mirror of
https://github.com/google-deepmind/deepmind-research.git
synced 2026-05-09 21:07:49 +08:00
Shaobo Hou
89 lines
2.9 KiB
Python
89 lines
2.9 KiB
Python
# Lint as: python3
|
|
# pylint: disable=g-bad-file-header
|
|
# Copyright 2020 DeepMind Technologies Limited. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
# ============================================================================
|
|
"""Keyboard utils."""
|
|
|
|
import numpy as np
|
|
|
|
from option_keyboard import configs
|
|
from option_keyboard import environment_wrappers
|
|
from option_keyboard import experiment
|
|
from option_keyboard import keyboard_agent
|
|
from option_keyboard import scavenger
|
|
|
|
|
|
def create_and_train_keyboard(num_episodes,
|
|
policy_weights=None,
|
|
export_path=None):
|
|
"""Train an option keyboard."""
|
|
if policy_weights is None:
|
|
policy_weights = np.eye(2, dtype=np.float32)
|
|
|
|
env_config = configs.get_pretrain_config()
|
|
env = scavenger.Scavenger(**env_config)
|
|
env = environment_wrappers.EnvironmentWithLogging(env)
|
|
|
|
agent = keyboard_agent.Agent(
|
|
obs_spec=env.observation_spec(),
|
|
action_spec=env.action_spec(),
|
|
policy_weights=policy_weights,
|
|
network_kwargs=dict(
|
|
output_sizes=(64, 128),
|
|
activate_final=True,
|
|
),
|
|
epsilon=0.1,
|
|
additional_discount=0.9,
|
|
batch_size=10,
|
|
optimizer_name="AdamOptimizer",
|
|
optimizer_kwargs=dict(learning_rate=3e-4,))
|
|
|
|
if num_episodes:
|
|
experiment.run(env, agent, num_episodes=num_episodes)
|
|
agent.export(export_path)
|
|
|
|
return agent
|
|
|
|
|
|
def create_and_train_keyboard_with_phi(num_episodes,
|
|
phi_model_path,
|
|
policy_weights,
|
|
export_path=None):
|
|
"""Train an option keyboard."""
|
|
env_config = configs.get_pretrain_config()
|
|
env = scavenger.Scavenger(**env_config)
|
|
env = environment_wrappers.EnvironmentWithLogging(env)
|
|
env = environment_wrappers.EnvironmentWithLearnedPhi(env, phi_model_path)
|
|
|
|
agent = keyboard_agent.Agent(
|
|
obs_spec=env.observation_spec(),
|
|
action_spec=env.action_spec(),
|
|
policy_weights=policy_weights,
|
|
network_kwargs=dict(
|
|
output_sizes=(64, 128),
|
|
activate_final=True,
|
|
),
|
|
epsilon=0.1,
|
|
additional_discount=0.9,
|
|
batch_size=10,
|
|
optimizer_name="AdamOptimizer",
|
|
optimizer_kwargs=dict(learning_rate=3e-4,))
|
|
|
|
if num_episodes:
|
|
experiment.run(env, agent, num_episodes=num_episodes)
|
|
agent.export(export_path)
|
|
|
|
return agent
|