def c_support_code_struct(self, node, nodename):
         dtype_x = node.inputs[0].dtype
         dtype_y = node.inputs[1].dtype
         dtype_ind = node.inputs[2].dtype
@@ -765,7 +769,7 @@ __device__ ga_half atomicAdd(ga_half *addr, ga_half val) {
         itemsize_out = numpy.dtype(dtype_out).itemsize
         k_var = "k_vector_add_fast_" + nodename
 
-        return super(GpuAdvancedIncSubtensor1_dev20, self).c_support_code_apply(node, nodename) + """
+        return super(GpuAdvancedIncSubtensor1_dev20, self).c_support_code_struct(node, nodename) + """
         int GpuArray_vector_add_fast(PyGpuArrayObject* py_self,
                                      PyGpuArrayObject* py_other,
                                      PyGpuArrayObject *indices_arr)