def main(_):
# These make up for the empty __init__.py files.
api_generator.utils.recursive_import(tfx.orchestration)
api_generator.utils.recursive_import(tfx.components)
api_generator.utils.recursive_import(tfx.extensions)
do_not_generate_docs_for = []
for name in ["utils", "proto", "dependencies", "version"]:
submodule = getattr(tfx, name, None)
if submodule is not None:
do_not_generate_docs_for.append(submodule)
for obj in do_not_generate_docs_for:
doc_controls.do_not_generate_docs(obj)
doc_generator = generate_lib.DocGenerator(
root_title="TFX",
py_modules=[("tfx", tfx)],
code_url_prefix=FLAGS.code_url_prefix,
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
private_map={},
# local_definitions_filter ensures that shared modules are only
# documented in the location that defines them, instead of every location
# that imports them.
callbacks=[
api_generator.public_api.local_definitions_filter,
ignore_test_objects
])
doc_generator.build(output_dir=FLAGS.output_dir)
def main(_):
do_not_generate_docs_for = []
for name in ["utils", "dependencies", "version", "examples"]:
submodule = getattr(tfx, name, None)
if submodule is not None:
do_not_generate_docs_for.append(submodule)
for obj in do_not_generate_docs_for:
doc_controls.do_not_generate_docs(obj)
doc_generator = generate_lib.DocGenerator(
root_title="TFX",
py_modules=[("tfx", tfx)],
code_url_prefix=FLAGS.code_url_prefix,
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
gen_report=FLAGS.gen_report,
private_map={},
# local_definitions_filter ensures that shared modules are only
# documented in the location that defines them, instead of every location
# that imports them.
callbacks=[
api_generator.public_api.explicit_package_contents_filter,
ignore_test_objects, ignore_proto_method
])
doc_generator.build(output_dir=FLAGS.output_dir)
def main(args):
if args[1:]:
raise ValueError("Unrecognized Command line args", args[1:])
for obj in supress_docs_for:
doc_controls.do_not_generate_docs(obj)
for name, value in inspect.getmembers(tfdv):
if inspect.ismodule(value):
doc_controls.do_not_generate_docs(value)
for name, value in inspect.getmembers(beam.PTransform):
# This ensures that the methods of PTransform are not documented in any
# derived classes.
if name == "__init__":
continue
try:
doc_controls.do_not_doc_inheritable(value)
except (TypeError, AttributeError):
pass
doc_generator = generate_lib.DocGenerator(
root_title="TensorFlow Data Validation",
py_modules=[("tfdv", tfdv)],
code_url_prefix=FLAGS.code_url_prefix,
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
# local_definitions_filter ensures that shared modules are only
# documented in the location that defines them, instead of every location
# that imports them.
callbacks=[
public_api.local_definitions_filter, _filter_class_attributes
])
return doc_generator.build(output_dir=FLAGS.output_dir)
def main(args):
if args[1:]:
raise ValueError('Unrecognized command line args', args[1:])
suppress_docs_for = []
for name in ['version', 'goo' + 'gle', 'metadata_store', 'pywrap']:
submodule = getattr(mlmd, name, None)
if submodule is not None:
suppress_docs_for.append(submodule)
for obj in suppress_docs_for:
doc_controls.do_not_generate_docs(obj)
doc_generator = generate_lib.DocGenerator(
root_title='ML Metadata',
py_modules=[('mlmd', mlmd)],
base_dir=os.path.dirname(mlmd.__file__),
code_url_prefix=FLAGS.code_url_prefix,
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
private_map={},
callbacks=[
# This filters out objects not defined in the current module or its
# sub-modules.
public_api.local_definitions_filter,
ignore_proto_method,
ignore_attrs_method
])
doc_generator.build(output_dir=FLAGS.output_dir)
def main(args):
if args[1:]:
raise ValueError('Unrecognized Command line args', args[1:])
tft_out = pathlib.Path(tempfile.mkdtemp())
doc_generator = generate_lib.DocGenerator(
root_title='TF-Transform',
py_modules=[('tft', transform)],
code_url_prefix=FLAGS.code_url_prefix,
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
callbacks=[public_api.explicit_package_contents_filter])
doc_generator.build(tft_out)
doc_controls.do_not_generate_docs(tft_beam.analyzer_impls)
tft_beam_out = pathlib.Path(tempfile.mkdtemp())
doc_generator = generate_lib.DocGenerator(
root_title='TFT-Beam',
py_modules=[('tft_beam', tft_beam)],
code_url_prefix=FLAGS.code_url_prefix + '/beam',
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
callbacks=[
public_api.explicit_package_contents_filter,
public_api.local_definitions_filter
])
doc_generator.build(tft_beam_out)
output_dir = pathlib.Path(FLAGS.output_dir)
def splice(name, tmp_dir):
shutil.rmtree(output_dir / name, ignore_errors=True)
shutil.copytree(tmp_dir / name, output_dir / name)
shutil.copy(tmp_dir / f'{name}.md', output_dir / f'{name}.md')
try:
shutil.copy(tmp_dir / '_redirects.yaml',
output_dir / name / '_redirects.yaml')
except FileNotFoundError:
pass
shutil.copy(tmp_dir / '_toc.yaml', output_dir / name / '_toc.yaml')
splice('tft', tft_out)
splice('tft_beam', tft_beam_out)
toc_path = output_dir / '_toc.yaml'
toc_text = yaml.dump({
'toc': [{
'include': f'{FLAGS.site_path}/tft/_toc.yaml'
}, {
'break': True
}, {
'include': f'{FLAGS.site_path}/tft_beam/_toc.yaml'
}]
})
toc_path.write_text(toc_text)
def build_docs(output_dir, code_url_prefix, search_hints=True):
"""Build api docs for tensorflow v2.
Args:
output_dir: A string path, where to put the files.
code_url_prefix: prefix for "Defined in" links.
search_hints: Bool. Include meta-data search hints at the top of each file.
"""
# The custom page will be used for raw_ops.md not the one generated above.
doc_controls.set_custom_page_content(tf.raw_ops, generate_raw_ops_doc())
_hide_layer_and_module_methods()
try:
doc_controls.do_not_generate_docs(tf.tools)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.compat.v1.pywrap_tensorflow)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.pywrap_tensorflow)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.flags)
except AttributeError:
pass
base_dir = path.normpath(path.join(tf.__file__, "../.."))
base_dirs = (
path.join(base_dir, "tensorflow_core"),
# External packages base directories
path.dirname(tensorboard.__file__),
path.dirname(tensorflow_estimator.__file__),
)
code_url_prefixes = (
code_url_prefix,
# External packages source repositories,
"https://github.com/tensorflow/tensorboard/tree/master/tensorboard",
"https://github.com/tensorflow/estimator/tree/master/tensorflow_estimator",
)
doc_generator = generate_lib.DocGenerator(
root_title="TensorFlow 2",
py_modules=[("tf", tf)],
base_dir=base_dirs,
search_hints=search_hints,
code_url_prefix=code_url_prefixes,
site_path=FLAGS.site_path,
visitor_cls=TfExportAwareVisitor,
private_map=_PRIVATE_MAP)
doc_generator.build(output_dir)
def main(unused_argv):
for obj in DO_NOT_GENERATE_DOCS_FOR:
doc_controls.do_not_generate_docs(obj)
doc_generator = generate_lib.DocGenerator(
root_title="TensorFlow Probability",
py_modules=[("tfp", tfp)],
base_dir=os.path.dirname(tfp.__file__),
code_url_prefix=FLAGS.code_url_prefix,
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
private_map={"tfp": ["google", "staging", "python"]},
callbacks=[internal_filter])
doc_generator.build(output_dir=FLAGS.output_dir)
def build_docs(output_dir, code_url_prefix, search_hints=True):
"""Build api docs for tensorflow v2.
Args:
output_dir: A string path, where to put the files.
code_url_prefix: prefix for "Defined in" links.
search_hints: Bool. Include meta-data search hints at the top of each file.
"""
_hide_layer_and_module_methods()
try:
doc_controls.do_not_generate_docs(tf.tools)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.compat.v1.pywrap_tensorflow)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.pywrap_tensorflow)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.flags)
except AttributeError:
pass
base_dir = path.dirname(tf.__file__)
base_dirs = (
base_dir,
# External packages base directories,
path.dirname(tensorboard.__file__),
path.dirname(tensorflow_estimator.__file__),
)
code_url_prefixes = (
code_url_prefix,
# External packages source repositories,
"https://github.com/tensorflow/tensorboard/tree/master/tensorboard",
"https://github.com/tensorflow/estimator/tree/master/tensorflow_estimator",
)
doc_generator = generate_lib.DocGenerator(
root_title="TensorFlow 2.0 Preview",
py_modules=[("tf", tf)],
base_dir=base_dirs,
search_hints=search_hints,
code_url_prefix=code_url_prefixes,
site_path=FLAGS.site_path,
visitor_cls=TfExportAwareDocGeneratorVisitor,
private_map=PRIVATE_MAP,
do_not_descend_map=DO_NOT_DESCEND_MAP)
doc_generator.build(output_dir)
def main(_):
do_not_generate_docs_for = []
for blocked_doc in do_not_generate_docs_for:
doc_controls.do_not_generate_docs(blocked_doc)
doc_generator = generate_lib.DocGenerator(
root_title="Neural Structured Learning",
py_modules=[("nsl", nsl)],
code_url_prefix=FLAGS.code_url_prefix,
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
# local_definitions_filter ensures that shared modules are only
# documented in the location that defines them, instead of every location
# that imports them.
callbacks=[public_api.local_definitions_filter])
doc_generator.build(output_dir=FLAGS.output_dir)
def main(args):
if args[1:]:
raise ValueError('Unrecognized Command line args', args[1:])
doc_controls.do_not_generate_docs(tft_beam.analyzer_impls)
doc_generator = generate_lib.DocGenerator(
root_title='TFT-Beam',
py_modules=[('tft_beam', tft_beam)],
code_url_prefix=FLAGS.code_url_prefix + '/beam',
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
callbacks=[
public_api.explicit_package_contents_filter,
public_api.local_definitions_filter
])
doc_generator.build(FLAGS.output_dir)
def main(args):
if args[1:]:
raise ValueError('Unrecognized command line args', args[1:])
for obj in suppress_docs_for:
doc_controls.do_not_generate_docs(obj)
doc_generator = generate_lib.DocGenerator(
root_title='TensorFlow Model Analysis',
py_modules=[('tfma', tfma)],
base_dir=os.path.dirname(tfma.__file__),
code_url_prefix=FLAGS.code_url_prefix,
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
callbacks=[
public_api.local_definitions_filter, depth_filter, suppress_docs
])
return doc_generator.build(output_dir=FLAGS.output_dir)
def main(args):
if args[1:]:
raise ValueError('Unrecognized command line args', args[1:])
for obj in suppress_docs_for:
doc_controls.do_not_generate_docs(obj)
doc_generator = generate_lib.DocGenerator(
root_title='TensorFlow Hub',
py_modules=[('hub', hub)],
base_dir=os.path.dirname(hub.__file__),
code_url_prefix=FLAGS.code_url_prefix,
search_hints=FLAGS.search_hints,
site_path=FLAGS.site_path,
private_map={},
callbacks=[
# This filters out objects not defined in the current module or its
# sub-modules.
public_api.local_definitions_filter
])
doc_generator.build(output_dir=FLAGS.output_dir)
def build_docs(output_dir, code_url_prefix, search_hints=True):
"""Build api docs for tensorflow v2.
Args:
output_dir: A string path, where to put the files.
code_url_prefix: prefix for "Defined in" links.
search_hints: Bool. Include meta-data search hints at the top of each file.
"""
try:
doc_controls.do_not_generate_docs(tf.tools)
except AttributeError:
pass
base_dir = path.dirname(tf.__file__)
base_dirs = (
base_dir,
path.normpath(path.join(base_dir, "../../tensorflow")),
path.dirname(tensorboard.__file__),
path.dirname(tensorflow_estimator.__file__),
)
code_url_prefixes = (
code_url_prefix,
# External packages source repositories
"https://github.com/tensorflow/tensorboard/tree/master/tensorboard"
"https://github.com/tensorflow/estimator/tree/master/tensorflow_estimator"
)
doc_generator = generate_lib.DocGenerator(
root_title="TensorFlow 2.0 Preview",
py_modules=[("tf", tf)],
base_dir=base_dirs,
search_hints=search_hints,
code_url_prefix=code_url_prefixes,
site_path=FLAGS.site_path,
visitor_cls=TfExportAwareDocGeneratorVisitor)
doc_generator.build(output_dir)
def build_docs(output_dir, code_url_prefix, search_hints=True):
"""Build api docs for tensorflow v2.
Args:
output_dir: A string path, where to put the files.
code_url_prefix: prefix for "Defined in" links.
search_hints: Bool. Include meta-data search hints at the top of each file.
"""
try:
doc_controls.do_not_generate_docs(tf.tools)
except AttributeError:
pass
base_dir = path.dirname(tf.__file__)
base_dirs = (
base_dir,
path.normpath(path.join(base_dir, "../../tensorflow")),
path.dirname(tensorboard.__file__),
path.dirname(tensorflow_estimator.__file__),
)
code_url_prefixes = (
code_url_prefix,
# External packages source repositories
"https://github.com/tensorflow/tensorboard/tree/master/tensorboard"
"https://github.com/tensorflow/estimator/tree/master/tensorflow_estimator"
)
doc_generator = generate_lib.DocGenerator(
root_title="TensorFlow 2.0 Preview",
py_modules=[("tf", tf)],
base_dir=base_dirs,
search_hints=search_hints,
code_url_prefix=code_url_prefixes,
site_path=FLAGS.site_path,
visitor_cls=TfExportAwareDocGeneratorVisitor)
doc_generator.build(output_dir)
def build_docs(output_dir, code_url_prefix, search_hints):
"""Build api docs for tensorflow v2.
Args:
output_dir: A string path, where to put the files.
code_url_prefix: prefix for "Defined in" links.
search_hints: Bool. Include meta-data search hints at the top of each file.
"""
if distutils.version.LooseVersion(tf.__version__) >= "2.9":
doc_controls.set_deprecated(tf.keras.preprocessing)
# The custom page will be used for raw_ops.md not the one generated above.
doc_controls.set_custom_page_builder_cls(tf.raw_ops, RawOpsPageInfo)
# Hide raw_ops from search.
for name, obj in tf_inspect.getmembers(tf.raw_ops):
if not name.startswith("_"):
doc_controls.hide_from_search(obj)
for cls in [
tf.Module, tf.keras.layers.Layer, tf.keras.optimizers.Optimizer
]:
doc_controls.decorate_all_class_attributes(
decorator=doc_controls.do_not_doc_in_subclasses,
cls=cls,
skip=["__init__"])
do_not_document = [
"tf.__internal__", "tf.keras.__internal__", "tf.__operators__",
"tf.tools", "tf.compat.v1.pywrap_tensorflow", "tf.pywrap_tensorflow",
"tf.flags", "tf.batch_mat_mul_v3", "tf.sparse_segment_sum_grad"
]
for path in do_not_document:
item = tf
for part in path.split(".")[1:]:
item = getattr(item, part, None)
if item is None:
continue
doc_controls.do_not_generate_docs(item)
base_dirs, code_url_prefixes = base_dir.get_base_dirs_and_prefixes(
code_url_prefix)
doc_generator = generate_lib.DocGenerator(
root_title="TensorFlow 2",
py_modules=[("tf", tf)],
base_dir=base_dirs,
search_hints=search_hints,
code_url_prefix=code_url_prefixes,
site_path=FLAGS.site_path,
visitor_cls=TfExportAwareVisitor,
private_map=_PRIVATE_MAP,
extra_docs=_EXTRA_DOCS)
doc_generator.build(output_dir)
out_path = pathlib.Path(output_dir)
expected_path_contents = {
"tf/summary/audio.md": "tensorboard/plugins/audio/summary_v2.py",
"tf/estimator/DNNClassifier.md":
"tensorflow_estimator/python/estimator/canned/dnn.py",
"tf/nn/sigmoid_cross_entropy_with_logits.md": "python/ops/nn_impl.py",
"tf/keras/Model.md": "keras/engine/training.py",
}
all_passed = True
error_msg_parts = [
'Some "view source" links seem to be broken, please check:'
]
for (rel_path, contents) in expected_path_contents.items():
path = out_path / rel_path
if contents not in path.read_text():
all_passed = False
error_msg_parts.append(" " + str(path))
if not all_passed:
raise ValueError("\n".join(error_msg_parts))
rejected_path_contents = {
"tf/keras/optimizers.md": "keras/optimizers/__init__.py",
}
all_passed = True
error_msg_parts = [
'Bad "view source" links in generated files, please check:'
]
for rel_path, content in rejected_path_contents.items():
path = out_path / rel_path
if content in path.read_text():
all_passed = False
error_msg_parts.append(" " + str(path))
if not all_passed:
raise ValueError("\n".join(error_msg_parts))
num_files = len(list(out_path.rglob("*")))
if num_files < MIN_NUM_FILES_EXPECTED:
raise ValueError(
f"The TensorFlow api should be more than {MIN_NUM_FILES_EXPECTED} files"
f"(found {num_files}).")
def build_docs(output_dir, code_url_prefix, search_hints=True):
"""Build api docs for tensorflow v2.
Args:
output_dir: A string path, where to put the files.
code_url_prefix: prefix for "Defined in" links.
search_hints: Bool. Include meta-data search hints at the top of each file.
"""
# The custom page will be used for raw_ops.md not the one generated above.
doc_controls.set_custom_page_content(tf.raw_ops, generate_raw_ops_doc())
# Hide raw_ops from search.
for name, obj in tf_inspect.getmembers(tf.raw_ops):
if not name.startswith("_"):
doc_controls.hide_from_search(obj)
_hide_layer_and_module_methods()
try:
doc_controls.do_not_generate_docs(tf.__operators__)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.tools)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.compat.v1.pywrap_tensorflow)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.pywrap_tensorflow)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.flags)
except AttributeError:
pass
base_dirs, code_url_prefixes = base_dir.get_base_dirs_and_prefixes(
code_url_prefix)
doc_generator = generate_lib.DocGenerator(
root_title="TensorFlow 2",
py_modules=[("tf", tf)],
base_dir=base_dirs,
search_hints=search_hints,
code_url_prefix=code_url_prefixes,
site_path=FLAGS.site_path,
visitor_cls=TfExportAwareVisitor,
private_map=_PRIVATE_MAP)
doc_generator.build(output_dir)
out_path = pathlib.Path(output_dir)
num_files = len(list(out_path.rglob("*")))
if num_files < 2000:
raise ValueError("The TensorFlow api should be more than 2500 files"
"(found {}).".format(num_files))
expected_path_contents = {
"tf/summary/audio.md":
"tensorboard/plugins/audio/summary_v2.py",
"tf/estimator/DNNClassifier.md":
"tensorflow_estimator/python/estimator/canned/dnn.py",
"tf/nn/sigmoid_cross_entropy_with_logits.md":
"python/ops/nn_impl.py",
"tf/keras/Model.md":
"tensorflow/python/keras/engine/training.py",
"tf/compat/v1/gradients.md":
"tensorflow/python/ops/gradients_impl.py",
}
all_passed = True
error_msg_parts = [
'Some "view source" links seem to be broken, please check:'
]
for (rel_path, contents) in expected_path_contents.items():
path = out_path / rel_path
if contents not in path.read_text():
all_passed = False
error_msg_parts.append(" " + str(path))
if not all_passed:
raise ValueError("\n".join(error_msg_parts))
output_dir=".",
code_url_prefix=CODE_URL_PREFIX,
search_hints=False,
gen_report=False)
wandb_run = [
'init',
'log',
'config',
'summary',
'login',
'alert',]
wandb.__all__ = wandb_run
try:
doc_controls.do_not_generate_docs(wandb.settings.Console)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(wandb.settings.Source)
except AttributeError:
pass
build_docs(
name_pair=("run",wandb),
output_dir="./library",
code_url_prefix=CODE_URL_PREFIX,
search_hints=False,
gen_report=False)
wandb_datatypes = [
'Image',
def build_docs(output_dir, code_url_prefix, search_hints, gen_report):
"""Build api docs for tensorflow v2.
Args:
output_dir: A string path, where to put the files.
code_url_prefix: prefix for "Defined in" links.
search_hints: Bool. Include meta-data search hints at the top of each file.
gen_report: Bool. Generates an API report containing the health of the
docstrings of the public API.
"""
# The custom page will be used for raw_ops.md not the one generated above.
doc_controls.set_custom_page_content(tf.raw_ops, generate_raw_ops_doc())
# Hide raw_ops from search.
for name, obj in tf_inspect.getmembers(tf.raw_ops):
if not name.startswith("_"):
doc_controls.hide_from_search(obj)
for cls in [
tf.Module, tf.keras.layers.Layer, tf.keras.optimizers.Optimizer
]:
doc_controls.decorate_all_class_attributes(
decorator=doc_controls.do_not_doc_in_subclasses,
cls=cls,
skip=["__init__"])
try:
doc_controls.do_not_generate_docs(tf.__internal__)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.keras.__internal__)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.__operators__)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.tools)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.compat.v1.pywrap_tensorflow)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.pywrap_tensorflow)
except AttributeError:
pass
try:
doc_controls.do_not_generate_docs(tf.flags)
except AttributeError:
pass
base_dirs, code_url_prefixes = base_dir.get_base_dirs_and_prefixes(
code_url_prefix)
doc_generator = generate_lib.DocGenerator(
root_title="TensorFlow 2",
py_modules=[("tf", tf)],
base_dir=base_dirs,
search_hints=search_hints,
code_url_prefix=code_url_prefixes,
site_path=FLAGS.site_path,
visitor_cls=TfExportAwareVisitor,
private_map=_PRIVATE_MAP,
gen_report=gen_report,
extra_docs=_EXTRA_DOCS)
doc_generator.build(output_dir)
if gen_report:
return
out_path = pathlib.Path(output_dir)
expected_path_contents = {
"tf/summary/audio.md":
"tensorboard/plugins/audio/summary_v2.py",
"tf/estimator/DNNClassifier.md":
"tensorflow_estimator/python/estimator/canned/dnn.py",
"tf/nn/sigmoid_cross_entropy_with_logits.md":
"python/ops/nn_impl.py",
"tf/keras/Model.md":
"keras/engine/training.py",
"tf/keras/preprocessing/image/random_brightness.md":
"keras_preprocessing/image/affine_transformations.py"
}
all_passed = True
error_msg_parts = [
'Some "view source" links seem to be broken, please check:'
]
for (rel_path, contents) in expected_path_contents.items():
path = out_path / rel_path
if contents not in path.read_text():
all_passed = False
error_msg_parts.append(" " + str(path))
if not all_passed:
raise ValueError("\n".join(error_msg_parts))
rejected_path_contents = {
"tf/keras/optimizers.md": "keras/optimizers/__init__.py",
}
all_passed = True
error_msg_parts = [
'Bad "view source" links in generated files, please check:'
]
for rel_path, content in rejected_path_contents.items():
path = out_path / rel_path
if content in path.read_text():
all_passed = False
error_msg_parts.append(" " + str(path))
if not all_passed:
raise ValueError("\n".join(error_msg_parts))
num_files = len(list(out_path.rglob("*")))
if num_files < 2000:
raise ValueError("The TensorFlow api should be more than 2000 files"
"(found {}).".format(num_files))
