[NFC] remove redundant dependency (#1869)

* remove redundant config

* remove redundant dependency

examples/images/diffusion/README.md

@@ -59,7 +59,7 @@ you should the change the `data.file_path` in the `config/train_colossalai.yaml`
 
 ## Training
 
-we provide the script `train.sh` to run the training task , and three Stategy in `configs`:`train_colossalai.yaml`, `train_ddp.yaml`, `train_deepspeed.yaml`
+we provide the script `train.sh` to run the training task , and two Stategy in `configs`:`train_colossalai.yaml`, `train_ddp.yaml`
 
 for example, you can run the training from colossalai by
 ```

examples/images/diffusion/configs/train_deepspeed.yaml

@@ -1,117 +0,0 @@
-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: caption
-    image_size: 32
-    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: [ 10000 ]
-        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
-        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
-        use_fp16: True
-
-    first_stage_config:
-      target: ldm.models.autoencoder.AutoencoderKL
-      params:
-        embed_dim: 4
-        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
-    wrap: False
-    train:
-      target: ldm.data.base.Txt2ImgIterableBaseDataset
-      params:
-        file_path: "/data/scratch/diffuser/laion_part0/"
-        world_size: 1
-        rank: 0
-
-lightning:
-  trainer:
-    accelerator: 'gpu' 
-    devices: 4
-    log_gpu_memory: all
-    max_epochs: 2
-    precision: 16
-    auto_select_gpus: False
-    strategy:
-      target: pytorch_lightning.strategies.DeepSpeedStrategy
-      params:
-        stage: 2
-        zero_optimization: True
-        offload_optimizer: False
-        offload_parameters: False
-    log_every_n_steps: 2
-#    max_steps: 6o
-    logger: True
-    default_root_dir: "/tmp/diff_log/"
-    profiler: pytorch
-
-  logger_config:
-    wandb:
-      target: pytorch_lightning.loggers.WandbLogger
-      params:
-          name: nowname
-          save_dir: logdir
-          offline: opt.debug
-          id: nowname
-    
-

examples/images/diffusion/environment.yaml

@@ -26,7 +26,6 @@ dependencies:
     - transformers==4.19.2
     - torchmetrics==0.6.0
     - kornia==0.6
-    - deepspeed==0.7.4
     - prefetch_generator
     - -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers
     - -e git+https://github.com/openai/CLIP.git@main#egg=clip