Clean up move of cusparse to dadi distribution

dadi/cuda/__init__.py

@@ -2,8 +2,8 @@ import atexit
 
 import pycuda.autoinit
 from pycuda.tools import clear_context_caches, make_default_context
-from dadi.cuda.cusparse import cusparseCreate, cusparseDestroy
 from skcuda.cublas import cublasCreate, cublasDestroy, cublasDgeam
+from .cusparse import cusparseCreate, cusparseDestroy
 
 ctx = make_default_context()
 cusparse_handle = cusparseCreate()

dadi/cuda/cusparse.py

-#!/usr/bin/env python
-
 """
-Python interface to CUSPARSE functions.
+Python interface to CUSPARSE functions for solving batch tridiagonal systems.
 
-Note: this module does not explicitly depend on PyCUDA.
+The set up code for this module is heavily based on the cusparse module within scikit-cuda.
+It is duplicated here because, as of version 0.5.3, the cusparse module within scikit-cuda raises an error upon import.
+My pull request to fix this error and add the batch tridiagonal functions scikit-cuda was not acted for
+over two months, hence I moved the code into the dadi distribution itself.
 """
-
-from __future__ import absolute_import
-
-import ctypes
-import platform
+import ctypes, platform, sys
 from string import Template
-import sys
 
-from skcuda import cuda
+#(base) PS C:\Users\rgute\Desktop\dadi-devel\tests> python test_CUDA.py -v                                               C:\Users\rgute\anaconda3\lib\site-packages\skcuda\cublas.py:284: UserWarning: creating CUBLAS context to get version number
+#  warnings.warn('creating CUBLAS context to get version number')
+#test_2d_const_params (__main__.CUDATestCase) ... C:\Users\rgute\anaconda3\lib\site-packages\pycuda\gpuarray.py:183: DeprecationWarning: np.asscalar(a) is deprecated since NumPy v1.16, use a.item() instead
+#  s = np.asscalar(s)
 
 # Load library:
 _linux_version_list = [10.2, 10.1, 10.0, 9.2, 9.1, 9.0, 8.0, 7.5, 7.0, 6.5, 6.0, 5.5, 5.0, 4.0]
@@ -153,67 +152,6 @@ def cusparseDestroy(handle):
     status = _libcusparse.cusparseDestroy(handle)
     cusparseCheckStatus(status)
 
-_libcusparse.cusparseGetVersion.restype = int
-_libcusparse.cusparseGetVersion.argtypes = [ctypes.c_void_p, ctypes.c_void_p]
-def cusparseGetVersion(handle):
-    """
-    Return CUSPARSE library version.
-
-    Returns the version number of the CUSPARSE library.
-
-    Parameters
-    ----------
-    handle : int
-        CUSPARSE library context.
-
-    Returns
-    -------
-    version : int
-        CUSPARSE library version number.
-    """
-    version = ctypes.c_int()
-    status = _libcusparse.cusparseGetVersion(handle,
-                                             ctypes.byref(version))
-    cusparseCheckStatus(status)
-    return version.value
-
-_libcusparse.cusparseSetStream.restype = int
-_libcusparse.cusparseSetStream.argtypes = [ctypes.c_void_p, ctypes.c_int]
-def cusparseSetStream(handle, id):
-    """
-    Sets the CUSPARSE stream in which kernels will run.
-
-    Parameters
-    ----------
-    handle : int
-        CUSPARSE library context.
-    id : int
-        Stream ID.
-    """
-    status = _libcusparse.cusparseSetStream(handle, id)
-    cusparseCheckStatus(status)
-
-_libcusparse.cusparseGetStream.restype = int
-_libcusparse.cusparseGetStream.argtypes = [ctypes.c_void_p, ctypes.c_void_p]
-def cusparseGetStream(handle):
-    """
-    Gets the CUSPARSE stream in which kernels will run.
-
-    Parameters
-    ----------
-    handle : int
-        CUSPARSE library context.
-
-    Returns
-    -------
-    handle : int
-        CUSPARSE library context.
-    """
-    id = ctypes.c_int()
-    status = _libcusparse.cusparseGetStream(handle, ctypes.byref(id))
-    cusparseCheckStatus(status)
-    return id.value
-
 gtsv2StridedBatch_bufferSizeExt_doc = Template(
     """
     Calculate size of work buffer used by cusparse<t>gtsv2StridedBatch.

tests/test_CUDA.py

@@ -26,7 +26,7 @@ class CUDATestCase(unittest.TestCase):
     
         dadi.cuda_enabled(True)
         phi_gpu = dadi.Integration.two_pops(phi.copy(), xx, *args,
-                enable_cuda_const=True)
+                enable_cuda_cached=True)
 
         self.assertTrue(np.allclose(phi_cpu, phi_gpu))
 
@@ -73,7 +73,7 @@ class CUDATestCase(unittest.TestCase):
                        m12, m13, m21, m23, m31, m32,
                        gamma1, gamma2, gamma3, h1, h2, h3,
                        theta0, initial_t, frozen1, frozen2,
-                       frozen3, enable_cuda_const=True)
+                       frozen3, enable_cuda_cached=True)
         
         self.assertTrue(np.allclose(phi_cpu, phi_gpu))