Add tiny Wan debug pipeline

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer/tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: apache-2.0
+library_name: diffusers
+pipeline_tag: text-to-video
+tags:
+- diffusers
+- wan
+- tiny-random
+- debug
+---
+
+# Tiny Wan2.2 T2V A14B Debug Pipeline
+
+This is a randomly initialized, tiny Diffusers `WanPipeline` fixture for `Wan-AI/Wan2.2-T2V-A14B`.
+Wan2.2 T2V-A14B high/low-noise expert layout represented as a Diffusers WanPipeline with `transformer` and `transformer_2`.
+
+It is intended for fast load-path and inference-control debugging only. It is not trained and should
+not be used for generation quality evaluation.
+
+```python
+from diffusers import WanPipeline
+
+pipe = WanPipeline.from_pretrained("Erland/tiny-wan2.2-t2v-a14b-debug")
+pipe.set_progress_bar_config(disable=True)
+frames = pipe(
+    prompt="debug prompt",
+    height=64,
+    width=64,
+    num_frames=5,
+    num_inference_steps=1,
+    guidance_scale=1.0,
+    max_sequence_length=8,
+).frames[0]
+```

model_index.json

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+{
+  "_class_name": "WanPipeline",
+  "_diffusers_version": "0.37.1",
+  "boundary_ratio": 0.875,
+  "expand_timesteps": false,
+  "scheduler": [
+    "diffusers",
+    "FlowMatchEulerDiscreteScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "UMT5EncoderModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "T5Tokenizer"
+  ],
+  "transformer": [
+    "diffusers",
+    "WanTransformer3DModel"
+  ],
+  "transformer_2": [
+    "diffusers",
+    "WanTransformer3DModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKLWan"
+  ]
+}

scheduler/scheduler_config.json

@@ -0,0 +1,18 @@
+{
+  "_class_name": "FlowMatchEulerDiscreteScheduler",
+  "_diffusers_version": "0.37.1",
+  "base_image_seq_len": 256,
+  "base_shift": 0.5,
+  "invert_sigmas": false,
+  "max_image_seq_len": 4096,
+  "max_shift": 1.15,
+  "num_train_timesteps": 10,
+  "shift": 3.0,
+  "shift_terminal": null,
+  "stochastic_sampling": false,
+  "time_shift_type": "exponential",
+  "use_beta_sigmas": false,
+  "use_dynamic_shifting": false,
+  "use_exponential_sigmas": false,
+  "use_karras_sigmas": false
+}

text_encoder/config.json

@@ -0,0 +1,31 @@
+{
+  "architectures": [
+    "UMT5EncoderModel"
+  ],
+  "classifier_dropout": 0.0,
+  "d_ff": 64,
+  "d_kv": 16,
+  "d_model": 32,
+  "decoder_start_token_id": 0,
+  "dense_act_fn": "gelu_new",
+  "dropout_rate": 0.0,
+  "dtype": "float32",
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
+  "initializer_factor": 1.0,
+  "is_decoder": false,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "umt5",
+  "num_decoder_layers": 1,
+  "num_heads": 2,
+  "num_layers": 1,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.8.0",
+  "use_cache": true,
+  "vocab_size": 256300
+}

text_encoder/model.safetensors

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tokenizer/tokenizer.json

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tokenizer/tokenizer_config.json

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+}

transformer/config.json

@@ -0,0 +1,24 @@
+{
+  "_class_name": "WanTransformer3DModel",
+  "_diffusers_version": "0.37.1",
+  "added_kv_proj_dim": null,
+  "attention_head_dim": 16,
+  "cross_attn_norm": true,
+  "eps": 1e-06,
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+  "freq_dim": 32,
+  "image_dim": null,
+  "in_channels": 4,
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+  "num_layers": 1,
+  "out_channels": 4,
+  "patch_size": [
+    1,
+    2,
+    2
+  ],
+  "pos_embed_seq_len": null,
+  "qk_norm": "rms_norm_across_heads",
+  "rope_max_seq_len": 64,
+  "text_dim": 32
+}

transformer/diffusion_pytorch_model.safetensors

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transformer_2/config.json

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+{
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+  "_diffusers_version": "0.37.1",
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+  "text_dim": 32
+}

transformer_2/diffusion_pytorch_model.safetensors

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vae/config.json

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+{
+  "_class_name": "AutoencoderKLWan",
+  "_diffusers_version": "0.37.1",
+  "attn_scales": [],
+  "base_dim": 8,
+  "decoder_base_dim": 8,
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+  "scale_factor_temporal": 4,
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+  ],
+  "z_dim": 4
+}

vae/diffusion_pytorch_model.safetensors

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