[feat] Support text encoder weight override and quantization (#983)

examples/inference/optimizations/text_encoder_quant_example.py

@@ -0,0 +1,46 @@
+from fastvideo import VideoGenerator
+import argparse
+
+OUTPUT_PATH = "video_samples_wan2_2_5B_ti2v"
+
+
+def main(text_encoder_path: str):
+    # 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_name = "Wan-AI/Wan2.2-TI2V-5B-Diffusers"
+    generator = VideoGenerator.from_pretrained(
+        model_name,
+        # FastVideo will automatically handle distributed setup
+        num_gpus=1,
+        use_fsdp_inference=True,
+        dit_cpu_offload=True,
+        vae_cpu_offload=False,
+        text_encoder_cpu_offload=False,
+        # AbsMaxFP8 is the quantization method used by ComfyUI; 
+        # check fastvideo/layers/quantization/* for more quantization methods
+        override_text_encoder_quant="AbsMaxFP8",
+        # for Wan 2.2, this is the path to "umt5_xxl_fp8_e4m3fn_scaled.safetensors"
+        override_text_encoder_safetensors=text_encoder_path,
+        pin_cpu_memory=True,  # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument"
+    )
+
+    # I2V is triggered just by passing in an image_path argument
+    prompt = "Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression. Blurred beach scenery forms the background featuring crystal-clear waters, distant green hills, and a blue sky dotted with white clouds. The cat assumes a naturally relaxed posture, as if savoring the sea breeze and warm sunlight. A close-up shot highlights the feline's intricate details and the refreshing atmosphere of the seaside."
+    image_path = "https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG"
+    video = generator.generate_video(
+        prompt, output_path=OUTPUT_PATH, save_video=True, image_path=image_path
+    )
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--text_encoder_path",
+        type=str,
+        required=True,
+        help="Path to the quantized text encoder safetensors file.",
+    )
+    args = parser.parse_args()
+    main(args.text_encoder_path)