delete useless file

configs/deploy/clip_aslp_3df+3dc+abo+gso+toy+t10k+obj+sp+pk=256_01_4096_8_ckpt_250000_udt=110M_finetune_500000_deploy.yaml

@@ -1,181 +0,0 @@
-name: "0630_clip_aslp_3df+3dc+abo+gso+toy+t10k+obj+sp+pk=256_01_4096_8_ckpt_250000_udt=110M_finetune_500000"
-#wandb:
-#  project: "image_diffuser"
-#  offline: false
-
-
-training:
-  steps: 500000
-  use_amp: true
-  ckpt_path: ""
-  base_lr: 1.e-4
-  gradient_clip_val: 5.0
-  gradient_clip_algorithm: "norm"
-  every_n_train_steps: 5000
-  val_check_interval: 1024
-  limit_val_batches: 16
-
-dataset:
-  target: michelangelo.data.asl_webdataset.MultiAlignedShapeLatentModule
-  params:
-    batch_size: 38
-    num_workers: 4
-    val_num_workers: 4
-    buffer_size: 256
-    return_normal: true
-    random_crop: false
-    surface_sampling: true
-    pc_size: &pc_size 4096
-    image_size: 384
-    mean: &mean [0.5, 0.5, 0.5]
-    std: &std [0.5, 0.5, 0.5]
-    cond_stage_key: "image"
-
-    meta_info:
-      3D-FUTURE:
-        render_folder: "/root/workspace/cq_workspace/datasets/3D-FUTURE/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/3D-FUTURE"
-
-      ABO:
-        render_folder: "/root/workspace/cq_workspace/datasets/ABO/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/ABO"
-
-      GSO:
-        render_folder: "/root/workspace/cq_workspace/datasets/GSO/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/GSO"
-
-      TOYS4K:
-        render_folder: "/root/workspace/cq_workspace/datasets/TOYS4K/TOYS4K/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/TOYS4K"
-
-      3DCaricShop:
-        render_folder: "/root/workspace/cq_workspace/datasets/3DCaricShop/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/3DCaricShop"
-
-      Thingi10K:
-        render_folder: "/root/workspace/cq_workspace/datasets/Thingi10K/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/Thingi10K"
-
-      shapenet:
-        render_folder: "/root/workspace/cq_workspace/datasets/shapenet/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/shapenet"
-
-      pokemon:
-        render_folder: "/root/workspace/cq_workspace/datasets/pokemon/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/pokemon"
-
-      objaverse:
-        render_folder: "/root/workspace/cq_workspace/datasets/objaverse/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/objaverse"
-
-model:
-  target: michelangelo.models.asl_diffusion.clip_asl_diffuser_pl_module.ClipASLDiffuser
-  params:
-    first_stage_config:
-      target: michelangelo.models.tsal.asl_pl_module.AlignedShapeAsLatentPLModule
-      params:
-        shape_module_cfg:
-          target: michelangelo.models.tsal.sal_perceiver.AlignedShapeLatentPerceiver
-          params:
-            num_latents: &num_latents 256
-            embed_dim: &embed_dim 64
-            point_feats: 3   # normal
-            num_freqs: 8
-            include_pi: false
-            heads: 12
-            width: 768
-            num_encoder_layers: 8
-            num_decoder_layers: 16
-            use_ln_post: true
-            init_scale: 0.25
-            qkv_bias: false
-            use_checkpoint: false
-        aligned_module_cfg:
-          target: michelangelo.models.tsal.clip_asl_module.CLIPAlignedShapeAsLatentModule
-          params:
-            clip_model_version: "/mnt/shadow_cv_training/stevenxxliu/checkpoints/clip/clip-vit-large-patch14"
-            # clip_model_version: "/root/workspace/checkpoints/clip/clip-vit-large-patch14"
-
-        loss_cfg:
-          target: torch.nn.Identity
-
-    cond_stage_config:
-      target: michelangelo.models.conditional_encoders.encoder_factory.FrozenCLIPImageGridEmbedder
-      params:
-        version: "/mnt/shadow_cv_training/stevenxxliu/checkpoints/clip/clip-vit-large-patch14"
-        # version: "/root/workspace/checkpoints/clip/clip-vit-large-patch14"
-        zero_embedding_radio: 0.1
-
-    first_stage_key: "surface"
-    cond_stage_key: "image"
-    scale_by_std: false
-
-    denoiser_cfg:
-      target: michelangelo.models.asl_diffusion.asl_udt.ConditionalASLUDTDenoiser
-      params:
-        input_channels: *embed_dim
-        output_channels: *embed_dim
-        n_ctx: *num_latents
-        width: 768
-        layers: 6   # 2 * 6 + 1 = 13
-        heads: 12
-        context_dim: 1024
-        init_scale: 1.0
-        skip_ln: true
-        use_checkpoint: true
-
-    scheduler_cfg:
-      guidance_scale: 7.5
-      num_inference_steps: 50
-      eta: 0.0
-
-      noise:
-        target: diffusers.schedulers.DDPMScheduler
-        params:
-          num_train_timesteps: 1000
-          beta_start: 0.00085
-          beta_end: 0.012
-          beta_schedule: "scaled_linear"
-          variance_type: "fixed_small"
-          clip_sample: false
-      denoise:
-        target: diffusers.schedulers.DDIMScheduler
-        params:
-          num_train_timesteps: 1000
-          beta_start: 0.00085
-          beta_end: 0.012
-          beta_schedule: "scaled_linear"
-          clip_sample: false   # clip sample to -1~1
-          set_alpha_to_one: false
-          steps_offset: 1
-
-    optimizer_cfg:
-      optimizer:
-        target: torch.optim.AdamW
-        params:
-          betas: [0.9, 0.99]
-          eps: 1.e-6
-          weight_decay: 1.e-2
-
-      scheduler:
-        target: michelangelo.utils.trainings.lr_scheduler.LambdaWarmUpCosineFactorScheduler
-        params:
-          warm_up_steps: 5000
-          f_start: 1.e-6
-          f_min: 1.e-3
-          f_max: 1.0
-
-    loss_cfg:
-      loss_type: "mse"
-
-logger:
-  target: michelangelo.utils.trainings.mesh_log_callback.ImageConditionalASLDiffuserLogger
-  params:
-    step_frequency: 2000
-    num_samples: 4
-    sample_times: 4
-    mean: *mean
-    std: *std
-    bounds: [-1.1, -1.1, -1.1, 1.1, 1.1, 1.1]
-    octree_depth: 7
-    num_chunks: 10000

configs/deploy/clip_sp+pk_aslperceiver=256_01_4096_8_udt=03.yaml

@@ -1,180 +0,0 @@
-name: "0428_clip_subsp+pk_sal_perceiver=256_01_4096_8_udt=03"
-#wandb:
-#  project: "image_diffuser"
-#  offline: false
-
-training:
-  steps: 500000
-  use_amp: true
-  ckpt_path: ""
-  base_lr: 1.e-4
-  gradient_clip_val: 5.0
-  gradient_clip_algorithm: "norm"
-  every_n_train_steps: 5000
-  val_check_interval: 1024
-  limit_val_batches: 16
-
-# dataset
-dataset:
-  target: michelangelo.data.asl_torch_dataset.MultiAlignedShapeImageTextModule
-  params:
-    batch_size: 38
-    num_workers: 4
-    val_num_workers: 4
-    buffer_size: 256
-    return_normal: true
-    random_crop: false
-    surface_sampling: true
-    pc_size: &pc_size 4096
-    image_size: 384
-    mean: &mean [0.5, 0.5, 0.5]
-    std: &std [0.5, 0.5, 0.5]
-
-    cond_stage_key: "text"
-
-    meta_info:
-      3D-FUTURE:
-        render_folder: "/root/workspace/cq_workspace/datasets/3D-FUTURE/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/3D-FUTURE"
-
-      ABO:
-        render_folder: "/root/workspace/cq_workspace/datasets/ABO/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/ABO"
-
-      GSO:
-        render_folder: "/root/workspace/cq_workspace/datasets/GSO/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/GSO"
-
-      TOYS4K:
-        render_folder: "/root/workspace/cq_workspace/datasets/TOYS4K/TOYS4K/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/TOYS4K"
-
-      3DCaricShop:
-        render_folder: "/root/workspace/cq_workspace/datasets/3DCaricShop/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/3DCaricShop"
-
-      Thingi10K:
-        render_folder: "/root/workspace/cq_workspace/datasets/Thingi10K/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/Thingi10K"
-
-      shapenet:
-        render_folder: "/root/workspace/cq_workspace/datasets/shapenet/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/shapenet"
-
-      pokemon:
-        render_folder: "/root/workspace/cq_workspace/datasets/pokemon/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/pokemon"
-
-      objaverse:
-        render_folder: "/root/workspace/cq_workspace/datasets/objaverse/renders"
-        tar_folder: "/root/workspace/datasets/make_tars/objaverse"
-
-model:
-  target: michelangelo.models.asl_diffusion.clip_asl_diffuser_pl_module.ClipASLDiffuser
-  params:
-    first_stage_config:
-      target: michelangelo.models.tsal.asl_pl_module.AlignedShapeAsLatentPLModule
-      params:
-        # ckpt_path: "/root/workspace/cq_workspace/michelangelo/experiments/aligned_shape_latents/clip_aslperceiver_sp+pk_01_01/ckpt/ckpt-step=00230000.ckpt"
-        shape_module_cfg:
-          target: michelangelo.models.tsal.sal_perceiver.AlignedShapeLatentPerceiver
-          params:
-            num_latents: &num_latents 256
-            embed_dim: &embed_dim 64
-            point_feats: 3   # normal
-            num_freqs: 8
-            include_pi: false
-            heads: 12
-            width: 768
-            num_encoder_layers: 8
-            num_decoder_layers: 16
-            use_ln_post: true
-            init_scale: 0.25
-            qkv_bias: false
-            use_checkpoint: true
-        aligned_module_cfg:
-          target: michelangelo.models.tsal.clip_asl_module.CLIPAlignedShapeAsLatentModule
-          params:
-            clip_model_version: "/mnt/shadow_cv_training/stevenxxliu/checkpoints/clip/clip-vit-large-patch14"
-
-        loss_cfg:
-          target: torch.nn.Identity
-
-    cond_stage_config:
-      target: michelangelo.models.conditional_encoders.encoder_factory.FrozenAlignedCLIPTextEmbedder
-      params:
-        version: "/mnt/shadow_cv_training/stevenxxliu/checkpoints/clip/clip-vit-large-patch14"
-        zero_embedding_radio: 0.1
-        max_length: 77
-
-    first_stage_key: "surface"
-    cond_stage_key: "text"
-    scale_by_std: false
-
-    denoiser_cfg:
-      target: michelangelo.models.asl_diffusion.asl_udt.ConditionalASLUDTDenoiser
-      params:
-        input_channels: *embed_dim
-        output_channels: *embed_dim
-        n_ctx: *num_latents
-        width: 768
-        layers: 8   # 2 * 6 + 1 = 13
-        heads: 12
-        context_dim: 768
-        init_scale: 1.0
-        skip_ln: true
-        use_checkpoint: true
-
-    scheduler_cfg:
-      guidance_scale: 7.5
-      num_inference_steps: 50
-      eta: 0.0
-
-      noise:
-        target: diffusers.schedulers.DDPMScheduler
-        params:
-          num_train_timesteps: 1000
-          beta_start: 0.00085
-          beta_end: 0.012
-          beta_schedule: "scaled_linear"
-          variance_type: "fixed_small"
-          clip_sample: false
-      denoise:
-        target: diffusers.schedulers.DDIMScheduler
-        params:
-          num_train_timesteps: 1000
-          beta_start: 0.00085
-          beta_end: 0.012
-          beta_schedule: "scaled_linear"
-          clip_sample: false   # clip sample to -1~1
-          set_alpha_to_one: false
-          steps_offset: 1
-
-    optimizer_cfg:
-      optimizer:
-        target: torch.optim.AdamW
-        params:
-          betas: [0.9, 0.99]
-          eps: 1.e-6
-          weight_decay: 1.e-2
-
-      scheduler:
-        target: michelangelo.utils.trainings.lr_scheduler.LambdaWarmUpCosineFactorScheduler
-        params:
-          warm_up_steps: 5000
-          f_start: 1.e-6
-          f_min: 1.e-3
-          f_max: 1.0
-
-    loss_cfg:
-      loss_type: "mse"
-
-logger:
-  target: michelangelo.utils.trainings.mesh_log_callback.TextConditionalASLDiffuserLogger
-  params:
-    step_frequency: 1000
-    num_samples: 4
-    sample_times: 4
-    bounds: [-1.1, -1.1, -1.1, 1.1, 1.1, 1.1]
-    octree_depth: 7
-    num_chunks: 10000