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# python3 | ||
# Copyright 2022 InstaDeep Ltd. 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. | ||
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import json | ||
import os | ||
import time | ||
from typing import Dict, Optional | ||
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class JsonWriter: | ||
"""Writer to create json files for reporting experiment results. | ||
This writer follow suggested marl-eval protocol and was adapted from | ||
the implementation found in BenchMARL which can be viewed | ||
at https://tinyurl.com/2t6fy548 | ||
Args: | ||
path (str): where to write the file | ||
algorithm_name (str): algorithm name | ||
task_name (str): task name | ||
environment_name (str): environment name | ||
seed (int): random seed of the experiment | ||
""" | ||
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def __init__( | ||
self, | ||
path: str, | ||
algorithm_name: str, | ||
task_name: str, | ||
environment_name: str, | ||
seed: int, | ||
): | ||
"""Initialises the JsonWriter and creates the file if it doesn't exist.""" | ||
self.file_path = f"{path}/metrics.json" | ||
self.run_data: Dict = {"absolute_metrics": {}} | ||
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# If the file already exists, load it | ||
if os.path.isfile(self.file_path): | ||
with open(self.file_path) as f: | ||
data = json.load(f) | ||
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else: | ||
# Create the logging directory if it doesn't exist | ||
os.makedirs(path, exist_ok=True) | ||
data = {} | ||
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# Merge the existing data with the new data | ||
self.data = data | ||
if environment_name not in self.data: | ||
self.data[environment_name] = {} | ||
if task_name not in self.data[environment_name]: | ||
self.data[environment_name][task_name] = {} | ||
if algorithm_name not in self.data[environment_name][task_name]: | ||
self.data[environment_name][task_name][algorithm_name] = {} | ||
self.data[environment_name][task_name][algorithm_name][ | ||
f"seed_{seed}" | ||
] = self.run_data | ||
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with open(self.file_path, "w") as f: | ||
json.dump(self.data, f, indent=4) | ||
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def write( | ||
self, | ||
timestep: int, | ||
key: str, | ||
value: float, | ||
evaluation_step: Optional[int] = None, | ||
is_absolute_metric: bool = False, | ||
) -> None: | ||
"""Writes a step to the json reporting file | ||
Args: | ||
timestep (int): the current environment timestep | ||
key (str): the metric that should be logged | ||
value (str): the value of the metric that should be logged | ||
evaluation_step (int): the evaluation step | ||
is_absolute_metric (bool): whether the metric being logged is | ||
an absolute metric | ||
""" | ||
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current_time = time.time() | ||
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# This will ensure the first logged time is 0, which avoids taking compilation | ||
# into account for jax-based systems when plotting downstream. | ||
if evaluation_step == 0: | ||
self.start_time = current_time | ||
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metrics: Dict = {key: [value]} | ||
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if is_absolute_metric: | ||
self.run_data["absolute_metrics"].update(metrics) | ||
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else: | ||
step_metrics = { # type: ignore | ||
"step_count": timestep, | ||
"elapsed_time": current_time - self.start_time, | ||
} | metrics | ||
step_str = f"step_{evaluation_step}" | ||
if step_str in self.run_data: | ||
self.run_data[step_str].update(step_metrics) | ||
else: | ||
self.run_data[step_str] = step_metrics | ||
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with open(self.file_path, "w") as f: | ||
json.dump(self.data, f, indent=4) |