[Core]: (Last/N) Support prefill only models by Workflow Defined Engine #8964

noooop · 2024-09-30T11:28:20Z

This is the first part of [Support prefill only models by Workflow Defined Engine]

The main goal is to support the BERT model

Includes the following parts:

code organization：Modules are organized according to function-first. If there are new modules, you can create a new folder under the corresponding module. e.g.
- Reranker model input pairs. New modules can be organized as follows

inputs/
  data.py
  parse.py
  preprocess.py
  registry.py
  reranker/
    data.py
    preprocess.py

[Core]: (2/N) Support prefill only models by Workflow Defined Engine - Prefill only attention #9124
Prefill only attention
- In order to support bidirectional enable, the entire program uses the same AttnBackend instance. This way you can use attn_type to switch all Attention Backend AttentionType
- Attention Backend now supported
  - Flash Attention Backend
  - Torch SDPA Backend
  - XFormers Backend
  - FlashInfer Backend (Because prefill only models do not involve kv cache, When using Flashinfer backend in prefill only models, you are actually using FLASH ATTN backend
  - Torch naive backend (as a control group

[Core]: (1/N) Support prefill only models by Workflow Defined Engine - Prefill only scheduler #9181
InputProcessor: Input(request_id, inputs, params, arrival_time) -> InputProcessor -> Request
- Like other text input models, bert supports str, Dict, TextPrompt, TokensPrompt, TextOnlyInputs
- InputProcessor will do simple verification of the input, but will not do tokenizer.encode to avoid being stuck in a large number of submissions at the same time.
RequestProcessor: Request -> RequestProcessor -> SchedulableRequest
- RequestProcessor is the callback function of the scheduler. It will only be called when scheduling is needed, and tokenizer.encode will be executed.
Scheduler
- A simple first-come-first-serve scheduler that supports batched_tokens and num_requests to control concurrency
- Prefill only models, there is no dependency between tasks, so it supports both sync and async scheduling

[Core]: (3/N) Support prefill only models by Workflow Defined Engine - new models

loader
- Because AttnBackend instance needs to be passed into the model, the loader needs to be slightly modified.
modelzoo and ModelRegistry
- Because workflow parameters need to be supported, modelzoo and ModelRegistry need to be slightly modified.
new models
- bert

[Core]: (Last/N) Support prefill only models by Workflow Defined Engine #8964
ModelInputBuilder
- Just calculate seq_lens and call attention_metadata_builder. Convert seq_lens to seq_start_loc using torch.cumsum
Executor
- Support Sync\Async Executor. Async Executor data enters from the executor_in queue and goes out from the executor_out queue
Worker & Runner
- Temporarily need to use FakeGroupCoordinator to fix the distributed environment (parallel_state._TP, parallel_state._PP)
LLMEngine
- Workflow Defined Engine. Load modules on demand according to Workflow

Modifications required to the vllm code: (not yet submitted

MQLLMEngine
- Use wde ModelRegistry to determine whether the current model is supported. If so, use wde Engine.
entrypoints
- There may be some compatibility issues that need to be modified slightly

github-actions · 2024-09-30T11:28:33Z

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DarkLight1337 · 2024-09-30T14:56:00Z

For the PR that is going to be merged, can you please modify the existing vLLM code instead of transferring them into a completely new namespace/directory? Otherwise, it's difficult to see how the existing code needs to be changed. If the implementation is completely different, you can create a file in the existing directory but with wde suffix, similar to how we have block manager v2 right now.

noooop · 2024-09-30T16:50:13Z

Now the vllm project is divided by function. Modules with the same function are put together, all executors are put together, and all workers are put together. In fact, it is very painful to maintain. According to Conway's Law, systems should be built around business capabilities.

Although I really want more people to discuss the wde architecture, it seems that no one is very interested.

noooop · 2024-09-30T17:18:07Z

For example,
you have a set of tools for painting watercolors, pens, and paper.
You have a set of tools for painting oils, pens, and paper.
You also have pens and papers for daily use.

Divide by function, put all the pens together, put all the paper together, put all the paints together, the result is very inconvenient to use. .

Divided according to usage scenarios, it is obviously much easier to use and maintain.

This is how wde modules are divided.

noooop · 2024-09-30T17:26:53Z

Let's discuss it for a while, maybe there is a better way.

noooop · 2024-09-30T17:37:16Z

Let's focus on more specific issues.

InputProcessor

Reranker model input pairs. If using wde, I only need to switch to RerankerInputProcessor, plug and play. So where should I put this piece of code?

https://github.com/noooop/vllm/blob/wde_encode_only/vllm/wde/reranker/

DarkLight1337 · 2024-10-01T01:52:59Z

Although I really want more people to discuss the wde architecture, it seems that no one is very interested.

Even if your architecture is perfect (this is never the case, I keep throwing away my old code 😅), there is an important practical issue to consider, which is how to adopt this without breaking the guarantees currently provided by vLLM. Keep in mind that this is not a personal project, so you don't have the freedom to change everything in one commit - rather, hundreds of devs are working on this project at the same time. If you can't solve this issue, no one will be willing to jump to completely new code. So, I suggest keeping the original directory layout where possible.

Reranker model input pairs. If using wde, I only need to switch to RerankerInputProcessor, plug and play. So where should I put this piece of code?

Currently, our code is organized function-first, capability-second, as you have said. But, there's nothing preventing you from adding capability-specific files into function-specific directories for now.

noooop · 2024-10-01T04:07:12Z

Can we start reviewing the code as it is laid out now.

Specifically reviewing the module as I listed them from the top down, my code is also submitted in this order。

Focusing on the part where I have slightly modified the vllm module, should I keep both files or apply the changes to the original files.

Once the review is complete, I will change it to a functional-first organizational.

DarkLight1337 · 2024-10-01T04:09:16Z

Focusing on the part where I have slightly modified the vllm module, should I keep both files or apply the changes to the original files.

Please change the original files. It's difficult to see the diffs otherwise. Also this makes sure that your implementation can still work with existing vLLM code.

DarkLight1337 · 2024-10-01T04:10:24Z

Ideally we should be able to run our existing tests on your code to verify its correctness.

noooop · 2024-10-01T04:11:49Z

InputProcessor: Input(request_id, inputs, params, arrival_time) -> InputProcessor -> Request
- Like other text input models, bert supports str, Dict, TextPrompt, TokensPrompt, TextOnlyInputs
- InputProcessor will do simple verification of the input, but will not do tokenizer.encode to avoid being stuck in a large number of submissions at the same time.

82197c8

Can I put this code in the inputs folder?

https://github.com/vllm-project/vllm/tree/main/vllm/inputs

DarkLight1337 · 2024-10-01T04:13:56Z

InputProcessor: Input(request_id, inputs, params, arrival_time) -> InputProcessor -> Request
Can I put this code in the inputs folder?

Yes, please do so.

noooop · 2024-10-01T07:48:01Z

@DarkLight1337

The role of wde/core/schema/engine_io.py in wde is the same as that of inputs.data.

At the time of my first commit, you hadn't finished refactoring inputs.data.

I can change to using inputs.data

but where should I put the input of the reranker

Modify inputs.data directly
Place it under the inputs folder, no hierarchy

inputs
- data.py
- parse.py
- preprocess.py
- registry.py
- data_reranker.py
- preprocess_reranker.py

Place it under the inputs\reranker folder.

inputs
- data.py
- parse.py
- preprocess.py
- registry.py
- reranker
  - data.py
  - preprocess.py

put the previous code to the core or base folder

inputs
- core or base
  - data.py
  - parse.py
  - preprocess.py
  - registry.py
- reranker
  - data.py
  - reranker.py

Organized by business capabilities

inputs
- data.py
- parse.py
- preprocess.py
- registry.py
reranker
- inputs
  - data.py
  - preprocess.py

I will discuss the code organization structure with you only this time. Other modules will be reorganized according to the results of this discussion.

DarkLight1337 · 2024-10-01T10:07:46Z

The role of wde/core/schema/engine_io.py in wde is the same as that of inputs.data.

At the time of my first commit, you hadn't finished refactoring inputs.data.

I can change to using inputs.data

but where should I put the input of the reranker

I prefer option 3. We start with something like this:

inputs/
  data.py
  parse.py
  preprocess.py
  registry.py
  reranker/
    data.py
    preprocess.py

Then in future PRs, we can gradually move the existing code, e.g.:

inputs/
  parse.py
  registry.py
  base/
    data.py
    preprocess.py
  decoder_only/
    data.py
    preprocess.py
  encoder_decoder/
    data.py
    preprocess.py
  reranker/
    data.py
    preprocess.py

To increase the chance of acceptance, I further recommend only doing this reorganization within one main module (in this case, vllm/inputs) at a time. This will be a long and painful process but at least your PRs may get merged. Eventually, our code structure may look like:

core/
    base/
    decoder_only/
    encoder_decoder/
    ...
engine/
    base/
    decoder_only/
    encoder_decoder/
    ...
inputs/
    base/
    decoder_only/
    encoder_decoder/
    ...

Only afterwards can we even consider making the switch from function-first to capability-first at the top level:

base/
    engine/
    core/
    inputs/
decoder_only/
    engine/
    core/
    inputs/
encoder_decoder/
    engine/
    core/
    inputs/
...

noooop · 2024-10-01T10:53:55Z

@DarkLight1337

InputProcessor will do simple verification of the input, but will not do tokenizer.encode to avoid being stuck in a large number of submissions at the same time.
RequestProcessor is the callback function of the scheduler. It will only be called when scheduling is needed, and tokenizer.encode will be executed. （lazy Request Processor）

In vllm/inputs/preprocess.py , the verification and encoding parts are merged.

In wde preprocess is separated into two parts.

Do you ok with that?

Of course, this process will only be used on the prefill only scheduler and will not modify the previous scheduler.

DarkLight1337 · 2024-10-01T15:34:16Z

@DarkLight1337

next

InputProcessor will do simple verification of the input, but will not do tokenizer.encode to avoid being stuck in a large number of submissions at the same time.
RequestProcessor is the callback function of the scheduler. It will only be called when scheduling is needed, and tokenizer.encode will be executed. （lazy Request Processor）

In vllm/inputs/preprocess.py , the verification and encoding parts are merged.

In wde preprocess is separated into two parts.

Do you ok with that?

Of course, this process will only be used on the prefill only scheduler and will not modify the previous scheduler.

As long as this strategy works for other model types, I'm fine with it. (i.e. don't split them up only to find that it actually doesn't work e.g. for embedding models)

noooop · 2024-10-01T16:09:45Z

I'm busy these days, so I'll submit a new code on the 8th.

noooop · 2024-10-01T16:17:53Z

@DarkLight1337

Prefill only attention

In order to support bidirectional enable, the entire program uses the same AttnBackend instance. This way you can use attn_type to switch all Attention Backend AttentionType

Attention Backend now supported

Flash Attention Backend

Torch SDPA Backend

XFormers Backend

FlashInfer Backend (Because prefill only models do not involve kv cache, When using Flashinfer backend in prefill only models, you are actually using FLASH ATTN backend

Torch naive backend (as a control group

250be85

If you have time, please review the Prefill only attention related code.

I will put Prefill only attention under the attention folder

attention
    prefill_only  <- new
    backends
    ops
    __init__.py
    layer.py
    selector.py

Do you ok with that?

DarkLight1337 · 2024-10-01T16:21:20Z

I'm busy these days, so I'll submit a new code on the 8th.

No worries, take your time.

@DarkLight1337

next

Prefill only attention

In order to support bidirectional enable, the entire program uses the same AttnBackend instance. This way you can use attn_type to switch all Attention Backend AttentionType

Attention Backend now supported

Flash Attention Backend

Torch SDPA Backend

XFormers Backend

FlashInfer Backend (Because prefill only models do not involve kv cache, When using Flashinfer backend in prefill only models, you are actually using FLASH ATTN backend

Torch naive backend (as a control group

250be85

If you have time, please review the Prefill only attention related code.

I'm not familiar with the attention implementation, so you will have to ask someone else for this. This is another reason why we should split up the PR so each PR focuses on one module. Then we can have different people reviewing changes to each module.

noooop · 2024-10-01T16:23:37Z

Can you help me get someone to come take a look?

Prefill only attention has no decoding stage, so it is very simple

DarkLight1337 · 2024-10-01T16:35:05Z

@comaniac may be able to comment on the attention backend. But I suggest you split up the PR first.

DarkLight1337 · 2024-10-09T07:03:14Z

So far it seems that you're just adding brand new files. Are you going to further refine those PRs so vLLM actually uses them?

noooop · 2024-10-09T07:09:38Z

So far it seems that you're just adding brand new files. Are you going to further refine those PRs so vLLM actually uses them?

I organized the previous code according to function-first

noooop · 2024-10-09T07:13:29Z

Do you have any suggestions for the approximate location of the new code?

DarkLight1337 · 2024-10-09T07:14:14Z

So far it seems that you're just adding brand new files. Are you going to further refine those PRs so vLLM actually uses them?

I organized the previous code according to function-first

I prefer you delete the old files that have been split up to the new locations. This will prevent the issue of forgetting to copy over the changes from more recent PRs since your PR was first created (by forcing you to handle merge conflicts).

noooop · 2024-10-09T07:16:54Z

I prefer you delete the old files that have been split up to the new location. This will prevent the issue of forgetting to copy over the changes from more recent PRs since your PR was first created (by forcing you to handle merge conflicts).

I know, this PR is temporarily used to discuss how to segment. So submit all the code for now

DarkLight1337 · 2024-10-09T07:17:37Z

So far it seems that you're just adding brand new files. Are you going to further refine those PRs so vLLM actually uses them?

I organized the previous code according to function-first

I prefer you delete the old files that have been split up to the new locations. This will prevent the issue of forgetting to copy over the changes from more recent PRs since your PR was first created (by forcing you to handle merge conflicts).

For example:

You create a new TextInputProcessor which is based on the existing InputPreprocessor.
The logic of InputPreprocessor is then changed by someone else in another PR.
Your PR still works but doesn't include the changes by (2), resulting in a regression. Even though we have tests, they don't have 100% coverage so it's possible to miss this. The more files you create, the easier it is to miss such changes.

noooop · 2024-10-09T07:18:45Z

For example:

You create a new TextInputProcessor which is based on the existing InputPreprocessor.

The logic of InputPreprocessor is then changed by someone else in another PR.

Your PR still works but doesn't include the changes by (2). The more files you create, the easier it is to miss such changes.

I know, this PR is temporarily used to discuss how to segment. So submit all the code for now

This PR definitely needs to be resubmitted

DarkLight1337 · 2024-10-09T07:22:04Z

Your PR still works but doesn't include the changes by (2). The more files you create, the easier it is to miss such changes.
I know, this PR is temporarily used to discuss how to segment. So submit all the code for now

I find myself frequently having to switch over to another copy of the repo and find where your code originally comes from. It would ease the review process if you actually "move" the code.

DarkLight1337 · 2024-10-09T07:23:15Z

Also, to avoid triggering CI, please mark those PRs with draft status.

noooop · 2024-10-09T07:23:35Z

The current function of this pr is

Let's first roughly put all the modules in the correct location, and then try to split the pr.

We discuss specific code changes in #9124 #9181

Divide and conquer, coarse to fine

I will manually keep both sides in sync with the latest updates.

noooop · 2024-10-09T07:31:13Z

I find myself frequently having to switch over to another copy of the repo and find where your code originally comes from. It would ease the review process if you actually "move" the code.

Sorry, I don't want to make it so complicated

Previously

Towards efficiently support prefill only(encoder only) models. Motivatio\Terminology\Proposed Change
etc. PTAL [RFC]: Support encode only models by Workflow Defined Engine #8453
Proof of Concept, most features and all models are already supported and tested in [PoC]: Support encode only models by Workflow Defined Engine #8452
Discuss how to split and merge into main [Core]: (Last/N) Support prefill only models by Workflow Defined Engine #8964
- [Core]: (2/N) Support prefill only models by Workflow Defined Engine - Prefill only attention #9124
- [Core]: (1/N) Support prefill only models by Workflow Defined Engine - Prefill only scheduler #9181
- [Core]: (3/N) Support prefill only models by Workflow Defined Engine - new models (Submit when [Core]: (2/N) Support prefill only models by Workflow Defined Engine - Prefill only attention #9124 is merged

DarkLight1337 · 2024-10-09T10:01:56Z

Do you have any suggestions for the approximate location of the new code?

Honestly, I don't care too much about the location of the new files. The more important part is how to transition from the existing code to the new layout.

DarkLight1337 · 2024-10-09T10:06:48Z

I would rather you dive straight into the refactoring PRs one at a time instead of just partially showing the new layout. For looking at the new layout, I prefer the branch that has all the new files in one place so I can get the big picture.

noooop · 2024-10-09T10:31:18Z

I would rather you dive straight into the refactoring PRs one at a time instead of just partially showing the new layout. For looking at the new layout, I prefer the branch that has all the new files in one place so I can get the big picture.

So how should I cooperate?

This is all the code to support the first model : bert

DarkLight1337 · 2024-10-09T10:33:00Z

I would rather you dive straight into the refactoring PRs one at a time instead of just partially showing the new layout. For looking at the new layout, I prefer the branch that has all the new files in one place so I can get the big picture.

So how should I cooperate?

You can have two branches:

One branch with all the new files together (so, basically your original PR with wde/ directory, except that the files should be in the existing directories as we have discussed before)
One active branch which focuses on refactoring one module at a time. To avoid accumulating technical debt, I suggest you limit this to one module at a time (e.g. inputs) so you don't have to keep resolving merge conflicts.

noooop · 2024-10-09T10:45:50Z

You can have two branches:

One branch with all the new files together (so, basically your original PR with wde/ directory, except that the files should be in the existing directories as we have discussed before)
This pr (I've added back the previous wde code

One active branch which focuses on refactoring one module at a time. To avoid accumulating technical debt, I suggest you limit this to one module at a time (e.g. inputs) so you don't have to keep resolving merge conflicts.
[Core]: (1/N) Support prefill only models by Workflow Defined Engine - Prefill only scheduler #9181

noooop · 2024-10-09T11:00:20Z

@DarkLight1337

I've added back the previous wde code

Do you need to split the wde code by module and submit it multiple times?

DarkLight1337 · 2024-10-09T11:30:07Z

For viewing the layout, keep everything in the same PR (don't split it).

noooop · 2024-10-09T11:44:40Z

You can have two branches:

One branch with all the new files together (so, basically your original PR with wde/ directory, except that the files should be in the existing directories as we have discussed before)
This pr (I've added back the previous wde code

One active branch which focuses on refactoring one module at a time. To avoid accumulating technical debt, I suggest you limit this to one module at a time (e.g. inputs) so you don't have to keep resolving merge conflicts.
[Core]: (1/N) Support prefill only models by Workflow Defined Engine - Prefill only scheduler #9181

Is everything okay now

(Just a moment ago, Accidentally pushed -f to #8452, finally fixed. pushed -f is too dangerous

DarkLight1337 · 2024-10-09T12:07:23Z

It is better now. I don't think attention backends should be placed under layers though. Something like vllm.<workflow>.backends.attention would be more appropriate.

DarkLight1337 · 2024-10-09T12:12:52Z

Also, you have some inconsistent naming, where model tests are placed under models directory while the model implementations are inside modelzoo. I prefer renaming modelzoo to the current models so it's same as Transformers library.

noooop · 2024-10-09T12:41:25Z

It is better now. I don't think attention backends should be placed under layers though. Something like vllm.<workflow>.backends.attention would be more appropriate.

mark

Also, you have some inconsistent naming, where model tests are placed under models directory while the model implementations are inside modelzoo. I prefer renaming modelzoo to the current models so it's same as Transformers library.

mark

noooop · 2024-10-14T02:25:11Z

@DarkLight1337

The biggest difference between the prefill only models and the decoding model lies in the attention and scheduler.

attention

Prefill only models requires simpler attention implementations, no need to consider kvcache, no decoding phase

We need to support enable_bidirectional flag manually or read hf config automatically, enable bidirectional.

https://github.com/noooop/vllm/tree/wde_prefill_only_1/vllm/attention/prefill_only

scheduler

Prefill only models requires simpler scheduler, no need to consider kvcache and preemption

Prefill only models, there is no correlation between tasks, so it is easy to implement async scheduling

https://github.com/noooop/vllm/blob/wde_prefill_only_1/vllm/core/prefill_only_scheduler.py

Corresponding to #9124 and #9181

these two PRs are not directly related and can be reviewed at the same time without conflict.

Why not modify the existing code directly, but add a new file?

If we directly add new code, these modules are becoming increasingly complex
Some new features must be compromised for compatibility
Code related to decoding models is almost never used in prefill only models, and prefill only models are almost never used in decoding models. There is no need to force the two parts of code together.
Separating the two pieces of code can be optimized separately in the future. Combine them, for the sake of compatibility, ultimately leading to suboptimal results.
These are very important codes, and modifications may introduce bugs.

If we merge #9124 and #9181, the rest are very simple codes and are easy to merge.

As for the Workflow Defined Engine architecture, it is actually similar to the code below and is actually not complicated.

https://github.com/noooop/vllm/blob/49299c097f6696107c4cb8033679d9a419044a0f/vllm/core/scheduler.py#L314C1-L318C34

        version = "v1"
        if self.scheduler_config.use_v2_block_manager:
            version = "v2"
        if self.scheduler_config.embedding_mode:
            version = "embedding"

        BlockSpaceManagerImpl = BlockSpaceManager.get_block_space_manager_class(
            version)

DarkLight1337 · 2024-10-14T02:45:53Z

Since @WoosukKwon has already started the refactoring, you should coordinate this with him.

noooop · 2024-10-14T02:55:07Z

Since @WoosukKwon has already started the refactoring, you should coordinate this with him.

Do you mean that this PR is submitted directly to the refactored version?

DarkLight1337 · 2024-10-14T02:56:31Z

Since @WoosukKwon has already started the refactoring, you should coordinate this with him.

Do you mean that this PR is submitted directly to the refactored version?

You should ping him with a link to this PR.

noooop mentioned this pull request Sep 30, 2024

[PoC]: Support encode only models by Workflow Defined Engine #8452

Draft

noooop force-pushed the wde_prefill_only_1 branch from 97e7e5c to 5f05fa9 Compare September 30, 2024 11:56

noooop marked this pull request as ready for review September 30, 2024 14:11

noooop closed this Oct 7, 2024

noooop force-pushed the wde_prefill_only_1 branch from 75038b4 to 6c9ba48 Compare October 7, 2024 10:07

noooop reopened this Oct 7, 2024

prefill only attention

cb4946d

noooop force-pushed the wde_prefill_only_1 branch from 0333601 to cb4946d Compare October 7, 2024 11:03

noooop changed the title ~~[Core]: (1/N) Support prefill only models by Workflow Defined Engine~~ [Core]: (Last/N) Support prefill only models by Workflow Defined Engine Oct 7, 2024

noooop marked this pull request as draft October 9, 2024 07:23

+ wde

49299c0

This was referenced Oct 14, 2024

[WIP] Prototyping re-arch #9166

Closed

并发调用卡住，且内存锁住没有释放 noooop/light-vllm#2

Closed

[Core]: (Last/N) Support prefill only models by Workflow Defined Engine #8964

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[Core]: (Last/N) Support prefill only models by Workflow Defined Engine #8964

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DarkLight1337 commented Oct 9, 2024 • edited Loading

DarkLight1337 commented Oct 9, 2024

noooop commented Oct 9, 2024

noooop commented Oct 9, 2024 • edited Loading

Previously

DarkLight1337 commented Oct 9, 2024

DarkLight1337 commented Oct 9, 2024 • edited Loading

noooop commented Oct 9, 2024 • edited Loading

DarkLight1337 commented Oct 9, 2024 • edited Loading

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noooop commented Oct 9, 2024

DarkLight1337 commented Oct 9, 2024 • edited Loading

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noooop commented Oct 9, 2024

noooop commented Oct 14, 2024 • edited Loading

Why not modify the existing code directly, but add a new file?

DarkLight1337 commented Oct 14, 2024

noooop commented Oct 14, 2024

DarkLight1337 commented Oct 14, 2024

noooop commented Sep 30, 2024 •

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DarkLight1337 commented Sep 30, 2024 •

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DarkLight1337 commented Oct 1, 2024 •

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noooop commented Oct 1, 2024 •

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DarkLight1337 commented Oct 1, 2024 •

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DarkLight1337 commented Oct 1, 2024 •

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noooop commented Oct 1, 2024 •

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DarkLight1337 commented Oct 1, 2024 •

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noooop commented Oct 9, 2024 •

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DarkLight1337 commented Oct 9, 2024 •

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DarkLight1337 commented Oct 9, 2024 •

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DarkLight1337 commented Oct 9, 2024 •

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noooop commented Oct 9, 2024 •

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DarkLight1337 commented Oct 9, 2024 •

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noooop commented Oct 9, 2024 •

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DarkLight1337 commented Oct 9, 2024 •

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noooop commented Oct 9, 2024 •

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DarkLight1337 commented Oct 9, 2024 •

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noooop commented Oct 9, 2024 •

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DarkLight1337 commented Oct 9, 2024 •

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DarkLight1337 commented Oct 9, 2024 •

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noooop commented Oct 14, 2024 •

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