akro package¶
A library containing types of Spaces.

class
akro.
Space
(shape=None, dtype=None)[source]¶ Bases:
abc.ABC
,gym.spaces.space.Space
Provides a classification state spaces and action spaces.
Allows you to write generic code that applies to any Environment. E.g. to choose a random action.

flat_dim
¶ Return the length of the flattened vector of the space.

flatten
(x)[source]¶ Return a flattened observation x.
 Args:
 x (
Iterable
): The object to flatten.  Returns:
 np.ndarray: An array of x collapsed into one dimension.

flatten_n
(xs)[source]¶ Return flattened observations xs.
 Args:
 xs (
Iterable
): The object to reshape and flatten  Returns:
 np.ndarray: An array of xs in a shape inferred by the size of
 its first element.

to_tf_placeholder
(name, batch_dims)[source]¶ Create a tensor placeholder from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 tf.Tensor: Tensor object with the same properties as
 the Dict where the shape is modified by batch_dims.

to_theano_tensor
(name, batch_dims)[source]¶ Create a theano tensor from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 theano.tensor.TensorVariable: Tensor object with the
 same properties as the Dict where the shape is modified by batch_dims.


class
akro.
Box
(low, high, shape=None, dtype=<class 'numpy.float32'>)[source]¶ Bases:
gym.spaces.box.Box
,akro.space.Space
A box in R^n.
Each coordinate is bounded above and below.

bounds
¶ Return a 2tuple containing the lower and upper bounds.

flat_dim
¶ Return the length of the flattened vector of the space.

flatten
(x)[source]¶ Return a flattened observation x.
 Args:
 x (:obj:’Iterable`): The object to flatten.
 Returns:
 np.ndarray: An array of x collapsed into one dimension.

flatten_n
(obs)[source]¶ Return flattened observations obs.
 Args:
 obs (
Iterable
): The object to reshape and flatten  Returns:
 np.ndarray: An array of obs in a shape inferred by the size of
 its first element.

to_tf_placeholder
(name, batch_dims)[source]¶ Create a tensor placeholder from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 tf.Tensor: Tensor object with the same properties as
 the Box where the shape is modified by batch_dims.

to_theano_tensor
(name, batch_dims)[source]¶ Create a theano tensor from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 theano.tensor.TensorVariable: Tensor object with the
 same properties as the Box where the shape is modified by batch_dims.


class
akro.
Dict
(spaces=None, **spaces_kwargs)[source]¶ Bases:
gym.spaces.dict.Dict
,akro.space.Space
A dictionary of simpler spaces, e.g. Discrete, Box.
 Example usage:
 self.observation_space = spaces.Dict({“position”: spaces.Discrete(2),
 “velocity”: spaces.Discrete(3)})

flat_dim
¶ Return the length of the flattened vector of the space.

flatten
(x)[source]¶ Return an observation of x with collapsed values.
 Args:
 x (
Iterable
): The object to flatten.  Returns:
 Dict: A Dict where each value is collapsed into a single dimension.
 Keys are unchanged.

flatten_n
(xs)[source]¶ Return flattened observations xs.
 Args:
 xs (
Iterable
): The object to reshape and flatten  Returns:
 np.ndarray: An array of xs in a shape inferred by the size of
 its first element.

to_tf_placeholder
(name, batch_dims)[source]¶ Create a tensor placeholder from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 tf.Tensor: Tensor object with the same properties as
 the Dict where the shape is modified by batch_dims.

to_theano_tensor
(name, batch_dims)[source]¶ Create a theano tensor from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 theano.tensor.TensorVariable: Tensor object with the
 same properties as the Dict where the shape is modified by batch_dims.

class
akro.
Discrete
(n)[source]¶ Bases:
gym.spaces.discrete.Discrete
,akro.space.Space
{0,1,…,n1}.

flat_dim
¶ Return the length of the flattened vector of the space.

flatten
(x)[source]¶ Return a flattened observation x.
 Args:
 x (
Iterable
): The object to flatten.  Returns:
 np.ndarray: An array of x collapsed into one dimension.

flatten_n
(xs)[source]¶ Return flattened observations xs.
 Args:
 xs (
Iterable
): The object to reshape and flatten  Returns:
 np.ndarray: An array of xs in a shape inferred by the size of
 its first element.

to_tf_placeholder
(name, batch_dims)[source]¶ Create a tensor placeholder from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 tf.Tensor: Tensor object with the same properties as
 the Discrete obj where the shape is modified by batch_dims.

to_theano_tensor
(name, batch_dims)[source]¶ Create a theano tensor from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 theano.tensor.TensorVariable: Tensor object with the
 same properties as the Discrete obj where the shape is modified by batch_dims..

unflatten
(x)[source]¶ Return an unflattened observation x.
 Args:
 x (
Iterable
): The object to unflatten.  Returns:
 np.ndarray: An array of x in the shape of self.shape.


class
akro.
Tuple
(spaces)[source]¶ Bases:
gym.spaces.tuple.Tuple
,akro.space.Space
A Tuple of Spaces which produces samples which are Tuples of samples.

flat_dim
¶ Return the length of the flattened vector of the space.

flatten
(x)[source]¶ Return a flattened observation x.
 Args:
 x (
Iterable
): The object to flatten.  Returns:
 np.ndarray: An array of x collapsed into one dimension.

flatten_n
(obs)[source]¶ Return flattened observations obs.
 Args:
 obs (
Iterable
): The object to reshape and flatten  Returns:
 np.ndarray: An array of obs in a shape inferred by the size of
 its first element.

to_tf_placeholder
(name, batch_dims)[source]¶ Create a tensor placeholder from the Space object.
 Args:
 name (str): name to append to the akro type when naming
 the tensor. e.g. When name is ‘tmp’  ‘Boxtmp’, ‘Discretetmp’.
 batch_dims (
list
): batch dimensions to add to the  shape of each object in self.spaces.
 Returns:
 tuple(tf.Tensor): A tuple of Tensor objects converted
 from each Space in self.spaces. Each Tensor’s shape is modified by batch_dims.

to_theano_tensor
(name, batch_dims)[source]¶ Create a theano tensor from the Space object.
 Args:
 name (str): name to append to the akro type when naming
 the tensor. e.g. When name is ‘tmp’  ‘Boxtmp’, ‘Discretetmp’.
 batch_dims (
list
): batch dimensions to add to the  shape of each object in self.spaces.
 Returns:
 theano.tensor.TensorVariable: A tuple of Tensor objects converted
 from each Space in self.spaces. Each Tensor’s shape is modified by batch_dims.


akro.
from_gym
(space)[source]¶ Convert a gym.space to an akro.space.
 Args:
 space(
gym.Space
): The Space object to convert.  Returns:
 akro.Space: The gym.Space object converted to an
 akro.Space object.
Submodules¶
akro.box module¶
A Space representing a rectangular region of space.

class
akro.box.
Box
(low, high, shape=None, dtype=<class 'numpy.float32'>)[source]¶ Bases:
gym.spaces.box.Box
,akro.space.Space
A box in R^n.
Each coordinate is bounded above and below.

bounds
¶ Return a 2tuple containing the lower and upper bounds.

flat_dim
¶ Return the length of the flattened vector of the space.

flatten
(x)[source]¶ Return a flattened observation x.
 Args:
 x (:obj:’Iterable`): The object to flatten.
 Returns:
 np.ndarray: An array of x collapsed into one dimension.

flatten_n
(obs)[source]¶ Return flattened observations obs.
 Args:
 obs (
Iterable
): The object to reshape and flatten  Returns:
 np.ndarray: An array of obs in a shape inferred by the size of
 its first element.

to_tf_placeholder
(name, batch_dims)[source]¶ Create a tensor placeholder from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 tf.Tensor: Tensor object with the same properties as
 the Box where the shape is modified by batch_dims.

to_theano_tensor
(name, batch_dims)[source]¶ Create a theano tensor from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 theano.tensor.TensorVariable: Tensor object with the
 same properties as the Box where the shape is modified by batch_dims.

akro.dict module¶
Cartesian product of multiple named Spaces (also known as a dict of Spaces).
This Space produces samples which are dicts, where the values of those dicts are drawn from the values of this Space.

class
akro.dict.
Dict
(spaces=None, **spaces_kwargs)[source]¶ Bases:
gym.spaces.dict.Dict
,akro.space.Space
A dictionary of simpler spaces, e.g. Discrete, Box.
 Example usage:
 self.observation_space = spaces.Dict({“position”: spaces.Discrete(2),
 “velocity”: spaces.Discrete(3)})

flat_dim
¶ Return the length of the flattened vector of the space.

flatten
(x)[source]¶ Return an observation of x with collapsed values.
 Args:
 x (
Iterable
): The object to flatten.  Returns:
 Dict: A Dict where each value is collapsed into a single dimension.
 Keys are unchanged.

flatten_n
(xs)[source]¶ Return flattened observations xs.
 Args:
 xs (
Iterable
): The object to reshape and flatten  Returns:
 np.ndarray: An array of xs in a shape inferred by the size of
 its first element.

to_tf_placeholder
(name, batch_dims)[source]¶ Create a tensor placeholder from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 tf.Tensor: Tensor object with the same properties as
 the Dict where the shape is modified by batch_dims.

to_theano_tensor
(name, batch_dims)[source]¶ Create a theano tensor from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 theano.tensor.TensorVariable: Tensor object with the
 same properties as the Dict where the shape is modified by batch_dims.
akro.discrete module¶
A space representing a selection between a finite number of items.

class
akro.discrete.
Discrete
(n)[source]¶ Bases:
gym.spaces.discrete.Discrete
,akro.space.Space
{0,1,…,n1}.

flat_dim
¶ Return the length of the flattened vector of the space.

flatten
(x)[source]¶ Return a flattened observation x.
 Args:
 x (
Iterable
): The object to flatten.  Returns:
 np.ndarray: An array of x collapsed into one dimension.

flatten_n
(xs)[source]¶ Return flattened observations xs.
 Args:
 xs (
Iterable
): The object to reshape and flatten  Returns:
 np.ndarray: An array of xs in a shape inferred by the size of
 its first element.

to_tf_placeholder
(name, batch_dims)[source]¶ Create a tensor placeholder from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 tf.Tensor: Tensor object with the same properties as
 the Discrete obj where the shape is modified by batch_dims.

to_theano_tensor
(name, batch_dims)[source]¶ Create a theano tensor from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 theano.tensor.TensorVariable: Tensor object with the
 same properties as the Discrete obj where the shape is modified by batch_dims..

unflatten
(x)[source]¶ Return an unflattened observation x.
 Args:
 x (
Iterable
): The object to unflatten.  Returns:
 np.ndarray: An array of x in the shape of self.shape.

akro.requires module¶
Decorators used for calling tensorflow and theano functions safely.
akro.space module¶
The abstract base class for all Space types.

class
akro.space.
Space
(shape=None, dtype=None)[source]¶ Bases:
abc.ABC
,gym.spaces.space.Space
Provides a classification state spaces and action spaces.
Allows you to write generic code that applies to any Environment. E.g. to choose a random action.

flat_dim
¶ Return the length of the flattened vector of the space.

flatten
(x)[source]¶ Return a flattened observation x.
 Args:
 x (
Iterable
): The object to flatten.  Returns:
 np.ndarray: An array of x collapsed into one dimension.

flatten_n
(xs)[source]¶ Return flattened observations xs.
 Args:
 xs (
Iterable
): The object to reshape and flatten  Returns:
 np.ndarray: An array of xs in a shape inferred by the size of
 its first element.

to_tf_placeholder
(name, batch_dims)[source]¶ Create a tensor placeholder from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 tf.Tensor: Tensor object with the same properties as
 the Dict where the shape is modified by batch_dims.

to_theano_tensor
(name, batch_dims)[source]¶ Create a theano tensor from the Space object.
 Args:
name (str): name of the variable batch_dims (
list
): batch dimensions to add to theshape of the object. Returns:
 theano.tensor.TensorVariable: Tensor object with the
 same properties as the Dict where the shape is modified by batch_dims.

akro.tuple module¶
Cartesian product of multiple Spaces (also known as a tuple of Spaces).
This Space produces samples which are Tuples, where the elments of those Tuples are drawn from the components of this Space.

class
akro.tuple.
Tuple
(spaces)[source]¶ Bases:
gym.spaces.tuple.Tuple
,akro.space.Space
A Tuple of Spaces which produces samples which are Tuples of samples.

flat_dim
¶ Return the length of the flattened vector of the space.

flatten
(x)[source]¶ Return a flattened observation x.
 Args:
 x (
Iterable
): The object to flatten.  Returns:
 np.ndarray: An array of x collapsed into one dimension.

flatten_n
(obs)[source]¶ Return flattened observations obs.
 Args:
 obs (
Iterable
): The object to reshape and flatten  Returns:
 np.ndarray: An array of obs in a shape inferred by the size of
 its first element.

to_tf_placeholder
(name, batch_dims)[source]¶ Create a tensor placeholder from the Space object.
 Args:
 name (str): name to append to the akro type when naming
 the tensor. e.g. When name is ‘tmp’  ‘Boxtmp’, ‘Discretetmp’.
 batch_dims (
list
): batch dimensions to add to the  shape of each object in self.spaces.
 Returns:
 tuple(tf.Tensor): A tuple of Tensor objects converted
 from each Space in self.spaces. Each Tensor’s shape is modified by batch_dims.

to_theano_tensor
(name, batch_dims)[source]¶ Create a theano tensor from the Space object.
 Args:
 name (str): name to append to the akro type when naming
 the tensor. e.g. When name is ‘tmp’  ‘Boxtmp’, ‘Discretetmp’.
 batch_dims (
list
): batch dimensions to add to the  shape of each object in self.spaces.
 Returns:
 theano.tensor.TensorVariable: A tuple of Tensor objects converted
 from each Space in self.spaces. Each Tensor’s shape is modified by batch_dims.
