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Eric Hambro authoredEric Hambro authored
__init__.py 1.71 KiB
# Copyright (c) Facebook, Inc. and its affiliates.
#
# 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.
from nle.env import tasks
from nle.env.base import DUNGEON_SHAPE
from .baseline import BaselineNet
from omegaconf import OmegaConf
import torch
ENVS = dict(
staircase=tasks.NetHackStaircase,
score=tasks.NetHackScore,
pet=tasks.NetHackStaircasePet,
oracle=tasks.NetHackOracle,
gold=tasks.NetHackGold,
eat=tasks.NetHackEat,
scout=tasks.NetHackScout,
challenge=tasks.NetHackChallenge,
)
def create_model(flags, device):
model_string = flags.model
if model_string == "baseline":
model_cls = BaselineNet
else:
raise NotImplementedError("model=%s" % model_string)
action_space = ENVS[flags.env](savedir=None, archivefile=None)._actions
model = model_cls(DUNGEON_SHAPE, action_space, flags, device)
model.to(device=device)
return model
def load_model(load_dir, device):
flags = OmegaConf.load(load_dir + "/config.yaml")
flags.checkpoint = load_dir + "/checkpoint.tar"
model = create_model(flags, device)
checkpoint_states = torch.load(flags.checkpoint, map_location=device)
model.load_state_dict(checkpoint_states["model_state_dict"])
return model