您最多选择25个主题
主题必须以中文或者字母或数字开头，可以包含连字符 (-)，并且长度不得超过35个字符
94 行
3.9 KiB
94 行
3.9 KiB
import pathlib
|
|
import logging
|
|
import os
|
|
from mlagents.trainers.buffer import Buffer
|
|
from mlagents.envs.brain import BrainParameters, BrainInfo
|
|
from mlagents.envs.communicator_objects import *
|
|
from google.protobuf.internal.decoder import _DecodeVarint32
|
|
|
|
logger = logging.getLogger("mlagents.trainers")
|
|
|
|
|
|
def make_demo_buffer(brain_infos, brain_params, sequence_length):
|
|
# Create and populate buffer using experiences
|
|
demo_buffer = Buffer()
|
|
for idx, experience in enumerate(brain_infos):
|
|
if idx > len(brain_infos) - 2:
|
|
break
|
|
current_brain_info = brain_infos[idx]
|
|
next_brain_info = brain_infos[idx + 1]
|
|
demo_buffer[0].last_brain_info = current_brain_info
|
|
demo_buffer[0]['done'].append(next_brain_info.local_done[0])
|
|
demo_buffer[0]['rewards'].append(next_brain_info.rewards[0])
|
|
for i in range(brain_params.number_visual_observations):
|
|
demo_buffer[0]['visual_obs%d' % i] \
|
|
.append(current_brain_info.visual_observations[i][0])
|
|
if brain_params.vector_observation_space_size > 0:
|
|
demo_buffer[0]['vector_obs'] \
|
|
.append(current_brain_info.vector_observations[0])
|
|
demo_buffer[0]['actions'].append(next_brain_info.previous_vector_actions[0])
|
|
if next_brain_info.local_done[0]:
|
|
demo_buffer.append_update_buffer(0, batch_size=None,
|
|
training_length=sequence_length)
|
|
demo_buffer.reset_local_buffers()
|
|
demo_buffer.append_update_buffer(0, batch_size=None,
|
|
training_length=sequence_length)
|
|
return demo_buffer
|
|
|
|
|
|
def demo_to_buffer(file_path, sequence_length):
|
|
"""
|
|
Loads demonstration file and uses it to fill training buffer.
|
|
:param file_path: Location of demonstration file (.demo).
|
|
:param sequence_length: Length of trajectories to fill buffer.
|
|
:return:
|
|
"""
|
|
brain_params, brain_infos, _ = load_demonstration(file_path)
|
|
demo_buffer = make_demo_buffer(brain_infos, brain_params, sequence_length)
|
|
return brain_params, demo_buffer
|
|
|
|
|
|
def load_demonstration(file_path):
|
|
"""
|
|
Loads and parses a demonstration file.
|
|
:param file_path: Location of demonstration file (.demo).
|
|
:return: BrainParameter and list of BrainInfos containing demonstration data.
|
|
"""
|
|
|
|
# First 32 bytes of file dedicated to meta-data.
|
|
INITIAL_POS = 33
|
|
|
|
if not os.path.isfile(file_path):
|
|
raise FileNotFoundError("The demonstration file {} does not exist.".format(file_path))
|
|
file_extension = pathlib.Path(file_path).suffix
|
|
if file_extension != '.demo':
|
|
raise ValueError("The file is not a '.demo' file. Please provide a file with the "
|
|
"correct extension.")
|
|
|
|
brain_params = None
|
|
brain_infos = []
|
|
data = open(file_path, "rb").read()
|
|
next_pos, pos, obs_decoded = 0, 0, 0
|
|
total_expected = 0
|
|
while pos < len(data):
|
|
next_pos, pos = _DecodeVarint32(data, pos)
|
|
if obs_decoded == 0:
|
|
meta_data_proto = DemonstrationMetaProto()
|
|
meta_data_proto.ParseFromString(data[pos:pos + next_pos])
|
|
total_expected = meta_data_proto.number_steps
|
|
pos = INITIAL_POS
|
|
if obs_decoded == 1:
|
|
brain_param_proto = BrainParametersProto()
|
|
brain_param_proto.ParseFromString(data[pos:pos + next_pos])
|
|
brain_params = BrainParameters.from_proto(brain_param_proto)
|
|
pos += next_pos
|
|
if obs_decoded > 1:
|
|
agent_info = AgentInfoProto()
|
|
agent_info.ParseFromString(data[pos:pos + next_pos])
|
|
brain_info = BrainInfo.from_agent_proto([agent_info], brain_params)
|
|
brain_infos.append(brain_info)
|
|
if len(brain_infos) == total_expected:
|
|
break
|
|
pos += next_pos
|
|
obs_decoded += 1
|
|
return brain_params, brain_infos, total_expected
|