Move to xautodl

.gitmodules

@@ -4,3 +4,6 @@
 [submodule ".latent-data/NATS-Bench"]
 	path = .latent-data/NATS-Bench
 	url = git@github.com:D-X-Y/NATS-Bench.git
+[submodule ".latent-data/NAS-Bench-201"]
+	path = .latent-data/NAS-Bench-201
+	url = git@github.com:D-X-Y/NAS-Bench-201.git

.latent-data/NAS-Bench-201

@@ -0,0 +1 @@
+Subproject commit 8558547969c131f75af2725869ff1ece98e98f23

CHANGE-LOG.md

@@ -6,5 +6,6 @@
 - [2019.01.31] [13e908f] GDAS codes were publicly released.
 - [2020.07.01] [a45808b] Upgrade NAS-API to the 2.0 version.
 - [2020.09.16] [7052265] Create NATS-BENCH.
-- [2020.10.15] [446262a] Update NATS-BENCH to version 1.0
+- [2020.10.15] [446262a](https://github.com/D-X-Y/AutoDL-Projects/tree/446262a) Update NATS-BENCH to version 1.0
-- [2020.12.20] [dae387a] Update NATS-BENCH to version 1.1
+- [2020.12.20] [dae387a](https://github.com/D-X-Y/AutoDL-Projects/tree/dae387a) Update NATS-BENCH to version 1.1
+- [2021.05.18] [98fadf8](https://github.com/D-X-Y/AutoDL-Projects/tree/98fadf8086727f6311d477d0e4f2d5bb7e41ca59) Before moving to `xautodl`

docs/README_CN.md

@@ -88,7 +88,7 @@
 
 ## 准备工作
 
-请使用`3.6`以上的`Python`，更多的Python包参见[requirements.txt](docs/requirements.txt).
+请使用`3.6`以上的`Python`，更多的Python包参见[requirements.txt](requirements.txt).
 
 请下载并且解压缩`CIFAR`和`ImageNet`到`$TORCH_HOME`.
 

docs/requirements.txt

@@ -1,5 +1,5 @@
-nats_bench>=1.4
-torchvision
 torch
-# Optional
+torchvision
-opencv
+
+nats_bench>=1.4
+nas_201_api

exps/LFNA/lfna.py

@@ -10,23 +10,25 @@ from tqdm import tqdm
 from copy import deepcopy
 from pathlib import Path
 
-lib_dir = (Path(__file__).parent / ".." / ".." / "lib").resolve()
+from xautodl.procedures import (
-if str(lib_dir) not in sys.path:
+    prepare_seed,
-    sys.path.insert(0, str(lib_dir))
+    prepare_logger,
-from procedures import prepare_seed, prepare_logger, save_checkpoint, copy_checkpoint
+    save_checkpoint,
-from log_utils import time_string
+    copy_checkpoint,
-from log_utils import AverageMeter, convert_secs2time
+)
+from xautodl.log_utils import time_string
+from xautodl.log_utils import AverageMeter, convert_secs2time
 
-from utils import split_str2indexes
+from xautodl.utils import split_str2indexes
 
-from procedures.advanced_main import basic_train_fn, basic_eval_fn
+from xautodl.procedures.advanced_main import basic_train_fn, basic_eval_fn
-from procedures.metric_utils import SaveMetric, MSEMetric, ComposeMetric
+from xautodl.procedures.metric_utils import SaveMetric, MSEMetric, ComposeMetric
-from datasets.synthetic_core import get_synthetic_env, EnvSampler
+from xautodl.datasets.synthetic_core import get_synthetic_env, EnvSampler
-from models.xcore import get_model
+from xautodl.models.xcore import get_model
-from xlayers import super_core, trunc_normal_
+from xautodl.xlayers import super_core, trunc_normal_
 
-from lfna_utils import lfna_setup, train_model, TimeData
+from xautodl.lfna_utils import lfna_setup, train_model, TimeData
-from lfna_meta_model import LFNA_Meta
+from xautodl.lfna_meta_model import LFNA_Meta
 
 
 def epoch_train(loader, meta_model, base_model, optimizer, criterion, device, logger):

lib

@@ -0,0 +1 @@
+xautodl

setup.py

@@ -0,0 +1,59 @@
+#####################################################
+# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.05 #
+#####################################################
+"""The setup function for pypi."""
+# The following is to make nats_bench avaliable on Python Package Index (PyPI)
+#
+# conda install -c conda-forge twine  # Use twine to upload nats_bench to pypi
+#
+# python setup.py sdist bdist_wheel
+# python setup.py --help-commands
+# twine check dist/*
+#
+# twine upload --repository-url https://test.pypi.org/legacy/ dist/*
+# twine upload dist/*
+# https://pypi.org/project/xautodl
+#
+# TODO(xuanyidong): upload it to conda
+#
+# [2021.05.18] v1.0
+import os
+from setuptools import setup
+
+NAME = "xautodl"
+REQUIRES_PYTHON = ">=3.6"
+DESCRIPTION = "Automated Deep Learning Package"
+
+VERSION = "0.9.9"
+
+
+def read(fname="README.md"):
+    with open(os.path.join(os.path.dirname(__file__), fname), encoding="utf-8") as cfile:
+        return cfile.read()
+
+
+# What packages are required for this module to be executed?
+REQUIRED = ["numpy>=1.16.5,<=1.19.5"]
+
+setup(
+    name=NAME,
+    version=VERSION,
+    author="Xuanyi Dong",
+    author_email="dongxuanyi888@gmail.com",
+    description=DESCRIPTION,
+    license="MIT Licence",
+    keywords="NAS Dataset API DeepLearning",
+    url="https://github.com/D-X-Y/AutoDL-Projects",
+    packages=["xautodl"],
+    install_requires=REQUIRED,
+    python_requires=REQUIRES_PYTHON,
+    long_description=read("README.md"),
+    long_description_content_type="text/markdown",
+    classifiers=[
+        "Programming Language :: Python",
+        "Programming Language :: Python :: 3",
+        "Topic :: Database",
+        "Topic :: Scientific/Engineering :: Artificial Intelligence",
+        "License :: OSI Approved :: MIT License",
+    ],
+)

xautodl/__init__.py

@@ -0,0 +1,6 @@
+#####################################################
+# Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2021.05 #
+#####################################################
+# An Automated Deep Learning Package to support     #
+# research activities.                              #
+#####################################################