tensorforce package¶
Subpackages¶
- tensorforce.agents package
- Submodules
- tensorforce.agents.agent module
- tensorforce.agents.batch_agent module
- tensorforce.agents.constant_agent module
- tensorforce.agents.ddqn_agent module
- tensorforce.agents.dqfd_agent module
- tensorforce.agents.dqn_agent module
- tensorforce.agents.dqn_nstep_agent module
- tensorforce.agents.learning_agent module
- tensorforce.agents.memory_agent module
- tensorforce.agents.naf_agent module
- tensorforce.agents.ppo_agent module
- tensorforce.agents.random_agent module
- tensorforce.agents.trpo_agent module
- tensorforce.agents.vpg_agent module
- Module contents
- tensorforce.contrib package
- Submodules
- tensorforce.contrib.ale module
- tensorforce.contrib.deepmind_lab module
- tensorforce.contrib.maze_explorer module
- tensorforce.contrib.openai_gym module
- tensorforce.contrib.openai_universe module
- tensorforce.contrib.remote_environment module
- tensorforce.contrib.state_settable_environment module
- tensorforce.contrib.unreal_engine module
- Module contents
- tensorforce.core package
- Subpackages
- tensorforce.core.baselines package
- tensorforce.core.distributions package
- tensorforce.core.explorations package
- Submodules
- tensorforce.core.explorations.constant module
- tensorforce.core.explorations.epsilon_anneal module
- tensorforce.core.explorations.epsilon_decay module
- tensorforce.core.explorations.exploration module
- tensorforce.core.explorations.linear_decay module
- tensorforce.core.explorations.ornstein_uhlenbeck_process module
- Module contents
- tensorforce.core.memories package
- tensorforce.core.networks package
- tensorforce.core.optimizers package
- Subpackages
- Submodules
- tensorforce.core.optimizers.clipped_step module
- tensorforce.core.optimizers.evolutionary module
- tensorforce.core.optimizers.global_optimizer module
- tensorforce.core.optimizers.meta_optimizer module
- tensorforce.core.optimizers.multi_step module
- tensorforce.core.optimizers.natural_gradient module
- tensorforce.core.optimizers.optimized_step module
- tensorforce.core.optimizers.optimizer module
- tensorforce.core.optimizers.synchronization module
- tensorforce.core.optimizers.tf_optimizer module
- Module contents
- tensorforce.core.preprocessing package
- Submodules
- tensorforce.core.preprocessing.clip module
- tensorforce.core.preprocessing.divide module
- tensorforce.core.preprocessing.grayscale module
- tensorforce.core.preprocessing.image_resize module
- tensorforce.core.preprocessing.normalize module
- tensorforce.core.preprocessing.preprocessor module
- tensorforce.core.preprocessing.preprocessor_stack module
- tensorforce.core.preprocessing.running_standardize module
- tensorforce.core.preprocessing.sequence module
- tensorforce.core.preprocessing.standardize module
- Module contents
- Module contents
- Subpackages
- tensorforce.environments package
- tensorforce.execution package
- tensorforce.models package
- Submodules
- tensorforce.models.constant_model module
- tensorforce.models.distribution_model module
- tensorforce.models.model module
- tensorforce.models.pg_log_prob_model module
- tensorforce.models.pg_model module
- tensorforce.models.pg_prob_ratio_model module
- tensorforce.models.q_demo_model module
- tensorforce.models.q_model module
- tensorforce.models.q_naf_model module
- tensorforce.models.q_nstep_model module
- tensorforce.models.random_model module
- Module contents
- tensorforce.tests package
- Submodules
- tensorforce.tests.base_agent_test module
- tensorforce.tests.base_test module
- tensorforce.tests.test_constant_agent module
- tensorforce.tests.test_ddqn_agent module
- tensorforce.tests.test_dqfd_agent module
- tensorforce.tests.test_dqn_agent module
- tensorforce.tests.test_dqn_memories module
- tensorforce.tests.test_dqn_nstep_agent module
- tensorforce.tests.test_naf_agent module
- tensorforce.tests.test_ppo_agent module
- tensorforce.tests.test_quickstart_example module
- tensorforce.tests.test_random_agent module
- tensorforce.tests.test_reward_estimation module
- tensorforce.tests.test_trpo_agent module
- tensorforce.tests.test_tutorial_code module
- tensorforce.tests.test_vpg_agent module
- tensorforce.tests.test_vpg_baselines module
- tensorforce.tests.test_vpg_optimizers module
- Module contents
Submodules¶
tensorforce.exception module¶
tensorforce.meta_parameter_recorder module¶
-
class
tensorforce.meta_parameter_recorder.
MetaParameterRecorder
(current_frame)¶ Bases:
object
Class to record MetaParameters as well as Summary/Description for TensorBoard (TEXT & FILE will come later).
General:
- format_type: used to configure data conversion for TensorBoard=0, TEXT & JSON (not Implemented), etc
-
__init__
(current_frame)¶ Init the MetaPrameterRecord with “Agent” parameters by passing inspect.currentframe() from Agent Class.
The Init will search back to find the parent class to capture all passed parameters and store them in “self.meta_params”.
NOTE: Currently only optimized for TensorBoard output.
TODO: Add JSON Export, TEXT EXPORT
Parameters: current_frame – Frame value from class to obtain metaparameters[= inspect.currentframe()]
-
build_metagraph_list
()¶ Convert MetaParams into TF Summary Format and create summary_op.
Returns: Merged TF Op for TEXT summary elements, should only be executed once to reduce data duplication.
-
convert_data_to_string
(data, indent=0, format_type=0, separator=None, eol=None)¶
-
convert_dictionary_to_string
(data, indent=0, format_type=0, separator=None, eol=None)¶
-
convert_list_to_string
(data, indent=0, format_type=0, eol=None, count=True)¶
-
convert_ndarray_to_md
(data, format_type=0, eol=None)¶
-
merge_custom
(custom_dict)¶
-
text_output
(format_type=1)¶
tensorforce.util module¶
-
class
tensorforce.util.
SavableComponent
¶ Bases:
object
Component that can save and restore its own state.
-
__init__
¶ x.init(…) initializes x; see help(type(x)) for signature
-
get_savable_variables
()¶ Returns the list of all the variables this component is responsible to save and restore.
Returns: The list of variables that will be saved or restored.
-
register_saver_ops
()¶ Registers the saver operations to the graph in context.
-
restore
(sess, save_path)¶ Restores the values of the managed variables from disk location.
Parameters: - sess – The session for which to save the managed variables.
- save_path – The path used to save the data to.
-
save
(sess, save_path, timestep=None)¶ Saves this component’s managed variables.
Parameters: - sess – The session for which to save the managed variables.
- save_path – The path to save data to.
- timestep – Optional, the timestep to append to the file name.
Returns: Checkpoint path where the model was saved.
-
-
tensorforce.util.
get_object
(obj, predefined_objects=None, default_object=None, kwargs=None)¶ Utility method to map some kind of object specification to its content, e.g. optimizer or baseline specifications to the respective classes.
Parameters: - obj – A specification dict (value for key ‘type’ optionally specifies the object, options as follows), a module path (e.g., my_module.MyClass), a key in predefined_objects, or a callable (e.g., the class type object).
- predefined_objects – Dict containing predefined set of objects, accessible via their key
- default_object – Default object is no other is specified
- kwargs – Arguments for object creation
Returns: The retrieved object
-
tensorforce.util.
map_tensors
(fn, tensors)¶
-
tensorforce.util.
np_dtype
(dtype)¶ Translates dtype specifications in configurations to numpy data types. :param dtype: String describing a numerical type (e.g. ‘float’) or numerical type primitive.
Returns: Numpy data type
-
tensorforce.util.
prepare_kwargs
(raw, string_parameter='name')¶ Utility method to convert raw string/diction input into a dictionary to pass into a function. Always returns a dictionary.
Parameters: raw – string or dictionary, string is assumed to be the name of the activation activation function. Dictionary will be passed through unchanged. Returns: kwargs dictionary for **kwargs
-
tensorforce.util.
prod
(xs)¶ Computes the product along the elements in an iterable. Returns 1 for empty iterable.
Parameters: xs – Iterable containing numbers. Returns: Product along iterable.
-
tensorforce.util.
rank
(x)¶
-
tensorforce.util.
shape
(x, unknown=-1)¶
-
tensorforce.util.
strip_name_scope
(name, base_scope)¶
-
tensorforce.util.
tf_dtype
(dtype)¶ Translates dtype specifications in configurations to tensorflow data types.
Parameters: dtype – String describing a numerical type (e.g. ‘float’), numpy data type, or numerical type primitive. Returns: TensorFlow data type