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	CANN: GGML_OP_CPY optimization (#15070)
Signed-off-by: noemotiovon <757486878@qq.com>
This commit is contained in:
		| @@ -753,69 +753,55 @@ static void cann_copy(ggml_backend_cann_context& ctx, aclTensor* acl_src, | ||||
| void ggml_cann_dup(ggml_backend_cann_context& ctx, ggml_tensor* dst) { | ||||
|     ggml_tensor* src0 = dst->src[0]; | ||||
|  | ||||
|     aclTensor* acl_src = ggml_cann_create_tensor(src0); | ||||
|     aclTensor* acl_dst = ggml_cann_create_tensor(dst); | ||||
|     if (ggml_are_same_shape(src0, dst)) { | ||||
|         aclTensor* acl_src = ggml_cann_create_tensor(src0); | ||||
|         aclTensor* acl_dst = ggml_cann_create_tensor(dst); | ||||
|         if (dst->type == src0->type) { | ||||
|             cann_copy(ctx, acl_src, acl_dst); | ||||
|         } else { | ||||
|             aclnn_cast(ctx, acl_src, acl_dst, ggml_cann_type_mapping(dst->type)); | ||||
|         } | ||||
|         ggml_cann_release_resources(ctx, acl_src, acl_dst); | ||||
|     } else { | ||||
|         if (ggml_is_contiguous(src0) && ggml_is_contiguous(dst)) { | ||||
|             if (dst->type == src0->type) { | ||||
|                 size_t cpy_size = ggml_nbytes(dst); | ||||
|                 ggml_cann_async_memcpy(ctx, dst->data, src0->data, cpy_size, | ||||
|                     ACL_MEMCPY_DEVICE_TO_DEVICE); | ||||
|                 return; | ||||
|             } else { | ||||
|                 ggml_cann_pool_alloc src_buffer_allocator( | ||||
|                     ctx.pool(), | ||||
|                     ggml_nelements(dst) * ggml_type_size(dst->type)); | ||||
|                 void* src_trans_buffer = src_buffer_allocator.get(); | ||||
|                 size_t src_trans_nb[GGML_MAX_DIMS]; | ||||
|                 src_trans_nb[0] = ggml_type_size(dst->type); | ||||
|                 for (int i = 1; i < GGML_MAX_DIMS; i++) { | ||||
|                     src_trans_nb[i] = src_trans_nb[i - 1] * src0->ne[i - 1]; | ||||
|                 } | ||||
|                 aclTensor* src_trans_tensor = ggml_cann_create_tensor( | ||||
|                     src_trans_buffer, ggml_cann_type_mapping(dst->type), | ||||
|                     ggml_type_size(dst->type), src0->ne, src_trans_nb, | ||||
|                     GGML_MAX_DIMS); | ||||
|  | ||||
|                 aclnn_cast(ctx, acl_src, src_trans_tensor, ggml_cann_type_mapping(dst->type)); | ||||
|                 size_t cpy_size = ggml_nbytes(dst); | ||||
|                 ggml_cann_async_memcpy(ctx, dst->data, src_trans_buffer, cpy_size, | ||||
|                     ACL_MEMCPY_DEVICE_TO_DEVICE); | ||||
|                 ggml_cann_release_resources(ctx, src_trans_tensor); | ||||
|                 return; | ||||
|             } | ||||
|         } else if (ggml_is_contiguous(dst)) { | ||||
|             ggml_cann_pool_alloc src_buffer_allocator( | ||||
|                 ctx.pool(), ggml_nelements(dst) * ggml_type_size(dst->type)); | ||||
|             void* src_trans_buffer = src_buffer_allocator.get(); | ||||
|         void* src_trans_buffer = src0->data; | ||||
|         ggml_cann_pool_alloc src_buffer_allocator; | ||||
|         if (!ggml_is_contiguous(src0)) { | ||||
|             aclTensor* acl_src = ggml_cann_create_tensor(src0); | ||||
|             src_buffer_allocator.alloc(ctx.pool(), | ||||
|                 ggml_nelements(src0) * ggml_type_size(src0->type)); | ||||
|             src_trans_buffer = src_buffer_allocator.get(); | ||||
|             size_t src_trans_nb[GGML_MAX_DIMS]; | ||||
|             src_trans_nb[0] = ggml_type_size(dst->type); | ||||
|             src_trans_nb[0] = ggml_type_size(src0->type); | ||||
|             for (int i = 1; i < GGML_MAX_DIMS; i++) { | ||||
|                 src_trans_nb[i] = src_trans_nb[i - 1] * src0->ne[i - 1]; | ||||
|             } | ||||
|             aclTensor* src_trans_tensor = ggml_cann_create_tensor( | ||||
|                 src_trans_buffer, ggml_cann_type_mapping(dst->type), | ||||
|                 ggml_type_size(dst->type), src0->ne, src_trans_nb, | ||||
|                 src_trans_buffer, ggml_cann_type_mapping(src0->type), | ||||
|                 ggml_type_size(src0->type), src0->ne, src_trans_nb, | ||||
|                 GGML_MAX_DIMS); | ||||
|  | ||||
|             aclnn_cast(ctx, acl_src, src_trans_tensor, ggml_cann_type_mapping(dst->type)); | ||||
|  | ||||
|             size_t cpy_size = ggml_nbytes(dst); | ||||
|             ggml_cann_async_memcpy(ctx, dst->data, src_trans_buffer, cpy_size, | ||||
|                 ACL_MEMCPY_DEVICE_TO_DEVICE); | ||||
|             ggml_cann_release_resources(ctx, src_trans_tensor); | ||||
|             return; | ||||
|         } else { | ||||
|             GGML_ABORT("Unsupport dst is not contiguous."); | ||||
|             cann_copy(ctx, acl_src, src_trans_tensor); | ||||
|             ggml_cann_release_resources(ctx, acl_src, src_trans_tensor); | ||||
|         } | ||||
|  | ||||
|         size_t src_reshape_nb[GGML_MAX_DIMS]; | ||||
|         src_reshape_nb[0] = ggml_type_size(src0->type); | ||||
|         for (int i = 1; i < GGML_MAX_DIMS; i++) { | ||||
|             src_reshape_nb[i] = src_reshape_nb[i - 1] * dst->ne[i - 1]; | ||||
|         } | ||||
|  | ||||
|         aclTensor* trans_acl_src = ggml_cann_create_tensor(src_trans_buffer, | ||||
|             ggml_cann_type_mapping(src0->type),ggml_type_size(src0->type), | ||||
|             dst->ne, src_reshape_nb, GGML_MAX_DIMS, ACL_FORMAT_ND); | ||||
|         aclTensor* acl_dst = ggml_cann_create_tensor(dst); | ||||
|  | ||||
|         if (dst->type == src0->type) { | ||||
|             cann_copy(ctx, trans_acl_src, acl_dst); | ||||
|         } else { | ||||
|             aclnn_cast(ctx, trans_acl_src, acl_dst, ggml_cann_type_mapping(dst->type)); | ||||
|         } | ||||
|         ggml_cann_release_resources(ctx, trans_acl_src, acl_dst); | ||||
|     } | ||||
|     ggml_cann_release_resources(ctx, acl_src, acl_dst); | ||||
|     return; | ||||
| } | ||||
|  | ||||
| /** | ||||
|   | ||||
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	 Chenguang Li
					Chenguang Li