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https://github.com/Farama-Foundation/Gymnasium.git
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remove MultiDiscrete adaptors
This commit is contained in:
John Schulman
@@ -1,8 +1,7 @@
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import numpy as np
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import gym
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from gym.spaces import prng, Discrete, Box
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from gym.error import Error
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from gym.spaces import prng
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class MultiDiscrete(gym.Space):
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"""
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@@ -46,167 +45,3 @@ class MultiDiscrete(gym.Space):
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return "MultiDiscrete" + str(self.num_discrete_space)
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def __eq__(self, other):
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return np.array_equal(self.low, other.low) and np.array_equal(self.high, other.high)
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# Adapters
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class DiscreteToMultiDiscrete(Discrete):
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"""
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Adapter that adapts the MultiDiscrete action space to a Discrete action space of any size
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The converted action can be retrieved by calling the adapter with the discrete action
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discrete_to_multi_discrete = DiscreteToMultiDiscrete(multi_discrete)
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discrete_action = discrete_to_multi_discrete.sample()
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multi_discrete_action = discrete_to_multi_discrete(discrete_action)
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It can be initialized using 3 configurations:
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Configuration 1) - DiscreteToMultiDiscrete(multi_discrete) [2nd param is empty]
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Would adapt to a Discrete action space of size (1 + nb of discrete in MultiDiscrete)
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where
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0 returns NOOP [ 0, 0, 0, ...]
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1 returns max for the first discrete space [max, 0, 0, ...]
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2 returns max for the second discrete space [ 0, max, 0, ...]
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etc.
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Configuration 2) - DiscreteToMultiDiscrete(multi_discrete, list_of_discrete) [2nd param is a list]
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Would adapt to a Discrete action space of size (1 + nb of items in list_of_discrete)
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e.g.
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if list_of_discrete = [0, 2]
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0 returns NOOP [ 0, 0, 0, ...]
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1 returns max for first discrete in list [max, 0, 0, ...]
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2 returns max for second discrete in list [ 0, 0, max, ...]
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etc.
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Configuration 3) - DiscreteToMultiDiscrete(multi_discrete, discrete_mapping) [2nd param is a dict]
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Would adapt to a Discrete action space of size (nb_keys in discrete_mapping)
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where discrete_mapping is a dictionnary in the format { discrete_key: multi_discrete_mapping }
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e.g. for the Nintendo Game Controller [ [0,4], [0,1], [0,1] ] a possible mapping might be;
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mapping = {
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0: [0, 0, 0], # NOOP
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1: [1, 0, 0], # Up
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2: [3, 0, 0], # Down
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3: [2, 0, 0], # Right
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4: [2, 1, 0], # Right + A
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5: [2, 0, 1], # Right + B
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6: [2, 1, 1], # Right + A + B
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7: [4, 0, 0], # Left
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8: [4, 1, 0], # Left + A
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9: [4, 0, 1], # Left + B
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10: [4, 1, 1], # Left + A + B
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11: [0, 1, 0], # A only
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12: [0, 0, 1], # B only,
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13: [0, 1, 1], # A + B
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}
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"""
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def __init__(self, multi_discrete, options=None):
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assert isinstance(multi_discrete, MultiDiscrete)
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self.multi_discrete = multi_discrete
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self.num_discrete_space = self.multi_discrete.num_discrete_space
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# Config 1
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if options is None:
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self.n = self.num_discrete_space + 1 # +1 for NOOP at beginning
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self.mapping = {i: [0] * self.num_discrete_space for i in range(self.n)}
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for i in range(self.num_discrete_space):
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self.mapping[i + 1][i] = self.multi_discrete.high[i]
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# Config 2
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elif isinstance(options, list):
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assert len(options) <= self.num_discrete_space
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self.n = len(options) + 1 # +1 for NOOP at beginning
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self.mapping = {i: [0] * self.num_discrete_space for i in range(self.n)}
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for i, disc_num in enumerate(options):
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assert disc_num < self.num_discrete_space
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self.mapping[i + 1][disc_num] = self.multi_discrete.high[disc_num]
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# Config 3
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elif isinstance(options, dict):
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self.n = len(options.keys())
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self.mapping = options
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for i, key in enumerate(options.keys()):
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if i != key:
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raise Error('DiscreteToMultiDiscrete must contain ordered keys. ' \
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'Item {0} should have a key of "{0}", but key "{1}" found instead.'.format(i, key))
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if not self.multi_discrete.contains(options[key]):
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raise Error('DiscreteToMultiDiscrete mapping for key {0} is ' \
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'not contained in the underlying MultiDiscrete action space. ' \
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'Invalid mapping: {1}'.format(key, options[key]))
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# Unknown parameter provided
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else:
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raise Error('DiscreteToMultiDiscrete - Invalid parameter provided.')
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def __call__(self, discrete_action):
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return self.mapping[discrete_action]
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class BoxToMultiDiscrete(Box):
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"""
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Adapter that adapts the MultiDiscrete action space to a Box action space
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The converted action can be retrieved by calling the adapter with the box action
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box_to_multi_discrete = BoxToMultiDiscrete(multi_discrete)
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box_action = box_to_multi_discrete.sample()
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multi_discrete_action = box_to_multi_discrete(box_action)
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It can be initialized using 2 configurations:
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Configuration 1) - BoxToMultiDiscrete(multi_discrete) [2nd param is empty]
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Would adapt to a Box action space of shape (nb of discrete space, ), with the min-max of
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each Discrete space sets as Box boundaries
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e.g. a MultiDiscrete with parameters [ [0,4], [0,1], [0,1] ], adapted through BoxToMultiDiscrete(multi_discrete)
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would adapt to a Box with parameters low=np.array([0.0, 0.0, 0.0]) high=np.array([4.0, 1.0, 1.0])
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The box action would then be rounded to the nearest integer.
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e.g. [ 2.560453, 0.3523456, 0.674546 ] would be converted to the multi discrete action of [3, 0, 1]
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Configuration 2) - BoxToMultiDiscrete(multi_discrete, list_of_discrete) [2nd param is a list]
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Would adapt to a Box action space of shape (nb of items in list_of_discrete, ), where list_of_discrete
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is the index of the discrete space in the MultiDiscrete space
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e.g. a MultiDiscrete with parameters [ [0,4], [0,1], [0,1] ], adapted through BoxToMultiDiscrete(multi_discrete, [2, 0])
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would adapt to a Box with parameters low=np.array([0.0, 0.0]) high=np.array([1.0, 4.0])
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where
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0.0 = min(discrete space #2), 1.0 = max(discrete space #2)
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0.0 = min(discrete space #0), 4.0 = max(discrete space #0)
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The box action would then be rounded to the nearest integer and mapped to the correct discrete space in multi-discrete.
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e.g. [ 0.7412057, 3.0174142 ] would be converted to the multi discrete action of [3, 0, 1]
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This configuration is useful if you want to ignore certain discrete spaces in the MultiDiscrete space.
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"""
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def __init__(self, multi_discrete, options=None):
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assert isinstance(multi_discrete, MultiDiscrete)
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self.multi_discrete = multi_discrete
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self.num_discrete_space = self.multi_discrete.num_discrete_space
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if options is None:
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options = list(range(self.num_discrete_space))
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if not isinstance(options, list):
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raise Error('BoxToMultiDiscrete - Invalid parameter provided.')
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assert len(options) <= self.num_discrete_space
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self.low = np.array([self.multi_discrete.low[x] for x in options])
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self.high = np.array([self.multi_discrete.high[x] for x in options])
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self.mapping = { i: disc_num for i, disc_num in enumerate(options)}
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def __call__(self, box_action):
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multi_discrete_action = [0] * self.num_discrete_space
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for i in self.mapping:
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multi_discrete_action[self.mapping[i]] = int(round(box_action[i], 0))
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return multi_discrete_action
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