Hello,
I'm new to using pycuda and I've run into the following issue. It seems
that the definition of __rmul__ in GPUArray asserts that the dtype is
float32. Is was wondering if there a reason for this? I would like to do
this operation with other types such as float64.
(line 328 of gpuarray.py)
def _rdiv_scalar(self, other, out, stream=None):
"""Divides an array by a scalar::
y = n / self
"""
if not self.flags.forc:
raise RuntimeError("only contiguous arrays may "
"be used as arguments to this operation")
assert self.dtype == np.float32
func = elementwise.get_rdivide_elwise_kernel(self.dtype)
func.prepared_async_call(self._grid, self._block, stream,
self.gpudata, other,
out.gpudata, self.mem_size)
Thanks
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