def __init__(self, nvec):
"""
nvec: vector of counts of each categorical variable
"""
self.nvec = np.asarray(nvec, dtype=np.int32)
assert self.nvec.ndim == 1, 'nvec should be a 1d array (or list) of ints'
Space.__init__(self, (self.nvec.size, ), np.int8)
def __init__(self, spaces):
if isinstance(spaces, dict):
spaces = OrderedDict(sorted(list(spaces.items())))
if isinstance(spaces, list):
spaces = OrderedDict(spaces)
self.spaces = spaces
Space.__init__(self, None, None) # None for shape and dtype, since it'll require special handling
def __init__(self,
n,
low=None,
high=None):
self._n = n
self._low = low or -10000.0
self._high = high or 100000.0
Space.__init__(self, shape=(n,))
def __init__(self,
n,
low=None,
high=None):
self._n = n
self._low = low
self._high = high
Space.__init__(self, shape=(n,))
def __init__(self, spaces):
if isinstance(spaces, dict):
spaces = OrderedDict(sorted(list(spaces.items())))
if isinstance(spaces, list):
spaces = OrderedDict(spaces)
self.spaces = spaces
Space.__init__(
self, None, None
) # None for shape and dtype, since it'll require special handling
def __init__(self, low=None, high=None, shape=None, dtype=np.float32):
"""
Two kinds of valid input:
Box(low=-1.0, high=1.0, shape=(3,4)) # low and high are scalars, and shape is provided
Box(np.array(low=[-1.0,-2.0]), high=np.array([2.0,4.0])) # low and high are arrays of the same shape
"""
if shape is None:
assert low.shape == high.shape
shape = low.shape
else:
assert np.isscalar(low) and np.isscalar(high)
low = low + np.zeros(shape)
high = high + np.zeros(shape)
self.low = low.astype(dtype)
self.high = high.astype(dtype)
if (self.high == 255).all() and dtype != np.uint8:
logger.warn('Box constructor got high=255 but dtype!=uint8')
Space.__init__(self, shape, dtype)
def __init__(self, low=None, high=None, shape=None, dtype=None):
"""
Two kinds of valid input:
Box(low=-1.0, high=1.0, shape=(3,4)) # low and high are scalars, and shape is provided
Box(np.array(low=[-1.0,-2.0]), high=np.array([2.0,4.0])) # low and high are arrays of the same shape
"""
if shape is None:
assert low.shape == high.shape
shape = low.shape
else:
assert np.isscalar(low) and np.isscalar(high)
low = low + np.zeros(shape)
high = high + np.zeros(shape)
if dtype is None: # Autodetect type
if (high == 255).all():
dtype = np.uint8
else:
dtype = np.float32
logger.warn(
"gym.spaces.Box autodetected dtype as %s. Please provide explicit dtype."
% dtype)
self.low = low.astype(dtype)
self.high = high.astype(dtype)
Space.__init__(self, shape, dtype)
def __init__(self, n):
self.n = n
Space.__init__(self, (), np.int64)
def __init__(self, n):
self.n = n
Space.__init__(self, (self.n, ), np.int8)
def __init__(self, spaces):
self.spaces = spaces
Space.__init__(self, None, None)
def __init__(self, n):
self.n = n
Space.__init__(self, (), np.int64)
def __init__(self, n):
self.n = n
Space.__init__(self, (self.n,), np.int8)