[fp8] Merge feature/fp8_comm to main branch of Colossalai (#6016)

* add SimPO

* fix dataloader

* remove debug code

* add orpo

* fix style

* fix colossalai, transformers version

* fix colossalai, transformers version

* fix colossalai, transformers version

* fix torch colossalai version

* update transformers version

* [shardformer] DeepseekMoE support (#5871)

* [Feature] deepseek moe expert parallel implement

* [misc] fix typo, remove redundant file (#5867)

* [misc] fix typo

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* [Feature] deepseek support & unit test

* [misc] remove debug code & useless print

* [misc] fix typos (#5872)

* [Feature] remove modeling file, use auto config. (#5884)

* [misc] fix typos

* [Feature] deepseek support via auto model, remove modeling file

* [misc] delete useless file

* [misc] fix typos

* [Deepseek] remove redundant code (#5888)

* [misc] fix typos

* [Feature] deepseek support via auto model, remove modeling file

* [misc] delete useless file

* [misc] fix typos

* [misc] remove redundant code

* [Feature/deepseek] resolve comment. (#5889)

* [misc] fix typos

* [Feature] deepseek support via auto model, remove modeling file

* [misc] delete useless file

* [misc] fix typos

* [misc] remove redundant code

* [misc] mv module replacement into if branch

* [misc] add some warning message and modify some code in unit test

* [misc] fix typos

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* [Hoxfix] Fix CUDA_DEVICE_MAX_CONNECTIONS for comm overlap

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* [Feat] Diffusion Model(PixArtAlpha/StableDiffusion3) Support (#5838)

* Diffusion Model Inference support

* Stable Diffusion 3 Support

* pixartalpha support

* [HotFix] CI,import,requirements-test for #5838 (#5892)

* [Hot Fix] CI,import,requirements-test

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* [Feature] Enable PP + SP for llama (#5868)

* fix cross-PP-stage position id length diff bug

* fix typo

* fix typo

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* use a one cross entropy func for all shardformer models

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* [ShardFormer] Add Ulysses Sequence Parallelism support for Command-R, Qwen2 and ChatGLM (#5897)

* add benchmark for sft, dpo, simpo, orpo. Add benchmarking result. Support lora with gradient checkpoint

* fix style

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix eval

* hotfix citation

* [zero] support all-gather overlap (#5898)

* [zero] support all-gather overlap

* [zero] add overlap all-gather flag

* [misc] fix typo

* [zero] update api

* fix orpo cross entropy loss

* [Auto Parallel]: Speed up intra-op plan generation by 44% (#5446)

* Remove unnecessary calls to deepcopy

* Build DimSpec's difference dict only once

This change considerably speeds up construction speed of DimSpec objects. The difference_dict is the same for each DimSpec object, so a single copy of it is enough.

* Fix documentation of DimSpec's difference method

* [ShardFormer] fix qwen2 sp (#5903)

* [compatibility] support torch 2.2 (#5875)

* Support Pytorch 2.2.2

* keep build_on_pr file and update .compatibility

* fix object_to_tensor usage when torch>=2.3.0 (#5820)

* [misc] support torch2.3 (#5893)

* [misc] support torch2.3

* [devops] update compatibility ci

* [devops] update compatibility ci

* [devops] add debug

* [devops] add debug

* [devops] add debug

* [devops] add debug

* [devops] remove debug

* [devops] remove debug

* [release] update version (#5912)

* [plugin] support all-gather overlap for hybrid parallel (#5919)

* [plugin] fixed all-gather overlap support for hybrid parallel

* add kto

* fix style, add kto data sample

* [Examples] Add lazy init to OPT and GPT examples (#5924)

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* [ColossalChat] Hotfix for ColossalChat (#5910)

* add ignore and tiny llama

* fix path issue

* run style

* fix issue

* update bash

* add ignore and tiny llama

* fix path issue

* run style

* fix issue

* update bash

* fix ddp issue

* add Qwen 1.5 32B

* refactor tokenization

* [FIX BUG] UnboundLocalError: cannot access local variable 'default_conversation' where it is not associated with a value (#5931)

* cannot access local variable 'default_conversation' where it is not associated with a value

set default value for 'default_conversation'

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* fix test data

* refactor evaluation

* remove real data path

* remove real data path

* Add n_fused as an input from native_module (#5894)

* [FIX BUG] convert env param to int in (#5934)

* [Hotfix] Fix ZeRO typo #5936

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* [Feature] Add a switch to control whether the model checkpoint needs to be saved after each epoch ends (#5941)

* Add a switch to control whether the model checkpoint needs to be saved after each epoch ends

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* fix style

* fix style

* fix style

* [shardformer] hotfix attn mask (#5945)

* [shardformer] hotfix attn mask (#5947)

* [Feat] Distrifusion Acceleration Support for Diffusion Inference (#5895)

* Distrifusion Support source

* comp comm overlap optimization

* sd3 benchmark

* pixart distrifusion bug fix

* sd3 bug fix and benchmark

* generation bug fix

* naming fix

* add docstring, fix counter and shape error

* add reference

* readme and requirement

* [zero] hotfix update master params (#5951)

* [release] update version (#5952)

* [Chat] Fix lora (#5946)

* fix merging

* remove filepath

* fix style

* Update README.md (#5958)

* [hotfix] Remove unused plan section (#5957)

* remove readme

* fix readme

* update

* [test] add mixtral for sequence classification

* [test] add mixtral transformer test

* [moe] fix plugin

* [test] mixtra pp shard test

* [chore] handle non member group

* [zero] solve hang

* [test] pass mixtral shardformer test

* [moe] implement transit between non moe tp and ep

* [zero] solve hang

* [misc] solve booster hang by rename the variable

* solve hang when parallel mode = pp + dp

* [moe] implement submesh initialization

* [moe] add mixtral dp grad scaling when not all experts are activated

* [chore] manually revert unintended commit

* [chore] trivial fix

* [chore] arg pass & remove drop token

* [test] add mixtral modelling test

* [moe] implement tp

* [moe] test deepseek

* [moe] clean legacy code

* [Feature] MoE Ulysses Support (#5918)

* moe sp support

* moe sp bug solve

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* [chore] minor fix

* [moe] init moe plugin comm setting with sp

* moe sp + ep bug fix

* [moe] finalize test (no pp)

* [moe] full test for deepseek and mixtral (pp + sp to fix)

* [chore] minor fix after rebase

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* [chore] solve moe ckpt test failure and some other arg pass failure

* [moe] remove ops

* [test] fix test: test_zero1_2

* [bug] fix: somehow logger hangs the program

* [moe] deepseek moe sp support

* [test] add check

* [deepseek] replace attn (a workaround for bug in transformers)

* [misc] skip redunant test

* [misc] remove debug/print code

* [moe] refactor mesh assignment

* Revert "[moe] implement submesh initialization"

This reverts commit 2f9bce6686.

* [chore] change moe_pg_mesh to private

* [misc] remove incompatible test config

* [misc] fix ci failure: change default value to false in moe plugin

* [misc] remove useless condition

* [chore] docstring

* [moe] remove force_overlap_comm flag and add warning instead

* [doc] add MoeHybridParallelPlugin docstring

* [moe] solve dp axis issue

* [chore] remove redundant test case, print string & reduce test tokens

* [feat] Dist Loader for Eval (#5950)

* support auto distributed data loader

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* support auto distributed data loader

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix tp error

* remove unused parameters

* remove unused

* update inference

* update docs

* update inference

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* [lora] lora support hybrid parallel plugin (#5956)

* lora support hybrid plugin

* fix

* fix

* fix

* fix

* Support overall loss, update KTO logging

* [Docs] clarify launch port

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* [Hotfix] README link (#5966)

* update ignore

* update readme

* run style

* update readme

* [Hotfix] Avoid fused RMSnorm import error without apex (#5985)

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* [Chat] fix readme (#5989)

* fix readme

* fix readme, tokenization fully tested

* fix readme, tokenization fully tested

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* fix sync condition (#6000)

* [plugin] add cast inputs option for zero (#6003)

* [pre-commit.ci] pre-commit autoupdate (#5995)

updates:
- [github.com/psf/black-pre-commit-mirror: 24.4.2 → 24.8.0](https://github.com/psf/black-pre-commit-mirror/compare/24.4.2...24.8.0)

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* [misc] Bypass the huggingface bug to solve the mask mismatch problem (#5991)

* [Feature] Zigzag Ring attention (#5905)

* halfway

* fix cross-PP-stage position id length diff bug

* fix typo

* fix typo

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* unified cross entropy func for all shardformer models

* remove redundant lines

* add basic ring attn; debug cross entropy

* fwd bwd logic complete

* fwd bwd logic complete; add experimental triton rescale

* precision tests passed

* precision tests passed

* fix typos and remove misc files

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* add sp_mode to benchmark; fix varlen interface

* update softmax_lse shape by new interface

* change tester name

* remove buffer clone; support packed seq layout

* add varlen tests

* fix typo

* all tests passed

* add dkv_group; fix mask

* remove debug statements

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* [misc] update compatibility (#6008)

* [misc] update compatibility

* [misc] update requirements

* [devops] disable requirements cache

* [test] fix torch ddp test

* [test] fix rerun on address in use

* [test] fix lazy init

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix the merge

* fix the merge

* overlap kv comm with output rescale (#6017)

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* fix the merge

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix the merge

* fix

* fix

* fix the merge

* fix

* [misc] Use dist logger in plugins (#6011)

* use dist logger in plugins

* remove trash

* print on rank 0

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* fix

* fix

* fix

* fix

* fix the merge

* fix

* fix

* fix

* fix

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tests/test_shardformer/test_model/_utils.py

@@ -10,6 +10,7 @@ from torch.distributed import ProcessGroup
 from torch.nn import Module
 from torch.optim import Adam, Optimizer
 from torch.testing import assert_close
+from transformers.modeling_outputs import BaseModelOutputWithPast
 
 from colossalai.accelerator import get_accelerator
 from colossalai.booster import Booster
@@ -259,7 +260,6 @@ def run_forward_backward_with_hybrid_plugin(
     org_output = org_model(**unshard_test_data)
     org_loss = criterion(org_output)
     org_loss.backward()
-
     return org_loss, org_output, sharded_loss, sharded_output
 
 
@@ -302,11 +302,12 @@ def run_forward_backward_with_low_level_zero_plugin(
 
 
 def check_output_hidden_state(
-    org_output: Tensor,
-    sharded_output: Tensor,
+    org_output: BaseModelOutputWithPast,
+    sharded_output: BaseModelOutputWithPast,
     stage_manager: Optional[PipelineStageManager] = None,
     atol: float = 1e-5,
     rtol: float = 1e-3,
+    shard_config: Optional[ShardConfig] = None,
 ):
     org_hidden_state = org_output.last_hidden_state
 
@@ -315,6 +316,14 @@ def check_output_hidden_state(
     else:
         sharded_hidden_state = sharded_output.last_hidden_state
 
+    # Check if the output sequence is gathered before cross entropy
+    if shard_config is not None:
+        seq_dim = 1
+        sp_group = shard_config.sequence_parallel_process_group
+        sp_size = shard_config.sequence_parallel_size
+        if org_hidden_state.shape[seq_dim] == sharded_hidden_state.shape[seq_dim] * sp_size:
+            org_hidden_state = org_hidden_state.chunk(sp_size, dim=seq_dim)[dist.get_rank(sp_group)]
+
     assert_close(org_hidden_state.float(), sharded_hidden_state.float(), atol=atol, rtol=rtol)
 
 
@@ -374,8 +383,11 @@ def get_grad_tensors_for_check(
             shard_grad = torch.cat(shard_grad_list, dim=dim)
 
         # embedding may be resized when using tensor parallel
-        if shard_grad.shape[0] > org_grad.shape[0]:
-            shard_grad = shard_grad[: org_grad.shape[0], :]
+        try:
+            if shard_grad.shape[0] > org_grad.shape[0]:
+                shard_grad = shard_grad[: org_grad.shape[0], :]
+        except:
+            pass
         if verbose and dist.get_rank() == 0:
             print(f"'{suffix}' grad: {org_grad}, {shard_grad}")
 
@@ -404,9 +416,6 @@ def check_grad(
         org_grad = getattr_(org_model, suffix).weight.grad
         shard_grad = getattr_(sharded_model, suffix).weight.grad
         shard_weight = getattr_(sharded_model, suffix).weight
-        # if verbose and dist.get_rank() == 0:
-        #     print("shard_weight", shard_weight)
-        #     print("org_grad", org_grad)
         if is_distributed_tensor(shard_weight) or is_customized_distributed_tensor(shard_weight):
             shard_grad_list = [torch.zeros_like(shard_grad).to("cuda") for _ in range(dist.get_world_size(tp_group))]
             dist.all_gather(shard_grad_list, shard_grad, tp_group)
@@ -440,7 +449,7 @@ def check_all_grad_tensors(check_tensors):
     "org_grad": tensor to be compared from the original model
     "shard_grad": tensor to be compared from the sharded model
     """
-    for suffix, check_info in check_tensors.items():
+    for idx, (suffix, check_info) in enumerate(check_tensors.items()):
         org_grad = check_info["org_grad"]
         shard_grad = check_info["shard_grad"]
         rtol = check_info["rtol"]