maml_zoo.policies.distributions package¶

Submodules¶

maml_zoo.policies.distributions.base module¶

class meta_policy_search.policies.distributions.base.Distribution[source]¶

Bases: object

General methods for a generic distribution

dim¶

dist_info_keys¶

dist_info_specs¶

entropy(dist_info)[source]¶

Compute the entropy of the distribution

Parameters:	dist_info (dict) – dict of distribution parameters as numpy array
Returns:	entropy
Return type:	(numpy array)

entropy_sym(dist_info_vars)[source]¶

Symbolic entropy of the distribution

Parameters:	dist_info (dict) – dict of distribution parameters as tf.Tensor
Returns:	entropy
Return type:	(tf.Tensor)

kl(old_dist_info, new_dist_info)[source]¶

Compute the KL divergence of two distributions

Parameters:	old_dist_info (dict) – dict of old distribution parameters as numpy array new_dist_info (dict) – dict of new distribution parameters as numpy array
Returns:	kl divergence of distributions
Return type:	(numpy array)

kl_sym(old_dist_info_vars, new_dist_info_vars)[source]¶

Symbolic KL divergence of two distributions

Parameters:	old_dist_info_vars (dict) – dict of old distribution parameters as tf.Tensor new_dist_info_vars (dict) – dict of new distribution parameters as tf.Tensor
Returns:	Symbolic representation of kl divergence (tensorflow op)
Return type:	(tf.Tensor)

likelihood_ratio(x_var, old_dist_info, new_dist_info)[source]¶

Compute the likelihood ratio p_new(x)/p_old(x) of two distributions

Parameters:	x_var (numpy array) – variable where to evaluate the likelihood ratio p_new(x)/p_old(x) old_dist_info_vars (dict) – dict of old distribution parameters as numpy array new_dist_info_vars (dict) – dict of new distribution parameters as numpy array
Returns:	likelihood ratio
Return type:	(numpy array)

likelihood_ratio_sym(x_var, old_dist_info_vars, new_dist_info_vars)[source]¶

Symbolic likelihood ratio p_new(x)/p_old(x) of two distributions

Parameters:	x_var (tf.Tensor) – variable where to evaluate the likelihood ratio p_new(x)/p_old(x) old_dist_info_vars (dict) – dict of old distribution parameters as tf.Tensor new_dist_info_vars (dict) – dict of new distribution parameters as tf.Tensor
Returns:	likelihood ratio
Return type:	(tf.Tensor)

log_likelihood(xs, dist_info)[source]¶

Compute the log likelihood log p(x) of the distribution

Parameters:	x_var (numpy array) – variable where to evaluate the log likelihood dist_info_vars (dict) – dict of distribution parameters as numpy array
Returns:	log likelihood
Return type:	(numpy array)

log_likelihood_sym(x_var, dist_info_vars)[source]¶

Symbolic log likelihood log p(x) of the distribution

Parameters:	x_var (tf.Tensor) – variable where to evaluate the log likelihood dist_info_vars (dict) – dict of distribution parameters as tf.Tensor
Returns:	log likelihood
Return type:	(numpy array)

sample(dist_info)[source]¶

Draws a sample from the distribution

Parameters:	dist_info (dict) – dict of distribution parameter instantiations as numpy array
Returns:	sample drawn from the corresponding instantiation
Return type:	(obj)

maml_zoo.policies.distributions.diagonal_gaussian module¶

class meta_policy_search.policies.distributions.diagonal_gaussian.DiagonalGaussian(dim)[source]¶

Bases: meta_policy_search.policies.distributions.base.Distribution

General methods for a diagonal gaussian distribution of this size

dim¶

dist_info_specs¶