repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
rlmeta | rlmeta-main/tests/data/segment_tree_test.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import pickle
import unittest
from math import prod
import numpy as np
import torch
from rlmeta.data import SumSegmentTree
from tests.tes... | 4,036 | 35.044643 | 77 | py |
rlmeta | rlmeta-main/tests/data/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
| 179 | 35 | 65 | py |
rlmeta | rlmeta-main/tests/ops/discounted_return_test.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
from typing import Union
import torch
import rlmeta.ops as ops
from tests.test_utils import TestCaseBase
class Discoun... | 2,278 | 29.797297 | 79 | py |
rlmeta | rlmeta-main/tests/ops/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
| 179 | 35 | 65 | py |
rlmeta | rlmeta-main/tests/ops/generalized_advantage_estimation_test.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
from typing import Optional, Union
import torch
import rlmeta.ops as ops
from tests.test_utils import TestCaseBase
cla... | 3,929 | 33.173913 | 74 | py |
rlmeta | rlmeta-main/docs/source/conf.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# ... | 2,078 | 35.473684 | 79 | py |
rlmeta | rlmeta-main/rlmeta/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
| 179 | 35 | 65 | py |
rlmeta | rlmeta-main/rlmeta/core/callbacks.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Any, Dict
from rlmeta.core.types import Action, TimeStep
# The EpisodeCallbacks class is adapted from RLLib's DefaultCa... | 1,865 | 31.172414 | 116 | py |
rlmeta | rlmeta-main/rlmeta/core/loop.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import annotations
import abc
import asyncio
import copy
import logging
import time
from typing import Dict, List, NoRetur... | 12,555 | 30.949109 | 113 | py |
rlmeta | rlmeta-main/rlmeta/core/launchable.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import abc
class Launchable(abc.ABC):
@abc.abstractmethod
def init_launching(self) -> None:
"""
"""
@abc.abs... | 394 | 18.75 | 65 | py |
rlmeta | rlmeta-main/rlmeta/core/server.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import annotations
import asyncio
import logging
from typing import Any, Callable, List, NoReturn, Optional, Sequence, Uni... | 5,518 | 28.994565 | 78 | py |
rlmeta | rlmeta-main/rlmeta/core/model.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import copy
import functools
import random
from enum import IntEnum
from typing import (Any, Awaitable, Callable, Dict, Optional, Sequence,... | 11,670 | 35.358255 | 80 | py |
rlmeta | rlmeta-main/rlmeta/core/types.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import torch
from typing import Any, NamedTuple, Optional, Union
Tensor = Union[np.ndarray, torch.Tensor]
# NestedTens... | 2,108 | 33.57377 | 109 | py |
rlmeta | rlmeta-main/rlmeta/core/controller.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass
from enum import IntFlag
from typing import Dict, Optional, Union
import rlmeta.core.remote as remote
fr... | 2,275 | 27.098765 | 77 | py |
rlmeta | rlmeta-main/rlmeta/core/rescalers.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import abc
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from rlmeta.utils.running_stats import RunningMom... | 5,106 | 26.605405 | 78 | py |
rlmeta | rlmeta-main/rlmeta/core/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
| 179 | 35 | 65 | py |
rlmeta | rlmeta-main/rlmeta/core/replay_buffer.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import collections
import time
import logging
from typing import Callable, Optional, Sequence, Tuple, Union
from rich.console import Conso... | 8,167 | 33.464135 | 79 | py |
rlmeta | rlmeta-main/rlmeta/core/remote.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import annotations
import abc
import functools
from typing import Any, Callable, List, Optional
import moolib
from rlmet... | 4,865 | 29.993631 | 76 | py |
rlmeta | rlmeta-main/rlmeta/envs/gym_wrapper.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Callable, Optional
import numpy as np
import gym
from gym.wrappers.frame_stack import LazyFrames
from gym.wrappers.ste... | 2,873 | 30.582418 | 79 | py |
rlmeta | rlmeta-main/rlmeta/envs/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
| 179 | 35 | 65 | py |
rlmeta | rlmeta-main/rlmeta/envs/atari_wrapper.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Optional
import numpy as np
import gym
from gym.wrappers.atari_preprocessing import AtariPreprocessing
from gym.wrappe... | 4,344 | 35.822034 | 80 | py |
rlmeta | rlmeta-main/rlmeta/envs/env.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import abc
from typing import Optional, Type
from rlmeta.core.types import Action, TimeStep
from rlmeta.core.types import NestedTensor
c... | 976 | 21.204545 | 77 | py |
rlmeta | rlmeta-main/rlmeta/models/actor_critic.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Sequence, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from rlmeta.models.utils import MLP
... | 1,699 | 32.333333 | 76 | py |
rlmeta | rlmeta-main/rlmeta/models/utils.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Sequence
import torch
import torch.nn as nn
# The MLP class is inspired from the MLP class in DeepMind's haiku lib.
# h... | 2,810 | 32.464286 | 111 | py |
rlmeta | rlmeta-main/rlmeta/models/dqn.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Sequence
import torch
import torch.nn as nn
from rlmeta.models.utils import MLP
class DQNHead(nn.Module):
def __... | 1,306 | 29.395349 | 68 | py |
rlmeta | rlmeta-main/rlmeta/models/atari.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
from rlmeta.models.utils import ResidualBlock
class NatureCNNBackbone(nn.Module):
def __init__(se... | 1,990 | 28.716418 | 76 | py |
rlmeta | rlmeta-main/rlmeta/agents/agent.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import abc
import asyncio
import copy
from concurrent.futures import Future
from typing import Any, Optional, Type, Union
import rlmeta.co... | 3,867 | 28.30303 | 101 | py |
rlmeta | rlmeta-main/rlmeta/agents/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
| 179 | 35 | 65 | py |
rlmeta | rlmeta-main/rlmeta/agents/ppo/ppo_model.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import abc
from typing import Tuple
import torch
import torch.nn as nn
from rlmeta.core.model import RemotableModel
class PPOModel(Remo... | 1,555 | 28.358491 | 79 | py |
rlmeta | rlmeta-main/rlmeta/agents/ppo/ppo_rnd_agent.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Callable, Dict, List, Optional, Sequence
import torch
import torch.nn as nn
import rlmeta.utils.data_utils as data_util... | 10,632 | 39.276515 | 80 | py |
rlmeta | rlmeta-main/rlmeta/agents/ppo/ppo_rnd_model.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import abc
from typing import Tuple
import torch
import torch.nn as nn
from rlmeta.core.model import RemotableModel
class PPORNDModel(R... | 1,906 | 27.893939 | 78 | py |
rlmeta | rlmeta-main/rlmeta/agents/ppo/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from rlmeta.agents.ppo.ppo_agent import PPOAgent
from rlmeta.agents.ppo.ppo_rnd_agent import PPORNDAgent
from rlmeta.agents.ppo.ppo_model im... | 475 | 27 | 65 | py |
rlmeta | rlmeta-main/rlmeta/agents/ppo/ppo_agent.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import time
from concurrent.futures import Future, ThreadPoolExecutor
from typing import Dict, Iterable, List, Optional, Sequence, Tuple, U... | 13,953 | 36.210667 | 80 | py |
rlmeta | rlmeta-main/rlmeta/agents/dqn/dqn_model.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import abc
from typing import Optional, Tuple
import torch
import torch.nn as nn
from rlmeta.core.model import RemotableModel
from rlmeta... | 2,058 | 28 | 76 | py |
rlmeta | rlmeta-main/rlmeta/agents/dqn/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from rlmeta.agents.dqn.apex_dqn_agent import (ApexDQNAgent, ApexDQNAgentFactory,
ConstantEpsFu... | 514 | 29.294118 | 80 | py |
rlmeta | rlmeta-main/rlmeta/agents/dqn/apex_dqn_agent.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import time
from concurrent.futures import Future, ThreadPoolExecutor
from typing import Callable, Dict, List, Optional, Sequence, Union
i... | 17,509 | 36.255319 | 80 | py |
rlmeta | rlmeta-main/rlmeta/samplers/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from _rlmeta_extension import Sampler, UniformSampler, PrioritizedSampler
__all__ = [
"Sampler",
"UniformSampler",
"Prioritized... | 332 | 24.615385 | 73 | py |
rlmeta | rlmeta-main/rlmeta/storage/storage.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import abc
from typing import Optional, Sequence, Tuple, Union
import numpy as np
from rlmeta.core.types import Tensor, NestedTensor
cl... | 1,262 | 19.704918 | 79 | py |
rlmeta | rlmeta-main/rlmeta/storage/tensor_circular_buffer.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Callable, Optional, Sequence, Tuple, Union
import numpy as np
import _rlmeta_extension
from rlmeta.core.types import N... | 1,809 | 26.014925 | 73 | py |
rlmeta | rlmeta-main/rlmeta/storage/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from rlmeta.storage.storage import Storage
from rlmeta.storage.circular_buffer import CircularBuffer
from rlmeta.storage.tensor_circular_buf... | 432 | 27.866667 | 70 | py |
rlmeta | rlmeta-main/rlmeta/storage/circular_buffer.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Callable, Optional, Sequence, Tuple, Union
import numpy as np
import rlmeta.utils.nested_utils as nested_utils
import r... | 2,650 | 30.559524 | 73 | py |
rlmeta | rlmeta-main/rlmeta/utils/asyncio_utils.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import asyncio
from typing import Awaitable
def handle_task_exception(task: asyncio.Task) -> None:
try:
task.result()
exc... | 585 | 23.416667 | 78 | py |
rlmeta | rlmeta-main/rlmeta/utils/loss_utils.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Any, Dict, Optional
import torch
import torch.nn as nn
_NAME_TO_LOSS = {
"huber": nn.HuberLoss,
"huber_loss": n... | 872 | 26.28125 | 77 | py |
rlmeta | rlmeta-main/rlmeta/utils/optimizer_utils.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Any, Iterable, Dict, Optional, Union
import torch
_NAME_TO_OPTIMIZER = {
"adadelta": torch.optim.Adadelta,
"ada... | 990 | 29.96875 | 69 | py |
rlmeta | rlmeta-main/rlmeta/utils/random_utils.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import random
import numpy as np
import torch
def manual_seed(seed: int) -> None:
random.seed(seed)
np.random.seed(seed)
torc... | 377 | 21.235294 | 65 | py |
rlmeta | rlmeta-main/rlmeta/utils/data_utils.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import io
import os
from typing import Any, Dict, Sequence, Tuple, Union
import numpy as np
import torch
import rlmeta.utils.nested_utils... | 3,056 | 26.294643 | 76 | py |
rlmeta | rlmeta-main/rlmeta/utils/moolib_utils.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import uuid
def generate_random_name() -> str:
return str(uuid.uuid4())
def expend_name_by_index(name: str, index: int) -> str:
... | 346 | 22.133333 | 65 | py |
rlmeta | rlmeta-main/rlmeta/utils/hydra_utils.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import json
import hydra
from omegaconf import DictConfig, OmegaConf
def config_to_json(cfg: OmegaConf) -> str:
return json.dumps(Ome... | 346 | 23.785714 | 65 | py |
rlmeta | rlmeta-main/rlmeta/utils/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
| 179 | 35 | 65 | py |
rlmeta | rlmeta-main/rlmeta/utils/nested_utils.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from _rlmeta_extension.nested_utils import *
| 225 | 31.285714 | 65 | py |
rlmeta | rlmeta-main/rlmeta/utils/running_stats.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
class RunningRMS(nn.Module):
def __init__(self,
... | 4,699 | 33.306569 | 79 | py |
rlmeta | rlmeta-main/rlmeta/utils/remote_utils.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Optional, Union
from rlmeta.core.remote import Remotable, Remote
from rlmeta.core.server import Server
def make_remote... | 521 | 29.705882 | 66 | py |
rlmeta | rlmeta-main/rlmeta/utils/stats_dict.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import annotations
import json
import math
from typing import Dict, Optional
from tabulate import tabulate
class StatsI... | 3,586 | 24.992754 | 79 | py |
rlmeta | rlmeta-main/rlmeta/data/segment_tree.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Optional, Union
import numpy as np
import torch
from _rlmeta_extension import SumSegmentTreeFp32, SumSegmentTreeFp64
fr... | 1,899 | 26.941176 | 72 | py |
rlmeta | rlmeta-main/rlmeta/data/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from rlmeta.data.segment_tree import SumSegmentTree
__all__ = [
"SumSegmentTree",
]
| 269 | 23.545455 | 65 | py |
rlmeta | rlmeta-main/rlmeta/ops/__init__.py | # Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from _rlmeta_extension.ops import *
| 216 | 30 | 65 | py |
LDEAlgsComparison | LDEAlgsComparison-master/scripts/generate.py | import subprocess
import sys
res = subprocess.Popen("python3 stressTest.py %s" % ' '.join(sys.argv[1:]), shell=True)
if res.wait() != 0:
print("Error") | 155 | 21.285714 | 87 | py |
LDEAlgsComparison | LDEAlgsComparison-master/scripts/stressTest.py | import time
import os
import subprocess
import sys
from random import randint, seed
exes = ["./ldegraphmain", "./slopesV7i"]
def checkSkip(n, m, mxVal):
if len(sys.argv) > 1:
mx1, mx2, n1, m1, n2, m2 = map(int, sys.argv[1:])
if mxVal < mx1 or mxVal > mx2:
return True
if n < n1 or n > n2:
r... | 5,592 | 34.624204 | 199 | py |
LDEAlgsComparison | LDEAlgsComparison-master/scripts/doComparison.py | from os import system
import sys
system("gcc -static slopesV7i.c -std=c11 -O3 -o slopesV7i")
system("g++ -static -lm -s -x c++ -std=c++17 -O3 -o ldegraphmain ldegraphmain.cpp ../src/ldegraphalg.cpp ../src/ldealg.cpp")
system("python3 generate.py %s" % ' '.join(sys.argv[1:])) | 276 | 45.166667 | 124 | py |
JOLLE | JOLLE-main/label_embedding_python/run_nn_ce_lshtc1.py | import torch
import numpy as np
from time import time
from sklearn.datasets import load_svmlight_files
import math
from nn_utils import *
import sys
seed = 20220510 # gonna use this integer to sample random seeds for different functions
max_int = np.iinfo(np.int32).max
rng = np.random.default_rng(seed)
train_path =... | 3,797 | 40.282609 | 170 | py |
JOLLE | JOLLE-main/label_embedding_python/run_nn_dmoz.py | import torch
import numpy as np
from time import time
from sklearn.datasets import load_svmlight_files
import math
from nn_utils import *
import sys
seed = 20230508
max_int = np.iinfo(np.int32).max
rng = np.random.default_rng(seed)
train_path = # TODO: fill the data path
val_path = # TODO: fill the data path
test_p... | 4,139 | 42.125 | 169 | py |
JOLLE | JOLLE-main/label_embedding_python/run_nn_odp.py | import torch
import numpy as np
from time import time
from sklearn.datasets import load_svmlight_files
import math
from nn_utils import *
import sys
seed = 20230508
max_int = np.iinfo(np.int32).max
rng = np.random.default_rng(seed)
train_path = # TODO: fill the data path
val_path = # TODO: fill the data path
test_p... | 4,345 | 42.029703 | 170 | py |
JOLLE | JOLLE-main/label_embedding_python/run_nn_lshtc1.py | import torch
import numpy as np
from time import time
from sklearn.datasets import load_svmlight_files
import math
from nn_utils import *
import sys
seed = 20230508
max_int = np.iinfo(np.int32).max
rng = np.random.default_rng(seed)
train_path = # TODO: fill the data path
val_path = # TODO: fill the data path
test_p... | 4,522 | 44.23 | 169 | py |
JOLLE | JOLLE-main/label_embedding_python/run_nn_sq_dmoz.py | import torch
import numpy as np
from time import time
from sklearn.datasets import load_svmlight_files
import math
from nn_utils import *
import sys
seed = 20220510 # gonna use this integer to sample random seeds for different functions
max_int = np.iinfo(np.int32).max
rng = np.random.default_rng(seed)
train_path =... | 3,764 | 39.923913 | 169 | py |
JOLLE | JOLLE-main/label_embedding_python/run_nn_ce_dmoz.py | import torch
import numpy as np
from time import time
from sklearn.datasets import load_svmlight_files
import math
from nn_utils import *
import sys
seed = 20220510 # gonna use this integer to sample random seeds for different functions
max_int = np.iinfo(np.int32).max
rng = np.random.default_rng(seed)
train_path =... | 3,793 | 40.23913 | 169 | py |
JOLLE | JOLLE-main/label_embedding_python/run_nn_sq_odp.py | import torch
import numpy as np
from time import time
from sklearn.datasets import load_svmlight_files
import math
from nn_utils import *
seed = 20230508
max_int = np.iinfo(np.int32).max
rng = np.random.default_rng(seed)
train_path = # TODO: fill the data path
val_path = # TODO: fill the data path
test_path = # TODO... | 4,026 | 40.091837 | 170 | py |
JOLLE | JOLLE-main/label_embedding_python/run_nn_sq_lshtc1.py | import torch
import numpy as np
from time import time
from sklearn.datasets import load_svmlight_files
import math
from nn_utils import *
import sys
seed = 20220510 # gonna use this integer to sample random seeds for different functions
max_int = np.iinfo(np.int32).max
rng = np.random.default_rng(seed)
train_path =... | 3,849 | 39.957447 | 169 | py |
JOLLE | JOLLE-main/label_embedding_python/run_nn_ce_odp.py | import torch
import numpy as np
from time import time
from sklearn.datasets import load_svmlight_files
import math
from nn_utils import *
seed = 20230508
max_int = np.iinfo(np.int32).max
rng = np.random.default_rng(seed)
train_path = # TODO: fill the data path
val_path = # TODO: fill the data path
test_path = # TODO... | 3,972 | 40.385417 | 170 | py |
JOLLE | JOLLE-main/label_embedding_python/nn_utils.py | import torch
from sklearn.metrics import pairwise_distances
import numpy as np
class sparse_dataset(torch.utils.data.Dataset):
def __init__(self, x, y):
self.x = x
self.y = y
self.n_features = x.shape[1]
def __len__(self):
return self.x.shape[0]
def __getitem__(sel... | 4,296 | 41.127451 | 145 | py |
graphlaxy | graphlaxy-master/GraphlaxyDataGen.py | #!/usr/bin/env python
import argparse
import sys
class Graphlaxy(object):
def __init__(self):
parser = argparse.ArgumentParser(
description='Tool used to create synthetic graph datasets using \'Nash Bargin Scheme\' optimization.',
usage='''gdg <command> [<args>]
The available com... | 10,767 | 55.376963 | 213 | py |
graphlaxy | graphlaxy-master/processes/optimization.py | from pathlib import Path
import numpy as np
import pandas as pd
from scipy.optimize import minimize
from utils.filesystem import add_to_csv
from .bargin import grid_bargin, gen_metric_grid, gen_param_grid
def store_params(dataset_folder, name, params, i = None):
if i is not None:
name = "{}_{}".format(name,i)
... | 1,536 | 28.557692 | 80 | py |
graphlaxy | graphlaxy-master/processes/baseline_dataset.py | import random
import numpy as np
from pathlib import Path
from utils.rmat import rmat_to_file
def generate_baseline(
dataset_folder = "../baseline_dataset",
dataset_size = 10000,
edges_between = (1000,1000000),
multiprocess = False):
Path(dataset_folder,'graphs').mkdir(parents=True, exist_ok=True... | 1,520 | 31.361702 | 121 | py |
graphlaxy | graphlaxy-master/processes/result_dataset.py | import random
import numpy as np
from pathlib import Path
import pandas as pd
from utils.rmat import rmat_to_file
from utils.probability import beta_rvs_shifted, beta_rvs_discrete_shifted
def generate_result_dataset(
from_file = True,
custom_weights = [1] *8,
param_file = "../baseline_dataset/parameters.c... | 2,200 | 30.898551 | 121 | py |
graphlaxy | graphlaxy-master/processes/bargin.py | import numpy as np
import pandas as pd
from utils.probability import beta_cdf_interval, beta_cdf_mean, beta_cdf_mean_2d
def get_grid(m=10,
limits = [(0,1),(-6,-1)]):
block0 = np.linspace(limits[0][0], limits[0][1], m + 1)
block1 = np.linspace(limits[1][0], limits[1][1], m + 1)
return [block0,... | 3,465 | 32.326923 | 156 | py |
graphlaxy | graphlaxy-master/processes/statistics.py | import pandas as pd
from pathlib import Path
def statistics(
dataset_folder = "../baseline_dataset",
samples = 1000
):
print("Loading Dataset...")
df = pd.read_csv(Path(dataset_folder, "dataset_metrics.csv")).head(samples)
print("correlation: ", df["density_log"].corr(df["clustering"]... | 723 | 37.105263 | 79 | py |
graphlaxy | graphlaxy-master/processes/metrics.py | import pandas as pd
import networkx as nx
import numpy as np
from pathlib import Path
from utils.filesystem import read_graph, add_to_csv
import multiprocessing as mp
lock = mp.Lock()
def _metrics(dataset_folder, row, trials):
a = row['a']
b = row['b']
c = row['c']
d = 1 - a - b - c
G = re... | 1,723 | 30.345455 | 96 | py |
graphlaxy | graphlaxy-master/processes/plot.py | from argparse import ArgumentError
import random
from statistics import mean
import pandas as pd
import numpy as np
from pathlib import Path
from matplotlib import pyplot as plt
from utils.probability import beta_rvs_shifted
from scipy.stats import beta, uniform
from .bargin import gen_param_grid, gen_weights, gen_me... | 8,500 | 34.569038 | 94 | py |
graphlaxy | graphlaxy-master/processes/__init__.py | __all__ = ["baseline_dataset", "metrics", "optimization", "plot", "result_dataset"] | 83 | 83 | 83 | py |
graphlaxy | graphlaxy-master/utils/probability.py | import numpy as np
from scipy.stats import beta
def beta_cdf_interval(interval, a, b, interval_shift):
low = interval_shift[0]
up = interval_shift[1]
if up - low <= 0:
return 0
return beta.cdf(interval.right, a, b, loc = low, scale = up - low) -\
beta.cdf(interval.left, a, b, loc = low, scale = up - lo... | 1,558 | 34.431818 | 96 | py |
graphlaxy | graphlaxy-master/utils/rmat.py | from pathlib import Path
import numpy as np
import multiprocessing as mp
import networkit as nk
from utils.filesystem import add_to_csv
lock = mp.Lock()
def rmat_to_file(N, E, a, b, c, d, dataset_folder, s):
scale = np.ceil(np.log2(N))
factor = E/N
reduce = np.power(2, scale) - N
Graph = nk.generators.RmatG... | 1,080 | 37.607143 | 119 | py |
graphlaxy | graphlaxy-master/utils/filesystem.py | import os
import csv
import networkx as nx
def add_to_csv(path, data):
if os.path.exists(path):
with open(path, 'a', newline='') as f:
w = csv.DictWriter(f, data.keys())
w.writerow(data)
else:
with open(path, 'w', newline='') as f:
w = csv.DictWriter(f, data.keys())
... | 483 | 23.2 | 49 | py |
graphlaxy | graphlaxy-master/utils/__init__.py | 0 | 0 | 0 | py | |
graphlaxy | graphlaxy-master/utils/multiprocess.py | def pebble_timeout_callback(future):
try:
future.result() # blocks until results are ready
except TimeoutError as error:
print("Function took longer than %d seconds" % error.args[1])
except Exception as error:
print("Function raised %s" % error)
if hasattr(error, "traceback"... | 384 | 41.777778 | 69 | py |
apicarver | apicarver-main/restats/app.py | from pathlib import Path
import sys
import json
import core.pairing as pairing
import core.statistic as stat
import utils.parsers as par
def callOptionMethod(confDict):
modules = confDict['modules']
# Extract data from specification (needed to parse pairs)
specDict = par.extractSpecificationData(conf['specificat... | 3,165 | 33.043011 | 127 | py |
apicarver | apicarver-main/restats/__init__.py | 0 | 0 | 0 | py | |
apicarver | apicarver-main/restats/core/statistic.py | from pathlib import Path
import json
import utils.parsers as parsers
import utils.dbmanager as dbm
# dest = None
jsonTestedKey = 'documentedAndTested'
jsonNotTestedKey = 'documentedAndNotTested'
jsonNotExpectedKey = 'notDocumentedAndTested'
jsonFoundKey = 'totalTested'
jsonTotalKey = 'documented'
def getPathCoverage... | 14,042 | 29.728665 | 141 | py |
apicarver | apicarver-main/restats/core/__init__.py | 0 | 0 | 0 | py | |
apicarver | apicarver-main/restats/core/pairing.py | import os
from pathlib import Path
import re
import json
from ruamel import yaml
import utils
import utils.parsers as parsers
import utils.dbmanager as dbm
import ruamel.yaml
def addSpecToDB(pair):
#####################
#### POPULATE DB ####
pathID = dbm.getPathID(pair['request']['path'])
method = pair['reques... | 23,948 | 27.612903 | 125 | py |
apicarver | apicarver-main/restats/utils/dbmanager.py | import sqlite3
from sqlite3 import Error
conn = None
def create_connection(dbfile):
""" create a database connection to the SQLite database
specified by db_file
:param db_file: database file
:return: Connection object or None
"""
global conn
try:
conn = sqlite3.connect(dbfile)... | 6,221 | 22.044444 | 93 | py |
apicarver | apicarver-main/restats/utils/parsers.py | import traceback
from urllib.parse import parse_qs, urlsplit
import json
import ruamel.yaml
methodsWithRequestBody = {'post', 'put', 'patch'}
def parsePostData(postData):
params = {}
if postData is None:
print("Cannot parse None")
return None
if type(postData) is dict and "string" in postData.keys():
postDa... | 17,544 | 26.982456 | 113 | py |
apicarver | apicarver-main/restats/utils/__init__.py | 0 | 0 | 0 | py | |
apicarver | apicarver-main/testCarver/pythonCode/runEvoMaster.py | import glob
import os
import shutil
from datetime import datetime
import constants
from constants import RUN_SCHEMATHESIS_COMMAND, APPS, STATUS_SUCCESSFUL, STATUS_SKIPPED, STATUS_ERRORED, CASETTE_YAML, \
SCHEMATHESIS_OUTPUT
from utilsRun import monitorProcess, cleanup, startProcess, restartDocker, MODE
def runAl... | 6,598 | 35.865922 | 160 | py |
apicarver | apicarver-main/testCarver/pythonCode/constants.py | import os.path
# APPS = ['medical']
APPS = ['petclinic', 'parabank', 'realworld', 'booker', 'jawa', 'medical', 'ecomm']
DOCKER_LOCATION = os.path.abspath('../src/main/resources/webapps')
RUN_CARVER_COMMAND = ['java', '-Xmx8G', '-Xss1G', '-cp', 'target/testCarver-0.0.1-SNAPSHOT-jar-with-dependencies.jar',
... | 2,633 | 29.627907 | 118 | py |
apicarver | apicarver-main/testCarver/pythonCode/runGeneratedTests.py | import glob
import os
from datetime import datetime, timedelta
import constants
from constants import APPS, STATUS_SUCCESSFUL, STATUS_ERRORED
from utilsRun import restartDocker, startProcess, monitorProcess, getDockerName, cleanup, MODE, exportJson
# BASE_COMMAND_HYBRID = ['sh', 'runTests.sh']
BASE_COMMAND = ['sh', '... | 6,899 | 29 | 137 | py |
apicarver | apicarver-main/testCarver/pythonCode/utilsRun.py | import csv
import json
import os
import subprocess
from datetime import datetime
from enum import Enum
from subprocess import check_call, CalledProcessError, Popen
from time import sleep
import psutil
from constants import DOCKER_LOCATION, STATUS_SUCCESSFUL
def getDockerName(appName):
return appName
def restartD... | 4,316 | 22.983333 | 113 | py |
apicarver | apicarver-main/testCarver/pythonCode/runSchemathesis.py | import glob
import os
import shutil
from datetime import datetime
import constants
from constants import RUN_SCHEMATHESIS_COMMAND, APPS, STATUS_SUCCESSFUL, STATUS_SKIPPED, STATUS_ERRORED, CASETTE_YAML, \
SCHEMATHESIS_OUTPUT
from utilsRun import monitorProcess, cleanup, startProcess, restartDocker, MODE
def runAl... | 6,970 | 39.063218 | 134 | py |
apicarver | apicarver-main/testCarver/pythonCode/rq1_executionTime.py | import glob
import os.path
from datetime import datetime
import utilsRun
from constants import APPS
from coverageStats import getCovFiles
from runCarver import getExistingCarverRun
from runGeneratedTests import getCrawlsToAnalyze, getExistingCrawl
from utilsRun import importJson
def findAllOutputs(ALL_CRAWLS="../cra... | 3,289 | 37.255814 | 142 | py |
apicarver | apicarver-main/testCarver/pythonCode/parseRestatsOutput.py | import os
from datetime import datetime
import constants
import runRestats
import utilsRun
def fetchRestatsOutputDir(appName):
returnDict = {}
toolOutputs = runRestats.getExistingOutput(appName)
if toolOutputs is None:
print("No restats results found {}".format(appName))
return None
f... | 12,307 | 45.621212 | 156 | py |
apicarver | apicarver-main/testCarver/pythonCode/runRestats.py | import glob
import os.path
from datetime import datetime
from enum import Enum
import constants
import utilsRun
from constants import APPS, STATUS_ERRORED, STATUS_SUCCESSFUL, STATUS_SKIPPED, RUN_RESTATS_COMMAND, \
RESULT_RESPONSES_JSON, SCHEMATHESIS_OUTPUT, CASETTE_YAML, PROBER_RESPONSES_JSON, INFERRED_YAML, PROBE... | 24,223 | 42.963702 | 185 | py |
apicarver | apicarver-main/testCarver/pythonCode/scratch_1.py | import glob
import os
# print(os.path.splitext("../a/b/c.json")[0])
# carverRecords = "../a/c.json"
#
# dir = os.path.pathsep.join(os.path.split(carverRecords)[0:len(os.path.split(carverRecords))-1])
# print(dir)
import constants
import coverageStats
from constants import RESULT_RESPONSES_JSON
# print(glob.glob( "/Te... | 450 | 27.1875 | 100 | py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.