API del Producte - Treball Final de Màster
by Rafael Jesús Castaño Ribes, January 2021

Els mètodes derivats, si no ha estat sobreescrita, hereten la documentació de les seves superclasses. L'autoria de la documentació en aquests casos correspon al desenvolupador de la superclasse.
index -> experiments.rnd_experiment
index
..\src\experiments\rnd_experiment.py

Train and Eval Random Policy Agent.

 
Modules
       
absl.logging
os
tf_agents.agents.random.random_agent
tensorflow
time

 
Classes
       
experiments.off_p_tsb_experiment.OffPolicyTimeStepBasedExperiment(builtins.object)
RndExperiment

 
class RndExperiment(experiments.off_p_tsb_experiment.OffPolicyTimeStepBasedExperiment)
    RndExperiment(root_dir='', num_eval_episodes=10, summary_interval=1000, env_name='BipedalWalker-v3', env_action_repeat_times=4, debug_summaries=False, summarize_grads_and_vars=False, replay_buffer_capacity=1000000, initial_collect_steps=10000, collect_steps_per_iteration=1, use_tf_functions=True, sample_batch_size=256, num_iterations=3000000, train_steps_per_iteration=1, log_interval=1000, eval_interval=10000, train_checkpoint_interval=50000, policy_checkpoint_interval=50000, replay_buffer_checkpoint_interval=50000, name='default_naf_experiment')
 
A simple train and eval class for a Random Policy Agent.
 
 
Method resolution order:
RndExperiment
experiments.off_p_tsb_experiment.OffPolicyTimeStepBasedExperiment
builtins.object

Methods defined here:
__init__(self, root_dir='', num_eval_episodes=10, summary_interval=1000, env_name='BipedalWalker-v3', env_action_repeat_times=4, debug_summaries=False, summarize_grads_and_vars=False, replay_buffer_capacity=1000000, initial_collect_steps=10000, collect_steps_per_iteration=1, use_tf_functions=True, sample_batch_size=256, num_iterations=3000000, train_steps_per_iteration=1, log_interval=1000, eval_interval=10000, train_checkpoint_interval=50000, policy_checkpoint_interval=50000, replay_buffer_checkpoint_interval=50000, name='default_naf_experiment')
Initialize self.  See help(type(self)) for accurate signature.

Methods inherited from experiments.off_p_tsb_experiment.OffPolicyTimeStepBasedExperiment:
copy(self)
launch(self)

Data descriptors inherited from experiments.off_p_tsb_experiment.OffPolicyTimeStepBasedExperiment:
__dict__
dictionary for instance variables (if defined)
__weakref__
list of weak references to the object (if defined)

 
Data
        absolute_import = _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0), 16384)
division = _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)
print_function = _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 65536)