code: def get_test_input_for_op(val, dtype):
      """Returns a list containing all the possible inputs with a given dtype.
  
      Args:
        val: value to convert to test input.
        dtype: a tuple of format (tf.Dtype, bool) where the bool value represents
          whether the dtype is "weak" or not.
  
      Returns:
        A list of all possible inputs given a value and a dtype.
      """
      python_inferred_types = {
          (dtypes.int32, True): 1,
          (dtypes.float32, True): 1.0,
          (dtypes.complex128, True): 1.0j,
      }
      dtype, weak = dtype
      inputs = []
      if weak:
          # WeakTensor and Python input types.
          inputs.append(convert_to_input_type(val, "WeakTensor", dtype))
          if dtype in python_inferred_types:
              # There are only 3 possible Python default types : int, float, complex.
              val_in_dtype = val * python_inferred_types[dtype]
              inputs.append(val_in_dtype)
              inputs.append(
                  convert_to_input_type(val_in_dtype, "Tensor", None)
              )
      else:
          # Tensor and NumPy input types.
          inputs.append(convert_to_input_type(val, "Tensor", dtype))
          inputs.append(convert_to_input_type(val, "NumPy", dtype))
      return inputs
  
file_path: tensorflow-upstream/tensorflow/python/ops/weak_tensor_test_util.py
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework.weak_tensor import WeakTensor
label_desc: Use image node_id 1 for calling a global function with example usage: get_test_input_for_op(val, dtype) and returns: inputs