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data/external_models/MindEyeV2/sd_xl_base.yaml

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+model:
+  target: sgm.models.diffusion.DiffusionEngine
+  params:
+    scale_factor: 0.13025
+    disable_first_stage_autocast: True
+
+    denoiser_config:
+      target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
+      params:
+        num_idx: 1000
+
+        scaling_config:
+          target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling
+        discretization_config:
+          target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
+
+    network_config:
+      target: sgm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        adm_in_channels: 2816
+        num_classes: sequential
+        use_checkpoint: True
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [4, 2]
+        num_res_blocks: 2
+        channel_mult: [1, 2, 4]
+        num_head_channels: 64
+        use_linear_in_transformer: True
+        transformer_depth: [1, 2, 10]
+        context_dim: 2048
+        spatial_transformer_attn_type: softmax-xformers
+
+    conditioner_config:
+      target: sgm.modules.GeneralConditioner
+      params:
+        emb_models:
+          - is_trainable: False
+            input_key: txt
+            target: sgm.modules.encoders.modules.FrozenCLIPEmbedder
+            params:
+              layer: hidden
+              layer_idx: 11
+
+          - is_trainable: False
+            input_key: txt
+            target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2
+            params:
+              arch: ViT-bigG-14
+              version: laion2b_s39b_b160k
+              freeze: True
+              layer: penultimate
+              always_return_pooled: True
+              legacy: False
+
+          - is_trainable: False
+            input_key: original_size_as_tuple
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256
+
+          - is_trainable: False
+            input_key: crop_coords_top_left
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256
+
+          - is_trainable: False
+            input_key: target_size_as_tuple
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256
+
+    first_stage_config:
+      target: sgm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          attn_type: vanilla-xformers
+          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

data/external_models/MindEyeV2/unclip6.yaml

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+model:
+  base_learning_rate: 1.0e-5
+  target: sgm.models.diffusion.DiffusionEngine
+  params:
+    scale_factor: 0.13025
+    disable_first_stage_autocast: True
+    no_cond_log: True
+
+    ckpt_config:
+      target: sgm.modules.checkpoint.CheckpointEngine
+      params:
+        ckpt_path: checkpoints/sd_xl_base_1.0.safetensors
+        pre_adapters:
+          - target: sgm.modules.checkpoint.Finetuner
+            params:
+              keys:
+                - model\.diffusion_model\.(input_blocks|middle_block|output_blocks)(\.[0-9])?\.[0-9]\.transformer_blocks\.[0-9]\.attn2\.(to_k|to_v)\.weight
+          - target: sgm.modules.checkpoint.Pruner
+            params:
+              keys:
+                - model\.diffusion_model\.label_emb\.0\.0\.weight
+              slices:
+                - ":, :1024"
+        print_sd_keys: False
+        print_model: False
+
+    scheduler_config:
+      target: sgm.lr_scheduler.LambdaLinearScheduler
+      params:
+        warm_up_steps: [ 1000 ]
+        cycle_lengths: [ 10000000000000 ]
+        f_start: [ 1.e-6 ]
+        f_max: [ 1. ]
+        f_min: [ 1. ]
+
+    denoiser_config:
+      target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
+      params:
+        num_idx: 1000
+
+        scaling_config:
+          target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling
+
+        discretization_config:
+          target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
+
+    network_config:
+      target: sgm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        adm_in_channels: 1024 #2816
+        num_classes: sequential
+        use_checkpoint: True
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4 ]
+        num_head_channels: 64
+        use_linear_in_transformer: True
+        transformer_depth: [ 1, 2, 10 ]  # note: the first is unused (due to attn_res starting at 2) 32, 16, 8 --> 64, 32, 16
+        context_dim: 1664 #1280
+        spatial_transformer_attn_type: softmax-xformers
+
+    conditioner_config:
+      target: sgm.modules.GeneralConditioner
+      params:
+        emb_models:
+          # cross atn 
+          - is_trainable: False
+            input_key: jpg
+            target: sgm.modules.encoders.modules.FrozenOpenCLIPImageEmbedder
+            params:
+              arch: ViT-bigG-14
+              version: laion2b_s39b_b160k
+              freeze: True
+              repeat_to_max_len: False
+              output_tokens: True
+              only_tokens: True
+          # vector cond
+          - is_trainable: False
+            input_key: original_size_as_tuple
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256  # multiplied by two
+          # vector cond
+          - is_trainable: False
+            input_key: crop_coords_top_left
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256  # multiplied by two
+          # # vector cond
+          # - is_trainable: False
+          #   input_key: target_size_as_tuple
+          #   target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+          #   params:
+          #     outdim: 256  # multiplied by two
+
+    first_stage_config:
+      target: sgm.models.autoencoder.AutoencoderKLInferenceWrapper
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          attn_type: vanilla-xformers
+          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
+
+    loss_fn_config:
+      target: sgm.modules.diffusionmodules.loss.StandardDiffusionLoss
+      params:
+        offset_noise_level: 0.04
+        sigma_sampler_config:
+          target: sgm.modules.diffusionmodules.sigma_sampling.DiscreteSampling
+          params:
+            num_idx: 1000
+
+            discretization_config:
+              target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
+        loss_weighting_config:
+          target: sgm.modules.diffusionmodules.loss_weighting.EpsWeighting
+
+    sampler_config:
+      target: sgm.modules.diffusionmodules.sampling.EulerEDMSampler
+      params:
+        num_steps: 50
+
+        discretization_config:
+          target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
+
+        guider_config:
+          target: sgm.modules.diffusionmodules.guiders.VanillaCFG
+          params:
+            scale: 5.0
+
+data:
+  target: sgm.data.dataset.StableDataModuleFromConfig
+  params:
+    train:
+      datapipeline:
+        urls:
+          - s3://stability-west/sddatasets/laiocosplitv1c/
+        pipeline_config:
+          shardshuffle: 10000
+          sample_shuffle: 10000
+
+        preprocessors:
+          - target: sdata.filters.SimpleKeyFilter
+            params:
+              keys: [txt, jpg]
+          - target: sdata.filters.AttributeFilter
+            params:
+              filter_dict:
+                SSCD_65: False
+                is_spawning: True
+                is_getty: True
+
+        decoders:
+          - pil
+
+      loader:
+        batch_size: 1
+        num_workers: 4
+        batched_transforms:
+          - target: sdata.mappers.MultiAspectCacher
+            params:
+              batch_size: 16
+              debug: False
+              crop_coords_key: crop_coords_top_left
+              target_size_key: target_size_as_tuple
+              original_size_key: original_size_as_tuple
+              max_pixels: 262144
+
+
+lightning:
+  strategy:
+    target: pytorch_lightning.strategies.DDPStrategy
+
+  modelcheckpoint:
+    params:
+      every_n_train_steps: 100000
+
+  callbacks:
+    metrics_over_trainsteps_checkpoint:
+      params:
+        every_n_train_steps: 5000
+
+    image_logger:
+      target: sgm.modules.loggers.train_logging.SampleLogger
+      params:
+        disabled: False
+        enable_autocast: True
+        batch_frequency: 2000
+        max_images: 4
+        increase_log_steps: True
+        log_first_step: False
+        log_before_first_step: True
+        log_images_kwargs:
+          N: 4
+          num_steps:
+            - 50
+          ucg_keys: [ ]
+
+  trainer:
+    devices: 0,
+    benchmark: False
+    num_sanity_val_steps: 0
+    accumulate_grad_batches: 1
+    max_epochs: 1000
+    precision: 16

data/external_models/MindEyeV2/unclip6_epoch0_step110000.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6bd7033dee484bba449d243408f36f080ace62b774d0da7894fd898fdf155652
+size 17980447939

data/external_models/SDXL/sd_xl_base.yaml

@@ -0,0 +1,93 @@
+model:
+  target: sgm.models.diffusion.DiffusionEngine
+  params:
+    scale_factor: 0.13025
+    disable_first_stage_autocast: True
+
+    denoiser_config:
+      target: sgm.modules.diffusionmodules.denoiser.DiscreteDenoiser
+      params:
+        num_idx: 1000
+
+        scaling_config:
+          target: sgm.modules.diffusionmodules.denoiser_scaling.EpsScaling
+        discretization_config:
+          target: sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization
+
+    network_config:
+      target: sgm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        adm_in_channels: 2816
+        num_classes: sequential
+        use_checkpoint: True
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [4, 2]
+        num_res_blocks: 2
+        channel_mult: [1, 2, 4]
+        num_head_channels: 64
+        use_linear_in_transformer: True
+        transformer_depth: [1, 2, 10]
+        context_dim: 2048
+        spatial_transformer_attn_type: softmax-xformers
+
+    conditioner_config:
+      target: sgm.modules.GeneralConditioner
+      params:
+        emb_models:
+          - is_trainable: False
+            input_key: txt
+            target: sgm.modules.encoders.modules.FrozenCLIPEmbedder
+            params:
+              layer: hidden
+              layer_idx: 11
+
+          - is_trainable: False
+            input_key: txt
+            target: sgm.modules.encoders.modules.FrozenOpenCLIPEmbedder2
+            params:
+              arch: ViT-bigG-14
+              version: laion2b_s39b_b160k
+              freeze: True
+              layer: penultimate
+              always_return_pooled: True
+              legacy: False
+
+          - is_trainable: False
+            input_key: original_size_as_tuple
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256
+
+          - is_trainable: False
+            input_key: crop_coords_top_left
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256
+
+          - is_trainable: False
+            input_key: target_size_as_tuple
+            target: sgm.modules.encoders.modules.ConcatTimestepEmbedderND
+            params:
+              outdim: 256
+
+    first_stage_config:
+      target: sgm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          attn_type: vanilla-xformers
+          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

data/external_models/SDXL/zavychromaxl_v30.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f1270c1f025398346c59dab6d9ee234ec50b8f650b01f19376f9b647e6411b75
+size 6938040682