or4cl3ai/Aiden_t5
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from setuptools import setup, find_packages
setup(
name='coinrun',
packages=find_packages(),
version='0.0.1',
)
|
import numpy as np
from coinrun import setup_utils, make
def random_agent(num_envs=1, max_steps=100000):
setup_utils.setup_and_load(use_cmd_line_args=False)
env = make('standard', num_envs=num_envs)
for step in range(max_steps):
acts = np.array([env.action_space.sample() for _ in range(env.num_env... |
"""
Load an agent trained with train_agent.py and
"""
import time
import tensorflow as tf
import numpy as np
from coinrun import setup_utils
import coinrun.main_utils as utils
from coinrun.config import Config
from coinrun import policies, wrappers
mpi_print = utils.mpi_print
def create_act_model(sess, env, nenvs)... |
"""
Train an agent using a PPO2 based on OpenAI Baselines.
"""
import time
from mpi4py import MPI
import tensorflow as tf
from baselines.common import set_global_seeds
import coinrun.main_utils as utils
from coinrun import setup_utils, policies, wrappers, ppo2
from coinrun.config import Config
def main():
args = ... |
from mpi4py import MPI
import argparse
import os
class ConfigSingle(object):
"""
A global config object that can be initialized from command line arguments or
keyword arguments.
"""
def __init__(self):
self.WORKDIR = './saved_models/'
self.TB_DIR = '/tmp/tensorflow'
if not o... |
"""
This is a copy of PPO from openai/baselines (https://github.com/openai/baselines/blob/52255beda5f5c8760b0ae1f676aa656bb1a61f80/baselines/ppo2/ppo2.py) with some minor changes.
"""
import time
import joblib
import numpy as np
import tensorflow as tf
from collections import deque
from mpi4py import MPI
from coinru... |
import tensorflow as tf
from mpi4py import MPI
from coinrun.config import Config
import numpy as np
def clean_tb_dir():
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
if rank == 0:
if tf.gfile.Exists(Config.TB_DIR):
tf.gfile.DeleteRecursively(Config.TB_DIR)
tf.gfile.MakeDirs(Con... |
from .coinrunenv import init_args_and_threads
from .coinrunenv import make
__all__ = [
'init_args_and_threads',
'make'
]
|
import gym
import numpy as np
class EpsilonGreedyWrapper(gym.Wrapper):
"""
Wrapper to perform a random action each step instead of the requested action,
with the provided probability.
"""
def __init__(self, env, prob=0.05):
gym.Wrapper.__init__(self, env)
self.prob = prob
s... |
"""
Run a CoinRun environment in a window where you can interact with it using the keyboard
"""
from coinrun.coinrunenv import lib
from coinrun import setup_utils
def main():
setup_utils.setup_and_load(paint_vel_info=0)
print("""Control with arrow keys,
F1, F2 -- switch resolution,
F5, F6, F7, F8 -- zoom,
F9... |
import tensorflow as tf
import os
import joblib
import numpy as np
from mpi4py import MPI
from baselines.common.vec_env.vec_frame_stack import VecFrameStack
from coinrun.config import Config
from coinrun import setup_utils, wrappers
import platform
def make_general_env(num_env, seed=0, use_sub_proc=True):
from ... |
from coinrun.config import Config
import os
import joblib
def load_for_setup_if_necessary():
restore_file(Config.RESTORE_ID)
def restore_file(restore_id, load_key='default'):
if restore_id is not None:
load_file = Config.get_load_filename(restore_id=restore_id)
filepath = file_to_path(load_fi... |
from coinrun import random_agent
def test_coinrun():
random_agent.random_agent(num_envs=16, max_steps=100)
if __name__ == '__main__':
test_coinrun() |
import numpy as np
import tensorflow as tf
from baselines.a2c.utils import conv, fc, conv_to_fc, batch_to_seq, seq_to_batch, lstm
from baselines.common.distributions import make_pdtype
from baselines.common.input import observation_input
from coinrun.config import Config
def impala_cnn(images, depths=[16, 32, 32]):
... |
"""
Python interface to the CoinRun shared library using ctypes.
On import, this will attempt to build the shared library.
"""
import os
import atexit
import random
import sys
from ctypes import c_int, c_char_p, c_float, c_bool
import gym
import gym.spaces
import numpy as np
import numpy.ctypeslib as npct
from basel... |
import json
import pickle
import math
import sys
import argparse
import warnings
from os import makedirs
from os.path import basename, join, exists, dirname, splitext, realpath
from wikidata_linker_utils.progressbar import get_progress_bar
from dataset import TSVDataset, CombinedDataset, H5Dataset, ClassificationHand... |
import numpy as np
import subprocess
import h5py
import ciseau
from os.path import exists, splitext, join
from wikidata_linker_utils.wikidata_ids import load_wikidata_ids
def count_examples(lines, comment, ignore_value, column_indices):
example_length = 0
has_labels = False
found = 0
for line in lines:... |
import queue
import threading
def prefetch_generator(generator, to_fetch=10):
q = queue.Queue(maxsize=to_fetch)
def thread_worker(queue, gen):
for val in gen:
queue.put(val)
queue.put(None)
t = threading.Thread(target=thread_worker, args=(q, generator))
some_exception = N... |
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Models trained or fine-tuned on kye/all-openai-github-code