mirror of https://github.com/hpcaitech/ColossalAI
aibig-modeldata-parallelismdeep-learningdistributed-computingfoundation-modelsheterogeneous-traininghpcinferencelarge-scalemodel-parallelismpipeline-parallelism
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112 lines
2.6 KiB
112 lines
2.6 KiB
model: |
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base_learning_rate: 1.0e-4 |
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params: |
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parameterization: "v" |
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linear_start: 0.00085 |
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linear_end: 0.0120 |
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num_timesteps_cond: 1 |
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log_every_t: 200 |
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timesteps: 1000 |
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first_stage_key: image |
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cond_stage_key: txt |
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image_size: 64 |
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channels: 4 |
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cond_stage_trainable: false |
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conditioning_key: crossattn |
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monitor: val/loss_simple_ema |
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scale_factor: 0.18215 |
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use_ema: False # we set this to false because this is an inference only config |
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scheduler_config: # 10000 warmup steps |
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warm_up_steps: [ 1 ] # NOTE for resuming. use 10000 if starting from scratch |
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cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases |
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f_start: [ 1.e-6 ] |
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f_max: [ 1.e-4 ] |
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f_min: [ 1.e-10 ] |
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unet_config: |
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use_checkpoint: True |
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use_fp16: True |
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image_size: 32 # unused |
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in_channels: 4 |
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out_channels: 4 |
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model_channels: 320 |
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attention_resolutions: [ 4, 2, 1 ] |
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num_res_blocks: 2 |
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channel_mult: [ 1, 2, 4, 4 ] |
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num_head_channels: 64 # need to fix for flash-attn |
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use_spatial_transformer: True |
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use_linear_in_transformer: True |
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transformer_depth: 1 |
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context_dim: 1024 |
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legacy: False |
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first_stage_config: |
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embed_dim: 4 |
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monitor: val/rec_loss |
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ddconfig: |
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#attn_type: "vanilla-xformers" |
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double_z: true |
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z_channels: 4 |
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resolution: 256 |
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in_channels: 3 |
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out_ch: 3 |
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ch: 128 |
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ch_mult: |
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- 1 |
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- 2 |
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- 4 |
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- 4 |
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num_res_blocks: 2 |
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attn_resolutions: [] |
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dropout: 0.0 |
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lossconfig: |
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cond_stage_config: |
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freeze: True |
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layer: "penultimate" |
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data: |
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batch_size: 4 |
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num_workers: 4 |
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train: |
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target: ldm.data.cifar10.hf_dataset |
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params: |
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name: cifar10 |
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image_transforms: |
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- target: torchvision.transforms.Resize |
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params: |
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size: 512 |
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interpolation: 3 |
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- target: torchvision.transforms.RandomCrop |
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params: |
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size: 512 |
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- target: torchvision.transforms.RandomHorizontalFlip |
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lightning: |
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trainer: |
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accelerator: 'gpu' |
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devices: 1 |
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log_gpu_memory: all |
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max_epochs: 2 |
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precision: 16 |
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auto_select_gpus: False |
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strategy: |
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use_chunk: True |
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enable_distributed_storage: True |
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placement_policy: cuda |
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force_outputs_fp32: true |
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min_chunk_size: 64 |
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log_every_n_steps: 2 |
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logger: True |
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default_root_dir: "/tmp/diff_log/" |
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# profiler: pytorch |
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logger_config: |
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wandb: |
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name: nowname |
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save_dir: "/tmp/diff_log/" |
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offline: opt.debug |
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id: nowname
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