code
stringlengths
3
6.57k
value (maximum)
get_maximum_with_tolerance(value, tolerance)
percentage (between 0.0 and 1.0)
value (minimum)
check_data_exists(data_path, expected_files_list)
os.path.exists(data_path)
os.path.isfile(os.path.join(data_path, filename)
__init__(self, response: Text)
response.json()
get_json(self)
RequestsImplementation(ABC)
__init__(self, url: Text, *args, **kwargs)
URL.url_validator(url)
url.replace("https", "http")
self.requests_retry_session(kwargs["session"])
requests.Session()
requests_retry_session(retries=3, backoff_factor=0.3, status_forcelist=(500, 502, 504)
requests.Session()
requests.Session()
HTTPAdapter(max_retries=retry)
session.mount("http://", adapter)
session.mount("https://", adapter)
get(self)
logger(self)
TfExampleDecoder(object)
__init__(self, include_mask=False)
tf.io.FixedLenFeature(()
tf.io.FixedLenFeature(()
tf.io.FixedLenFeature(()
tf.io.FixedLenFeature(()
tf.io.VarLenFeature(tf.float32)
tf.io.VarLenFeature(tf.float32)
tf.io.VarLenFeature(tf.float32)
tf.io.VarLenFeature(tf.float32)
tf.io.VarLenFeature(tf.int64)
tf.io.VarLenFeature(tf.float32)
tf.io.VarLenFeature(tf.int64)
tf.io.VarLenFeature(tf.string)
_decode_image(self, parsed_tensors)
tf.io.decode_image(parsed_tensors['image/encoded'], channels=3)
image.set_shape([None, None, 3])
_decode_boxes(self, parsed_tensors)
tf.stack([ymin, xmin, ymax, xmax], axis=-1)
_decode_masks(self, parsed_tensors)
_decode_png_mask(png_bytes)
tf.io.decode_png(png_bytes, channels=1, dtype=tf.uint8)
tf.cast(mask, dtype=tf.float32)
mask.set_shape([None, None])
tf.greater(tf.size(input=masks)
tf.map_fn(_decode_png_mask, masks, dtype=tf.float32)
tf.zeros([0, height, width], dtype=tf.float32)
_decode_areas(self, parsed_tensors)
tf.greater(tf.shape(parsed_tensors['image/object/area'])
decode(self, serialized_example)
isinstance(parsed_tensors[k], tf.SparseTensor)
self._decode_image(parsed_tensors)
self._decode_boxes(parsed_tensors)
self._decode_areas(parsed_tensors)
tf.greater(tf.shape(parsed_tensors['image/object/is_crowd'])
tf.cast(parsed_tensors['image/object/is_crowd'], dtype=tf.bool)
tf.zeros_like(parsed_tensors['image/object/class/label'], dtype=tf.bool)
self._decode_masks(parsed_tensors)
CPU(Component)
Column(Integer, ForeignKey("Component.unique_id")
Column(String)
Column(String)
Column(String)
Column(Integer)
Column(Integer)
Column(Integer)
Column(Float)
Column(Float)
threads(self)
__repr__(self)
CPU({self.manufacturer} {self.model} ({self.core_count}/{self.threads}x{self.nominal_frequency} GHz {self.isa})
set_sources(apps, schema_editor)
apps.get_model("music", "Source")
apps.get_model("music", "TemporaryMusic")
Source.objects.get(name="Youtube")
TemporaryMusic.objects.all()
tempMusic.save()
Migration(migrations.Migration)
models.ForeignKey(to='music.Source', null=True, on_delete=models.CASCADE)
migrations.RunPython(set_sources)
models.ForeignKey(to='music.Source', on_delete=models.CASCADE)
test_training(storage, capsys)
list(itertools.islice(annotations, 0, 300)
capsys.readouterr()
np.asarray([a.type for a in annotations])
get_Xy(annotations, form_types, full_type_names=False)
crf.predict(X)
flat_accuracy_score(y, y_pred)
storage.get_field_schema()
set(field_schema.types_inv.keys()
set(crf.classes_)
issubset(short_names)
parse_options(args)
argparse.ArgumentParser(description=description)
parser.parse_args(args)
main(args=None)