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fix(build): c10::optional for CoreX CUDA 10.2 — std::optional incompatible

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CoreX PyTorch uses c10::optional, not std::optional. The forward-declared
ixformer::infer signatures must match the actual .so ABI.
This commit is contained in:
Claude
2026-08-14 01:49:25 +00:00
parent 1d9b620416
commit 56fe58ada3
2 changed files with 21 additions and 21 deletions
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20
qwen3_6_scripts/ix_moe_bridge.cpp
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@@ -17,7 +17,7 @@
#include <vector>
#include <optional>
static const std::optional<torch::Tensor> kNoneTensor = {};
static const c10::optional<torch::Tensor> kNoneTensor = {};
// Forward-declare ixformer C++ API (from base image SDK)
namespace ixformer {
@@ -34,9 +34,9 @@ void moe_compute_token_index_api(
torch::Tensor& src_dst,
torch::Tensor& dst_src,
torch::Tensor& expert_sizes_gpu,
const std::optional<torch::Tensor>& expert_mask,
const std::optional<torch::Tensor>& expert_sizes_cpu,
const std::optional<torch::Tensor>& expand_tokens_gpu,
const c10::optional<torch::Tensor>& expert_mask,
const c10::optional<torch::Tensor>& expert_sizes_cpu,
const c10::optional<torch::Tensor>& expand_tokens_gpu,
int64_t start_expert_id,
int64_t end_expert_id,
int64_t num_experts);
@@ -44,7 +44,7 @@ void moe_compute_token_index_api(
void moe_expand_input(torch::Tensor outputs,
torch::Tensor inputs,
torch::Tensor dst_to_src,
const std::optional<torch::Tensor>& src_to_dst,
const c10::optional<torch::Tensor>& src_to_dst,
int64_t dst_tokens,
int64_t expand_factor);
@@ -52,17 +52,17 @@ void moe_w16a16_group_gemm(torch::Tensor output,
torch::Tensor inputs,
torch::Tensor weights,
torch::Tensor tokens_per_experts,
const std::optional<torch::Tensor>& dst_to_src,
const std::optional<torch::Tensor>& bias,
const c10::optional<torch::Tensor>& dst_to_src,
const c10::optional<torch::Tensor>& bias,
std::string format,
int64_t persistent,
int64_t output_n);
void moe_output_reduce_sum(torch::Tensor outputs,
torch::Tensor inputs,
const std::optional<torch::Tensor>& mul_weight,
const std::optional<torch::Tensor>& mask,
const std::optional<torch::Tensor>& extra_residual,
const c10::optional<torch::Tensor>& mul_weight,
const c10::optional<torch::Tensor>& mask,
const c10::optional<torch::Tensor>& extra_residual,
double scaling_factor);
void silu_and_mul(torch::Tensor& input, torch::Tensor& output);