[chore] Fix copyright headers & fixed issue with mypy & NumPy versions in pre-commit (#951)

* copyright headers

* isort and pyproject.toml

* precommit and requirement for isort-seed-config

* mypy

* dummy change

* numpy version for pre-commit

* fix mypy issue caused by numpy
Co-authored-by: Min Xu <min.xu.public@gmail.com>

docs/Makefile

+# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
+#
+# This source code is licensed under the BSD license found in the
+# LICENSE file in the root directory of this source tree.
+
 # Minimal makefile for Sphinx documentation
 #
 

docs/source/conf.py

+# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
+#
+# This source code is licensed under the BSD license found in the
+# LICENSE file in the root directory of this source tree.
+
 # type: ignore
 # Configuration file for the Sphinx documentation builder.
 #

pyproject.toml

@@ -27,4 +27,4 @@ use_parentheses = true
 skip_glob = ["build/*", "stubs/*"]
 # Don't split "import" and "from".
 force_sort_within_sections = true
-known_third_party = ["benchmark_dataset", "datasets", "golden_configs", "models", "numpy", "parameterized", "pytest", "recommonmark", "setuptools", "sklearn", "torch", "torchtext", "torchvision", "utils"]
+known_third_party = ["benchmark_dataset", "datasets", "distutils", "golden_configs", "models", "numpy", "parameterized", "pytest", "recommonmark", "setuptools", "sklearn", "torch", "torchtext", "torchvision", "utils"]

requirements-dev.txt

@@ -10,6 +10,7 @@ black == 21.10b0
 flake8 == 4.0.1
 flake8-annotations == 2.7.0
 isort == 5.10.1
+seed-isort-config == 2.2.0
 mypy == 0.910
 pre-commit >= 2.15.0
 
@@ -26,8 +27,10 @@ docutils == 0.17
 # For torch.cuda.list_gpu_processes()
 pynvml == 8.0.4
 
-# For mypy typing
-numpy >= 1.21
+# For mypy typing. It is important to have a fixed version. Otherwise, you
+# may run into mypy errors out differently for different versions.
+# Using 1.21.5 for now because py3.7 only has up to 1.21.5, not 1.22.x.
+numpy == 1.21.5
 
 # For layerwise gradient scaler
 sklearn >= 0.0