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[Issue]: Expected dout_seq_stride == out_seq_stride to be true, but got false #40

Open
ehartford opened this issue Jan 30, 2024 · 14 comments · May be fixed by #58
Open

[Issue]: Expected dout_seq_stride == out_seq_stride to be true, but got false #40

ehartford opened this issue Jan 30, 2024 · 14 comments · May be fixed by #58

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@ehartford
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Problem Description

[rank4]:     _flash_attn_varlen_backward(
[rank4]:   File "/shared/prod/home/ehartford/.conda/envs/axolotl/lib/python3.11/site-packages/flash_attn-2.0.4-py3.11-linux-x86_64.egg/flash_attn/flash_attn_interface.py", line 79, in _flash_attn_varlen_backward
[rank4]:     dq, dk, dv, softmax_d, = flash_attn_cuda.varlen_bwd(
[rank4]:                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^
[rank4]: RuntimeError: Expected dout_seq_stride == out_seq_stride to be true, but got false.  (Could this error message be improved?  If so, please report an enhancement request to PyTorch.)```

### Operating System

Ubuntu 22.04.1 LTS (Jammy Jellyfish)

### CPU

AMD EPYC 7763 64-Core Processor  

### GPU

AMD Instinct MI210

### ROCm Version

ROCm 5.7.1

### ROCm Component

_No response_

### Steps to Reproduce

_No response_

### (Optional for Linux users) Output of /opt/rocm/bin/rocminfo --support

(axolotl) ehartford@smc-r08-08:~/axolotl$ rocminfo --support
ROCk module is loaded
=====================    
HSA System Attributes    
=====================    
Runtime Version:         1.1
System Timestamp Freq.:  1000.000000MHz
Sig. Max Wait Duration:  18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model:           LARGE                              
System Endianness:       LITTLE                             
Mwaitx:                  DISABLED
DMAbuf Support:          YES

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      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx90a:sramecc+:xnack-
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
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  Name:                    gfx90a                             
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  Max Clock Freq. (MHz):   1700                               
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    y                        1024(0x400)                        
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  Max Work-item Per CU:    2048(0x800)                        
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      Name:                    amdgcn-amd-amdhsa--gfx90a:sramecc+:xnack-
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  ISA Info:                
    ISA 1                    
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*******                  
Agent 7                  
*******                  
  Name:                    gfx90a                             
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  Vendor Name:             AMD                                
  Feature:                 KERNEL_DISPATCH                    
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  Cache Info:              
    L1:                      16(0x10) KB                        
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  WatchPts on Addr. Ranges:4                                  
  Features:                KERNEL_DISPATCH 
  Fast F16 Operation:      TRUE                               
  Wavefront Size:          64(0x40)                           
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  Workgroup Max Size per Dimension:
    x                        1024(0x400)                        
    y                        1024(0x400)                        
    z                        1024(0x400)                        
  Max Waves Per CU:        32(0x20)                           
  Max Work-item Per CU:    2048(0x800)                        
  Grid Max Size:           4294967295(0xffffffff)             
  Grid Max Size per Dimension:
    x                        4294967295(0xffffffff)             
    y                        4294967295(0xffffffff)             
    z                        4294967295(0xffffffff)             
  Max fbarriers/Workgrp:   32                                 
  Packet Processor uCode:: 78                                 
  SDMA engine uCode::      8                                  
  IOMMU Support::          None                               
  Pool Info:               
    Pool 1                   
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      Alloc Granule:           4KB                                
      Alloc Alignment:         4KB                                
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    Pool 2                   
      Segment:                 GLOBAL; FLAGS:                     
      Size:                    67092480(0x3ffc000) KB             
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      Alloc Alignment:         4KB                                
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    Pool 3                   
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      Alloc Granule:           4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 4                   
      Segment:                 GROUP                              
      Size:                    64(0x40) KB                        
      Allocatable:             FALSE                              
      Alloc Granule:           0KB                                
      Alloc Alignment:         0KB                                
      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx90a:sramecc+:xnack-
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
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*** Done ***    

### Additional Information

_No response_
@donglixp
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donglixp commented Feb 3, 2024

The similar error: #41

@jayz0123
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jayz0123 commented Feb 7, 2024

@ehartford, can I have the scripts you are running?

@ehartford
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I will try to define the configuration so you can reproduce it

@seungduk-yanolja
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+1

https://github.com/ROCm/flash-attention/blob/flash_attention_for_rocm/csrc/flash_attn_rocm/src/params.hpp#L450
here, it checks if they are the same but my log printed

dout_seq_stride: 4096, out_seq_stride: 128

and I modified this code to print some logs
https://github.com/ROCm/flash-attention/blob/flash_attention_for_rocm/flash_attn/flash_attn_interface.py#L73
like this

def _flash_attn_varlen_backward(dout, q, k, v, out, softmax_lse, dq, dk, dv,
                                cu_seqlens_q, cu_seqlens_k, max_seqlen_q, max_seqlen_k,
                                dropout_p, softmax_scale, causal, rng_state=None):

    print("Input tensor (dout) shape:", dout.shape)
    print("Input tensor (dout) strides:", dout.stride())
    print("Output tensor (out) shape:", out.shape)
    print("Output tensor (out) strides:", out.stride())

    maybe_contiguous = lambda x: x.contiguous() if x.stride(-1) != 1 else x
    # dq, dk, dv are allocated by us so they should already be contiguous
    dout, q, k, v, out = [maybe_contiguous(x) for x in (dout, q, k, v, out)]


    print("After Input tensor (dout) shape:", dout.shape)
    print("After Input tensor (dout) strides:", dout.stride())
    print("After Output tensor (out) shape:", out.shape)
    print("After Output tensor (out) strides:", out.stride())

    dq, dk, dv, softmax_d, = flash_attn_cuda.varlen_bwd(
        dout, q, k, v, out, softmax_lse, dq, dk, dv, cu_seqlens_q, cu_seqlens_k,
        max_seqlen_q, max_seqlen_k, dropout_p, softmax_scale, False, causal, None, rng_state
    )
    # if dk.isnan().any() or dk.isnan().any() or dv.isnan().any() or softmax_d.isnan().any():
    #     breakpoint()
    return dq, dk, dv, softmax_d

and result

Input tensor (dout) shape: torch.Size([32768, 32, 128])
Input tensor (dout) strides: (4096, 128, 1)
Output tensor (out) shape: torch.Size([32768, 32, 128])
Output tensor (out) strides: (128, 4194304, 1)
After Input tensor (dout) shape: torch.Size([32768, 32, 128])
After Input tensor (dout) strides: (4096, 128, 1)
After Output tensor (out) shape: torch.Size([32768, 32, 128])
After Output tensor (out) strides: (128, 4194304, 1)

@seungduk-yanolja seungduk-yanolja mentioned this issue Apr 5, 2024
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@jamestwhedbee
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Running into this as well

@ehartford
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I just discovered it again

RuntimeError: Expected dout_seq_stride == out_seq_stride to be true, but got false.  (Could this error message be improved?  If so, please report an enhancement request to PyTorch.)
  File "/home/ehartford/miniconda3/envs/axolotl/lib/python3.11/site-packages/torch/autograd/__init__.py", line 251, in backward
    _flash_attn_varlen_backward(
  File "/home/ehartford/miniconda3/envs/axolotl/lib/python3.11/site-packages/flash_attn/flash_attn_interface.py", line 79, in _flash_attn_varlen_backward
    dq, dk, dv, softmax_d, = flash_attn_cuda.varlen_bwd(
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass 
    File "/home/ehartford/miniconda3/envs/axolotl/lib/python3.11/site-packages/torch/autograd/function.py", line 288, in apply
                            return user_fn(self, *args) 
 ^^^^^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^^^^^^^^^^^^^^^^^^^^^^^^
^^^^RuntimeError^^: ^Expected dout_seq_stride == out_seq_stride to be true, but got false.  (Could this error message be improved?  If so, please report an enhancement request to PyTorch.)^

  File "/home/ehartford/miniconda3/envs/axolotl/lib/python3.11/site-packages/flash_attn/flash_attn_interface.py", line 139, in backward
    _flash_attn_varlen_backward(
  File "/home/ehartford/miniconda3/envs/axolotl/lib/python3.11/site-packages/flash_attn/flash_attn_interface.py", line 79, in _flash_attn_varlen_backward
    dq, dk, dv, softmax_d, = flash_attn_cuda.varlen_bwd(
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^

@ehartford
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ehartford commented May 27, 2024 •
edited
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Hello, I am blocked from using flash attention on ROCm by this bug

@ehartford ehartford mentioned this issue May 27, 2024
Closed
@ehartford
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This still happening with ROCm 6.0.2

@ehartford
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gfx942 mi300x

@NathanGodey
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I just ran into the same issue (MI250x) when using GPTNeoXForCausalLM from HuggingFace. I could fix it by just making all the inputs contiguous right before the flash-attention call, which I guess is suboptimal but still much better than the torch implementation.

@clintg6 clintg6 linked a pull request May 31, 2024 that will close this issue
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@ehartford
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I will try

@rocking5566
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I just submit an PR to support AMD / ROCm on FlashAttention 2
Dao-AILab#1010
This PR using composable_kernel as backend

@ehartford
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I will try this

@carlushuang
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cc @danyao12

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Fix stride issues in flash_attn_interface ROCm/flash-attention
8 participants
@donglixp @ehartford @carlushuang @rocking5566 @jamestwhedbee @NathanGodey @jayz0123 @seungduk-yanolja