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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 14, 23:45 UTC

[AMD][CI/Build][Bugfix] Guarding CUDA specific functions by ifndef ROCM (#21766)

Signed-off-by: Gregory Shtrasberg <Gregory.Shtrasberg@amd.com>

Gregory Shtrasberg committed Jul 28, 2025 at 23:35 UTC 12a223ef9bfebcc61e477047dce049495fe8c8a8
1 file changed +6 -2
csrc/quantization/compressed_tensors/int8_quant_kernels.cu
+6 -2
@@ -1,7 +1,9 @@
1 #include <ATen/cuda/CUDAContext.h>
2 #include <torch/all.h>
3
4 -#include "../per_token_group_quant_8bit.h"
4 +#ifndef USE_ROCM
5 + #include "../per_token_group_quant_8bit.h"
6 +#endif
7
8 #include <cmath>
9
@@ -339,10 +341,12 @@ void dynamic_scaled_int8_quant(
341 });
342 }
343
344 +#ifndef USE_ROCM
345 void per_token_group_quant_int8(const torch::Tensor& input,
346 torch::Tensor& output_q,
347 torch::Tensor& output_s, int64_t group_size,
348 double eps, double int8_min, double int8_max) {
349 per_token_group_quant_8bit(input, output_q, output_s, group_size, eps,
350 int8_min, int8_max);
348 -}
\ No newline at end of file
351 +}
352 +#endif