use unique names for the different _var_core kernels
@@ -588,25 +588,29 @@ __device__ double my_norm(const complex<double>& x) { return norm(x); }
cdef _var_core_float16 = ReductionKernel(
'S x, T mean, float32 alpha', 'float16 out',
'my_norm(x - mean)',
- 'a + b', 'out = alpha * a', '0', '_var_core', preamble=_norm_preamble)
+ 'a + b', 'out = alpha * a', '0', 'cupy_var_core_float16',
+ preamble=_norm_preamble)
cdef _var_core_float32 = ReductionKernel(
'S x, T mean, float32 alpha', 'float32 out',
'my_norm(x - mean)',
- 'a + b', 'out = alpha * a', '0', '_var_core', preamble=_norm_preamble)
+ 'a + b', 'out = alpha * a', '0', 'cupy_var_core_float32',
+ preamble=_norm_preamble)
cdef _var_core_float64 = ReductionKernel(
'S x, T mean, float64 alpha', 'float64 out',
'my_norm(x - mean)',
- 'a + b', 'out = alpha * a', '0', '_var_core', preamble=_norm_preamble)
+ 'a + b', 'out = alpha * a', '0', 'cupy_var_core_float64',
+ preamble=_norm_preamble)
cdef _var_core_out = ReductionKernel(
'S x, T mean, U alpha', 'U out',
'my_norm(x - mean)',
- 'a + b', 'out = alpha * a', '0', '_var_core', preamble=_norm_preamble)
+ 'a + b', 'out = alpha * a', '0', 'cupy_var_core_out',
+ preamble=_norm_preamble)
# TODO(okuta) needs cast
