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cuda : enable i16 and i32 for DUP (#28897)

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* cuda : enable i16 and i32 for DUP

* docs : update ops table for DUP on CUDA
This commit is contained in:
Aman Karki
2026-09-15 11:42:21 +08:00
committed by GitHub
parent 69eb250670
commit 4c9233c034
4 changed files with 14 additions and 9 deletions
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docs/ops.md
+1 -1
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@@ -44,7 +44,7 @@ Legend:
| DSV4_HC_COMB | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ |
| DSV4_HC_POST | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ |
| DSV4_HC_PRE | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ |
| DUP | ❌ | ✅ | ✅ | 🟡 | ❌ | ❌ | 🟡 | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ |
| DUP | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | 🟡 | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ |
| ELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | ❌ | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ |
| EXP | ❌ | ✅ | ✅ | 🟡 | 🟡 | 🟡 | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ |
| EXPM1 | ❌ | ❌ | ✅ | 🟡 | 🟡 | ❌ | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ |
docs/ops/CUDA.csv
+4 -4
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@@ -5000,14 +5000,14 @@
"CUDA0","REPEAT_BACK","type=f32,ne=[8,6,4,2],nr=[1,1,1,2],v=1","support","1","yes","CUDA"
"CUDA0","DUP","type=f32,ne=[10,10,20,1]","support","1","yes","CUDA"
"CUDA0","DUP","type=f16,ne=[10,10,20,1]","support","1","yes","CUDA"
"CUDA0","DUP","type=i32,ne=[10,10,20,1]","support","0","no","CUDA"
"CUDA0","DUP","type=i16,ne=[10,10,20,1]","support","0","no","CUDA"
"CUDA0","DUP","type=i32,ne=[10,10,20,1]","support","1","yes","CUDA"
"CUDA0","DUP","type=i16,ne=[10,10,20,1]","support","1","yes","CUDA"
"CUDA0","DUP","type=f32,ne=[10,10,5,1],permute=[0,2,1,3]","support","1","yes","CUDA"
"CUDA0","DUP","type=f16,ne=[10,10,5,1],permute=[0,2,1,3]","support","1","yes","CUDA"
"CUDA0","DUP","type=f32,ne=[10,10,5,1],permute=[1,0,2,3]","support","1","yes","CUDA"
"CUDA0","DUP","type=f16,ne=[10,10,5,1],permute=[1,0,2,3]","support","1","yes","CUDA"
"CUDA0","DUP","type=i16,ne=[10,8,3,1],permute=[0,2,1,3]","support","0","no","CUDA"
"CUDA0","DUP","type=i16,ne=[10,8,3,1],permute=[1,2,0,3]","support","0","no","CUDA"
"CUDA0","DUP","type=i16,ne=[10,8,3,1],permute=[0,2,1,3]","support","1","yes","CUDA"
"CUDA0","DUP","type=i16,ne=[10,8,3,1],permute=[1,2,0,3]","support","1","yes","CUDA"
"CUDA0","SET","type_src=f32,type_dst=f32,ne=[6,5,4,3],dim=1","support","1","yes","CUDA"
"CUDA0","SET","type_src=f32,type_dst=f32,ne=[6,5,4,3],dim=2","support","1","yes","CUDA"
"CUDA0","SET","type_src=f32,type_dst=f32,ne=[6,5,4,3],dim=3","support","1","yes","CUDA"
Can't render this file because it is too large.
ggml/src/ggml-cuda/cpy.cu
+8
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@@ -589,6 +589,14 @@ void ggml_cuda_cpy(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, gg
ggml_cpy_scalar_cuda<int32_t, int32_t>
(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
}
} else if (src0->type == GGML_TYPE_I16 && src1->type == GGML_TYPE_I16) {
if (can_be_transposed) {
ggml_cpy_scalar_cuda<int16_t, int16_t, true>
(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
} else {
ggml_cpy_scalar_cuda<int16_t, int16_t>
(src0_ddc, src1_ddc, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13, main_stream);
}
} else if (src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_I32) {
if (contiguous_srcs) {
ggml_cpy_scalar_contiguous_cuda<float, int32_t>
ggml/src/ggml-cuda/ggml-cuda.cu
+1 -4
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@@ -5298,10 +5298,7 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
return false;
} break;
case GGML_OP_DUP:
{
ggml_type src0_type = op->src[0]->type;
return src0_type != GGML_TYPE_I32 && src0_type != GGML_TYPE_I16;
} break;
return true;
case GGML_OP_ARGMAX:
case GGML_OP_COUNT_EQUAL:
{