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FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/README.md

@@ -90,8 +90,8 @@ You may reuse the base model text encoder for inference.
 
 ## Training settings
 
-- Training epochs: 5
-- Training steps: 15000
+- Training epochs: 8
+- Training steps: 25000
 - Learning rate: 1.0
   - Learning rate schedule: constant
   - Warmup steps: 0

FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-24500/README.md

@@ -0,0 +1,173 @@
+---
+license: other
+base_model: "black-forest-labs/FLUX.2-dev"
+tags:
+  - flux2
+  - flux2-diffusers
+  - text-to-image
+  - image-to-image
+  - diffusers
+  - simpletuner
+  - not-for-all-audiences
+  - lora
+
+  - template:sd-lora
+  - lycoris
+pipeline_tag: text-to-image
+inference: true
+
+---
+
+# FLUX.2-DEV-DLAY-LyCORIS
+
+This is a LyCORIS adapter derived from [black-forest-labs/FLUX.2-dev](https://huggingface.co/black-forest-labs/FLUX.2-dev).
+
+No validation prompt was used during training.
+
+None
+
+
+
+## Validation settings
+- CFG: `4.0`
+- CFG Rescale: `0.0`
+- Steps: `28`
+- Sampler: `FlowMatchEulerDiscreteScheduler`
+- Seed: `42`
+- Resolution: `1024x1024`
+
+
+Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
+
+
+
+
+<Gallery />
+
+The text encoder **was not** trained.
+You may reuse the base model text encoder for inference.
+
+
+## Training settings
+
+- Training epochs: 8
+- Training steps: 24500
+- Learning rate: 1.0
+  - Learning rate schedule: constant
+  - Warmup steps: 0
+- Max grad norm: 1.0
+- Effective batch size: 8
+  - Micro-batch size: 1
+  - Gradient accumulation steps: 1
+  - Number of GPUs: 8
+- Gradient checkpointing: False
+- Prediction type: flow_matching[]
+- Optimizer: prodigy (config=d_coef=2.0,weight_decay=0.01,use_bias_correction=False,schedulefree_c=75,use_orthograd=True)
+- Trainable parameter precision: Pure BF16
+- Base model precision: `no_change`
+- Caption dropout probability: 0.1%
+
+
+
+
+### LyCORIS Config:
+```json
+{
+    "algo": "lokr",
+    "multiplier": 1.0,
+    "factor": 12,
+    "linear_dim": 100000,
+    "linear_alpha": 1,
+    "conv_dim": 0,
+    "conv_alpha": 0,
+    "dora_wd": true,
+    "apply_preset": {
+        "target_module": [
+            "Flux2TransformerBlock",
+            "Flux2SingleTransformerBlock"
+        ]
+    }
+}
+```
+
+
+## Datasets
+
+### dlay-subject-data
+- Repeats: 10
+- Total number of images: ~2152
+- Total number of aspect buckets: 1
+- Resolution: 1.048576 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+
+
+## Inference
+
+
+```python
+import torch
+from diffusers import DiffusionPipeline
+from lycoris import create_lycoris_from_weights
+
+
+def download_adapter(repo_id: str):
+    import os
+    from huggingface_hub import hf_hub_download
+    adapter_filename = "pytorch_lora_weights.safetensors"
+    cache_dir = os.environ.get('HF_PATH', os.path.expanduser('~/.cache/huggingface/hub/models'))
+    cleaned_adapter_path = repo_id.replace("/", "_").replace("\\", "_").replace(":", "_")
+    path_to_adapter = os.path.join(cache_dir, cleaned_adapter_path)
+    path_to_adapter_file = os.path.join(path_to_adapter, adapter_filename)
+    os.makedirs(path_to_adapter, exist_ok=True)
+    hf_hub_download(
+        repo_id=repo_id, filename=adapter_filename, local_dir=path_to_adapter
+    )
+
+    return path_to_adapter_file
+    
+model_id = 'black-forest-labs/FLUX.2-dev'
+adapter_repo_id = 'ThatDustyGuy/FLUX.2-DEV-DLAY-LyCORIS'
+adapter_filename = 'pytorch_lora_weights.safetensors'
+adapter_file_path = download_adapter(repo_id=adapter_repo_id)
+pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
+lora_scale = 1.0
+wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_file_path, pipeline.transformer)
+wrapper.merge_to()
+
+prompt = "An astronaut is riding a horse through the jungles of Thailand."
+negative_prompt = 'blurry, cropped, ugly'
+
+## Optional: quantise the model to save on vram.
+## Note: The model was not quantised during training, so it is not necessary to quantise it during inference time.
+#from optimum.quanto import quantize, freeze, qint8
+#quantize(pipeline.transformer, weights=qint8)
+#freeze(pipeline.transformer)
+    
+pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') # the pipeline is already in its target precision level
+model_output = pipeline(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    num_inference_steps=28,
+    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(42),
+    width=1024,
+    height=1024,
+    guidance_scale=4.0,
+).images[0]
+
+model_output.save("output.png", format="PNG")
+
+```
+
+
+
+## Exponential Moving Average (EMA)
+
+SimpleTuner generates a safetensors variant of the EMA weights and a pt file.
+
+The safetensors file is intended to be used for inference, and the pt file is for continuing finetuning.
+
+The EMA model may provide a more well-rounded result, but typically will feel undertrained compared to the full model as it is a running decayed average of the model weights.
+

FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-24500/ema/ema_model.safetensors

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FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-24500/lycoris_config.json

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+{
+  "algo": "lokr",
+  "multiplier": 1.0,
+  "factor": 12,
+  "linear_dim": 100000,
+  "linear_alpha": 1,
+  "conv_dim": 0,
+  "conv_alpha": 0,
+  "dora_wd": true,
+  "apply_preset": {
+    "target_module": [
+      "Flux2TransformerBlock", 
+      "Flux2SingleTransformerBlock"
+    ]
+  }
+}

FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-24500/pytorch_lora_weights.safetensors

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FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-24500/simpletuner_config.json

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+    "push_checkpoints_to_hub": false,
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+    "model_type_label": "Flux.2",
+    "use_deepspeed_optimizer": false,
+    "use_deepspeed_scheduler": false,
+    "base_weight_dtype": "torch.bfloat16",
+    "is_quanto": false,
+    "is_torchao": false,
+    "is_bnb": false,
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+}

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FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-25000/README.md

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+---
+license: other
+base_model: "black-forest-labs/FLUX.2-dev"
+tags:
+  - flux2
+  - flux2-diffusers
+  - text-to-image
+  - image-to-image
+  - diffusers
+  - simpletuner
+  - not-for-all-audiences
+  - lora
+
+  - template:sd-lora
+  - lycoris
+pipeline_tag: text-to-image
+inference: true
+
+---
+
+# FLUX.2-DEV-DLAY-LyCORIS
+
+This is a LyCORIS adapter derived from [black-forest-labs/FLUX.2-dev](https://huggingface.co/black-forest-labs/FLUX.2-dev).
+
+No validation prompt was used during training.
+
+None
+
+
+
+## Validation settings
+- CFG: `4.0`
+- CFG Rescale: `0.0`
+- Steps: `28`
+- Sampler: `FlowMatchEulerDiscreteScheduler`
+- Seed: `42`
+- Resolution: `1024x1024`
+
+
+Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
+
+
+
+
+<Gallery />
+
+The text encoder **was not** trained.
+You may reuse the base model text encoder for inference.
+
+
+## Training settings
+
+- Training epochs: 8
+- Training steps: 25000
+- Learning rate: 1.0
+  - Learning rate schedule: constant
+  - Warmup steps: 0
+- Max grad norm: 1.0
+- Effective batch size: 8
+  - Micro-batch size: 1
+  - Gradient accumulation steps: 1
+  - Number of GPUs: 8
+- Gradient checkpointing: False
+- Prediction type: flow_matching[]
+- Optimizer: prodigy (config=d_coef=2.0,weight_decay=0.01,use_bias_correction=False,schedulefree_c=75,use_orthograd=True)
+- Trainable parameter precision: Pure BF16
+- Base model precision: `no_change`
+- Caption dropout probability: 0.1%
+
+
+
+
+### LyCORIS Config:
+```json
+{
+    "algo": "lokr",
+    "multiplier": 1.0,
+    "factor": 12,
+    "linear_dim": 100000,
+    "linear_alpha": 1,
+    "conv_dim": 0,
+    "conv_alpha": 0,
+    "dora_wd": true,
+    "apply_preset": {
+        "target_module": [
+            "Flux2TransformerBlock",
+            "Flux2SingleTransformerBlock"
+        ]
+    }
+}
+```
+
+
+## Datasets
+
+### dlay-subject-data
+- Repeats: 10
+- Total number of images: ~2152
+- Total number of aspect buckets: 1
+- Resolution: 1.048576 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+
+
+## Inference
+
+
+```python
+import torch
+from diffusers import DiffusionPipeline
+from lycoris import create_lycoris_from_weights
+
+
+def download_adapter(repo_id: str):
+    import os
+    from huggingface_hub import hf_hub_download
+    adapter_filename = "pytorch_lora_weights.safetensors"
+    cache_dir = os.environ.get('HF_PATH', os.path.expanduser('~/.cache/huggingface/hub/models'))
+    cleaned_adapter_path = repo_id.replace("/", "_").replace("\\", "_").replace(":", "_")
+    path_to_adapter = os.path.join(cache_dir, cleaned_adapter_path)
+    path_to_adapter_file = os.path.join(path_to_adapter, adapter_filename)
+    os.makedirs(path_to_adapter, exist_ok=True)
+    hf_hub_download(
+        repo_id=repo_id, filename=adapter_filename, local_dir=path_to_adapter
+    )
+
+    return path_to_adapter_file
+    
+model_id = 'black-forest-labs/FLUX.2-dev'
+adapter_repo_id = 'ThatDustyGuy/FLUX.2-DEV-DLAY-LyCORIS'
+adapter_filename = 'pytorch_lora_weights.safetensors'
+adapter_file_path = download_adapter(repo_id=adapter_repo_id)
+pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
+lora_scale = 1.0
+wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_file_path, pipeline.transformer)
+wrapper.merge_to()
+
+prompt = "An astronaut is riding a horse through the jungles of Thailand."
+negative_prompt = 'blurry, cropped, ugly'
+
+## Optional: quantise the model to save on vram.
+## Note: The model was not quantised during training, so it is not necessary to quantise it during inference time.
+#from optimum.quanto import quantize, freeze, qint8
+#quantize(pipeline.transformer, weights=qint8)
+#freeze(pipeline.transformer)
+    
+pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') # the pipeline is already in its target precision level
+model_output = pipeline(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    num_inference_steps=28,
+    generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(42),
+    width=1024,
+    height=1024,
+    guidance_scale=4.0,
+).images[0]
+
+model_output.save("output.png", format="PNG")
+
+```
+
+
+
+## Exponential Moving Average (EMA)
+
+SimpleTuner generates a safetensors variant of the EMA weights and a pt file.
+
+The safetensors file is intended to be used for inference, and the pt file is for continuing finetuning.
+
+The EMA model may provide a more well-rounded result, but typically will feel undertrained compared to the full model as it is a running decayed average of the model weights.
+

FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-25000/ema/ema_model.safetensors

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FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-25000/lycoris_config.json

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+  "algo": "lokr",
+  "multiplier": 1.0,
+  "factor": 12,
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+  "linear_alpha": 1,
+  "conv_dim": 0,
+  "conv_alpha": 0,
+  "dora_wd": true,
+  "apply_preset": {
+    "target_module": [
+      "Flux2TransformerBlock", 
+      "Flux2SingleTransformerBlock"
+    ]
+  }
+}

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+    "push_checkpoints_to_hub": false,
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+}

FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-25000/training_state-dlay-subject-data.json

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FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/simpletuner_config.json

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wandb/run-20251217_155825-6c9f2fa0804028c23c550af7a5c7aeb4/files/config.yaml

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+    value: false
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+    value: false
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+    value: null
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+    value: null
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+    value: INFERENCE
+same_network:
+    value: true
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+    value: 5
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+    value: unmodified
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+    value: no_change
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+    value: no_change
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+    value: no_change
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+    value: no_change
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+    value: 100
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+    value: 0
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+    value: 2959
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+    value: 7500
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+    value: gallery
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+    value: FLUX.2-DEV-DLAY-Persona
+tracker_run_name:
+    value: dlay-persona-prodigy-bf16-8xB300-V2-dynamo
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+    value: /root/SimpleTuner/config/FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2/user_prompt_library.json
+vae_batch_size:
+    value: 4
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+    value: false
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+    value: false
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+    value: recreate
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+    value: bf16
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+    value: false
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+    value: false
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+    value: false
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+    value: black-forest-labs/FLUX.2-dev
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+    value: blurry, cropped, ugly
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+    value: 128

wandb/run-20251217_155825-6c9f2fa0804028c23c550af7a5c7aeb4/files/output.log

@@ -416,6 +416,94 @@ Found EMA checkpoint!
 Processing Files (1 / 1)                : 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB,  100MB/s  
 New Data Upload                         : 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 30.6MB / 30.6MB, 8.06MB/s  
   ...int-24000/ema/ema_model.safetensors: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB            
-Epoch 9/9, Steps:  97%|███████████▋| 24272/25000 [5:10:44<24:53,  2.05s/it, grad_norm=0.00058, lr=0.000497, step_loss=0.0962]
+Processing Files (1 / 1)                : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB, 4.62MB/s  
 [RANK 0] 2025-12-17 20:55:55,806 [INFO] [Rank 0] Processing 8 local validation work items (distributed_mode=False, total=8, work_item_prompts=['DLAY man in a professional studio portrait with soft lighting, high quality photography, sharp focus', 'DLAY man standing outdoors in natural sunlight, casual pose, candid photography style', 'DLAY man in a formal business suit, professional headshot, corporate photography', 'DLAY man in an artistic portrait with dramatic lighting and shadows, fine art photography', 'DLAY man in a cinematic composition, film grain, moody atmosphere, dramatic lighting', 'DLAY man in dynamic action pose, sports photography style, sharp motion capture', 'DLAY man walking through a busy city street, urban photography, street style', 'close up portrait of DLAY man, detailed face, professional lighting, 85mm lens'])
-                                                                                                                                                                                                                                              
+New Data Upload                         : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB, 4.62MB/s  
+
+
+[RANK 0] 2025-12-17 21:17:04,916 [INFO] Saving EMA model to /root/output/FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-24500/transformer_ema/ema_model.pt
+[RANK 0] 2025-12-17 21:17:05,135 [INFO] EMA model state saved to /root/output/FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-24500/transformer_ema/ema_model.pt
+[RANK 0] 2025-12-17 21:17:06,233 [INFO] LyCORIS weights have been saved to disk
+[RANK 0] 2025-12-17 21:17:06,721 [INFO] Checkpoint path: /root/output/FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-24500
+[RANK 0] 2025-12-17 21:17:06,725 [INFO] - Repeats: 10
+- Total number of images: ~2152
+- Total number of aspect buckets: 1
+- Resolution: 1.048576 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+
+[RANK 0] 2025-12-17 21:17:06,971 [WARNING] No files have been modified since last commit. Skipping to prevent empty commit.
+  ...00/pytorch_lora_weights.safetensors: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB            
+Checking for EMA path: transformer_ema
+Found EMA checkpoint!
+Processing Files (1 / 1)                : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB, 55.6MB/s  
+New Data Upload                         : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  443MB /  443MB, 55.4MB/s  
+  ...-24500/transformer_ema/ema_model.pt: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB            
+Checking for EMA path: unet_ema
+Checking for EMA path: controlnet_ema
+Checking for EMA path: ema
+Found EMA checkpoint!
+Processing Files (1 / 1)                : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB,  106MB/s  
+New Data Upload                         : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 27.3MB / 27.3MB, 7.58MB/s  
+  ...int-24500/ema/ema_model.safetensors: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB            
+Processing Files (1 / 1)                : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB, 57.0MB/s  
+[RANK 0] 2025-12-17 21:17:51,290 [INFO] [Rank 0] Processing 8 local validation work items (distributed_mode=False, total=8, work_item_prompts=['DLAY man in a professional studio portrait with soft lighting, high quality photography, sharp focus', 'DLAY man standing outdoors in natural sunlight, casual pose, candid photography style', 'DLAY man in a formal business suit, professional headshot, corporate photography', 'DLAY man in an artistic portrait with dramatic lighting and shadows, fine art photography', 'DLAY man in a cinematic composition, film grain, moody atmosphere, dramatic lighting', 'DLAY man in dynamic action pose, sports photography style, sharp motion capture', 'DLAY man walking through a busy city street, urban photography, street style', 'close up portrait of DLAY man, detailed face, professional lighting, 85mm lens'])
+New Data Upload                         : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB, 57.0MB/s  
+
+
+[RANK 0] 2025-12-17 21:40:44,738 [INFO] Saving EMA model to /root/output/FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-25000/transformer_ema/ema_model.pt
+[RANK 0] 2025-12-17 21:40:44,950 [INFO] EMA model state saved to /root/output/FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-25000/transformer_ema/ema_model.pt
+[RANK 0] 2025-12-17 21:40:45,855 [INFO] LyCORIS weights have been saved to disk
+[RANK 0] 2025-12-17 21:40:46,307 [INFO] Checkpoint path: /root/output/FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/checkpoint-25000
+[RANK 0] 2025-12-17 21:40:46,311 [INFO] - Repeats: 10
+- Total number of images: ~2152
+- Total number of aspect buckets: 1
+- Resolution: 1.048576 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+
+[RANK 0] 2025-12-17 21:40:46,664 [WARNING] No files have been modified since last commit. Skipping to prevent empty commit.
+  ...00/pytorch_lora_weights.safetensors: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB            
+Checking for EMA path: transformer_ema
+Found EMA checkpoint!
+Processing Files (1 / 1)                : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB, 79.4MB/s  
+New Data Upload                         : 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████��██████████████████████████████████████████████████|  443MB /  443MB, 79.2MB/s  
+  ...-25000/transformer_ema/ema_model.pt: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB            
+Checking for EMA path: unet_ema
+Checking for EMA path: controlnet_ema
+Checking for EMA path: ema
+Found EMA checkpoint!
+Processing Files (1 / 1)                : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB,  112MB/s  
+New Data Upload                         : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 30.3MB / 30.3MB, 8.90MB/s  
+  ...int-25000/ema/ema_model.safetensors: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB            
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+[RANK 0] 2025-12-17 21:41:16,667 [INFO] [Rank 0] Processing 8 local validation work items (distributed_mode=False, total=8, work_item_prompts=['DLAY man in a professional studio portrait with soft lighting, high quality photography, sharp focus', 'DLAY man standing outdoors in natural sunlight, casual pose, candid photography style', 'DLAY man in a formal business suit, professional headshot, corporate photography', 'DLAY man in an artistic portrait with dramatic lighting and shadows, fine art photography', 'DLAY man in a cinematic composition, film grain, moody atmosphere, dramatic lighting', 'DLAY man in dynamic action pose, sports photography style, sharp motion capture', 'DLAY man walking through a busy city street, urban photography, street style', 'close up portrait of DLAY man, detailed face, professional lighting, 85mm lens'])
+New Data Upload                         : 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████��████████████████████| 24.4MB / 24.4MB, 9.39MB/s  
+[RANK 0] 2025-12-17 21:45:01,554 [INFO] - Repeats: 10
+- Total number of images: ~2152
+- Total number of aspect buckets: 1
+- Resolution: 1.048576 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+- Used for regularisation data: No
+
+  ...digy-V2-dynamo/assets/image_0_0.png: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2.50MB / 2.50MB            
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+  ...digy-V2-dynamo/assets/image_2_0.png: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2.53MB / 2.53MB            
+  ...digy-V2-dynamo/assets/image_3_0.png: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2.70MB / 2.70MB            
+  ...digy-V2-dynamo/assets/image_4_0.png: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4.04MB / 4.04MB            
+  ...digy-V2-dynamo/assets/image_5_0.png: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3.34MB / 3.34MB            
+  ...digy-V2-dynamo/assets/image_6_0.png: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3.01MB / 3.01MB            
+  ...digy-V2-dynamo/assets/image_7_0.png: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3.26MB / 3.26MB            
+Processing Files (1 / 1)                : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB, 61.7MB/s  
+New Data Upload                         : 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  429MB /  429MB, 59.6MB/s  
+  ...mo/pytorch_lora_weights.safetensors: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████|  444MB /  444MB            
+Checking for EMA path: transformer_ema
+Checking for EMA path: unet_ema
+Checking for EMA path: controlnet_ema
+Checking for EMA path: ema

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wandb/run-20251217_155825-6c9f2fa0804028c23c550af7a5c7aeb4/logs/debug.log

@@ -34,3 +34,8 @@ config: {'_wandb': {}}
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'pipeline_quantization_base': False, 'flow_matching': True, 'enable_adamw_bf16': True, 'overrode_max_train_steps': False, 'total_num_batches': 2959, 'num_update_steps_per_epoch': 2959, 'total_batch_size': 8, 'is_schedulefree': True, 'is_lr_scheduler_disabled': False, 'total_steps_remaining_at_start': 7500}
 2025-12-17 16:02:42,834 INFO    MainThread:476545 [logging.py:_log():419] config_cb ('_wandb', 'visualize', 'timesteps_scatter') {'panel_type': 'Vega2', 'panel_config': {'panelDefId': 'wandb/scatter/v0', 'fieldSettings': {'x': 'global_step', 'y': 'timestep'}, 'stringSettings': {'title': 'Timestep distribution by step'}, 'transform': {'name': 'tableWithLeafColNames'}, 'userQuery': {'queryFields': [{'name': 'runSets', 'args': [{'name': 'runSets', 'value': '${runSets}'}], 'fields': [{'name': 'id', 'fields': []}, {'name': 'name', 'fields': []}, {'name': '_defaultColorIndex', 'fields': []}, {'name': 'summaryTable', 'args': [{'name': 'tableKey', 'value': 'timesteps_scatter_table'}], 'fields': []}]}]}}} None
 2025-12-17 16:02:45,176 INFO    MainThread:476545 [logging.py:_log():419] config_cb ('_wandb', 'visualize', 'timesteps_scatter') {'panel_type': 'Vega2', 'panel_config': {'panelDefId': 'wandb/scatter/v0', 'fieldSettings': {'x': 'global_step', 'y': 'timestep'}, 'stringSettings': {'title': 'Timestep distribution by step'}, 'transform': {'name': 'tableWithLeafColNames'}, 'userQuery': {'queryFields': [{'name': 'runSets', 'args': [{'name': 'runSets', 'value': '${runSets}'}], 'fields': [{'name': 'id', 'fields': []}, {'name': 'name', 'fields': []}, {'name': '_defaultColorIndex', 'fields': []}, {'name': 'summaryTable', 'args': [{'name': 'tableKey', 'value': 'timesteps_scatter_table'}], 'fields': []}]}]}}} None
+2025-12-17 21:45:22,904 INFO    MainThread:476545 [logging.py:_log():419] finishing run thatdustyguy-personal/FLUX.2-DEV-DLAY-Persona/6c9f2fa0804028c23c550af7a5c7aeb4
+2025-12-17 21:45:22,906 INFO    MainThread:476545 [logging.py:_log():419] got exitcode: 0
+2025-12-17 21:45:22,907 INFO    MainThread:476545 [logging.py:_log():419] restore
+2025-12-17 21:45:22,907 INFO    MainThread:476545 [logging.py:_log():419] restore done
+2025-12-17 21:45:24,499 INFO    MainThread:476545 [logging.py:_log():419] logging synced files
+2025-12-17 21:45:28,308 INFO    wandb-AsyncioManager-main:476545 [logging.py:_log():419] Reached EOF.
+2025-12-17 21:45:28,310 INFO    wandb-AsyncioManager-main:476545 [logging.py:_log():419] Closing mailbox, abandoning 1 handles.

wandb/run-20251217_155828-6c9f2fa0804028c23c550af7a5c7aeb4/logs/debug.log

@@ -7,3 +7,10 @@ config: {'_wandb': {}}
 2025-12-17 15:58:28,199 INFO    MainThread:476545 [logging.py:_log():419] config_cb None None {'model_family': 'flux2', 'model_flavour': 'dev', 'controlnet': False, 'pretrained_model_name_or_path': 'black-forest-labs/FLUX.2-dev', 'output_dir': '/root/output/FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo', 'logging_dir': '/root/output/FLUX.2-DEV-DLAY-Persona-8xB300-prodigy-V2-dynamo/logs', 'model_type': 'lora', 'seed': 42, 'resolution': 1024, 'resume_from_checkpoint': 'checkpoint-17500', 'prediction_type': None, 'pretrained_vae_model_name_or_path': 'black-forest-labs/FLUX.2-dev', 'vae_dtype': 'bf16', 'vae_cache_ondemand': False, 'vae_cache_disable': False, 'accelerator_cache_clear_interval': None, 'aspect_bucket_rounding': 2, 'base_model_precision': 'no_change', 'text_encoder_1_precision': 'no_change', 'text_encoder_2_precision': 'no_change', 'text_encoder_3_precision': 'no_change', 'text_encoder_4_precision': 'no_change', 'gradient_checkpointing_interval': None, 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'validation_adapter_path': None, 'validation_adapter_name': None, 'validation_adapter_strength': 1.0, 'validation_adapter_mode': 'adapter_only', 'validation_adapter_config': None, 'i_know_what_i_am_doing': False, 'diff2flow_enabled': False, 'diff2flow_loss': False, 'scheduled_sampling_max_step_offset': 0, 'scheduled_sampling_strategy': 'uniform', 'scheduled_sampling_probability': 0.0, 'scheduled_sampling_prob_start': 0.0, 'scheduled_sampling_prob_end': 0.5, 'scheduled_sampling_ramp_steps': 0, 'scheduled_sampling_start_step': 0, 'scheduled_sampling_ramp_shape': 'linear', 'scheduled_sampling_sampler': 'unipc', 'scheduled_sampling_order': 2, 'scheduled_sampling_reflexflow': None, 'scheduled_sampling_reflexflow_alpha': 1.0, 'scheduled_sampling_reflexflow_beta1': 10.0, 'scheduled_sampling_reflexflow_beta2': 1.0, 'flow_sigmoid_scale': 1.0, 'flux_fast_schedule': False, 'flow_use_uniform_schedule': False, 'flow_use_beta_schedule': False, 'flow_beta_schedule_alpha': 2.0, 'flow_beta_schedule_beta': 2.0, 'flow_schedule_shift': 3.0, 'flow_schedule_auto_shift': False, 'flow_custom_timesteps': None, 'flux_guidance_mode': 'constant', 'flux_attention_masked_training': False, 'flux_guidance_value': 1.0, 'flux_guidance_min': 0.0, 'flux_guidance_max': 4.0, 't5_padding': 'unmodified', 'sd3_clip_uncond_behaviour': 'empty_string', 'sd3_t5_uncond_behaviour': None, 'soft_min_snr_sigma_data': None, 'mixed_precision': 'bf16', 'attention_mechanism': 'flash-attn', 'sla_config': None, 'sageattention_usage': 'INFERENCE', 'disable_tf32': True, 'set_grads_to_none': False, 'noise_offset': 0.1, 'noise_offset_probability': 0.25, 'input_perturbation': 0.0, 'input_perturbation_steps': 0, 'lr_end': 4e-07, 'lr_scale': False, 'lr_scale_sqrt': False, 'ignore_final_epochs': False, 'freeze_encoder_before': 12, 'freeze_encoder_after': 17, 'freeze_encoder_strategy': 'after', 'layer_freeze_strategy': None, 'fully_unload_text_encoder': False, 'save_text_encoder': False, 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False, 'debug_dataset_loader': False, 'print_filenames': False, 'print_sampler_statistics': False, 'timestep_bias_strategy': None, 'timestep_bias_begin': 0, 'timestep_bias_end': 1000, 'timestep_bias_multiplier': 1.0, 'timestep_bias_portion': 0.25, 'training_scheduler_timestep_spacing': 'trailing', 'inference_scheduler_timestep_spacing': 'trailing', 'loss_type': 'l2', 'huber_schedule': 'snr', 'huber_c': 0.1, 'snr_gamma': 5, 'masked_loss_probability': 1.0, 'hidream_use_load_balancing_loss': False, 'hidream_load_balancing_loss_weight': None, 'crepa_enabled': False, 'crepa_block_index': 8, 'crepa_lambda': 0.5, 'crepa_adjacent_distance': 1, 'crepa_adjacent_tau': 1.0, 'crepa_encoder': 'dinov2_vitg14', 'crepa_encoder_image_size': 518, 'crepa_drop_vae_encoder': False, 'crepa_normalize_by_frames': True, 'crepa_spatial_align': True, 'twinflow_enabled': False, 'twinflow_target_step_count': 1, 'adam_beta1': 0.9, 'adam_beta2': 0.999, 'optimizer_beta1': None, 'optimizer_beta2': None, 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'pipeline_quantization_base': False, 'flow_matching': True, 'enable_adamw_bf16': True, 'overrode_max_train_steps': False, 'total_num_batches': 2959, 'num_update_steps_per_epoch': 2959, 'total_batch_size': 8, 'is_schedulefree': True, 'is_lr_scheduler_disabled': False, 'total_steps_remaining_at_start': 7500}
 2025-12-17 16:02:42,834 INFO    MainThread:476545 [logging.py:_log():419] config_cb ('_wandb', 'visualize', 'timesteps_scatter') {'panel_type': 'Vega2', 'panel_config': {'panelDefId': 'wandb/scatter/v0', 'fieldSettings': {'x': 'global_step', 'y': 'timestep'}, 'stringSettings': {'title': 'Timestep distribution by step'}, 'transform': {'name': 'tableWithLeafColNames'}, 'userQuery': {'queryFields': [{'name': 'runSets', 'args': [{'name': 'runSets', 'value': '${runSets}'}], 'fields': [{'name': 'id', 'fields': []}, {'name': 'name', 'fields': []}, {'name': '_defaultColorIndex', 'fields': []}, {'name': 'summaryTable', 'args': [{'name': 'tableKey', 'value': 'timesteps_scatter_table'}], 'fields': []}]}]}}} None
 2025-12-17 16:02:45,176 INFO    MainThread:476545 [logging.py:_log():419] config_cb ('_wandb', 'visualize', 'timesteps_scatter') {'panel_type': 'Vega2', 'panel_config': {'panelDefId': 'wandb/scatter/v0', 'fieldSettings': {'x': 'global_step', 'y': 'timestep'}, 'stringSettings': {'title': 'Timestep distribution by step'}, 'transform': {'name': 'tableWithLeafColNames'}, 'userQuery': {'queryFields': [{'name': 'runSets', 'args': [{'name': 'runSets', 'value': '${runSets}'}], 'fields': [{'name': 'id', 'fields': []}, {'name': 'name', 'fields': []}, {'name': '_defaultColorIndex', 'fields': []}, {'name': 'summaryTable', 'args': [{'name': 'tableKey', 'value': 'timesteps_scatter_table'}], 'fields': []}]}]}}} None
+2025-12-17 21:45:22,904 INFO    MainThread:476545 [logging.py:_log():419] finishing run thatdustyguy-personal/FLUX.2-DEV-DLAY-Persona/6c9f2fa0804028c23c550af7a5c7aeb4
+2025-12-17 21:45:22,906 INFO    MainThread:476545 [logging.py:_log():419] got exitcode: 0
+2025-12-17 21:45:22,907 INFO    MainThread:476545 [logging.py:_log():419] restore
+2025-12-17 21:45:22,907 INFO    MainThread:476545 [logging.py:_log():419] restore done
+2025-12-17 21:45:24,499 INFO    MainThread:476545 [logging.py:_log():419] logging synced files
+2025-12-17 21:45:28,308 INFO    wandb-AsyncioManager-main:476545 [logging.py:_log():419] Reached EOF.
+2025-12-17 21:45:28,310 INFO    wandb-AsyncioManager-main:476545 [logging.py:_log():419] Closing mailbox, abandoning 1 handles.