code: def fake_tensor_from_spec(
      tensor_specs: Union[tf.TensorSpec, Sequence[tf.TensorSpec]]
  ):
      """Fake `Tensor`(s) from `TensorSpec`(s)."""
      if isinstance(tensor_specs, tf.TensorSpec):
          shape = tensor_specs.shape
          dtype = tensor_specs.dtype
          shape = tuple(dim if dim is not None else 1 for dim in shape)
          if shape == () and dtype == tf.bool:
              # This may be the `training` parameter, we should assume it is False
              return False
          return tf.ones(shape=shape, dtype=dtype)
      else:
          return [fake_tensor_from_spec(spec) for spec in tensor_specs]
  
imports: import warnings
  from typing import Sequence, Union, Optional
  from bigdl.nano.utils.common import invalidInputError
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: fake_tensor_from_spec(tensor_specs) and returns: tf, unknown, False