File size: 2,591 Bytes
42d9709 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 | # SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# 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.
import gymnasium as gym
import json
import os
from abc import ABC, abstractmethod
from datetime import datetime
from typing import Dict, Optional
JSON_INDENT = 4
class EvaluatorBase(ABC):
"""
Base class for all evaluators. An evaluator tracks the performance of a task over a series of demos.
"""
def __init__(self, checkpoint_name: str, eval_file_path: Optional[str] = None, seed: int = 10) -> None:
"""
Initializes the EvaluatorBase object.
Args:
eval_file_path (os.path, optional): The path where the the evaluation file should be stored.
Defaults to None (which means no evaluation file will be stored).
checkpoint_name (str, optional): Name of checkpoint used for evaluation.
"""
if eval_file_path is not None:
assert os.path.exists(os.path.dirname(eval_file_path))
self.eval_file_path = eval_file_path
self.eval_dict = {}
self.eval_dict["metadata"] = {
"checkpoint_name": checkpoint_name,
"seed": seed,
"date": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
}
@abstractmethod
def evaluate_step(self, env: gym.Env) -> None:
"""
Evaluates the current state of the task.
Args:
observed_state (State): The observed state of the environment.
env (gym.Env): The environment in which the cube stacking task is being evaluated.
"""
pass
def maybe_write_eval_file(self):
"""
If the evaluation file is set, the eval dict will be written to it.
"""
if self.eval_file_path is not None:
with open(self.eval_file_path, "w") as json_file:
json.dump(self.eval_dict, json_file, indent=JSON_INDENT)
@abstractmethod
def summarize_demos(self) -> Dict:
pass
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