garage.tf.models.module

Interface for primitives which build on top of models.

class Module(name)

Bases: abc.ABC

A module that builds on top of model.

Parameters:name (str) – Module name, also the variable scope.

name

Name of this module.

Type:str

state_info_specs

State info specification.

Returns:

keys and shapes for the information related to the

module’s state when taking an action.

Return type:List[str]

state_info_keys

State info keys.

Returns:

keys for the information related to the module’s state

when taking an input.

Return type:List[str]

reset(self, do_resets=None)

Reset the module.

This is effective only to recurrent modules. do_resets is effective only to vectoried modules.

For a vectorized modules, do_resets is an array of boolean indicating which internal states to be reset. The length of do_resets should be equal to the length of inputs.

Parameters:do_resets (numpy.ndarray) – Bool array indicating which states to be reset.

terminate(self)

Clean up operation.

get_trainable_vars(self)

Get trainable variables.

Returns:

A list of trainable variables in the current

variable scope.

Return type:List[tf.Variable]

get_global_vars(self)

Get global variables.

Returns:

A list of global variables in the current

variable scope.

Return type:List[tf.Variable]

get_regularizable_vars(self)

Get all network weight variables in the current scope.

Returns:

A list of network weight variables in the

current variable scope.

Return type:List[tf.Variable]

get_params(self)

Get the trainable variables.

Returns:

A list of trainable variables in the current

variable scope.

Return type:List[tf.Variable]

get_param_shapes(self)

Get parameter shapes.

Returns:A list of variable shapes. Return type:List[tuple]

get_param_values(self)

Get param values.

Returns:

Values of the parameters evaluated in

the current session

Return type:np.ndarray

set_param_values(self, param_values)

Set param values.

Parameters:param_values (np.ndarray) – A numpy array of parameter values.

flat_to_params(self, flattened_params)

Unflatten tensors according to their respective shapes.

Parameters:flattened_params (np.ndarray) – A numpy array of flattened params. Returns:

A list of parameters reshaped to the

shapes specified.

Return type:List[np.ndarray]

class StochasticModule(name)

Bases: garage.tf.models.module.Module

Stochastic Module.

distribution

Distribution.

name

Name of this module.

Type:str

state_info_specs

State info specification.

Returns:

keys and shapes for the information related to the

module’s state when taking an action.

Return type:List[str]

state_info_keys

State info keys.

Returns:

keys for the information related to the module’s state

when taking an input.

Return type:List[str]

reset(self, do_resets=None)

Reset the module.

This is effective only to recurrent modules. do_resets is effective only to vectoried modules.

For a vectorized modules, do_resets is an array of boolean indicating which internal states to be reset. The length of do_resets should be equal to the length of inputs.

Parameters:do_resets (numpy.ndarray) – Bool array indicating which states to be reset.

terminate(self)

Clean up operation.

get_trainable_vars(self)

Get trainable variables.

Returns:

A list of trainable variables in the current

variable scope.

Return type:List[tf.Variable]

get_global_vars(self)

Get global variables.

Returns:

A list of global variables in the current

variable scope.

Return type:List[tf.Variable]

get_regularizable_vars(self)

Get all network weight variables in the current scope.

Returns:

A list of network weight variables in the

current variable scope.

Return type:List[tf.Variable]

get_params(self)

Get the trainable variables.

Returns:

A list of trainable variables in the current

variable scope.

Return type:List[tf.Variable]

get_param_shapes(self)

Get parameter shapes.

Returns:A list of variable shapes. Return type:List[tuple]

get_param_values(self)

Get param values.

Returns:

Values of the parameters evaluated in

the current session

Return type:np.ndarray

set_param_values(self, param_values)

Set param values.

Parameters:param_values (np.ndarray) – A numpy array of parameter values.

flat_to_params(self, flattened_params)

Unflatten tensors according to their respective shapes.

Parameters:flattened_params (np.ndarray) – A numpy array of flattened params. Returns:

A list of parameters reshaped to the

shapes specified.

Return type:List[np.ndarray]