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Remove ordereddict in favour of python dict (#977)

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This commit is contained in:
Mark Towers
2024-03-22 11:19:41 +00:00
committed by GitHub
parent a79e5d6e8a
commit 15d179087e
8 changed files with 54 additions and 81 deletions
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13
gymnasium/envs/mujoco/mujoco_rendering.py
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@@ -1,4 +1,3 @@
import collections
import os
import time
from typing import Dict, Optional
@@ -27,13 +26,11 @@ def _import_osmesa(width, height):
return GLContext(width, height)
_ALL_RENDERERS = collections.OrderedDict(
[
("glfw", _import_glfw),
("egl", _import_egl),
("osmesa", _import_osmesa),
]
)
_ALL_RENDERERS = {
"glfw": _import_glfw,
"egl": _import_egl,
"osmesa": _import_osmesa,
}
class BaseRender:

35
gymnasium/spaces/dict.py
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@@ -3,7 +3,6 @@ from __future__ import annotations
import collections.abc
import typing
from collections import OrderedDict
from typing import Any, KeysView, Sequence
import numpy as np
@@ -20,7 +19,7 @@ class Dict(Space[typing.Dict[str, Any]], typing.Mapping[str, Space[Any]]):
>>> from gymnasium.spaces import Dict, Box, Discrete
>>> observation_space = Dict({"position": Box(-1, 1, shape=(2,)), "color": Discrete(3)}, seed=42)
>>> observation_space.sample()
OrderedDict([('color', 0), ('position', array([-0.3991573 , 0.21649833], dtype=float32))])
{'color': 0, 'position': array([-0.3991573 , 0.21649833], dtype=float32)}
With a nested dict:
@@ -67,23 +66,23 @@ class Dict(Space[typing.Dict[str, Any]], typing.Mapping[str, Space[Any]]):
**spaces_kwargs: If ``spaces`` is ``None``, you need to pass the constituent spaces as keyword arguments, as described above.
"""
# Convert the spaces into an OrderedDict
if isinstance(spaces, collections.abc.Mapping) and not isinstance(
spaces, OrderedDict
):
if isinstance(spaces, collections.abc.Mapping):
# for legacy reasons, we need to preserve the sorted dictionary items.
# as this could matter for projects flatten the dictionary.
try:
spaces = OrderedDict(sorted(spaces.items()))
spaces = dict(sorted(spaces.items()))
except TypeError:
# Incomparable types (e.g. `int` vs. `str`, or user-defined types) found.
# The keys remain in the insertion order.
spaces = OrderedDict(spaces.items())
spaces = dict(spaces.items())
elif isinstance(spaces, Sequence):
spaces = OrderedDict(spaces)
spaces = dict(spaces)
elif spaces is None:
spaces = OrderedDict()
spaces = dict()
else:
assert isinstance(
spaces, OrderedDict
), f"Unexpected Dict space input, expecting dict, OrderedDict or Sequence, actual type: {type(spaces)}"
raise TypeError(
f"Unexpected Dict space input, expecting dict, OrderedDict or Sequence, actual type: {type(spaces)}"
)
# Add kwargs to spaces to allow both dictionary and keywords to be used
for key, space in spaces_kwargs.items():
@@ -164,11 +163,9 @@ class Dict(Space[typing.Dict[str, Any]], typing.Mapping[str, Space[Any]]):
assert (
mask.keys() == self.spaces.keys()
), f"Expect mask keys to be same as space keys, mask keys: {mask.keys()}, space keys: {self.spaces.keys()}"
return OrderedDict(
[(k, space.sample(mask[k])) for k, space in self.spaces.items()]
)
return {k: space.sample(mask=mask[k]) for k, space in self.spaces.items()}
return OrderedDict([(k, space.sample()) for k, space in self.spaces.items()])
return {k: space.sample() for k, space in self.spaces.items()}
def contains(self, x: Any) -> bool:
"""Return boolean specifying if x is a valid member of this space."""
@@ -221,9 +218,7 @@ class Dict(Space[typing.Dict[str, Any]], typing.Mapping[str, Space[Any]]):
for key, space in self.spaces.items()
}
def from_jsonable(
self, sample_n: dict[str, list[Any]]
) -> list[OrderedDict[str, Any]]:
def from_jsonable(self, sample_n: dict[str, list[Any]]) -> list[dict[str, Any]]:
"""Convert a JSONable data type to a batch of samples from this space."""
dict_of_list: dict[str, list[Any]] = {
key: space.from_jsonable(sample_n[key])
@@ -232,7 +227,7 @@ class Dict(Space[typing.Dict[str, Any]], typing.Mapping[str, Space[Any]]):
n_elements = len(next(iter(dict_of_list.values())))
result = [
OrderedDict({key: value[n] for key, value in dict_of_list.items()})
{key: value[n] for key, value in dict_of_list.items()}
for n in range(n_elements)
]
return result

18
gymnasium/spaces/utils.py
View File

@@ -7,7 +7,6 @@ from __future__ import annotations
import operator as op
import typing
from collections import OrderedDict
from functools import reduce, singledispatch
from typing import Any, TypeVar, Union, cast
@@ -201,7 +200,7 @@ def _flatten_dict(space: Dict, x: dict[str, Any]) -> dict[str, Any] | NDArray[An
return np.concatenate(
[np.array(flatten(s, x[key])) for key, s in space.spaces.items()]
)
return OrderedDict((key, flatten(s, x[key])) for key, s in space.spaces.items())
return {key: flatten(s, x[key]) for key, s in space.spaces.items()}
@flatten.register(Graph)
@@ -361,16 +360,15 @@ def _unflatten_dict(space: Dict, x: NDArray[Any] | dict[str, Any]) -> dict[str,
if space.is_np_flattenable:
dims = np.asarray([flatdim(s) for s in space.spaces.values()], dtype=np.int_)
list_flattened = np.split(x, np.cumsum(dims[:-1]))
return OrderedDict(
[
(key, unflatten(s, flattened))
return {
key: unflatten(s, flattened)
for flattened, (key, s) in zip(list_flattened, space.spaces.items())
]
)
}
assert isinstance(
x, dict
), f"{space} is not numpy-flattenable. Thus, you should only unflatten dictionary for this space. Got a {type(x)}"
return OrderedDict((key, unflatten(s, x[key])) for key, s in space.spaces.items())
return {key: unflatten(s, x[key]) for key, s in space.spaces.items()}
@unflatten.register(Graph)
@@ -532,9 +530,7 @@ def _flatten_space_dict(space: Dict) -> Box | Dict:
dtype=np.result_type(*[s.dtype for s in space_list]),
)
return Dict(
spaces=OrderedDict(
(key, flatten_space(space)) for key, space in space.spaces.items()
)
spaces={key: flatten_space(space) for key, space in space.spaces.items()}
)

20
gymnasium/vector/utils/shared_memory.py
View File

@@ -2,7 +2,6 @@
from __future__ import annotations
import multiprocessing as mp
from collections import OrderedDict
from ctypes import c_bool
from functools import singledispatch
from typing import Any
@@ -81,12 +80,10 @@ def _create_tuple_shared_memory(space: Tuple, n: int = 1, ctx=mp):
@create_shared_memory.register(Dict)
def _create_dict_shared_memory(space: Dict, n: int = 1, ctx=mp):
return OrderedDict(
[
(key, create_shared_memory(subspace, n=n, ctx=ctx))
return {
key: create_shared_memory(subspace, n=n, ctx=ctx)
for (key, subspace) in space.spaces.items()
]
)
}
@create_shared_memory.register(Text)
@@ -163,15 +160,12 @@ def _read_tuple_from_shared_memory(space: Tuple, shared_memory, n: int = 1):
@read_from_shared_memory.register(Dict)
def _read_dict_from_shared_memory(space: Dict, shared_memory, n: int = 1):
subspace_samples = OrderedDict(
[
(key, read_from_shared_memory(subspace, shared_memory[key], n=n))
subspace_samples = {
key: read_from_shared_memory(subspace, shared_memory[key], n=n)
for (key, subspace) in space.spaces.items()
]
)
}
return tuple(
OrderedDict({key: subspace_samples[key][i] for key in space.keys()})
for i in range(n)
{key: subspace_samples[key][i] for key in space.keys()} for i in range(n)
)

24
gymnasium/vector/utils/space_utils.py
View File

@@ -7,7 +7,6 @@
"""
from __future__ import annotations
from collections import OrderedDict
from copy import deepcopy
from functools import singledispatch
from typing import Any, Iterable, Iterator
@@ -163,9 +162,9 @@ def iterate(space: Space[T_cov], items: Iterable[T_cov]) -> Iterator:
>>> items = space.sample()
>>> it = iterate(space, items)
>>> next(it)
OrderedDict([('position', array([0.77395606, 0.43887845, 0.85859793], dtype=float32)), ('velocity', array([0.77395606, 0.43887845], dtype=float32))])
{'position': array([0.77395606, 0.43887845, 0.85859793], dtype=float32), 'velocity': array([0.77395606, 0.43887845], dtype=float32)}
>>> next(it)
OrderedDict([('position', array([0.697368 , 0.09417735, 0.97562236], dtype=float32)), ('velocity', array([0.85859793, 0.697368 ], dtype=float32))])
{'position': array([0.697368 , 0.09417735, 0.97562236], dtype=float32), 'velocity': array([0.85859793, 0.697368 ], dtype=float32)}
>>> next(it)
Traceback (most recent call last):
...
@@ -226,7 +225,7 @@ def _iterate_dict(space: Dict, items: dict[str, Any]):
]
)
for item in zip(*values):
yield OrderedDict({key: value for key, value in zip(keys, item)})
yield {key: value for key, value in zip(keys, item)}
@singledispatch
@@ -287,12 +286,10 @@ def _concatenate_tuple(
def _concatenate_dict(
space: Dict, items: Iterable, out: dict[str, Any]
) -> dict[str, Any]:
return OrderedDict(
{
return {
key: concatenate(subspace, [item[key] for item in items], out[key])
for key, subspace in space.items()
}
)
@concatenate.register(Graph)
@@ -330,9 +327,9 @@ def create_empty_array(
... 'position': Box(low=0, high=1, shape=(3,), dtype=np.float32),
... 'velocity': Box(low=0, high=1, shape=(2,), dtype=np.float32)})
>>> create_empty_array(space, n=2, fn=np.zeros)
OrderedDict([('position', array([[0., 0., 0.],
[0., 0., 0.]], dtype=float32)), ('velocity', array([[0., 0.],
[0., 0.]], dtype=float32))])
{'position': array([[0., 0., 0.],
[0., 0., 0.]], dtype=float32), 'velocity': array([[0., 0.],
[0., 0.]], dtype=float32)}
"""
raise TypeError(
f"The space provided to `create_empty_array` is not a gymnasium Space instance, type: {type(space)}, {space}"
@@ -356,12 +353,9 @@ def _create_empty_array_tuple(space: Tuple, n: int = 1, fn=np.zeros) -> tuple[An
@create_empty_array.register(Dict)
def _create_empty_array_dict(space: Dict, n: int = 1, fn=np.zeros) -> dict[str, Any]:
return OrderedDict(
{
key: create_empty_array(subspace, n=n, fn=fn)
for key, subspace in space.items()
return {
key: create_empty_array(subspace, n=n, fn=fn) for key, subspace in space.items()
}
)
@create_empty_array.register(Graph)

5
gymnasium/wrappers/utils.py
View File

@@ -1,5 +1,4 @@
"""Utility functions for the wrappers."""
from collections import OrderedDict
from functools import singledispatch
import numpy as np
@@ -119,9 +118,7 @@ def _create_tuple_zero_array(space: Tuple):
@create_zero_array.register(Dict)
def _create_dict_zero_array(space: Dict):
return OrderedDict(
{key: create_zero_array(subspace) for key, subspace in space.spaces.items()}
)
return {key: create_zero_array(subspace) for key, subspace in space.spaces.items()}
@create_zero_array.register(Sequence)

4
gymnasium/wrappers/vector/vectorize_observation.py
View File

@@ -189,10 +189,10 @@ class FilterObservation(VectorizeTransformObservation):
>>> obs, info = envs.reset(seed=123)
>>> envs.close()
>>> obs
OrderedDict([('obs', array([[ 0.01823519, -0.0446179 , -0.02796401, -0.03156282],
{'obs': array([[ 0.01823519, -0.0446179 , -0.02796401, -0.03156282],
[ 0.02852531, 0.02858594, 0.0469136 , 0.02480598],
[ 0.03517495, -0.000635 , -0.01098382, -0.03203924]],
dtype=float32))])
dtype=float32)}
"""
def __init__(self, env: VectorEnv, filter_keys: Sequence[str | int]):

2
tests/spaces/test_dict.py
View File

@@ -10,7 +10,7 @@ from gymnasium.spaces import Box, Dict, Discrete
def test_dict_init():
with pytest.raises(
AssertionError,
TypeError,
match=r"^Unexpected Dict space input, expecting dict, OrderedDict or Sequence, actual type: ",
):
Dict(Discrete(2))