Follow the rename of libgpuarray.

doc/introduction.txt

@@ -184,7 +184,7 @@ Here is the state of that vision as of December 3th, 2013 (after Theano release
 
 * We have a CUDA backend for tensors of type `float32` only.
 * Efforts have begun towards a generic GPU ndarray (GPU tensor) (started in the
-  `compyte <https://github.com/inducer/compyte/wiki>`_ project)
+  `libgpuarray <https://github.com/abergeron/libgpuarray>`_ project)
 
   * Move GPU backend outside of Theano (on top of PyCUDA/PyOpenCL)
   * Will provide better support for GPU on Windows and use an OpenCL backend on CPU.

theano/sandbox/gpuarray/basic_ops.py

@@ -112,7 +112,7 @@ class GpuKernelBase(object):
         return '|'.join(flags)
 
     def c_headers(self):
-        return ['compyte/types.h']
+        return ['gpuarray/types.h']
 
     def c_support_code_apply(self, node, name):
         kcode = self.c_kernel_code(node)
@@ -326,8 +326,8 @@ class GpuFromCuda(Op):
         return xshp
 
     def c_headers(self):
-        return ['<cuda_ndarray.cuh>', '<compyte/extension.h>',
-                '<compyte/types.h>', '<cuda.h>']
+        return ['<cuda_ndarray.cuh>', '<gpuarray/extension.h>',
+                '<gpuarray/types.h>', '<cuda.h>']
 
     def c_header_dirs(self):
         import cuda_ndarray
@@ -355,8 +355,8 @@ class GpuFromCuda(Op):
         """
 
     def c_init_code(self):
-        return ['cuda_get_ctx = (CUcontext (*)(void *))compyte_get_extension("cuda_get_ctx");',
-                'cuda_make_buf = (gpudata *(*)(void *, CUdeviceptr, size_t))compyte_get_extension("cuda_make_buf");']
+        return ['cuda_get_ctx = (CUcontext (*)(void *))gpuarray_get_extension("cuda_get_ctx");',
+                'cuda_make_buf = (gpudata *(*)(void *, CUdeviceptr, size_t))gpuarray_get_extension("cuda_make_buf");']
 
     def c_code(self, node, name, inputs, outputs, sub):
         return """
@@ -462,7 +462,7 @@ class CudaFromGpu(Op):
         return shp
 
     def c_headers(self):
-        return ['<cuda_ndarray.cuh>', '<compyte/extension.h>', '<cuda.h>']
+        return ['<cuda_ndarray.cuh>', '<gpuarray/extension.h>', '<cuda.h>']
 
     def c_header_dirs(self):
         import cuda_ndarray
@@ -490,8 +490,8 @@ class CudaFromGpu(Op):
         """
 
     def c_init_code(self):
-        return ['cuda_get_ctx = (CUcontext (*)(void *ctx))compyte_get_extension("cuda_get_ctx");',
-                'cuda_get_ptr = (CUdeviceptr (*)(gpudata *g))compyte_get_extension("cuda_get_ptr");']
+        return ['cuda_get_ctx = (CUcontext (*)(void *ctx))gpuarray_get_extension("cuda_get_ctx");',
+                'cuda_get_ptr = (CUdeviceptr (*)(gpudata *g))gpuarray_get_extension("cuda_get_ptr");']
 
     def c_code(self, node, name, inputs, outputs, sub):
         return """
@@ -806,7 +806,7 @@ KERNEL void k(GLOBAL_MEM %(ctype)s *a, ga_size n, ga_size m) {
         err = GpuKernel_call(&%(kname)s, 0, 1, 256, args);
         if (err != GA_NO_ERROR) {
             PyErr_Format(PyExc_RuntimeError,
-                         "compyte error: kEye: %%s. n%%lu, m=%%lu.",
+                         "gpuarray error: kEye: %%s. n%%lu, m=%%lu.",
                          GpuKernel_error(&%(kname)s, err),
                          (unsigned long)dims[0], (unsigned long)dims[1]);
             %(fail)s;

theano/sandbox/gpuarray/conv.py

@@ -183,14 +183,14 @@ class GpuConv(gof.Op):
 
     def c_headers(self):
         return ['<stdio.h>', 'cuda.h',
-                '<compyte/extension.h>', '<numpy_compat.h>']
+                '<gpuarray/extension.h>', '<numpy_compat.h>']
 
     def c_code_cache_version(self):
         # raise this whenever modifying any of the support_code_files
         return (0, 20)
 
     def c_init_code(self):
-        return ['cuda_get_ptr_raw = (CUdeviceptr (*)(gpudata *g))compyte_get_extension("cuda_get_ptr");']
+        return ['cuda_get_ptr_raw = (CUdeviceptr (*)(gpudata *g))gpuarray_get_extension("cuda_get_ptr");']
 
     def c_support_code_apply(self, node, nodename):
         # REMEMBER TO RAISE c_code_cache_version when changing any of

theano/sandbox/gpuarray/elemwise.py

@@ -177,8 +177,8 @@ class GpuElemwise(HideC, Elemwise):
     def c_headers(self):
         if pygpu.get_default_context().kind == 'opencl':
             raise MethodNotDefined('cuda only')
-        return ['cuda.h', '<compyte/extension.h>', '<numpy_compat.h>',
-                '<compyte/ext_cuda.h>']
+        return ['cuda.h', '<gpuarray/extension.h>', '<numpy_compat.h>',
+                '<gpuarray/ext_cuda.h>']
 
     def c_compiler(self):
         if pygpu.get_default_context().kind == 'opencl':
@@ -678,8 +678,8 @@ class GpuCAReduceCuda(HideC, CAReduce):
         return True
 
     def c_headers(self):
-        return ['cuda.h', '<compyte/extension.h>', '<numpy_compat.h>',
-                '<compyte/ext_cuda.h>']
+        return ['cuda.h', '<gpuarray/extension.h>', '<numpy_compat.h>',
+                '<gpuarray/ext_cuda.h>']
 
     def c_compiler(self):
         return NVCC_compiler
@@ -2317,7 +2317,7 @@ class GpuCAReduceCuda(HideC, CAReduce):
 
 
 class GpuCAReduceCPY(GpuKernelBase, HideC, CAReduceDtype):
-    """CAReduce that reuse the python code from compyte.
+    """CAReduce that reuse the python code from gpuarray.
 
     Too slow for now as it only have a python interface.
 
@@ -2535,7 +2535,7 @@ class GpuCAReduceCPY(GpuKernelBase, HideC, CAReduceDtype):
         err = GpuKernel_call(&%(k_var)s, 0, %(ls)s, gs, args);
         if (err != GA_NO_ERROR) {
             PyErr_Format(PyExc_RuntimeError,
-                         "compyte error: GpuCAReduceCPY: %%s.",
+                         "gpuarray error: GpuCAReduceCPY: %%s.",
                          GpuKernel_error(&%(k_var)s, err));
             %(fail)s
         }
@@ -2544,7 +2544,7 @@ class GpuCAReduceCPY(GpuKernelBase, HideC, CAReduceDtype):
             err = GpuArray_move(&%(output)s->ga, &tmp->ga);
             if (err != GA_NO_ERROR) {
                 PyErr_Format(PyExc_RuntimeError,
-                             "compyte error: GpuCAReduceCPY [cast]: %%s.",
+                             "gpuarray error: GpuCAReduceCPY [cast]: %%s.",
                              GpuArray_error(&tmp->ga, err));
                 %(fail)s
             }

theano/sandbox/gpuarray/neighbours.py

@@ -48,8 +48,8 @@ class GpuImages2Neibs(Images2Neibs, Op):
         return (9,1)
 
     def c_headers(self):
-        return ['cuda.h', '<compyte/extension.h>', '<numpy_compat.h>',
-                '<compyte/ext_cuda.h>']
+        return ['cuda.h', '<gpuarray/extension.h>', '<numpy_compat.h>',
+                '<gpuarray/ext_cuda.h>']
 
     def c_compiler(self):
         return NVCC_compiler

theano/sandbox/gpuarray/nnet.py

@@ -47,7 +47,7 @@ class GpuCrossentropySoftmaxArgmax1HotWithBias(Op):
         return Apply(self, [x, b, y_idx], [nll, sm, am])
 
     def c_headers(self):
-        return ['cuda.h', '<compyte/extension.h>', '<numpy_compat.h>']
+        return ['cuda.h', '<gpuarray/extension.h>', '<numpy_compat.h>']
 
     def c_support_code_apply(self, node, nodename):
         dtype_x = node.inputs[0].dtype
@@ -111,7 +111,7 @@ class GpuCrossentropySoftmaxArgmax1HotWithBias(Op):
         """ % locals()
 
     def c_init_code(self):
-        return ['cuda_get_ptr = (CUdeviceptr (*)(gpudata *g))compyte_get_extension("cuda_get_ptr");']
+        return ['cuda_get_ptr = (CUdeviceptr (*)(gpudata *g))gpuarray_get_extension("cuda_get_ptr");']
 
     def c_code(self, node, nodename, inp, out, sub):
         typecode_x = pygpu.gpuarray.dtype_to_typecode(node.inputs[0].dtype)
@@ -300,7 +300,7 @@ class GpuCrossentropySoftmax1HotWithBiasDx(Op):
         return (6,)
 
     def c_headers(self):
-        return ['cuda.h', '<compyte/extension.h>', '<numpy_compat.h>']
+        return ['cuda.h', '<gpuarray/extension.h>', '<numpy_compat.h>']
 
     def c_compiler(self):
         return NVCC_compiler
@@ -440,7 +440,7 @@ class GpuCrossentropySoftmax1HotWithBiasDx(Op):
         """ % locals()
 
     def c_init_code(self):
-        return ['cuda_get_ptr = (CUdeviceptr (*)(gpudata *g))compyte_get_extension("cuda_get_ptr");']
+        return ['cuda_get_ptr = (CUdeviceptr (*)(gpudata *g))gpuarray_get_extension("cuda_get_ptr");']
 
 gpu_crossentropy_softmax_1hot_with_bias_dx = GpuCrossentropySoftmax1HotWithBiasDx()
 
@@ -469,8 +469,8 @@ class GpuSoftmax (Op):
         return (12,) + inline_softmax.code_version
         
     def c_headers(self):
-        return ['cuda.h', '<compyte/extension.h>', '<numpy_compat.h>',
-                '<compyte/ext_cuda.h>']
+        return ['cuda.h', '<gpuarray/extension.h>', '<numpy_compat.h>',
+                '<gpuarray/ext_cuda.h>']
 
     def c_compiler(self):
         return NVCC_compiler
@@ -663,8 +663,8 @@ class GpuSoftmaxWithBias (Op):
         return (11,) + inline_softmax.code_version
         
     def c_headers(self):
-        return ['cuda.h', '<compyte/extension.h>', '<numpy_compat.h>',
-                '<compyte/ext_cuda.h>']
+        return ['cuda.h', '<gpuarray/extension.h>', '<numpy_compat.h>',
+                '<gpuarray/ext_cuda.h>']
 
     def c_compiler(self):
         return NVCC_compiler
@@ -852,4 +852,4 @@ class GpuSoftmaxWithBias (Op):
                            ])
         return (ret1 + "\n" + ret2) % locals()
 
-gpu_softmax_with_bias = GpuSoftmaxWithBias()
+gpu_softmax_with_bias = GpuSoftmaxWithBias()
\ No newline at end of file

theano/sandbox/gpuarray/subtensor.py

@@ -477,8 +477,8 @@ class GpuAdvancedIncSubtensor1_dev20(GpuAdvancedIncSubtensor1):
         return (2,)
 
     def c_headers(self):
-        return ['cuda.h', '<compyte/extension.h>', '<numpy_compat.h>',
-                '<compyte/ext_cuda.h>']
+        return ['cuda.h', '<gpuarray/extension.h>', '<numpy_compat.h>',
+                '<gpuarray/ext_cuda.h>']
 
     def c_compiler(self):
         return NVCC_compiler

theano/sandbox/gpuarray/tests/test_basic_ops.py

@@ -219,7 +219,8 @@ def test_transfer_cpu_gpu():
 
 def test_transfer_strided():
     # This is just to ensure that it works in theano
-    # compyte has a much more comprehensive suit of tests to ensure correctness
+    # libgpuarray has a much more comprehensive suit of tests to
+    # ensure correctness
     a = T.fmatrix('a')
     g = GpuArrayType(dtype='float32', broadcastable=(False, False))('g')
 

theano/sandbox/gpuarray/type.py

@@ -207,15 +207,15 @@ class GpuArrayType(Type):
     def c_headers(self):
         # We need arrayobject for the PyArrayDescr struct def
         # (even if we just use a pointer to it in a function def)
-        return ['<compyte/array.h>', '<compyte/kernel.h>', '<compyte/error.h>',
-                '<compyte/buffer_blas.h>', '<numpy/arrayobject.h>',
+        return ['<gpuarray/array.h>', '<gpuarray/kernel.h>', '<gpuarray/error.h>',
+                '<gpuarray/buffer_blas.h>', '<numpy/arrayobject.h>',
                 '<gpuarray_api.h>']
 
     def c_header_dirs(self):
         return [pygpu.get_include(), numpy.get_include()]
 
     def c_libraries(self):
-        return ['compyte']
+        return ['gpuarray']
 
     def c_code_cache_version(self):
         ver = pygpu.gpuarray.api_version()