test: 回退Docker context到26e6cb40完全一致——验证竞赛平台build

Dockerfile/qwen3_6_scripts/ex_engine/computility-run.yaml 全部
还原到26e6cb40的精确内容。删除所有26e6cb40不存在的新增文件
(prebuilt/*.so, wheels/*.whl, vendor_overrides/, 新增.cu/.sh等)。

目的：确认26e6cb40的文件内容在当前git状态下仍能通过竞赛平台build。
如果通过，说明问题在新增文件中；如果不通过，说明问题在git仓库层面。

ex_engine/csrc/moe/fused_moe_xllm.cpp

@@ -1,124 +0,0 @@
-/* Copyright 2025-2026 The xLLM Authors.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    https://github.com/jd-opensource/xllm/blob/main/LICENSE
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-#include "kernels/cuda/cuda_ops_api.h"
-#include "kernels/cuda/utils.h"
-#include "platform/device.h"
-#include "platform/platform.h"
-
-namespace xllm::kernel::cuda {
-
-torch::Tensor cutlass_fused_moe(
-    const torch::Tensor& input,                   // [num_tokens, hidden]
-    const torch::Tensor& token_selected_experts,  // [num_tokens, top_k]
-    const torch::Tensor& token_final_scales,      // [num_tokens, top_k]
-    const torch::Tensor&
-        fc1_expert_weights,  // [num_experts, inter_dim, hidden]
-    const torch::Tensor&
-        fc2_expert_weights,  // [num_experts, hidden, inter_dim]
-    torch::ScalarType output_dtype,
-    const std::vector<torch::Tensor>& quant_scales,
-    int32_t tp_size,
-    int32_t tp_rank,
-    int32_t ep_size,
-    int32_t ep_rank,
-    int32_t cluster_size,
-    int32_t cluster_rank,
-    const std::optional<torch::Tensor>& fc1_expert_biases,
-    const std::optional<torch::Tensor>& fc2_expert_biases,
-    const std::optional<torch::Tensor>& input_sf,
-    const std::optional<torch::Tensor>& swiglu_alpha,
-    const std::optional<torch::Tensor>& swiglu_beta,
-    const std::optional<torch::Tensor>& swiglu_limit,
-    const std::optional<torch::Tensor>& output,
-    bool enable_alltoall,
-    bool use_deepseek_fp8_block_scale,
-    bool use_w4_group_scaling,
-    bool use_mxfp8_act_scaling,
-    bool min_latency_mode,
-    bool use_packed_weights,
-    int32_t tune_max_num_tokens,
-    ActivationType activation_type) {
-  int64_t num_rows = input.size(0);
-  int64_t hidden_size = fc2_expert_weights.size(1);
-
-  if (min_latency_mode) {
-    num_rows *= fc2_expert_weights.size(0);
-  }
-
-  std::vector<int64_t> output_shape = {num_rows, hidden_size};
-  torch::Tensor result_output;
-  if (output.has_value() && output.value().defined()) {
-    result_output = output.value();
-  } else {
-    torch::TensorOptions options = input.options().dtype(output_dtype);
-    result_output = torch::empty(output_shape, options);
-  }
-
-  std::string fused_moe_uri = "fused_moe";
-  if (Platform::is_support_sm90a()) {
-    fused_moe_uri += "_90";
-  } else if (Platform::is_support_sm100a() || Platform::is_support_sm100f()) {
-    fused_moe_uri += "_100";
-  } else if (Platform::is_support_sm120a()) {
-    fused_moe_uri += "_120";
-  } else {
-    LOG(FATAL) << "FusedMoE is only supported on sm90, sm100, sm120.";
-  }
-
-  bind_tvmffi_stream_to_current_torch_stream(input.device());
-
-  ffi::Module fused_moe_runner =
-      get_function(fused_moe_uri, "init")(
-          to_dl_data_type(input.scalar_type()),
-          to_dl_data_type(fc1_expert_weights.scalar_type()),
-          to_dl_data_type(output_dtype),
-          use_deepseek_fp8_block_scale,
-          use_w4_group_scaling,
-          use_mxfp8_act_scaling,
-          use_packed_weights)
-          .cast<ffi::Module>();
-
-  fused_moe_runner->GetFunction("run_moe").value()(
-      to_ffi_tensor(result_output),
-      to_ffi_tensor(input),
-      to_ffi_tensor(token_selected_experts),
-      to_ffi_optional_tensor(token_final_scales),
-      to_ffi_tensor(fc1_expert_weights),
-      to_ffi_optional_tensor(fc1_expert_biases),
-      to_ffi_tensor(fc2_expert_weights),
-      to_ffi_optional_tensor(fc2_expert_biases),
-      to_ffi_optional_array_tensors(quant_scales),
-      to_ffi_optional_tensor(input_sf),
-      to_ffi_optional_tensor(swiglu_alpha),
-      to_ffi_optional_tensor(swiglu_beta),
-      to_ffi_optional_tensor(swiglu_limit),
-      tp_size,
-      tp_rank,
-      ep_size,
-      ep_rank,
-      cluster_size,
-      cluster_rank,
-      enable_alltoall,
-      min_latency_mode,
-      /*profile_ids=*/ffi::Optional<ffi::Array<int64_t>>(),  // TODO: support
-                                                             // auto tuning
-                                                             // profile ids
-      support_pdl(),
-      activation_type);
-
-  return result_output;
-}
-}  // namespace xllm::kernel::cuda