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96 行
3.8 KiB
96 行
3.8 KiB
import os
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from typing import List, Tuple
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import numpy as np
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from mlagents.trainers.buffer import AgentBuffer
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from mlagents_envs.communicator_objects.agent_info_action_pair_pb2 import (
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AgentInfoActionPairProto,
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)
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from mlagents.trainers.trajectory import ObsUtil
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from mlagents_envs.rpc_utils import behavior_spec_from_proto, steps_from_proto
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from mlagents_envs.base_env import BehaviorSpec
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from mlagents_envs.communicator_objects.brain_parameters_pb2 import BrainParametersProto
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from mlagents_envs.communicator_objects.demonstration_meta_pb2 import (
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DemonstrationMetaProto,
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)
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from mlagents_envs.timers import timed, hierarchical_timer
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from google.protobuf.internal.decoder import _DecodeVarint32 # type: ignore
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from google.protobuf.internal.encoder import _EncodeVarint # type: ignore
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INITIAL_POS = 33
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SUPPORTED_DEMONSTRATION_VERSIONS = frozenset([0, 1])
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@timed
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def load_demonstration(
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file_paths: List[str],
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) -> Tuple[BehaviorSpec, List[AgentInfoActionPairProto]]:
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"""
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Loads and parses a demonstration file.
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:param file_path: Location of demonstration file (.demo).
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:return: BrainParameter and list of AgentInfoActionPairProto containing demonstration data.
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"""
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# First 32 bytes of file dedicated to meta-data.
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behavior_spec = None
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brain_param_proto = None
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info_action_pairs = []
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total_expected = 0
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for _file_path in file_paths:
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with open(_file_path, "rb") as fp:
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with hierarchical_timer("read_file"):
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data = fp.read()
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next_pos, pos, obs_decoded = 0, 0, 0
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while pos < len(data):
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next_pos, pos = _DecodeVarint32(data, pos)
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if obs_decoded == 0:
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meta_data_proto = DemonstrationMetaProto()
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meta_data_proto.ParseFromString(data[pos : pos + next_pos])
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if (
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meta_data_proto.api_version
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not in SUPPORTED_DEMONSTRATION_VERSIONS
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):
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raise RuntimeError(
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f"Can't load Demonstration data from an unsupported version ({meta_data_proto.api_version})"
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)
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total_expected += meta_data_proto.number_steps
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pos = INITIAL_POS
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if obs_decoded == 1:
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brain_param_proto = BrainParametersProto()
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brain_param_proto.ParseFromString(data[pos : pos + next_pos])
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pos += next_pos
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if obs_decoded > 1:
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agent_info_action = AgentInfoActionPairProto()
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agent_info_action.ParseFromString(data[pos : pos + next_pos])
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if behavior_spec is None:
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behavior_spec = behavior_spec_from_proto(
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brain_param_proto, agent_info_action.agent_info
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)
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info_action_pairs.append(agent_info_action)
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if len(info_action_pairs) == total_expected:
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break
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pos += next_pos
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obs_decoded += 1
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if not behavior_spec:
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raise RuntimeError(
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f"No BrainParameters found in demonstration file(s) at {file_paths}."
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)
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return behavior_spec, info_action_pairs
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def write_delimited(f, message):
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msg_string = message.SerializeToString()
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msg_size = len(msg_string)
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_EncodeVarint(f.write, msg_size)
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f.write(msg_string)
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def write_demo(demo_path, meta_data_proto, brain_param_proto, agent_info_protos):
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with open(demo_path, "wb") as f:
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# write metadata
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write_delimited(f, meta_data_proto)
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f.seek(INITIAL_POS)
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write_delimited(f, brain_param_proto)
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for agent in agent_info_protos:
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write_delimited(f, agent)
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