My agent needs to set an action based on a position which can be represented as a integer value (e.g. np.int32). This integer value will then be used for indexing the certain array. Furthermore, a float number will be assigned to this position. Therefore I would like to specify the action by a list of tuples where the first element for each tuple has an integer dtype and the second element a float dtype. I tried to use a numpy structured array:
self._action_spec = array_spec.ArraySpec(
shape=(highestCoinIndex,2), dtype=[('id', np.int32), ('value', np.float64)], name='action')
This seems not to work because I get the following error:
TypeError: Cannot convert the argument `type_value`: dtype([('id', '<i4'), ('value', '<f8')]) to a TensorFlow DType.
In call to configurable 'BoundedArraySpec' (<class 'tf_agents.specs.array_spec.BoundedArraySpec'>)
Is there a way how I can specify a list or tuple with different dtypes for e.g. self._action_spec?