'pytorch_lightning.strategies' has no attribute 'ColossalAIStrategy'

[ziyeZzz]

Hi, I already installed the following packages with the guide of "Installation" pytorch-lightning 1.6.5 colossalai 0.1.11rc3+torch1.11cu11.4

But when I run training, it reports following error: AttributeError: module 'pytorch_lightning.strategies' has no attribute 'ColossalAIStrategy'

The yaml I used is as following: `model: base_learning_rate: 1.0e-04 target: ldm.models.diffusion.ddpm.LatentDiffusion params: linear_start: 0.00085 linear_end: 0.0120 num_timesteps_cond: 1 log_every_t: 200 timesteps: 1000 first_stage_key: image cond_stage_key: txt image_size: 64 channels: 4 cond_stage_trainable: false # Note: different from the one we trained before conditioning_key: crossattn monitor: val/loss_simple_ema scale_factor: 0.18215 use_ema: False

scheduler_config: # 10000 warmup steps
  target: ldm.lr_scheduler.LambdaLinearScheduler
  params:
    warm_up_steps: [ 1 ] # NOTE for resuming. use 10000 if starting from scratch
    cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
    f_start: [ 1.e-6 ]
    f_max: [ 1.e-4 ]
    f_min: [ 1.e-10 ]

unet_config:
  target: ldm.modules.diffusionmodules.openaimodel.UNetModel
  params:
    image_size: 32 # unused
    from_pretrained: '/home/tina/models/Diffusion/ckpt/sd-v1-4.ckpt'
    in_channels: 4
    out_channels: 4
    model_channels: 320
    attention_resolutions: [ 4, 2, 1 ]
    num_res_blocks: 2
    channel_mult: [ 1, 2, 4, 4 ]
    num_heads: 8
    use_spatial_transformer: True
    transformer_depth: 1
    context_dim: 768
    use_checkpoint: False
    legacy: False

first_stage_config:
  target: ldm.models.autoencoder.AutoencoderKL
  params:
    embed_dim: 4
    from_pretrained: '/home/tina/models/Diffusion/ckpt/sd-v1-4.ckpt'
    monitor: val/rec_loss
    ddconfig:
      double_z: true
      z_channels: 4
      resolution: 256
      in_channels: 3
      out_ch: 3
      ch: 128
      ch_mult:
      - 1
      - 2
      - 4
      - 4
      num_res_blocks: 2
      attn_resolutions: []
      dropout: 0.0
    lossconfig:
      target: torch.nn.Identity

cond_stage_config:
  target: ldm.modules.encoders.modules.FrozenCLIPEmbedder
  params:
    use_fp16: True

data: target: main.DataModuleFromConfig params: batch_size: 4 num_workers: 4 train: target: ldm.data.cifar10.hf_dataset params: name: cifar10 image_transforms: - target: torchvision.transforms.Resize params: size: 512 interpolation: 3 - target: torchvision.transforms.RandomCrop params: size: 512 - target: torchvision.transforms.RandomHorizontalFlip

lightning: trainer: accelerator: 'gpu' devices: 1 log_gpu_memory: all max_epochs: 2 precision: 16 auto_select_gpus: False strategy: target: pytorch_lightning.strategies.ColossalAIStrategy params: use_chunk: False enable_distributed_storage: True placement_policy: cuda force_outputs_fp32: False

log_every_n_steps: 2
logger: True
default_root_dir: "/home/tina/models/Diffusion/log/"
profiler: pytorch

logger_config: wandb: target: pytorch_lightning.loggers.WandbLogger params: name: nowname save_dir: "/home/tina/models/Diffusion/log/" offline: opt.debug id: nowname`

Do you have any idea about this error? Thanks a lot.

[ML-GCN]

pytorch-lightning

you can try pytorch-lightning == 1.8

[feifeibear]

You can fix the bug with the correct PL version. I closed the issue.