from __future__ import annotations
from daft.las.functions.image.image_resample import ImageResample
from daft.las.functions.udf import las_udf
if __name__ == "__main__":
if os.getenv("DAFT_RUNNER", "native") == "ray":
def configure_logging():
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
datefmt="%Y-%m-%d %H:%M:%S.%s".format(),
logging.getLogger("tracing.span").setLevel(logging.WARNING)
logging.getLogger("daft_io.stats").setLevel(logging.WARNING)
logging.getLogger("DaftStatisticsManager").setLevel(logging.WARNING)
logging.getLogger("DaftFlotillaScheduler").setLevel(logging.WARNING)
logging.getLogger("DaftFlotillaDispatcher").setLevel(logging.WARNING)
ray.init(dashboard_host="0.0.0.0", runtime_env={"worker_process_setup_hook": configure_logging})
daft.set_execution_config(actor_udf_ready_timeout=600)
daft.set_execution_config(min_cpu_per_task=0)
tos_dir_url = os.getenv("TOS_DIR_URL", "las-cn-beijing-public-online.tos-cn-beijing.volces.com")
f"https://{tos_dir_url}/public/shared_image_dataset/cat_ip_adapter.jpeg"
"image_name": ["cat_ip_adapter"],
image_src_type = "image_url"
target_size = (200, 200)
ds = daft.from_pydict(samples)
"image_suffix": image_suffix,
"image_src_type": image_src_type,
"target_size": target_size,
"target_dpi": target_dpi,
)(col("image"), col("image_name")),