model = bitblas.Linear(
in_features=1024,
out_features=1024,
bias=False,
A_dtype="bfloat16", # activation A dtype
W_dtype="uint2", # weight W dtype
accum_dtype="float32", # accumulation dtype
out_dtype="float16", # output dtype
# configs for weight only quantization
group_size=None, # setting for grouped quantization
with_scaling=True, # setting for scaling factor
with_zeros=True, # setting for zeros
zeros_mode="original", # setting for how to calculating zeros
fast_decoding=False,
# Target optimization var for dynamic symbolic.
# For detailed information please checkout docs/PythonAPI.md
# By default, the optimization var is [1, 16, 32, 64, 128, 256, 512]
opt_M=[1, 16, 32, 64, 128],
)2025-03-10 15:32:38 [BitBLAS:ERROR]: An exception occurred for hint {block_M=16,block_N=256,warp_M=16,warp_N=64,block_K=32,threads=128,num_stages=0,enable_rasterization=True,split_k_factor=16}: #include <tl_templates/cuda/gemm.h>
#include <tl_templates/cuda/copy.h>
#include <tl_templates/cuda/reduce.h>
#include <tl_templates/cuda/ldsm.h>
#include <tl_templates/cuda/threadblock_swizzle.h>
#include <tl_templates/cuda/debug.h>
extern "C" __global__ void __launch_bounds__(128) general_dequant_matmul_kernel(bfloat16_t* __restrict__ A, signed char* __restrict__ B, half_t* __restrict__ C, bfloat16_t* __restrict__ Scale, bfloat16_t* __restrict__ Zeros, int m) {
extern __shared__ __align__(1 ... u(36): error: identifier "__pack_nv_bfloat162" is undefined
condval = make_uint4(__pack_nv_bfloat162(bfloat16_t(0.000000e+00f), bfloat16_t(0.000000e+00f)), __pack_nv_bfloat162(bfloat16_t(0.000000e+00f), bfloat16_t(0.000000e+00f)), __pack_nv_bfloat162(bfloat16_t(0.000000e+00f), bfloat16_t(0.000000e+00f)), __pack_nv_bfloat162(bfloat16_t(0.000000e+00f), bfloat16_t(0.000000e+00f)));
^
1 error detected in the compilation of "/tmp/tmpa36zlrof/tvm_kernels.cu".
2025-03-10 15:32:38 [BitBLAS:ERROR]: An exception occurred for hint {block_M=16,block_N=32,warp_M=16,warp_N=16,block_K=256,threads=64,num_stages=0,enable_rasterization=True,split_k_factor=2}: #include <tl_templates/cuda/gemm.h>
#include <tl_templates/cuda/copy.h>
#include <tl_templates/cuda/reduce.h>
#include <tl_templates/cuda/ldsm.h>
#include <tl_templates/cuda/threadblock_swizzle.h>
#include <tl_templates/cuda/debug.h>
extern "C" __global__ void __launch_bounds__(128) general_dequant_matmul_kernel(bfloat16_t* __restrict__ A, signed char* __restrict__ B, half_t* __restrict__ C, bfloat16_t* __restrict__ Scale, bfloat16_t* __restrict__ Zeros, int m) {
extern __shared__ __align__(1 ... ls.cu(35): error: identifier "__pack_nv_bfloat162" is undefined
condval = make_uint4(__pack_nv_bfloat162(bfloat16_t(0.000000e+00f), bfloat16_t(0.000000e+00f)), __pack_nv_bfloat162(bfloat16_t(0.000000e+00f), bfloat16_t(0.000000e+00f)), __pack_nv_bfloat162(bfloat16_t(0.000000e+00f), bfloat16_t(0.000000e+00f)), __pack_nv_bfloat162(bfloat16_t(0.000000e+00f), bfloat16_t(0.000000e+00f)));
^
1 error detected in the compilation of "/tmp/tmpesebmis9/tvm_kernels.cu".
