code: def _load(filename, tensors=None, prefix=""):
      with h5py.File(filename, "r") as f:
          if tensors is None:
              tensors = {}
          for k in f.keys():
              if isinstance(f[k], h5py._hl.dataset.Dataset):
                  key = k if not prefix else f"{prefix}_{k}"
                  tensors[key] = tf.convert_to_tensor(np.array(f[k]))
              else:
                  tensors.update(
                      _load(f[k], tensors, prefix=f"{prefix}_{k}")
                  )
          return tensors
  
file_path: safetensors/bindings/python/benches/test_tf.py
imports: import os
  import tempfile
  import h5py
  import numpy
  import tensorflow
  from safetensors.tensorflow import load_file, save_file
label_desc: Use image node_id 1 for calling a global function with example usage: _load(filename, tensors, prefix) and returns: tensors