forked from keras-team/keras-core
-
Notifications
You must be signed in to change notification settings - Fork 0
/
pip_build.py
186 lines (158 loc) · 6.66 KB
/
pip_build.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
"""Script to create (and optionally install) a `.whl` archive for Keras Core.
Usage:
1. Create a `.whl` file in `dist/`:
```
python3 pip_build.py
```
2. Also install the new package immediately after:
```
python3 pip_build.py --install
```
"""
import argparse
import glob
import os
import pathlib
import shutil
import namex
# Needed because importing torch after TF causes the runtime to crash
import torch # noqa: F401
package = "keras_core"
build_directory = "tmp_build_dir"
dist_directory = "dist"
to_copy = ["setup.py", "README.md"]
def ignore_files(_, filenames):
return [f for f in filenames if f.endswith("_test.py")]
def build():
if os.path.exists(build_directory):
raise ValueError(f"Directory already exists: {build_directory}")
whl_path = None
try:
# Copy sources (`keras_core/` directory and setup files) to build
# directory
root_path = pathlib.Path(__file__).parent.resolve()
os.chdir(root_path)
os.mkdir(build_directory)
shutil.copytree(
package, os.path.join(build_directory, package), ignore=ignore_files
)
for fname in to_copy:
shutil.copy(fname, os.path.join(f"{build_directory}", fname))
os.chdir(build_directory)
# Restructure the codebase so that source files live in `keras_core/src`
namex.convert_codebase(package, code_directory="src")
# Generate API __init__.py files in `keras_core/`
namex.generate_api_files(package, code_directory="src", verbose=True)
# Make keras_core/_tf_keras/ by copying keras_core/
tf_keras_dirpath = os.path.join(package, "_tf_keras")
os.makedirs(tf_keras_dirpath)
with open(os.path.join(package, "__init__.py")) as f:
init_file = f.read()
init_file = init_file.replace(
"from keras_core import _legacy",
"from keras_core import _tf_keras",
)
with open(os.path.join(package, "__init__.py"), "w") as f:
f.write(init_file)
with open(os.path.join(tf_keras_dirpath, "__init__.py"), "w") as f:
f.write(init_file)
for dirname in os.listdir(package):
dirpath = os.path.join(package, dirname)
if os.path.isdir(dirpath) and dirname not in (
"_legacy",
"_tf_keras",
"src",
):
shutil.copytree(
dirpath,
os.path.join(tf_keras_dirpath, dirname),
ignore=ignore_files,
)
# Copy keras_core/_legacy/ file contents to keras_core/_tf_keras/
legacy_submodules = [
path[:-3]
for path in os.listdir(os.path.join(package, "src", "legacy"))
if path.endswith(".py")
]
legacy_submodules += [
path
for path in os.listdir(os.path.join(package, "src", "legacy"))
if os.path.isdir(os.path.join(package, "src", "legacy", path))
]
for root, _, fnames in os.walk(os.path.join(package, "_legacy")):
for fname in fnames:
if fname.endswith(".py"):
legacy_fpath = os.path.join(root, fname)
tf_keras_root = root.replace("/_legacy", "/_tf_keras")
core_api_fpath = os.path.join(
root.replace("/_legacy", ""), fname
)
if not os.path.exists(tf_keras_root):
os.makedirs(tf_keras_root)
tf_keras_fpath = os.path.join(tf_keras_root, fname)
with open(legacy_fpath) as f:
legacy_contents = f.read()
legacy_contents = legacy_contents.replace(
"keras_core._legacy", "keras_core._tf_keras"
)
if os.path.exists(core_api_fpath):
with open(core_api_fpath) as f:
core_api_contents = f.read()
core_api_contents = core_api_contents.replace(
"from keras_core import _tf_keras\n", ""
)
for legacy_submodule in legacy_submodules:
core_api_contents = core_api_contents.replace(
f"from keras_core import {legacy_submodule}\n",
"",
)
core_api_contents = core_api_contents.replace(
f"keras_core.{legacy_submodule}",
f"keras_core._tf_keras.{legacy_submodule}",
)
legacy_contents = (
core_api_contents + "\n" + legacy_contents
)
with open(tf_keras_fpath, "w") as f:
f.write(legacy_contents)
# Delete keras_core/_legacy/
shutil.rmtree(os.path.join(package, "_legacy"))
# Make sure to export the __version__ string
from keras_core.src.version import __version__ # noqa: E402
with open(os.path.join(package, "__init__.py")) as f:
init_contents = f.read()
with open(os.path.join(package, "__init__.py"), "w") as f:
f.write(init_contents + "\n\n" + f'__version__ = "{__version__}"\n')
# Build the package
os.system("python3 -m build")
# Save the dist files generated by the build process
os.chdir(root_path)
if not os.path.exists(dist_directory):
os.mkdir(dist_directory)
for fpath in glob.glob(
os.path.join(build_directory, dist_directory, "*.*")
):
shutil.copy(fpath, dist_directory)
# Find the .whl file path
for fname in os.listdir(dist_directory):
if __version__ in fname and fname.endswith(".whl"):
whl_path = os.path.abspath(os.path.join(dist_directory, fname))
print(f"Build successful. Wheel file available at {whl_path}")
finally:
# Clean up: remove the build directory (no longer needed)
shutil.rmtree(build_directory)
return whl_path
def install_whl(whl_fpath):
print(f"Installing wheel file: {whl_fpath}")
os.system(f"pip3 install {whl_fpath} --force-reinstall --no-dependencies")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--install",
action="store_true",
help="Whether to install the generated wheel file.",
)
args = parser.parse_args()
whl_path = build()
if whl_path and args.install:
install_whl(whl_path)