add wan22 test

fastvideo/pipelines/stages/denoising.py

@@ -205,13 +205,13 @@ class DenoisingStage(PipelineStage):
 
         # (Wan2.2) Calculate timestep to switch from high noise expert to low noise expert
         if fastvideo_args.pipeline_config.dit_config.boundary_ratio is not None:
-            boundary_timestep = fastvideo_args.pipeline_config.dit_config.boundary_ratio
-            if batch.boundary_timestep is not None:
-                logger.info("Overriding boundary timestep from %s to %s",
-                            boundary_timestep, batch.boundary_timestep)
-                boundary_timestep = batch.boundary_timestep
+            boundary_ratio = fastvideo_args.pipeline_config.dit_config.boundary_ratio
+            if batch.boundary_ratio is not None:
+                logger.info("Overriding boundary ratio from %s to %s",
+                            boundary_ratio, batch.boundary_ratio)
+                boundary_ratio = batch.boundary_ratio
 
-            boundary_timestep *= self.scheduler.num_train_timesteps
+            boundary_timestep = boundary_ratio * self.scheduler.num_train_timesteps
         else:
             boundary_timestep = None
         latent_model_input = latents.to(target_dtype)

fastvideo/tests/ssim/test_inference_similarity.py

@@ -28,14 +28,14 @@ HUNYUAN_PARAMS = {
     "width": 1280,
     "num_frames": 45,
     "num_inference_steps": 6,
-    "guidance_scale": 1,
-    "embedded_cfg_scale": 6,
-    "flow_shift": 17,
+    # "guidance_scale": 1,
+    # "embedded_cfg_scale": 6,
+    # "flow_shift": 17,
     "seed": 1024,
     "sp_size": 2,
     "tp_size": 1,
-    "vae_sp": True,
-    "fps": 24,
+    # "vae_sp": True,
+    # "fps": 24,
 }
 
 WAN_T2V_PARAMS = {
@@ -45,14 +45,14 @@ WAN_T2V_PARAMS = {
     "width": 832,
     "num_frames": 45,
     "num_inference_steps": 20,
-    "guidance_scale": 3,
-    "embedded_cfg_scale": 6,
-    "flow_shift": 7.0,
+    # "guidance_scale": 3,
+    # "embedded_cfg_scale": 6,
+    # "flow_shift": 7.0,
     "seed": 1024,
     "sp_size": 2,
     "tp_size": 1,
-    "vae_sp": True,
-    "fps": 24,
+    # "vae_sp": True,
+    # "fps": 24,
     "neg_prompt": "Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards",
     "text-encoder-precision": ("fp32",)
 }
@@ -64,18 +64,33 @@ WAN_I2V_PARAMS = {
     "width": 832,
     "num_frames": 45,
     "num_inference_steps": 6,
-    "guidance_scale": 5.0,
-    "embedded_cfg_scale": 6,
-    "flow_shift": 7.0,
+    # "guidance_scale": 5.0,
+    # "embedded_cfg_scale": 6,
+    # "flow_shift": 7.0,
     "seed": 1024,
     "sp_size": 2,
     "tp_size": 1,
-    "vae_sp": True,
-    "fps": 24,
-    "neg_prompt": "Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards",
+    # "vae_sp": True,
+    # "fps": 24,
+    # "neg_prompt": "Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards",
     "text-encoder-precision": ("fp32",)
 }
 
+WAN2_2_I2V_PARAMS = {
+    "num_gpus": 2,
+    "model_path": "Wan-AI/Wan2.2-I2V-A14B-Diffusers",
+    "height": 480,
+    "width": 832,
+    "num_frames": 45,
+    "num_inference_steps": 20,
+    # "guidance_scale": 5.0,
+    # "embedded_cfg_scale": 6,
+    # "flow_shift": 7.0,
+    "seed": 1024,
+    "sp_size": 2,
+    "tp_size": 1,
+}
+
 MODEL_TO_PARAMS = {
     "FastHunyuan-diffusers": HUNYUAN_PARAMS,
     "Wan2.1-T2V-1.3B-Diffusers": WAN_T2V_PARAMS,
@@ -83,6 +98,7 @@ MODEL_TO_PARAMS = {
 
 I2V_MODEL_TO_PARAMS = {
     "Wan2.1-I2V-14B-480P-Diffusers": WAN_I2V_PARAMS,
+    "Wan2.2-I2V-A14B-Diffusers": WAN2_2_I2V_PARAMS,
 }
 
 TEST_PROMPTS = [
@@ -125,7 +141,6 @@ def test_i2v_inference_similarity(prompt, ATTENTION_BACKEND, model_id):
 
     init_kwargs = {
         "num_gpus": BASE_PARAMS["num_gpus"],
-        "flow_shift": BASE_PARAMS["flow_shift"],
         "sp_size": BASE_PARAMS["sp_size"],
         "tp_size": BASE_PARAMS["tp_size"],
     }
@@ -142,10 +157,7 @@ def test_i2v_inference_similarity(prompt, ATTENTION_BACKEND, model_id):
         "height": BASE_PARAMS["height"],
         "width": BASE_PARAMS["width"],
         "num_frames": BASE_PARAMS["num_frames"],
-        "guidance_scale": BASE_PARAMS["guidance_scale"],
-        "embedded_cfg_scale": BASE_PARAMS["embedded_cfg_scale"],
         "seed": BASE_PARAMS["seed"],
-        "fps": BASE_PARAMS["fps"],
     }
     if "neg_prompt" in BASE_PARAMS:
         generation_kwargs["neg_prompt"] = BASE_PARAMS["neg_prompt"]
@@ -225,7 +237,6 @@ def test_inference_similarity(prompt, ATTENTION_BACKEND, model_id):
 
     init_kwargs = {
         "num_gpus": BASE_PARAMS["num_gpus"],
-        "flow_shift": BASE_PARAMS["flow_shift"],
         "sp_size": BASE_PARAMS["sp_size"],
         "tp_size": BASE_PARAMS["tp_size"],
         "dit_cpu_offload": True,
@@ -242,10 +253,7 @@ def test_inference_similarity(prompt, ATTENTION_BACKEND, model_id):
         "height": BASE_PARAMS["height"],
         "width": BASE_PARAMS["width"],
         "num_frames": BASE_PARAMS["num_frames"],
-        "guidance_scale": BASE_PARAMS["guidance_scale"],
-        "embedded_cfg_scale": BASE_PARAMS["embedded_cfg_scale"],
         "seed": BASE_PARAMS["seed"],
-        "fps": BASE_PARAMS["fps"],
     }
     if "neg_prompt" in BASE_PARAMS:
         generation_kwargs["neg_prompt"] = BASE_PARAMS["neg_prompt"]