Source code for rlgraph.components.common.dict_merger

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# Licensed under the Apache License, Version 2.0 (the "License");
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#     http://www.apache.org/licenses/LICENSE-2.0
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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import re

from rlgraph.components import Component
from rlgraph.utils.decorators import rlgraph_api
from rlgraph.utils.ops import DataOpDict


[docs]class DictMerger(Component): """ Merges incoming items into one FlattenedDataOp. API: merge(*inputs) -> DataOpDict with keys=`self.input_names` and values=inputs """ def __init__(self, *input_names, **kwargs): """ Args: *input_names (str): List of the names of the different inputs in the order they will be passed into the `merge` API-method in the returned merged Dict. Example: input_names = ["A", "B"] - merge(Dict(c=1, d=2), Tuple(3, 4)) - returned value: Dict(A=Dict(c=1, d=2), B=Tuple(3, 4)) """ super(DictMerger, self).__init__(scope=kwargs.pop("scope", "dict-merger"), **kwargs) assert all(isinstance(i, str) and not re.search(r'/', i) for i in input_names), \ "ERROR: Not all input names of DictMerger Component '{}' are strings or some of them have '/' characters in " \ "them, which are not allowed.".format(self.global_scope) self.input_names = input_names
[docs] def check_input_spaces(self, input_spaces, action_space=None): spaces = list() idx = 0 while True: key = "inputs[{}]".format(idx) if key not in input_spaces: break spaces.append(input_spaces[key]) idx += 1
#assert len(spaces) == len(self.input_names),\ # "ERROR: Number of incoming Spaces ({}) does not match number of given `input_names` in DictMerger Component " \ # "'{}'!".format(len(spaces), len(self.input_names), self.global_scope) # #for space in spaces: # # assert not isinstance(space, ContainerSpace),\ # # "ERROR: Single Space ({}) going into merger '{}' must not be a Container " \ # # "Space!".format(space, self.global_scope) @rlgraph_api def _graph_fn_merge(self, *inputs): """ Merges the inputs into a single FlattenedDataOp with the flat keys given in input_names. Args: *inputs (FlattenedDataOp): The input items to be merged into a FlattenedDataOp. Returns: FlattenedDataOp: The FlattenedDataOp as a merger of all api_methods. """ ret = DataOpDict() for i, op in enumerate(inputs): ret[self.input_names[i]] = op return ret