code stringlengths 3 6.57k |
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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) |
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