Revert "video gen working on apple silicon (addressed issues from prior pr) (…"

This reverts commit b79d1fc15b.

examples/inference/basic/basic_mps.py

@@ -1,40 +0,0 @@
-from fastvideo import VideoGenerator, PipelineConfig
-from fastvideo.v1.configs.sample import SamplingParam
-
-def main():
-    config = PipelineConfig.from_pretrained("Wan-AI/Wan2.1-T2V-1.3B-Diffusers")
-    config.text_encoder_precisions = ["fp16"]
-    
-    generator = VideoGenerator.from_pretrained(
-        "Wan-AI/Wan2.1-T2V-1.3B-Diffusers",
-        pipeline_config=config,
-        use_fsdp_inference=False,      # Disable FSDP for MPS
-        use_cpu_offload=True,          
-        text_encoder_offload=True,    
-        pin_cpu_memory=True,           
-        disable_autocast=False,        
-        num_gpus=1,      
-    )
-
-    # Create sampling parameters with reduced number of frames
-    sampling_param = SamplingParam.from_pretrained("Wan-AI/Wan2.1-T2V-1.3B-Diffusers")
-    sampling_param.num_frames = 3  # Reduce from default 81 to 25 frames bc we have to use the SDPA attn backend for mps
-    sampling_param.height = 256
-    sampling_param.width = 256
-
-    prompt = ("A curious raccoon peers through a vibrant field of yellow sunflowers, its eyes "
-             "wide with interest. The playful yet serene atmosphere is complemented by soft "
-             "natural light filtering through the petals. Mid-shot, warm and cheerful tones.")
-    
-    video = generator.generate_video(prompt, sampling_param=sampling_param)
-
-    prompt2 = ("A majestic lion strides across the golden savanna, its powerful frame "
-        "glistening under the warm afternoon sun. The tall grass ripples gently in "
-        "the breeze, enhancing the lion's commanding presence. The tone is vibrant, "
-        "embodying the raw energy of the wild. Low angle, steady tracking shot, "
-        "cinematic.")
-    
-    video2 = generator.generate_video(prompt2, sampling_param=sampling_param)
-
-if __name__ == "__main__":
-    main()

examples/inference/basic/test.py

@@ -1,39 +0,0 @@
-from fastvideo import VideoGenerator, PipelineConfig, SamplingParam
-
-# from fastvideo.v1.configs.sample import SamplingParam
-
-OUTPUT_PATH = "video_samples_fp16"
-def main():
-    # FastVideo will automatically use the optimal default arguments for the
-    # model.
-    # If a local path is provided, FastVideo will make a best effort
-    # attempt to identify the optimal arguments.
-    model = "Wan-AI/Wan2.1-T2V-1.3B-Diffusers"
-    pipeline_config = PipelineConfig.from_pretrained(model)
-    pipeline_config.text_encoder_precisions = ("bf16", )
-    generator = VideoGenerator.from_pretrained(
-        model,
-        # if num_gpus > 1, FastVideo will automatically handle distributed setup
-        pipeline_config=pipeline_config,
-        use_fsdp_inference=False,      # Disable FSDP for MPS
-        use_cpu_offload=True,          
-        text_encoder_offload=True,    
-        pin_cpu_memory=True,           
-        disable_autocast=False,        
-        num_gpus=1, 
-    )
-
-    sampling_param = SamplingParam.from_pretrained(model)
-    sampling_param.num_frames = 30
-    # sampling_param.image_path = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/astronaut.jpg"
-    # Generate videos with the same simple API, regardless of GPU count
-    prompt = "Will Smith casually eats noodles, his relaxed demeanor contrasting with the energetic background of a bustling street food market. The scene captures a mix of humor and authenticity. Mid-shot framing, vibrant lighting."
-    video = generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True, sampling_param=sampling_param)
-    # video = generator.generate_video(prompt, sampling_param=sampling_param, output_path="wan_t2v_videos/")
-
-    # Generate another video with a different prompt, without reloading the
-    # model!
-
-
-if __name__ == "__main__":
-    main()