[Dev] test(MoE): Add performance test for MoE layer

[Victarry]

What does this PR do ?

⚠️ For major changes (either in lines of code or in its impact), please make sure to first share discuss a design-doc with the team.

Added Test Cases

Proxy Models:

• Deepseek-V3 with reduced number of experts
• Mixtral-8x7B

Token dispatcher:

• Alltoall
• DeepEP
• HybridEP

Precision:

• BF16
• FP8

How this PR compare performance with baseline values

1. For each testcase, we run forward and backward 20 steps(after 3 warmup steps).
2. Collect the mean and std values of fwd/bwd latency from the 20 steps, the top3 values will be excluded for calculation.
   1. Assert (mean_latency / baselind_mean_latency) < 1.02 to guard performance regression.
   2. Assert (mean_latency / std_latency) < 1.02` to remove noisy test metrics.
3. Due to the intrinsic variance of hardware performance, we allow for 5 reruns after failure.

Contribution process

flowchart LR
    A[Pre-checks] --> B[PR Tests]
    subgraph Code Review/Approval
        C1[Expert Review] --> C2[Final Review]
    end
    B --> C1
    C2 --> D[Merge]

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Pre-checks

• I want this PR in a versioned release and have added the appropriate Milestone (e.g., Core 0.8)
• I have added relevant unit tests
• I have added relevant functional tests
• I have added proper typing to my code Typing guidelines
• I have added relevant documentation
• I have run the autoformatter.sh on my PR

Code review

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For MRs into `main` branch

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⚠️ Only proceed to the next step once all reviewers have approved, merge-conflict are resolved and the CI is passing.
Final Review might get declined if these requirements are not fulfilled.

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For MRs into `dev` branch

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MRs are mergable after one approval by either [email protected] or [email protected].

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[Victarry]

/ok to test d9ef668

[Victarry]

/ok to test 306b9c1

[Victarry]

TODO: change num_experts to 32 to align with actual training. (num_local_experts = 4)