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Add adaln-ddpm-p02 (PixCell-GE-B-p02)

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adaln-ddpm-p02/README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - histopathology
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+ - diffusion
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+ - spatial-transcriptomics
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+ - icml-2026-sd4h-workshop
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+ ---
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+
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+ # PixCell-GE-B-p02
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+
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+ EMA-only inference weights for the **PixCell-GE-B-p02** row reported in the
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+ ICML 2026 SD4H workshop submission *Transcriptomics-Conditioned Virtual Tissue
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+ Synthesis via Diffusion Transformers*.
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+
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+ - **Source checkpoint**: `step_0545000_ema.pt`
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+ - **Architecture**: see `training_config.yaml` in this folder.
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+ - **License**: Apache-2.0.
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+
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+ See the umbrella repo README at `stmdit-anon/stmdit-checkpoints` for usage.
adaln-ddpm-p02/model.pt ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:fb3997b8e6d1603ef5972101b32d32cda00ebfa946ed90e4a34d86c38405a4ed
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+ size 531422045
adaln-ddpm-p02/training_config.yaml ADDED
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+ # Training Configuration - PixArtGE-B with CancerFoundation Encoder
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+ # ==================================================================
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+ # Base variant (130M params) with CancerFoundation gene expression encoder.
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+ #
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+ # Usage:
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+ # run-training training.yaml --lightning
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+
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+ output_dir: "/cluster/work/grlab/projects/projects2025-virtual-tissue-gen/scratch/10x_TuPro/PixCell-GE/training/pixart-ge-cf-B-dropout-p02"
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+ device: "cuda"
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+
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+ # ============================================================================
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+ # MODEL
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+ # ============================================================================
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+
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+ model:
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+ type: "pixart_ge"
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+ variant: "B" # 130M params: depth=12, hidden=768, heads=12
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+ ge_encoder_type: "cancerfoundation"
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+ ge_hidden_dim: 512
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+ cf_model_dir: "/cluster/home/pvlachas/leomed-home/pretrained_model_weights/cancer-foundation"
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+ cf_freeze_backbone: true
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+
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+ # ============================================================================
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+ # DATA
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+ # ============================================================================
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+
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+ data:
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+ # Dataset-centric path
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+ features_dir: "/cluster/work/grlab/projects/projects2025-virtual-tissue-gen/scratch/10x_TuPro/feat-extraction/features_train"
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+ load_gene_expression: true
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+ load_gene_expression_binned: true
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+ num_workers: 8
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+ pin_memory: true
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+ val_split: 0.1
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+
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+ # ============================================================================
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+ # DIFFUSION
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+ # ============================================================================
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+
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+ diffusion:
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+ timesteps: 1000
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+ beta_schedule: "linear"
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+ image_size: 256
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+ latent_size: 32
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+
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+ # ============================================================================
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+ # TRAINING
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+ # ============================================================================
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+
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+ training:
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+ batch_size: 32
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+ batch_size_val: 32
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+ gradient_accumulation_steps: 4 # effective batch = 128 (matches original PixCell)
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+ num_epochs: 1000
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+ seed: 42
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+ gradient_clip: 0.01
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+ ema_rate: 0.9999
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+
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+ optimizer:
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+ lr: 2e-5 # matches original PixCell (was 1e-4)
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+ weight_decay: 0.01
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+ betas: [0.9, 0.999]
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+
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+ scheduler:
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+ warmup_steps: 1000
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+ min_lr_ratio: 0.1
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+
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+ classifier_free_guidance:
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+ conditioning_schedule:
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+ - mask: [uni, ge] # full conditioning (UNI + GE active)
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+ weight: 64
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+ - mask: [ge] # GE only (UNI dropped)
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+ weight: 16
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+ - mask: [uni] # UNI only (GE dropped)
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+ weight: 16
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+ - mask: [] # unconditional (both dropped)
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+ weight: 4
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+
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+ modality_monitor:
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+ enabled: true
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+ diagnostic_freq: 10
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+ diagnostic_batch_size: 64
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+
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+ # ============================================================================
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+ # DISTRIBUTED
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+ # ============================================================================
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+
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+ distributed:
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+ precision: "32"
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+
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+ # ============================================================================
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+ # CHECKPOINT
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+ # ============================================================================
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+
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+ checkpoint:
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+ save_every: 1000
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+ resume: null
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+
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+ # ============================================================================
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+ # LOGGING
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+ # ============================================================================
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+
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+ logging:
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+ log_every: 100
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+ validate_every: 0
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+ gpu_monitor: true
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+ gpu_monitor_interval: 60.0
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+ # Periodic image sampling (disabled; set vae_path + epochs/steps to enable)
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+ sample_every_epochs: 10
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+ sample_every_steps: 0
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+ num_samples: 16
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+ sample_guidance_scale: 3.0
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+ sample_num_steps: 20
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+ sample_vae_path: "/cluster/home/pvlachas/leomed-home/pretrained_model_weights/stability-ai-stable-diffusion-3-5-large/models--stabilityai--stable-diffusion-3.5-large/snapshots/ceddf0a7fdf2064ea28e2213e3b84e4afa170a0f/vae"