Delete raven/onnx_runtime.py

raven/onnx_runtime.py

@@ -1,39 +0,0 @@
-from __future__ import annotations
-import numpy as np
-
-
-def open_session(path: str, prefer_directml: bool = True):
-    try:
-        import onnxruntime as ort
-    except Exception as exc:
-        raise RuntimeError("Install requirements-directml.txt (or onnxruntime) first") from exc
-
-    available = ort.get_available_providers()
-    providers = []
-    opts = ort.SessionOptions()
-    opts.graph_optimization_level = ort.GraphOptimizationLevel.ORT_ENABLE_ALL
-
-    if prefer_directml and "DmlExecutionProvider" in available:
-
-        opts.execution_mode = ort.ExecutionMode.ORT_SEQUENTIAL
-        opts.enable_mem_pattern = False
-        providers.append("DmlExecutionProvider")
-    else:
-
-        opts.intra_op_num_threads = 6
-        opts.inter_op_num_threads = 1
-        providers.append("CPUExecutionProvider")
-
-    if "CPUExecutionProvider" not in providers:
-        providers.append("CPUExecutionProvider")
-    return ort.InferenceSession(path, sess_options=opts, providers=providers)
-
-
-def run_foundation(session, image: np.ndarray) -> np.ndarray:
-    return session.run(["embedding"], {"image": np.asarray(image, np.float32)})[0]
-
-
-def run_fusion(session, inputs: dict):
-    feed = {k: np.asarray(v, np.float32) for k, v in inputs.items()}
-    o = session.run(None, feed)
-    return {"logit_mean": o[0], "logit_std": o[1], "branch_mean": o[2], "gates_mean": o[3]}