{
  "_class_name": "UDiT",
  "name": "Ra",
  "format": "udm/v1",
  "step": 212000,
  "latent": {
    "channels": 32,
    "spatial_factor": 8,
    "mean": [
      -4.137261,
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      -1.435803,
      -2.187023,
      -4.161275,
      -1.58918,
      -2.527523,
      3.002302,
      2.793705,
      -2.091501,
      -2.632896,
      -3.59589,
      -3.069669,
      -4.568713,
      3.26668,
      -0.897648,
      2.072541,
      5.451158,
      1.747871,
      -2.113284,
      2.03444,
      -1.379274,
      0.66369,
      2.712183,
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      1.235881,
      -2.02777,
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      -2.454632,
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    "std": [
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      1.079687,
      0.957871,
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      1.102266,
      1.213605,
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      1.085991,
      1.093223,
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      1.010205,
      0.920466,
      1.044107,
      1.023179,
      0.992978,
      0.991627,
      1.073585,
      1.114629,
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      1.104078,
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    "source": "vae/ (Muinez/f8c32-ae)"
  },
  "text": {
    "encoder": "text_encoder/ (jhu-clsp/ettin-encoder-150m, 768-dim, 22 слоя)",
    "max_len": 192,
    "slices": [
      2,
      5,
      8,
      11,
      14,
      17,
      20
    ],
    "slice_blocks": 2,
    "trainable": "text_mixer.*"
  },
  "body": {
    "kind": "пирамидальный U: ширина растёт к низу",
    "levels": [
      {
        "level": 0,
        "tokens": "÷1",
        "width": 192,
        "blocks": "conv 6 enc / 4 dec + 1 self-attn на сторону",
        "text": "кросс-внимание в каждом conv-блоке и в self-attn"
      },
      {
        "level": 1,
        "tokens": "÷2",
        "width": 512,
        "blocks": "attn 4 enc / 3 dec",
        "text": "кросс-внимание"
      },
      {
        "level": 2,
        "tokens": "÷4",
        "width": 1024,
        "blocks": "attn 3 enc / 2 dec",
        "text": "кросс-внимание"
      },
      {
        "level": 3,
        "tokens": "÷8",
        "width": 1536,
        "blocks": "attn 2 (боттлнек)",
        "text": "кросс-внимание"
      }
    ],
    "skips": "аддитивные (SD-стиль): e0/e1/e2 прибавляются в декодере",
    "down": "mean-pool 2× + Linear",
    "up": "Linear + nearest 2×",
    "rope": "2D RoPE, base 100, фаза в латентных пикселях на каждом уровне",
    "parametrization": "x0 латента"
  },
  "tail": {
    "source": "декодер AE, 6 блоков @512, PixelShuffle ×3",
    "trained_as": "flow по пикселям, условие z0 + (ошибка тела).detach()",
    "sample_steps": 4
  },
  "params": {
    "body": 143.33,
    "text_mixer": 10.04,
    "tail": 23.87,
    "total": 177.24
  },
  "training": {
    "dataset": "LucasFang/FLUX-Reason-6M",
    "parts": "Aesthetics-Part01,Aesthetics-Part02,Imaginative,Text",
    "size": 256,
    "steps": 212000,
    "batch": 16,
    "accum": 1,
    "lr": 0.0001,
    "lr_tail": 3e-05,
    "drop_text": 0.1,
    "init": "tmp/flux2/ckpt/step_0192000.pt",
    "metrics": "FLUX-Reason Part01 on top of the 20k butterfly run; continued on Parts 01+02+Imaginative+Text from step 192000, mse_lat 0.244 (ema 0.245), low 0.026, high 0.57, mse_pix 0.019"
  },
  "storage_dtype": "float16"
}