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 |
|---|---|---|---|---|---|---|
cowrie | cowrie-master/src/backend_pool/__init__.py | 0 | 0 | 0 | py | |
cowrie | cowrie-master/src/backend_pool/libvirt/backend_service.py | # Copyright (c) 2019 Guilherme Borges <guilhermerosasborges@gmail.com>
# See the COPYRIGHT file for more information
from __future__ import annotations
import os
import random
import sys
import uuid
from twisted.python import log
import backend_pool.libvirt.guest_handler
import backend_pool.libvirt.network_handler
... | 6,096 | 29.949239 | 110 | py |
cowrie | cowrie-master/src/backend_pool/libvirt/guest_handler.py | # Copyright (c) 2019 Guilherme Borges <guilhermerosasborges@gmail.com>
# See the COPYRIGHT file for more information
from __future__ import annotations
import os
import sys
from configparser import NoOptionError
from twisted.python import log
import backend_pool.libvirt.snapshot_handler
import backend_pool.util
from ... | 3,677 | 31.548673 | 100 | py |
cowrie | cowrie-master/src/backend_pool/libvirt/snapshot_handler.py | # Copyright (c) 2019 Guilherme Borges <guilhermerosasborges@gmail.com>
# See the COPYRIGHT file for more information
from __future__ import annotations
import getpass
import shutil
import subprocess
def create_disk_snapshot(source_img, destination_img):
try:
shutil.chown(source_img, getpass.getuser())
... | 816 | 23.029412 | 89 | py |
cowrie | cowrie-master/src/backend_pool/libvirt/network_handler.py | # Copyright (c) 2019 Guilherme Borges <guilhermerosasborges@gmail.com>
# See the COPYRIGHT file for more information
from __future__ import annotations
import os
import sys
from twisted.python import log
import backend_pool.util
from cowrie.core.config import CowrieConfig
def create_filter(connection):
# lazy i... | 3,145 | 30.777778 | 103 | py |
cowrie | cowrie-master/src/backend_pool/libvirt/__init__.py | 0 | 0 | 0 | py | |
cowrie | cowrie-master/bin/createdynamicprocess.py | #!/usr/bin/env python
import datetime
import json
import random
import psutil
command: dict = {}
command["command"] = {}
command["command"]["ps"] = []
randomStates = ["Ss", "S<", "D<", "Ss+"]
for proc in psutil.process_iter():
try:
info = proc.as_dict(
attrs=[
"pid",
... | 1,592 | 26.947368 | 88 | py |
cowrie | cowrie-master/docs/conf.py | #
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup --------------------------------------------------------------
# If extensions (or ... | 6,383 | 30.141463 | 85 | py |
overcooked_ai | overcooked_ai-master/setup.py | #!/usr/bin/env python
from setuptools import find_packages, setup
with open("README.md", "r", encoding="UTF8") as fh:
long_description = fh.read()
setup(
name="overcooked_ai",
version="1.1.0",
description="Cooperative multi-agent environment based on Overcooked",
long_description=long_description... | 2,151 | 27.693333 | 101 | py |
overcooked_ai | overcooked_ai-master/testing/visualization_test.py | import copy
import json
import os
import unittest
import numpy as np
import pygame
from overcooked_ai_py.agents.agent import RandomAgent
from overcooked_ai_py.agents.benchmarking import AgentEvaluator
from overcooked_ai_py.mdp.overcooked_mdp import (
OvercookedGridworld,
OvercookedState,
Recipe,
)
from ov... | 9,206 | 33.743396 | 162 | py |
overcooked_ai | overcooked_ai-master/testing/overcooked_test.py | import copy
import glob
import json
import os
import shutil
import unittest
from math import factorial
import gym
import numpy as np
from overcooked_ai_py.agents.agent import (
AgentGroup,
AgentPair,
FixedPlanAgent,
GreedyHumanModel,
RandomAgent,
)
from overcooked_ai_py.agents.benchmarking import ... | 63,066 | 34.391134 | 112 | py |
overcooked_ai | overcooked_ai-master/testing/utils.py | import numpy as np
from overcooked_ai_py.agents.benchmarking import AgentEvaluator
# The point of this function is to generate serialized trajectories for MDP dynamics consistency testing
# NOTE: If intentionally updating MDP dynamics, this function should be used
def generate_serialized_trajectory(mdp, save_path):... | 754 | 34.952381 | 104 | py |
overcooked_ai | overcooked_ai-master/testing/planners_test.py | import unittest
from overcooked_ai_py.agents.agent import AgentPair, GreedyHumanModel
from overcooked_ai_py.agents.benchmarking import AgentEvaluator
from overcooked_ai_py.mdp.actions import Action, Direction
from overcooked_ai_py.mdp.overcooked_env import OvercookedEnv
from overcooked_ai_py.mdp.overcooked_mdp import ... | 32,663 | 34.084855 | 111 | py |
overcooked_ai | overcooked_ai-master/testing/agent_test.py | import unittest
import numpy as np
from overcooked_ai_py.agents.agent import (
AgentPair,
FixedPlanAgent,
GreedyHumanModel,
RandomAgent,
SampleAgent,
)
from overcooked_ai_py.agents.benchmarking import AgentEvaluator
from overcooked_ai_py.mdp.actions import Action, Direction
from overcooked_ai_py.m... | 13,226 | 32.656489 | 110 | py |
overcooked_ai | overcooked_ai-master/testing/mdp_gen_schedule_test.py | import unittest
import numpy as np
from overcooked_ai_py.agents.benchmarking import AgentEvaluator
from overcooked_ai_py.mdp.actions import Action, Direction
from overcooked_ai_py.mdp.overcooked_mdp import (
ObjectState,
OvercookedGridworld,
PlayerState,
)
np.random.seed(42)
n, s = Direction.NORTH, Dire... | 6,279 | 32.582888 | 106 | py |
overcooked_ai | overcooked_ai-master/testing/__init__.py | 0 | 0 | 0 | py | |
overcooked_ai | overcooked_ai-master/src/overcooked_demo/__init__.py | import os
import subprocess
def start_server():
dir_path = os.path.dirname(os.path.realpath(__file__))
os.chdir(dir_path)
subprocess.call("./up.sh")
def move_agent():
from overcooked_demo.server.move_agents import main
dir_path = os.path.dirname(os.path.realpath(__file__))
os.chdir(os.path.... | 357 | 20.058824 | 58 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_demo/server/app.py | import os
import sys
# Import and patch the production eventlet server if necessary
if os.getenv("FLASK_ENV", "production") == "production":
import eventlet
eventlet.monkey_patch()
import atexit
import json
import logging
# All other imports must come after patch to ensure eventlet compatibility
import pick... | 20,001 | 28.80924 | 159 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_demo/server/utils.py | import os
from threading import Lock
# this is the mounted volume
DOCKER_VOLUME = "/app/data"
class ThreadSafeSet(set):
def __init__(self, *args, **kwargs):
super(ThreadSafeSet, self).__init__(*args, **kwargs)
self.lock = Lock()
def add(self, *args):
with self.lock:
retva... | 2,329 | 25.781609 | 77 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_demo/server/move_agents.py | import argparse
import json
import os
import shutil
import sys
def main():
with open("config.json", "r") as f:
config = json.load(f)
# the agents dir
agent_dir = config["AGENT_DIR"]
parser = argparse.ArgumentParser(
prog="move_agent",
description="Create a directory for agent t... | 2,297 | 28.088608 | 125 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_demo/server/__init__.py | 0 | 0 | 0 | py | |
overcooked_ai | overcooked_ai-master/src/overcooked_demo/server/game.py | import json
import os
import pickle
import random
from abc import ABC, abstractmethod
from queue import Empty, Full, LifoQueue, Queue
from threading import Lock, Thread
from time import time
import ray
from utils import DOCKER_VOLUME, create_dirs
from human_aware_rl.rllib.rllib import load_agent
from overcooked_ai_py... | 31,851 | 32.248434 | 158 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/utils.py | import cProfile
import io
import json
import os
import pickle
import pstats
import tempfile
import uuid
from collections import defaultdict
from collections.abc import Iterable
from pathlib import Path
import numpy as np
from numpy import nan
from overcooked_ai_py.static import LAYOUTS_DIR
# I/O
def save_pickle(da... | 5,751 | 22.966667 | 93 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/__init__.py | from gym.envs.registration import register
register(
id="Overcooked-v0",
entry_point="overcooked_ai_py.mdp.overcooked_env:Overcooked",
)
| 146 | 20 | 65 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/static.py | import os
_current_dir = os.path.dirname(os.path.abspath(__file__))
DATA_DIR = os.path.join(_current_dir, "data")
HUMAN_DATA_DIR = os.path.join(DATA_DIR, "human_data")
PLANNERS_DIR = os.path.join(DATA_DIR, "planners")
LAYOUTS_DIR = os.path.join(DATA_DIR, "layouts")
GRAPHICS_DIR = os.path.join(DATA_DIR, "graphics")
FON... | 414 | 36.727273 | 57 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/agents/benchmarking.py | import copy
import numpy as np
from overcooked_ai_py.agents.agent import (
AgentPair,
GreedyHumanModel,
RandomAgent,
)
from overcooked_ai_py.mdp.layout_generator import LayoutGenerator
from overcooked_ai_py.mdp.overcooked_env import OvercookedEnv
from overcooked_ai_py.mdp.overcooked_mdp import (
Actio... | 21,055 | 35.366149 | 131 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/agents/agent.py | import itertools
import math
import os
from collections import defaultdict
import dill
import numpy as np
from overcooked_ai_py.mdp.actions import Action
from overcooked_ai_py.mdp.overcooked_mdp import Recipe
from overcooked_ai_py.utils import OvercookedException
class Agent(object):
agent_file_name = "agent.pi... | 26,870 | 36.740169 | 152 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/agents/__init__.py | 0 | 0 | 0 | py | |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/mdp/layout_generator.py | import copy
import random
import numpy as np
from overcooked_ai_py.mdp.actions import Action, Direction
from overcooked_ai_py.mdp.overcooked_mdp import OvercookedGridworld, Recipe
from overcooked_ai_py.utils import rnd_int_uniform, rnd_uniform
EMPTY = " "
COUNTER = "X"
ONION_DISPENSER = "O"
TOMATO_DISPENSER = "T"
PO... | 20,796 | 33.037643 | 134 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/mdp/actions.py | import copy
import itertools
import numpy as np
class Direction(object):
"""
The four possible directions a player can be facing.
"""
NORTH = (0, -1)
SOUTH = (0, 1)
EAST = (1, 0)
WEST = (-1, 0)
ALL_DIRECTIONS = INDEX_TO_DIRECTION = [NORTH, SOUTH, EAST, WEST]
DIRECTION_TO_INDEX = ... | 4,077 | 29.893939 | 78 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/mdp/overcooked_env.py | import copy
import time
import cv2
import gym
import gymnasium
import numpy as np
import pygame
import tqdm
from overcooked_ai_py.mdp.actions import Action
from overcooked_ai_py.mdp.overcooked_mdp import (
EVENT_TYPES,
OvercookedGridworld,
)
from overcooked_ai_py.mdp.overcooked_trajectory import (
DEFAULT... | 35,211 | 36.619658 | 145 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/mdp/overcooked_mdp.py | import copy
import itertools
import warnings
from collections import Counter, defaultdict
from functools import reduce
import numpy as np
from overcooked_ai_py.mdp.actions import Action, Direction
from overcooked_ai_py.utils import (
OvercookedException,
classproperty,
pos_distance,
read_layout_dict,
... | 127,017 | 37.327701 | 168 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/mdp/__init__.py | 0 | 0 | 0 | py | |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/mdp/overcooked_trajectory.py | import numpy as np
"""
NOTE: Currently under construction...
TODO: stretch goal of taking object-oriented approach to trajectories by creating Trajectory class.
This would require changes both throughout this repo and overcooked-ai repo, so it's blue sky goal for now
This file's utility functions represents a pri... | 3,430 | 41.358025 | 184 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/visualization/visualization_utils.py | from IPython.display import Image, display
from ipywidgets import IntSlider, interactive
def show_image_in_ipython(data, *args, **kwargs):
display(Image(data, *args, **kwargs))
def ipython_images_slider(image_pathes_list, slider_label="", first_arg=0):
def display_f(**kwargs):
display(Image(image_pa... | 950 | 23.384615 | 75 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/visualization/state_visualizer.py | import copy
import math
import os
import pygame
from overcooked_ai_py.mdp.actions import Action, Direction
from overcooked_ai_py.mdp.layout_generator import (
COUNTER,
DISH_DISPENSER,
EMPTY,
ONION_DISPENSER,
POT,
SERVING_LOC,
TOMATO_DISPENSER,
)
from overcooked_ai_py.static import FONTS_DI... | 27,047 | 36.776536 | 191 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/visualization/pygame_utils.py | import pygame
from pygame.locals import DOUBLEBUF, HWSURFACE, QUIT, RESIZABLE, VIDEORESIZE
from overcooked_ai_py.utils import load_from_json
def run_static_resizeable_window(surface, fps=30):
"""
window that can be resized and closed using gui
"""
pygame.init()
clock = pygame.time.Clock()
win... | 4,406 | 35.122951 | 158 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/visualization/__init__.py | 0 | 0 | 0 | py | |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/planning/planners.py | import itertools
import os
import pickle
import time
import numpy as np
from overcooked_ai_py.data.planners import (
PLANNERS_DIR,
load_saved_action_manager,
load_saved_motion_planner,
)
from overcooked_ai_py.mdp.actions import Action, Direction
from overcooked_ai_py.mdp.overcooked_mdp import (
EVENT_... | 93,753 | 41.94732 | 156 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/planning/__init__.py | 0 | 0 | 0 | py | |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/planning/search.py | import heapq
import time
import numpy as np
import scipy.sparse
class SearchTree(object):
"""
A class to help perform tree searches of various types. Once a goal state is found, returns a list of tuples
containing (action, state) pairs. This enables to recover the optimal action and state path.
Args... | 11,855 | 33.365217 | 131 | py |
overcooked_ai | overcooked_ai-master/src/overcooked_ai_py/data/planners/__init__.py | import os
import pickle
from overcooked_ai_py.static import PLANNERS_DIR
from overcooked_ai_py.utils import load_dict_from_file
def load_saved_action_manager(filename):
with open(os.path.join(PLANNERS_DIR, filename), "rb") as f:
mlp_action_manager = pickle.load(f)
return mlp_action_manager
def ... | 491 | 26.333333 | 63 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/data_dir.py | import os
DATA_DIR = os.path.abspath(".")
| 43 | 10 | 31 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/utils.py | import itertools
import json
import os
import random
import re
import shutil
import git
import numpy as np
import tensorflow as tf
WANDB_PROJECT = "Overcooked AI"
def delete_dir_if_exists(dir_path, verbose=False):
if os.path.exists(dir_path):
if verbose:
print("Deleting old dir", dir_path)
... | 6,341 | 27.567568 | 99 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/__init__.py | 0 | 0 | 0 | py | |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/human/human_data_forward_compat.py | import argparse
import os
import numpy as np
import pandas as pd
from human_aware_rl.human.data_processing_utils import AI_ID
from human_aware_rl.static import NEW_SCHEMA, OLD_SCHEMA
"""
Script for converting legacy-schema human data to current schema.
Note: This script, and working with the raw CSV files in genera... | 3,473 | 30.581818 | 133 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/human/tests.py | import copy
import os
import pickle
import shutil
import sys
import unittest
import numpy as np
from numpy.testing._private.utils import assert_raises
from human_aware_rl.human.process_dataframes import (
csv_to_df_pickle,
get_trajs_from_data,
)
from human_aware_rl.human.process_human_trials import (
main... | 7,837 | 35.119816 | 106 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/human/process_human_trials.py | import argparse
import copy
import json
import os
import pickle
import pandas as pd
from human_aware_rl.human.data_processing_utils import (
json_joint_action_to_python_action,
)
from overcooked_ai_py.mdp.overcooked_mdp import (
OvercookedGridworld,
OvercookedState,
)
from overcooked_ai_py.planning.planne... | 14,590 | 36.032995 | 154 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/human/data_processing_utils.py | import json
import time
import numpy as np
from overcooked_ai_py.agents.benchmarking import AgentEvaluator
from overcooked_ai_py.mdp.actions import Action, Direction
from overcooked_ai_py.mdp.overcooked_mdp import (
ObjectState,
OvercookedGridworld,
OvercookedState,
PlayerState,
)
AI_ID = "I am robot... | 9,152 | 32.405109 | 122 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/human/process_dataframes.py | import copy
import json
import os
import random
from collections import defaultdict
from typing import DefaultDict
import numpy as np
import pandas as pd
from numpy.core.numeric import full
from human_aware_rl.human.data_processing_utils import (
convert_joint_df_trajs_to_overcooked_single,
df_traj_to_python_... | 17,347 | 32.555126 | 150 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/human/__init__.py | import os
_curr_directory = os.path.dirname(os.path.abspath(__file__))
| 72 | 17.25 | 60 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/imitation/behavior_cloning_tf2_test.py | import argparse
import os
import pickle
import shutil
import sys
import unittest
import warnings
import numpy as np
import tensorflow as tf
from human_aware_rl.human.process_dataframes import get_trajs_from_data
from human_aware_rl.imitation.behavior_cloning_tf2 import (
BC_SAVE_DIR,
build_bc_model,
evalu... | 7,736 | 33.851351 | 130 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/imitation/reproduce_bc.py | import os
from human_aware_rl.imitation.behavior_cloning_tf2 import (
get_bc_params,
train_bc_model,
)
from human_aware_rl.static import (
CLEAN_2019_HUMAN_DATA_TEST,
CLEAN_2019_HUMAN_DATA_TRAIN,
)
if __name__ == "__main__":
# random 3 is counter_circuit
# random 0 is forced coordination
#... | 1,594 | 36.97619 | 161 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/imitation/__init__.py | 0 | 0 | 0 | py | |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/imitation/behavior_cloning_tf2.py | import copy
import os
import pickle
import numpy as np
import tensorflow as tf
from ray.rllib.policy import Policy as RllibPolicy
from tensorflow import keras
from tensorflow.compat.v1.keras.backend import get_session, set_session
from human_aware_rl.data_dir import DATA_DIR
from human_aware_rl.human.process_datafram... | 22,092 | 31.925484 | 144 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/rllib/tests.py | import copy
import unittest
from math import isclose
import numpy as np
from human_aware_rl.rllib.rllib import OvercookedMultiAgent
from human_aware_rl.rllib.utils import (
get_required_arguments,
iterable_equal,
softmax,
)
class RllibEnvTest(unittest.TestCase):
def setUp(self):
print(
... | 5,864 | 27.609756 | 79 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/rllib/utils.py | import inspect
import numpy as np
from overcooked_ai_py.agents.benchmarking import AgentEvaluator
def softmax(logits):
e_x = np.exp(logits.T - np.max(logits))
return (e_x / np.sum(e_x, axis=0)).T
def get_base_env(
mdp_params, env_params, outer_shape=None, mdp_params_schedule_fn=None
):
ae = get_ba... | 2,730 | 27.154639 | 73 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/rllib/__init__.py | 0 | 0 | 0 | py | |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/rllib/rllib.py | import copy
import logging
import os
import random
import tempfile
from datetime import datetime
import dill
import gym
import numpy as np
import ray
from ray.rllib.agents.ppo import PPOTrainer
from ray.rllib.algorithms.callbacks import DefaultCallbacks
from ray.rllib.env.multi_agent_env import MultiAgentEnv
from ray.... | 34,142 | 36.936667 | 145 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/ppo/ppo_rllib_client.py | # All imports except rllib
import argparse
import os
import sys
import warnings
import numpy as np
from overcooked_ai_py.agents.benchmarking import AgentEvaluator
warnings.simplefilter("ignore")
# environment variable that tells us whether this code is running on the server or not
LOCAL_TESTING = os.getenv("RUN_ENV... | 13,930 | 31.625293 | 164 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/ppo/evaluate.py | import os
import warnings
import numpy as np
from human_aware_rl.imitation.behavior_cloning_tf2 import (
BehaviorCloningPolicy,
_get_base_ae,
evaluate_bc_model,
load_bc_model,
)
from human_aware_rl.rllib.rllib import (
AgentPair,
RlLibAgent,
evaluate,
get_agent_from_trainer,
load_a... | 6,394 | 32.657895 | 163 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/ppo/ppo_rllib_from_params_client.py | # All imports except rllib
import argparse
import logging
import os
import sys
import numpy as np
from overcooked_ai_py.agents.benchmarking import AgentEvaluator
# environment variable that tells us whether this code is running on the server or not
LOCAL_TESTING = os.getenv("RUN_ENV", "production") == "local"
# Sac... | 15,308 | 30.630165 | 106 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/ppo/ppo_rllib.py | import numpy as np
import tensorflow as tf
from ray.rllib.models.tf.recurrent_net import RecurrentNetwork
from ray.rllib.models.tf.tf_modelv2 import TFModelV2
class RllibPPOModel(TFModelV2):
"""
Model that will map environment states to action probabilities. Will be shared across agents
"""
def __ini... | 8,450 | 34.508403 | 110 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/ppo/plot_graph.py | import os
import matplotlib.font_manager
import matplotlib.pyplot as plt
import numpy as np
from evaluate import eval_models
from matplotlib.patches import Patch
# importing from utils causes werid dependency conflicts. Copying here
def set_style(font_scale=1.6):
import matplotlib
import seaborn
seaborn... | 4,747 | 24.390374 | 114 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/ppo/__init__.py | 0 | 0 | 0 | py | |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/ppo/ppo_rllib_test.py | import glob
import os
import pickle
import random
import shutil
import unittest
import warnings
import ray
os.environ["RUN_ENV"] = "local"
import numpy as np
import tensorflow as tf
from human_aware_rl.data_dir import DATA_DIR
from human_aware_rl.imitation.behavior_cloning_tf2 import (
get_bc_params,
train_b... | 14,076 | 36.044737 | 154 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/ppo/plot_example_experiments.py | import os
import re
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from human_aware_rl.utils import *
from human_aware_rl.utils import set_style
envs = [
"cramped_room",
"forced_coordination",
"counter_circuit_o_1",
"coordination_ring",
"asymmetric_advantages",
]
def get_l... | 1,874 | 21.321429 | 75 | py |
overcooked_ai | overcooked_ai-master/src/human_aware_rl/static/__init__.py | import os
_curr_directory = os.path.dirname(os.path.abspath(__file__))
# Root dir where all hunan data is located
HUMAN_DATA_DIR = os.path.join(_curr_directory, "human_data")
# Paths to pre-processed data
CLEAN_HUMAN_DATA_DIR = os.path.join(HUMAN_DATA_DIR, "cleaned")
CLEAN_2020_HUMAN_DATA_ALL = os.path.join(
CLE... | 3,062 | 24.106557 | 72 | py |
CBA | CBA-main/vignette.py | #this file is to teach you how to use CBA
"""
Created on Fri Mar 27 18:58:59 2020
@author: 17b90
"""
import kBET
import scipy
import random
import keras as K
import numpy as np
import pandas as pd
import scanpy as sc
import seaborn as sns
import scipy.io as sio
import tensorflow as tf
from keras import layers
from ywb... | 30,327 | 46.76063 | 185 | py |
CBA | CBA-main/evaluation/evaluation_pancreas.py | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 27 18:58:59 2020
@author: 17b90
"""
import keras as K
import pandas as pd
from keras import layers
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
from sklearn.decomposition import PCA
import scanpy as sc
import scipy
import pickle
from sklearn... | 4,698 | 38.487395 | 118 | py |
CBA | CBA-main/lung/kBET.py | # -*- coding: utf-8 -*-
"""
Created on Sun Jan 31 10:41:54 2021
@author: 17b90
"""
import numpy as np
import anndata
import scanpy as sc
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.sparse.csgraph import connected_components
import pandas as pd
import numpy as... | 20,538 | 37.390654 | 180 | py |
CBA | CBA-main/lung/ywb_function.py | import scipy
import random
import keras as K
import numpy as np
import pandas as pd
import scanpy as sc
import seaborn as sns
import scipy.io as sio
import tensorflow as tf
from keras import layers
from ywb_function import *
from collections import Counter
import matplotlib.pyplot as plt
from keras.regularizers import... | 7,512 | 33.782407 | 158 | py |
CBA | CBA-main/lung/lung_main.py | """
Created on Fri Mar 27 18:58:59 2020
@author: 17b90
"""
import kBET
import scipy
import random
import keras as K
import numpy as np
import pandas as pd
import scanpy as sc
import seaborn as sns
import scipy.io as sio
import tensorflow as tf
from keras import layers
from ywb_function import *
import sklearn.metrics ... | 29,860 | 43.702096 | 177 | py |
CBA | CBA-main/pancreas/kBET.py | # -*- coding: utf-8 -*-
"""
Created on Sun Jan 31 10:41:54 2021
@author: 17b90
"""
import numpy as np
import anndata
import scanpy as sc
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.sparse.csgraph import connected_components
import pandas as pd
import numpy as... | 20,538 | 37.390654 | 180 | py |
CBA | CBA-main/pancreas/ywb_function.py | import scipy
import random
import keras as K
import numpy as np
import pandas as pd
import scanpy as sc
import seaborn as sns
import scipy.io as sio
import tensorflow as tf
from keras import layers
from ywb_function import *
from collections import Counter
import matplotlib.pyplot as plt
from keras.regularizers import... | 7,512 | 33.782407 | 158 | py |
CBA | CBA-main/pancreas/pancreas_main.py | """
Created on Fri Mar 27 18:58:59 2020
@author: 17b90
"""
import kBET
import scipy
import random
import keras as K
import numpy as np
import pandas as pd
import scanpy as sc
import seaborn as sns
import scipy.io as sio
import tensorflow as tf
from keras import layers
from ywb_function import *
import sklearn.metrics ... | 30,362 | 46.815748 | 185 | py |
CBA | CBA-main/species/kBET.py | # -*- coding: utf-8 -*-
"""
Created on Sun Jan 31 10:41:54 2021
@author: 17b90
"""
import numpy as np
import anndata
import scanpy as sc
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.sparse.csgraph import connected_components
import pandas as pd
import numpy as... | 20,538 | 37.390654 | 180 | py |
CBA | CBA-main/species/ywb_function.py | import scipy
import random
import keras as K
import numpy as np
import pandas as pd
import scanpy as sc
import seaborn as sns
import scipy.io as sio
import tensorflow as tf
from keras import layers
from ywb_function import *
from collections import Counter
import matplotlib.pyplot as plt
from keras.regularizers import... | 7,512 | 33.782407 | 158 | py |
CBA | CBA-main/species/species_main.py | """
Created on Fri Mar 27 18:58:59 2020
@author: 17b90
"""
import kBET
import scipy
import random
import keras as K
import numpy as np
import pandas as pd
import scanpy as sc
import seaborn as sns
import scipy.io as sio
import tensorflow as tf
from keras import layers
from ywb_function import *
import sklearn.metrics ... | 29,319 | 43.969325 | 198 | py |
ColBERT | ColBERT-master/setup.py | import setuptools
with open('README.md', 'r') as f:
long_description = f.read()
setuptools.setup(
name='ColBERT',
version='0.2.0',
author='Omar Khattab',
author_email='okhattab@stanford.edu',
description="Efficient and Effective Passage Search via Contextualized Late Interaction over BERT",
... | 538 | 28.944444 | 103 | py |
ColBERT | ColBERT-master/utility/supervision/triples.py | """
Example: --positives 5,50 1,1000 ~~> best-5 (in top-50) + best-1 (in top-1000)
"""
import os
import sys
import git
import tqdm
import ujson
import random
from argparse import ArgumentParser
from colbert.utils.utils import print_message, load_ranking, groupby_first_item, create_directory
from util... | 5,050 | 32.450331 | 123 | py |
ColBERT | ColBERT-master/utility/supervision/self_training.py | import os
import sys
import git
import tqdm
import ujson
import random
from argparse import ArgumentParser
from colbert.utils.utils import print_message, load_ranking, groupby_first_item
MAX_NUM_TRIPLES = 40_000_000
def sample_negatives(negatives, num_sampled, biased=False):
num_sampled = min(len(negatives), n... | 3,924 | 30.653226 | 132 | py |
ColBERT | ColBERT-master/utility/rankings/split_by_offset.py | """
Split the ranked lists after retrieval with a merged query set.
"""
import os
import random
from argparse import ArgumentParser
def main(args):
output_paths = ['{}.{}'.format(args.ranking, split) for split in args.names]
assert all(not os.path.exists(path) for path in output_paths), output_paths
ou... | 1,334 | 28.666667 | 137 | py |
ColBERT | ColBERT-master/utility/rankings/dev_subsample.py | import os
import ujson
import random
from argparse import ArgumentParser
from colbert.utils.utils import print_message, create_directory, load_ranking, groupby_first_item
from utility.utils.qa_loaders import load_qas_
def main(args):
print_message("#> Loading all..")
qas = load_qas_(args.qas)
rankings =... | 1,350 | 27.145833 | 97 | py |
ColBERT | ColBERT-master/utility/rankings/merge.py | """
Divide two or more ranking files, by score.
"""
import os
import tqdm
from argparse import ArgumentParser
from collections import defaultdict
from colbert.utils.utils import print_message, file_tqdm
def main(args):
Rankings = defaultdict(list)
for path in args.input:
print_message(f"#> Load... | 1,640 | 27.293103 | 76 | py |
ColBERT | ColBERT-master/utility/rankings/tune.py | import os
import ujson
import random
from argparse import ArgumentParser
from colbert.utils.utils import print_message, create_directory
from utility.utils.save_metadata import save_metadata
def main(args):
AllMetrics = {}
Scores = {}
for path in args.paths:
with open(path) as f:
met... | 1,741 | 25 | 95 | py |
ColBERT | ColBERT-master/utility/rankings/split_by_queries.py | import os
import sys
import tqdm
import ujson
import random
from argparse import ArgumentParser
from collections import OrderedDict
from colbert.utils.utils import print_message, file_tqdm
def main(args):
qid_to_file_idx = {}
for qrels_idx, qrels in enumerate(args.all_queries):
with open(qrels) as f... | 1,736 | 24.544118 | 97 | py |
ColBERT | ColBERT-master/utility/preprocess/docs2passages.py | """
Divide a document collection into N-word/token passage spans (with wrap-around for last passage).
"""
import os
import math
import ujson
import random
from multiprocessing import Pool
from argparse import ArgumentParser
from colbert.utils.utils import print_message
Format1 = 'docid,text' # MS MARCO Passages... | 4,790 | 30.94 | 110 | py |
ColBERT | ColBERT-master/utility/preprocess/queries_split.py | """
Divide a query set into two.
"""
import os
import math
import ujson
import random
from argparse import ArgumentParser
from collections import OrderedDict
from colbert.utils.utils import print_message
def main(args):
random.seed(12345)
"""
Load the queries
"""
Queries = OrderedDict()
... | 2,225 | 26.146341 | 104 | py |
ColBERT | ColBERT-master/utility/preprocess/wikipedia_to_tsv.py | import os
import ujson
from argparse import ArgumentParser
from colbert.utils.utils import print_message
def main(args):
input_path = args.input
output_path = args.output
assert not os.path.exists(output_path), output_path
RawCollection = []
walk = [(dirpath, filenames) for dirpath, _, filenam... | 1,793 | 27.03125 | 108 | py |
ColBERT | ColBERT-master/utility/evaluate/msmarco_passages.py | """
Evaluate MS MARCO Passages ranking.
"""
import os
import math
import tqdm
import ujson
import random
from argparse import ArgumentParser
from collections import defaultdict
from colbert.utils.utils import print_message, file_tqdm
def main(args):
qid2positives = defaultdict(list)
qid2ranking = defaul... | 4,193 | 32.023622 | 105 | py |
ColBERT | ColBERT-master/utility/evaluate/annotate_EM.py | import os
import sys
import git
import tqdm
import ujson
import random
from argparse import ArgumentParser
from multiprocessing import Pool
from colbert.utils.utils import print_message, load_ranking, groupby_first_item
from utility.utils.qa_loaders import load_qas_, load_collection_
from utility.utils.save_metadata ... | 2,883 | 34.170732 | 133 | py |
ColBERT | ColBERT-master/utility/evaluate/annotate_EM_helpers.py | from colbert.utils.utils import print_message
from utility.utils.dpr import DPR_normalize, has_answer
def tokenize_all_answers(args):
qid, question, answers = args
return qid, question, [DPR_normalize(ans) for ans in answers]
def assign_label_to_passage(args):
idx, (qid, pid, rank, passage, tokenized_an... | 2,495 | 32.28 | 81 | py |
ColBERT | ColBERT-master/utility/utils/save_metadata.py | import os
import sys
import git
import time
import copy
import ujson
import socket
def get_metadata(args):
args = copy.deepcopy(args)
args.hostname = socket.gethostname()
args.git_branch = git.Repo(search_parent_directories=True).active_branch.name
args.git_hash = git.Repo(search_parent_directories=T... | 1,068 | 24.452381 | 107 | py |
ColBERT | ColBERT-master/utility/utils/dpr.py | """
Source: DPR Implementation from Facebook Research
https://github.com/facebookresearch/DPR/tree/master/dpr
"""
import string
import spacy
import regex
import unicodedata
class Tokens(object):
"""A class to represent a list of tokenized text."""
TEXT = 0
TEXT_WS = 1
SPAN = 2
POS = 3
... | 7,071 | 28.714286 | 110 | py |
ColBERT | ColBERT-master/utility/utils/qa_loaders.py | import os
import ujson
from collections import defaultdict
from colbert.utils.utils import print_message, file_tqdm
def load_collection_(path, retain_titles):
with open(path) as f:
collection = []
for line in file_tqdm(f):
_, passage, title = line.strip().split('\t')
if ... | 726 | 20.382353 | 70 | py |
ColBERT | ColBERT-master/colbert/test.py | import os
import random
from colbert.utils.parser import Arguments
from colbert.utils.runs import Run
from colbert.evaluation.loaders import load_colbert, load_topK, load_qrels
from colbert.evaluation.loaders import load_queries, load_topK_pids, load_collection
from colbert.evaluation.ranking import evaluate
from col... | 1,627 | 31.56 | 120 | py |
ColBERT | ColBERT-master/colbert/index_faiss.py | import os
import random
import math
from colbert.utils.runs import Run
from colbert.utils.parser import Arguments
from colbert.indexing.faiss import index_faiss
from colbert.indexing.loaders import load_doclens
def main():
random.seed(12345)
parser = Arguments(description='Faiss indexing for end-to-end retr... | 1,377 | 30.318182 | 91 | py |
ColBERT | ColBERT-master/colbert/retrieve.py | import os
import random
from colbert.utils.parser import Arguments
from colbert.utils.runs import Run
from colbert.evaluation.loaders import load_colbert, load_qrels, load_queries
from colbert.indexing.faiss import get_faiss_index_name
from colbert.ranking.retrieval import retrieve
from colbert.ranking.batch_retrieva... | 1,882 | 32.035088 | 93 | py |
ColBERT | ColBERT-master/colbert/parameters.py | import torch
DEVICE = torch.device("cuda")
SAVED_CHECKPOINTS = [32*1000, 100*1000, 150*1000, 200*1000, 300*1000, 400*1000]
SAVED_CHECKPOINTS += [10*1000, 20*1000, 30*1000, 40*1000, 50*1000, 60*1000, 70*1000, 80*1000, 90*1000]
SAVED_CHECKPOINTS += [25*1000, 50*1000, 75*1000]
SAVED_CHECKPOINTS = set(SAVED_CHECKPOINTS)... | 321 | 31.2 | 102 | py |
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