def __rdiv__(self,other):
"""Divides an array by a scalar or an array::
x = n / self
"""
if isinstance(other, GPUArray):
if not self.flags.forc or not other.flags.forc:
raise RuntimeError("only contiguous arrays may "
"be used as arguments to this operation")
result = self._new_like_me(_get_common_dtype(self, other))
func = elementwise.get_divide_kernel()
func.prepared_async_call(self._grid, self._block, None,
other.gpudata, self.gpudata, result.gpudata,
self.mem_size)
return result
else:
if other == 1:
return self
else:
# create a new array for the result
result = self._new_like_me()
return self._rdiv_scalar(other, result)
def __rdiv__(self, other):
"""Divides an array by a scalar or an array::
x = n / self
"""
if isinstance(other, GPUArray):
if not self.flags.forc or not other.flags.forc:
raise RuntimeError("only contiguous arrays may "
"be used as arguments to this operation")
result = self._new_like_me(_get_common_dtype(self, other))
func = elementwise.get_divide_kernel()
func.prepared_async_call(self._grid, self._block, None,
other.gpudata, self.gpudata,
result.gpudata, self.mem_size)
return result
else:
if other == 1:
return self
else:
# create a new array for the result
result = self._new_like_me()
return self._rdiv_scalar(other, result)
def _div(self, other, out, stream=None):
"""Divides an array by another array."""
assert self.shape == other.shape
func = elementwise.get_divide_kernel(self.dtype, other.dtype, out.dtype)
func.set_block_shape(*self._block)
func.prepared_async_call(self._grid, stream,
self.gpudata, other.gpudata,
out.gpudata, self.mem_size)
return out
def __rdiv__(self,other):
"""Divides an array by a scalar or an array::
x = n / self
"""
if isinstance(other, GPUArray):
result = self._new_like_me(_get_common_dtype(self, other))
func = elementwise.get_divide_kernel()
func.set_block_shape(*self._block)
func.prepared_async_call(self._grid, None,
other.gpudata, self.gpudata, result.gpudata,
self.mem_size)
return result
else:
if other == 1:
return self
else:
# create a new array for the result
result = self._new_like_me()
return self._rdiv_scalar(other, result)
