[Intel HPU] enable MoE EP for hpu

[yanfeich]

Motivation

enable MoE EP for hpu with loader_v1

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💡 如若此PR是Cherry Pick，PR标题需遵循格式，在最开始加上[Cherry-Pick]标签，以及最后面加上原PR ID，例如[Cherry-Pick][CI] Add check trigger and logic(#5191)

Modifications

• fastdeploy/model_executor/layers/moe/moe.py
  HPU calls forward_normal no matter EP or TP, and won't fall into forward_split_allgather nor forward_chunked_moe

• fused_moe_hpu_backend.py
  change down_proj_in_scale from list to tensor.

• hpu_model_runner.py
  list to tensor, add padding dim for 0x80 alignment request.

• fastdeploy/model_executor/load_weight_utils.py
  needs up_gate_proj.activation_scale for EP in loader v0

• fastdeploy/model_executor/models/ernie4_5_moe.py‎
  add Attention related activation_scale name conversions

    - self_attn.
  

loaded_weight_name	checkpoint_to_fd_key_fn	all_param_mapping
qkv_proj.activation_scale	qkv_proj.in_scale	qkv_proj.act_scale
o_proj.activation_scale	o_proj.in_scale	o_proj.act_scale
cachek_matmul.activation_scale	cachek_matmul.in_scale	attn.cache_k_scale
cachev_matmul.activation_scale	cachev_matmul.in_scale	attn.cache_v_scale
q_matmul.activation_scale	q_matmul.in_scale	attn.q_scale
s_matmul.activation_scale	s_matmul.in_scale	attn.s_scale

    - mlp. & mlp.shared_experts.

loaded_weight_name	checkpoint_to_fd_key_fn	all_param_mapping
down_proj.activation_scale	down_proj.in_scale	down_proj.act_scale
up_gate_proj.activation_scale	up_gate_proj.in_scale	up_gate_proj.act_scale

    - mlp.experts. (all experts share same activation_scale)

loaded_weight_name	checkpoint_to_fd_key_fn	all_param_mapping
up_gate_proj.activation_scale	up_gate_proj.in_scale	up_gate_proj_in_scale

    - mlp.experts.{exp_id}.

loaded_weight_name	checkpoint_to_fd_key_fn	all_param_mapping
experts.{exp_id}.down_proj.activation_scale	experts.{exp_id}.down_proj.in_scale	experts.down_proj_in_scale

Usage or Command

set enable_expert_parallel=True, and disable_sequence_parallel_moe=True, to enable HPU MoE EP.

Accuracy Tests

Checklist

• [ Done ] Add at least a tag in the PR title.
  • Tag list: [[FDConfig],[APIServer],[Engine], [Scheduler], [PD Disaggregation], [Executor], [Graph Optimization], [Speculative Decoding], [RL], [Models], [Quantization], [Loader], [OP], [KVCache], [DataProcessor], [BugFix], [Docs], [CI], [Optimization], [Feature], [Benchmark], [Others], [XPU], [HPU], [GCU], [DCU], [Iluvatar], [Metax]]
  • You can add new tags based on the PR content, but the semantics must be clear.
• [ Done ] Format your code, run pre-commit before commit.
• [ Done ] Add unit tests. Please write the reason in this PR if no unit tests.
  conducted by local tests
• Provide accuracy results.
• If the current PR is submitting to the release branch, make sure the PR has been submitted to the develop branch, then cherry-pick it to the release branch with the [Cherry-Pick] PR tag.

[paddle-bot]

Thanks for your contribution!

[Copilot]

Pull request overview

This PR enables MoE (Mixture of Experts) Expert Parallelism (EP) for Intel HPU by modifying the execution path and weight handling to accommodate HPU-specific requirements.

Key changes:

• Modified MoE forward logic to route HPU through forward_normal regardless of EP/TP configuration
• Converted down_proj_in_scale from list to tensor and added padding alignment for HPU's 0x80 byte alignment requirement
• Added up_gate_proj.activation_scale weight loading support for EP mode

Reviewed changes

Copilot reviewed 5 out of 5 changed files in this pull request and generated 6 comments.

Show a summary per file

File	Description
fastdeploy/model_executor/layers/moe/moe.py	Routes HPU platform to use forward_normal path for both EP and TP modes
fastdeploy/model_executor/layers/backends/intel_hpu/moe/fused_moe_hpu_backend.py	Changes down_proj_in_scale handling from list to tensor and renames apply_tp to apply
fastdeploy/worker/hpu_model_runner.py	Adds alignment padding function for scales and implements early return for EP mode
fastdeploy/model_executor/load_weight_utils.py	Adds up_gate_proj_in_scale_key to weight loading for EP support
examples/intel_hpu/offline_demo.py	Enables EP configuration in demo script

[codecov-commenter]

Codecov Report

❌ Patch coverage is 18.18182% with 9 lines in your changes missing coverage. Please review.
⚠️ Please upload report for BASE (develop@decbbb3). Learn more about missing BASE report.

Files with missing lines	Patch %	Lines
fastdeploy/model_executor/layers/moe/moe.py	16.66%	4 Missing and 1 partial ⚠️
fastdeploy/model_executor/load_weight_utils.py	0.00%	2 Missing ⚠️
fastdeploy/model_executor/utils.py	33.33%	2 Missing ⚠️

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[yanfeich]

add @LeoZhao-Intel @fmiao2372
Please help review this patch, thanks!

[LeoZhao-Intel]

这个为什么不用tensor_model_parallel_all_reduce_custom ？