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[Kernel] fix types used in aqlm and ggml kernels to support dynamo (#7596)

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This commit is contained in:
bnellnm
2024-08-16 17:00:11 -04:00
committed by GitHub
parent 7759ae958f
commit 37fd47e780
7 changed files with 39 additions and 53 deletions
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2
csrc/quantization/gguf/dequantize.cuh
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@@ -487,7 +487,7 @@ static void dequantize_row_iq4_xs_cuda(const void * vx, dst_t * y, const int k,
dequantize_block_iq4_xs<<<nb, 32, 0, stream>>>(vx, y);
}
static to_fp16_cuda_t ggml_get_to_fp16_cuda(int type) {
static to_fp16_cuda_t ggml_get_to_fp16_cuda(int64_t type) {
switch (type) {
case 2:
return dequantize_block_cuda<QK4_0, QR4_0, dequantize_q4_0>;

8
csrc/quantization/gguf/gguf_kernel.cu
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@@ -60,7 +60,7 @@ static void quantize_row_q8_1_cuda(const half* x, void* vy, const int kx,
}
torch::Tensor ggml_dequantize(torch::Tensor W, // quant weight
int8_t type, int64_t m, int64_t n) {
int64_t type, int64_t m, int64_t n) {
const at::cuda::OptionalCUDAGuard device_guard(device_of(W));
auto options =
torch::TensorOptions().dtype(torch::kFloat16).device(W.device());
@@ -73,7 +73,7 @@ torch::Tensor ggml_dequantize(torch::Tensor W, // quant weight
torch::Tensor ggml_mul_mat_vec_a8(torch::Tensor W, // quant weight
torch::Tensor X, // input
int8_t type, int64_t row) {
int64_t type, int64_t row) {
int col = X.sizes()[1];
const int padded = (col + 512 - 1) / 512 * 512;
const at::cuda::OptionalCUDAGuard device_guard(device_of(X));
@@ -172,7 +172,7 @@ torch::Tensor ggml_mul_mat_vec_a8(torch::Tensor W, // quant weight
torch::Tensor ggml_mul_mat_a8(torch::Tensor W, // quant weight
torch::Tensor X, // input
int8_t type, int64_t row) {
int64_t type, int64_t row) {
int col = X.sizes()[1];
int padded = (col + 512 - 1) / 512 * 512;
int batch = X.sizes()[0];
@@ -239,4 +239,4 @@ torch::Tensor ggml_mul_mat_a8(torch::Tensor W, // quant weight
break;
}
return Y;
}
}