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adcgan
adcgan-main/BigGAN-PyTorch/inception_tf13.py
''' Tensorflow inception score code Derived from https://github.com/openai/improved-gan Code derived from tensorflow/tensorflow/models/image/imagenet/classify_image.py THIS CODE REQUIRES TENSORFLOW 1.3 or EARLIER to run in PARALLEL BATCH MODE To use this code, run sample.py on your model with --sample_npz, and then ...
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adcgan
adcgan-main/BigGAN-PyTorch/train_fns.py
''' train_fns.py Functions for the main loop of training different conditional image models ''' import torch import torch.nn as nn import torchvision import os import utils import losses # Dummy training function for debugging def dummy_training_function(): def train(x, y): return {} return train def GAN_t...
11,139
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adcgan
adcgan-main/BigGAN-PyTorch/BigGAN.py
import numpy as np import math import functools import torch import torch.nn as nn from torch.nn import init import torch.optim as optim import torch.nn.functional as F from torch.nn import Parameter as P import layers from sync_batchnorm import SynchronizedBatchNorm2d as SyncBatchNorm2d # Architectures for G # Att...
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adcgan
adcgan-main/BigGAN-PyTorch/utils.py
#!/usr/bin/env python # -*- coding: utf-8 -*- ''' Utilities file This file contains utility functions for bookkeeping, logging, and data loading. Methods which directly affect training should either go in layers, the model, or train_fns.py. ''' from __future__ import print_function import sys import os import numpy a...
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adcgan
adcgan-main/BigGAN-PyTorch/layers.py
''' Layers This file contains various layers for the BigGAN models. ''' import numpy as np import torch import torch.nn as nn from torch.nn import init import torch.optim as optim import torch.nn.functional as F from torch.nn import Parameter as P from sync_batchnorm import SynchronizedBatchNorm2d as SyncBN2d # ...
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adcgan
adcgan-main/BigGAN-PyTorch/datasets.py
''' Datasets This file contains definitions for our CIFAR, ImageFolder, and HDF5 datasets ''' import os import os.path import sys from PIL import Image import numpy as np from tqdm import tqdm, trange import torchvision.datasets as dset import torchvision.transforms as transforms from torchvision.datasets.utils im...
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adcgan
adcgan-main/BigGAN-PyTorch/inception_utils.py
''' Inception utilities This file contains methods for calculating IS and FID, using either the original numpy code or an accelerated fully-pytorch version that uses a fast newton-schulz approximation for the matrix sqrt. There are also methods for acquiring a desired number of samples from the Generat...
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adcgan
adcgan-main/BigGAN-PyTorch/animal_hash.py
c = ['Aardvark', 'Abyssinian', 'Affenpinscher', 'Akbash', 'Akita', 'Albatross', 'Alligator', 'Alpaca', 'Angelfish', 'Ant', 'Anteater', 'Antelope', 'Ape', 'Armadillo', 'Ass', 'Avocet', 'Axolotl', 'Baboon', 'Badger', 'Balinese', 'Bandicoot', 'Barb', 'Barnacle', 'Barracuda', 'Bat', 'Beagle', 'Bear', 'B...
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adcgan
adcgan-main/BigGAN-PyTorch/calculate_inception_moments.py
''' Calculate Inception Moments This script iterates over the dataset and calculates the moments of the activations of the Inception net (needed for FID), and also returns the Inception Score of the training data. Note that if you don't shuffle the data, the IS of true data will be under- estimated as it is lab...
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adcgan
adcgan-main/BigGAN-PyTorch/train.py
""" BigGAN: The Authorized Unofficial PyTorch release Code by A. Brock and A. Andonian This code is an unofficial reimplementation of "Large-Scale GAN Training for High Fidelity Natural Image Synthesis," by A. Brock, J. Donahue, and K. Simonyan (arXiv 1809.11096). Let's go. """ import os import fu...
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adcgan
adcgan-main/BigGAN-PyTorch/sync_batchnorm/replicate.py
# -*- coding: utf-8 -*- # File : replicate.py # Author : Jiayuan Mao # Email : maojiayuan@gmail.com # Date : 27/01/2018 # # This file is part of Synchronized-BatchNorm-PyTorch. # https://github.com/vacancy/Synchronized-BatchNorm-PyTorch # Distributed under MIT License. import functools from torch.nn.parallel.da...
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adcgan
adcgan-main/BigGAN-PyTorch/sync_batchnorm/unittest.py
# -*- coding: utf-8 -*- # File : unittest.py # Author : Jiayuan Mao # Email : maojiayuan@gmail.com # Date : 27/01/2018 # # This file is part of Synchronized-BatchNorm-PyTorch. # https://github.com/vacancy/Synchronized-BatchNorm-PyTorch # Distributed under MIT License. import unittest import torch class TorchTes...
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adcgan
adcgan-main/BigGAN-PyTorch/sync_batchnorm/batchnorm.py
# -*- coding: utf-8 -*- # File : batchnorm.py # Author : Jiayuan Mao # Email : maojiayuan@gmail.com # Date : 27/01/2018 # # This file is part of Synchronized-BatchNorm-PyTorch. # https://github.com/vacancy/Synchronized-BatchNorm-PyTorch # Distributed under MIT License. import collections import torch import torc...
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adcgan
adcgan-main/BigGAN-PyTorch/sync_batchnorm/batchnorm_reimpl.py
#! /usr/bin/env python3 # -*- coding: utf-8 -*- # File : batchnorm_reimpl.py # Author : acgtyrant # Date : 11/01/2018 # # This file is part of Synchronized-BatchNorm-PyTorch. # https://github.com/vacancy/Synchronized-BatchNorm-PyTorch # Distributed under MIT License. import torch import torch.nn as nn import torch...
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adcgan
adcgan-main/BigGAN-PyTorch/sync_batchnorm/comm.py
# -*- coding: utf-8 -*- # File : comm.py # Author : Jiayuan Mao # Email : maojiayuan@gmail.com # Date : 27/01/2018 # # This file is part of Synchronized-BatchNorm-PyTorch. # https://github.com/vacancy/Synchronized-BatchNorm-PyTorch # Distributed under MIT License. import queue import collections import threading...
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adcgan
adcgan-main/BigGAN-PyTorch/sync_batchnorm/__init__.py
# -*- coding: utf-8 -*- # File : __init__.py # Author : Jiayuan Mao # Email : maojiayuan@gmail.com # Date : 27/01/2018 # # This file is part of Synchronized-BatchNorm-PyTorch. # https://github.com/vacancy/Synchronized-BatchNorm-PyTorch # Distributed under MIT License. from .batchnorm import SynchronizedBatchNorm...
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adcgan
adcgan-main/BigGAN-PyTorch/TFHub/biggan_v1.py
# BigGAN V1: # This is now deprecated code used for porting the TFHub modules to pytorch, # included here for reference only. import numpy as np import torch from scipy.stats import truncnorm from torch import nn from torch.nn import Parameter from torch.nn import functional as F def l2normalize(v, eps=1e-4): retur...
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adcgan
adcgan-main/BigGAN-PyTorch/TFHub/converter.py
"""Utilities for converting TFHub BigGAN generator weights to PyTorch. Recommended usage: To convert all BigGAN variants and generate test samples, use: ```bash CUDA_VISIBLE_DEVICES=0 python converter.py --generate_samples ``` See `parse_args` for additional options. """ import argparse import os import sys impor...
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DeepSpectrum
DeepSpectrum-master/setup.py
#!/usr/bin/env python import re import sys import warnings warnings.filterwarnings('ignore', category=DeprecationWarning) warnings.filterwarnings('ignore', category=FutureWarning) from setuptools import setup, find_packages from subprocess import CalledProcessError, check_output PROJECT = "DeepSpectrum" VERSION = "0....
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/__main__.py
import sys, os # sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..', 'auDeep')) import warnings # from numba.errors import NumbaDeprecationWarning, NumbaPendingDeprecationWarning warnings.filterwarnings('ignore', category=DeprecationWarning) warnings.filterwarnings('ignore', category=FutureWarning) # w...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/__init__.py
import logging import sys logging.basicConfig(stream=sys.stdout, level=logging.INFO) __version__ = '0.6.9'
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/cli/features.py
import logging import click from deepspectrum.cli.configuration import Configuration, GENERAL_OPTIONS,\ PLOTTING_OPTIONS, EXTRACTION_OPTIONS, LABEL_OPTIONS, WRITER_OPTIONS, Filetypes from os import environ from .utils import add_options log = logging.getLogger(__name__) DESCRIPTION_EXTRACT = 'Extract deep spectrum fe...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/cli/utils.py
def add_options(options): def _add_options(func): for option in reversed(options): func = option(func) return func return _add_options
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/cli/configuration.py
import logging import click import configparser import fnmatch import re import decimal from enum import Enum from multiprocessing import cpu_count from os import makedirs, walk from matplotlib import cm from os.path import abspath, join, isfile, basename, dirname, realpath, splitext mpl_cmaps = list(cm.cmaps_listed)+...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/cli/plot.py
import click import logging from os import environ from tqdm import tqdm from deepspectrum.cli.configuration import Configuration, GENERAL_OPTIONS, PLOTTING_OPTIONS from .utils import add_options from ..backend.plotting import PlotGenerator environ['GLOG_minloglevel'] = '2' environ['TF_CPP_MIN_LOG_LEVEL'] = '3' log =...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/cli/__init__.py
0
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/cli/features_with_parser.py
from os import environ from .utils import add_options import logging import click from deepspectrum.cli.configuration import Configuration, GENERAL_OPTIONS, PLOTTING_OPTIONS, EXTRACTION_OPTIONS, PARSER_OPTIONS, WRITER_OPTIONS, Filetypes log = logging.getLogger(__name__) DESCRIPTION_EXTRACT = 'Extract deep spectrum f...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/cli/image_features.py
import numpy as np import click import logging from os import environ from os.path import basename from .configuration import Configuration, GENERAL_OPTIONS, EXTRACTION_OPTIONS, LABEL_OPTIONS, WRITER_OPTIONS, Filetypes from .utils import add_options from ..backend.plotting import PlotTuple from ..tools.path import get_...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/tools/feature_writer.py
import csv from tqdm import tqdm from .custom_arff import ArffWriter import logging log = logging.getLogger(__name__) class FeatureWriter: def __init__(self, output, label_dict, labels, continuous_labels, write_timestamps, no_labels): self.output = output self.label_dict = lab...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/tools/custom_arff.py
import logging log = logging.getLogger(__name__) class ArffWriter(): def __init__(self, file_object, relation_name, attributes): self.arff_file = file_object self.relation_name = relation_name self.attributes = attributes self._write_header() def _write_header(self): ...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/tools/label_parser.py
import csv import decimal from os.path import splitext, normpath class LabelParser(): def __init__(self, filepath, delimiter=',', timecontinuous=False, remove_extension=False): self._timecontinuous = timecontinuous self._filepath ...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/tools/path.py
import pathlib from os.path import basename def get_relative_path(path, prefix): filepath = pathlib.PurePath(path) if prefix is None: return basename(filepath) else: filepath = filepath.relative_to(prefix) return str(filepath)
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/tools/__init__.py
0
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/backend/plotting.py
import matplotlib import io import warnings # import librosa.display # import librosa import numpy as np import pathlib import logging from imread import imread_from_blob from os import environ, makedirs from os.path import basename, join, dirname, splitext from multiprocessing import cpu_count, Pool from functools imp...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/backend/extractor.py
import gc from collections import namedtuple import numpy as np import os os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3" import tensorflow as tf import torch from torchvision import models, transforms from PIL import Image import logging tf.compat.v1.logging.set_verbosity(logging.ERROR) log = logging.getLogger(__name__) ...
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DeepSpectrum
DeepSpectrum-master/src/deepspectrum/backend/__init__.py
0
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py
DeepSpectrum
DeepSpectrum-master/tests/__init__.py
0
0
0
py
DeepSpectrum
DeepSpectrum-master/tests/cli/test_features.py
from multiprocessing import cpu_count from deepspectrum.__main__ import cli from click.testing import CliRunner from os.path import dirname, join from os import listdir cur_dir = dirname(__file__) examples = join(dirname(dirname(cur_dir)), 'examples') def test_features_file_level(tmpdir): runner = CliRunner() ...
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DeepSpectrum
DeepSpectrum-master/tests/cli/test_image_features.py
from click.testing import CliRunner from deepspectrum.__main__ import cli from multiprocessing import cpu_count from os.path import join, dirname cur_dir = dirname(__file__) examples = join(dirname(dirname(cur_dir)), 'examples') def test_image_features(tmpdir): runner = CliRunner() result = runner.invoke(cli...
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DeepSpectrum
DeepSpectrum-master/tests/cli/test_plot.py
from click.testing import CliRunner from deepspectrum.__main__ import cli from multiprocessing import cpu_count from os.path import join, dirname cur_dir = dirname(__file__) examples = join(dirname(dirname(cur_dir)), 'examples') def test_plot(tmpdir): runner = CliRunner() result = runner.invoke(cli, ...
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DeepSpectrum
DeepSpectrum-master/tests/cli/__init__.py
0
0
0
py
ocp
ocp-main/main.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import argparse import copy import logging import submitit from ocpmodels.common.flags import flags from ocpmodels.common.utils import ( ...
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ocp
ocp-main/setup.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ from setuptools import find_packages, setup setup( name="ocp-models", version="0.0.3", description="Machine learning models for ...
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ocp
ocp-main/scripts/preprocess_relaxed.py
""" Creates LMDB files with extracted graph features from provided *.extxyz files for the S2EF task. """ import argparse import glob import multiprocessing as mp import os import pickle import random import sys import ase.io import lmdb import numpy as np import torch from tqdm import tqdm from ocpmodels.preprocessi...
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ocp
ocp-main/scripts/download_data.py
import argparse import glob import logging import os from typing import Dict, Optional import ocpmodels """ This script provides users with an automated way to download, preprocess (where applicable), and organize data to readily be used by the existing config files. """ DOWNLOAD_LINKS_s2ef: Dict[str, Dict[str, str]...
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ocp
ocp-main/scripts/make_submission_file.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import argparse import glob import os import numpy as np SPLITS = { "OC20": ["id", "ood_ads", "ood_cat", "ood_both"], "OC22": ["id"...
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ocp
ocp-main/scripts/preprocess_ef.py
""" Creates LMDB files with extracted graph features from provided *.extxyz files for the S2EF task. """ import argparse import glob import multiprocessing as mp import os import pickle import random import sys import ase.io import lmdb import numpy as np import torch from tqdm import tqdm from ocpmodels.preprocessi...
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ocp
ocp-main/scripts/gif_maker_parallelized.py
""" Script to generate gifs from traj Note: This is just a quick way to generate gifs and visalizations from traj, there are many parameters and settings in the code that people can vary to make visualizations better. We have chosen these settings as this seem to work fine for most of our systems. Requirements: povr...
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py
ocp
ocp-main/scripts/make_lmdb_sizes.py
""" This script provides the functionality to generate metadata.npz files necessary for load_balancing the DataLoader. """ import argparse import multiprocessing as mp import os import warnings import numpy as np from tqdm import tqdm from ocpmodels.datasets import SinglePointLmdbDataset, TrajectoryLmdbDataset from ...
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ocp
ocp-main/scripts/__init__.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """
178
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ocp
ocp-main/scripts/uncompress.py
""" Uncompresses downloaded S2EF datasets to be used by the LMDB preprocessing script - preprocess_ef.py """ import argparse import glob import lzma import multiprocessing as mp import os from typing import List, Tuple from tqdm import tqdm def read_lzma(inpfile: str, outfile: str) -> None: with open(inpfile, "...
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ocp
ocp-main/scripts/make_challenge_submission_file.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. ONLY for use in the NeurIPS 2021 Open Catalyst Challenge. For all other submissions please use make_submission_file.py. """ import argparse imp...
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ocp
ocp-main/scripts/hpo/run_tune.py
import os import ray from ray import tune from ray.tune import CLIReporter from ray.tune.schedulers import ASHAScheduler from ocpmodels.common.flags import flags from ocpmodels.common.registry import registry from ocpmodels.common.utils import build_config, setup_imports # this function is general and should work f...
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ocp
ocp-main/scripts/hpo/run_tune_pbt.py
import logging import os import ray from ray import tune from ray.tune import CLIReporter from ray.tune.schedulers import PopulationBasedTraining from ocpmodels.common.flags import flags from ocpmodels.common.registry import registry from ocpmodels.common.utils import build_config, setup_imports # this function is ...
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ocp
ocp-main/scripts/hpo/__init__.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """
178
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ocp
ocp-main/tests/conftest.py
""" Copyright (c) Facebook, Inc. and its 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 TYPE_CHECKING, Optional, Union import numpy as np import pytest from syrupy.extensions.amber import AmberSnapshotExtensio...
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ocp
ocp-main/tests/__init__.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """
178
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ocp
ocp-main/tests/common/test_data_parallel_batch_sampler.py
import tempfile from contextlib import contextmanager from pathlib import Path from typing import TypeVar import numpy as np import pytest from torch.utils.data import Dataset from ocpmodels.common.data_parallel import BalancedBatchSampler DATA = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] SIZE_ATOMS = [1, 1, 1, 1, 1, 1, 1, 1, ...
6,251
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ocp
ocp-main/tests/models/test_schnet.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import os import random import numpy as np import pytest import torch from ase.io import read from ocpmodels.common.registry import registr...
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ocp
ocp-main/tests/models/test_gemnet_oc.py
""" Copyright (c) Facebook, Inc. and its 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 logging import os import random import numpy as np import pytest import requests import torch from ase.io import read from...
4,631
27.95
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ocp
ocp-main/tests/models/test_gemnet.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import logging import os import random import numpy as np import pytest import torch from ase.io import read from ocpmodels.common.registry...
3,191
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ocp
ocp-main/tests/models/test_dimenet.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import os import random import numpy as np import pytest import torch from ase.io import read from ocpmodels.common.registry import registr...
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ocp
ocp-main/tests/models/test_cgcnn.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import os import random import numpy as np import pytest import torch from ase.io import read from ocpmodels.common.registry import registr...
2,759
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ocp
ocp-main/tests/models/test_forcenet.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import os import numpy as np import pytest from ase.io import read from ocpmodels.common.registry import registry from ocpmodels.common.uti...
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ocp
ocp-main/tests/models/test_gemnet_oc_scaling_mismatch.py
""" Copyright (c) Facebook, Inc. and its 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 pytest import requests import torch from ocpmodels.common.registry import registry from ocpmodels.common.utils import load...
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ocp
ocp-main/tests/models/test_dimenetpp.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import logging import os import random import numpy as np import pytest import torch from ase.io import read from ocpmodels.common.registry...
2,745
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ocp
ocp-main/tests/evaluator/test_evaluator.py
""" Copyright (c) Facebook, Inc. and its 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 pytest import torch from ocpmodels.modules.evaluator import ( Evaluator, cosine_similarity, magnitude_...
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ocp
ocp-main/tests/datasets/test_ase_lmdb.py
import os from pathlib import Path import numpy as np import pytest import tqdm from ase import build from ase.calculators.singlepoint import SinglePointCalculator from ase.constraints import FixAtoms from ase.io import write from ocpmodels.datasets.lmdb_database import LMDBDatabase DB_NAME = "ase_lmdb.lmdb" N_WRITE...
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ocp
ocp-main/tests/datasets/test_ase_datasets.py
import os import numpy as np import pytest from ase import build, db from ase.calculators.singlepoint import SinglePointCalculator from ase.io import Trajectory, write from ocpmodels.datasets import ( AseDBDataset, AseReadDataset, AseReadMultiStructureDataset, ) from ocpmodels.datasets.lmdb_database impor...
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ocp
ocp-main/tests/preprocessing/test_radius_graph_pbc.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import os import ase import numpy as np import pytest import torch from ase.io import read from ase.lattice.cubic import FaceCenteredCubic f...
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ocp
ocp-main/tests/preprocessing/test_atoms_to_graphs.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import os import numpy as np import pytest from ase.io import read from ase.neighborlist import NeighborList, NewPrimitiveNeighborList from...
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ocp
ocp-main/tests/preprocessing/test_pbc.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import os import numpy as np import pytest from ase.io import read from ocpmodels.common.utils import get_pbc_distances from ocpmodels.data...
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ocp-main/tests/preprocessing/__init__.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """
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ocp-main/docs/source/conf.py
""" Copyright (c) Facebook, Inc. and its 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 # l...
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ocp-main/ocpmodels/__init__.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """
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ocp
ocp-main/ocpmodels/modules/normalizer.py
""" Copyright (c) Facebook, Inc. and its 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 class Normalizer: """Normalize a Tensor and restore it later.""" def __init__(self, tensor=None, mean=None, std=None,...
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ocp
ocp-main/ocpmodels/modules/loss.py
import logging from typing import Optional import torch from torch import nn from ocpmodels.common import distutils class L2MAELoss(nn.Module): def __init__(self, reduction: str = "mean") -> None: super().__init__() self.reduction = reduction assert reduction in ["mean", "sum"] def ...
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ocp
ocp-main/ocpmodels/modules/exponential_moving_average.py
""" Copied (and improved) from: https://github.com/fadel/pytorch_ema/blob/master/torch_ema/ema.py (MIT license) """ from __future__ import division, unicode_literals import copy import weakref from typing import List, Iterable, Optional import torch from ocpmodels.common.typing import none_throws # Partially based...
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ocp
ocp-main/ocpmodels/modules/scheduler.py
import inspect import torch.optim.lr_scheduler as lr_scheduler from ocpmodels.common.utils import warmup_lr_lambda class LRScheduler: """ Learning rate scheduler class for torch.optim learning rate schedulers Notes: If no learning rate scheduler is specified in the config the default sc...
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ocp
ocp-main/ocpmodels/modules/evaluator.py
""" Copyright (c) Facebook, Inc. and its 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 Dict, Union """ An evaluation module for use with the OCP dataset and suite of tasks. It...
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ocp
ocp-main/ocpmodels/modules/__init__.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """
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ocp
ocp-main/ocpmodels/modules/scaling/fit.py
import logging import math import readline import sys from itertools import islice from pathlib import Path from typing import TYPE_CHECKING, Dict, Literal import torch import torch.nn as nn from torch.nn.parallel.distributed import DistributedDataParallel from ocpmodels.common.data_parallel import OCPDataParallel fr...
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ocp
ocp-main/ocpmodels/modules/scaling/scale_factor.py
import itertools import logging import math from contextlib import contextmanager from typing import Callable, Optional, TypedDict, Union import torch import torch.nn as nn class _Stats(TypedDict): variance_in: float variance_out: float n_samples: int IndexFn = Callable[[], None] def _check_consisten...
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ocp
ocp-main/ocpmodels/modules/scaling/util.py
import logging import torch.nn as nn from .scale_factor import ScaleFactor def ensure_fitted(module: nn.Module, warn: bool = False) -> None: for name, child in module.named_modules(): if not isinstance(child, ScaleFactor) or child.fitted: continue if child.name is not None: ...
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ocp
ocp-main/ocpmodels/modules/scaling/__init__.py
from .scale_factor import ScaleFactor __all__ = ["ScaleFactor"]
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ocp
ocp-main/ocpmodels/modules/scaling/compat.py
import json import logging from pathlib import Path from typing import Dict, Optional, Union import torch import torch.nn as nn from .scale_factor import ScaleFactor ScaleDict = Union[Dict[str, float], Dict[str, torch.Tensor]] def _load_scale_dict(scale_file: Optional[Union[str, ScaleDict]]): """ Loads sca...
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ocp
ocp-main/ocpmodels/common/distutils.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import logging import os import subprocess import torch import torch.distributed as dist from ocpmodels.common.typing import none_throws d...
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ocp
ocp-main/ocpmodels/common/data_parallel.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import heapq import logging from itertools import chain from pathlib import Path from typing import List, Literal, Protocol, Union, runtime_c...
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ocp
ocp-main/ocpmodels/common/registry.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ # Copyright (c) Facebook, Inc. and its affiliates. # Borrowed from https://github.com/facebookresearch/pythia/blob/master/pythia/common/regis...
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ocp
ocp-main/ocpmodels/common/typing.py
from typing import Optional, TypeVar, Type _T = TypeVar("_T") def assert_is_instance(obj: object, cls: Type[_T]) -> _T: if not isinstance(obj, cls): raise TypeError(f"obj is not an instance of cls: obj={obj}, cls={cls}") return obj def none_throws(x: Optional[_T], msg: Optional[str] = None) -> _T: ...
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ocp
ocp-main/ocpmodels/common/utils.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import ast import collections import copy import importlib import itertools import json import logging import os import sys import time from ...
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ocp
ocp-main/ocpmodels/common/logger.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import logging from abc import ABC, abstractmethod import torch import wandb from torch.utils.tensorboard import SummaryWriter from ocpmodel...
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ocp
ocp-main/ocpmodels/common/flags.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import argparse from pathlib import Path class Flags: def __init__(self) -> None: self.parser = argparse.ArgumentParser( ...
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ocp
ocp-main/ocpmodels/common/__init__.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """
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ocp-main/ocpmodels/common/gp_utils.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import math from typing import Any, Optional import torch from torch import distributed as dist """ Functions to support graph parallel trai...
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ocp
ocp-main/ocpmodels/common/transforms.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ # Borrowed from https://github.com/rusty1s/pytorch_geometric/blob/master/torch_geometric/transforms/random_rotate.py # with changes to keep t...
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ocp
ocp-main/ocpmodels/common/hpo_utils.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import math from ray import tune def tune_reporter( iters, train_metrics, val_metrics, test_metrics=None, metric_to_op...
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ocp
ocp-main/ocpmodels/common/relaxation/ase_utils.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. Utilities to interface OCP models/trainers with the Atomic Simulation Environment (ASE) """ import copy import logging import os import torch ...
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ocp
ocp-main/ocpmodels/common/relaxation/__init__.py
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ocp-main/ocpmodels/common/relaxation/ml_relaxation.py
""" Copyright (c) Facebook, Inc. and its affiliates. This source code is licensed under the MIT license found in the LICENSE file in the root directory of this source tree. """ import logging from collections import deque from pathlib import Path import torch from torch_geometric.data import Batch from ocpmodels.co...
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