code stringlengths 66 870k | docstring stringlengths 19 26.7k | func_name stringlengths 1 138 | language stringclasses 1
value | repo stringlengths 7 68 | path stringlengths 5 324 | url stringlengths 46 389 | license stringclasses 7
values |
|---|---|---|---|---|---|---|---|
def class_encoding():
"""Creates a set of functions to add a new class, convert a
class into an integer, and the integer back to a class."""
class_to_int_map = {}
int_to_class_map = None
def add_class(c):
global int_to_class_map
int_to_class_map = None
... | Creates a set of functions to add a new class, convert a
class into an integer, and the integer back to a class. | class_encoding | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/__init__.py | MIT |
def to_categorical(y, num_classes=None):
"""Converts a class vector (integers) to binary class matrix.
"""
y = np.array(y, dtype='int')
input_shape = y.shape
if input_shape and input_shape[-1] == 1 and len(input_shape) > 1:
input_shape = tuple(input_shape[:-1])
... | Converts a class vector (integers) to binary class matrix.
| to_categorical | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/__init__.py | MIT |
def _iterdump(connection):
"""
Returns an iterator to the dump of the database in an SQL text format.
Used to produce an SQL dump of the database. Useful to save an in-memory
database for later restoration. This function should not be called
directly but instead called from the Connection method,... |
Returns an iterator to the dump of the database in an SQL text format.
Used to produce an SQL dump of the database. Useful to save an in-memory
database for later restoration. This function should not be called
directly but instead called from the Connection method, iterdump().
| _iterdump | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/lib/dump.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/lib/dump.py | MIT |
def _sqlite_try_max_variable_number(num):
""" Tests whether SQLite can handle num variables """
db = sqlite3.connect(':memory:')
try:
db.cursor().execute(
"SELECT 1 IN (" + ",".join(["?"] * num) + ")",
([0] * num)
).fetchall()
return num
except BaseExcepti... | Tests whether SQLite can handle num variables | _sqlite_try_max_variable_number | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def __new__(cls, *args, **kwargs):
""" Returns a concatenated magnitude object, if Magnitude parameters """
if len(args) > 0 and isinstance(args[0], Magnitude):
obj = object.__new__(ConcatenatedMagnitude, *args, **kwargs)
obj.__init__(*args, **kwargs)
else:
ob... | Returns a concatenated magnitude object, if Magnitude parameters | __new__ | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _db(self, force_new=False):
"""Returns a cursor to the database. Each thread gets its
own cursor.
"""
identifier = threading.current_thread().ident
conn_exists = identifier in self._cursors
if not conn_exists or force_new:
if self.fd:
if os... | Returns a cursor to the database. Each thread gets its
own cursor.
| _db | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _key_t(self, key):
"""Transforms a key to lower case depending on case
sensitivity.
"""
if self.case_insensitive and (isinstance(key, str) or
isinstance(key, unicode)):
return key.lower()
return key | Transforms a key to lower case depending on case
sensitivity.
| _key_t | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _oov_key_t(self, key):
"""Transforms a key for out-of-vocabulary lookup.
"""
is_str = isinstance(key, str) or isinstance(key, unicode)
if is_str:
key = Magnitude.BOW + self._key_t(key) + Magnitude.EOW
return is_str, self._key_shrunk_2(key)
return is_st... | Transforms a key for out-of-vocabulary lookup.
| _oov_key_t | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _oov_english_stem_english_ixes(self, key):
"""Strips away common English prefixes and suffixes."""
key_lower = key.lower()
start_idx = 0
end_idx = 0
for p in Magnitude.ENGLISH_PREFIXES:
if key_lower[:len(p)] == p:
start_idx = len(p)
... | Strips away common English prefixes and suffixes. | _oov_english_stem_english_ixes | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _oov_stem(self, key):
"""Strips away common prefixes and suffixes."""
if self.language == 'en':
return self._oov_english_stem_english_ixes(key)
return key | Strips away common prefixes and suffixes. | _oov_stem | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _db_query_similar_keys_vector(self, key, orig_key, topn=3):
"""Finds similar keys in the database and gets the mean vector."""
def _sql_escape_single(s):
return s.replace("'", "''")
def _sql_escape_fts(s):
return ''.join("\\" + c if c in Magnitude.FTS_SPECIAL
... | Finds similar keys in the database and gets the mean vector. | _db_query_similar_keys_vector | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _seed(self, val):
"""Returns a unique seed for val and the (optional) namespace."""
if self._namespace:
return xxhash.xxh32(self._namespace + Magnitude.RARE_CHAR +
val.encode('utf-8')).intdigest()
else:
return xxhash.xxh32(val.encode('u... | Returns a unique seed for val and the (optional) namespace. | _seed | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _out_of_vocab_vector(self, key):
"""Generates a random vector based on the hash of the key."""
orig_key = key
is_str, key = self._oov_key_t(key)
if not is_str:
seed = self._seed(type(key).__name__)
Magnitude.OOV_RNG_LOCK.acquire()
np.random.seed(se... | Generates a random vector based on the hash of the key. | _out_of_vocab_vector | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _db_batch_generator(self, params):
""" Generates batches of paramaters that respect
SQLite's MAX_VARIABLE_NUMBER """
if len(params) <= Magnitude.SQLITE_MAX_VARIABLE_NUMBER:
yield params
else:
it = iter(params)
for batch in \
ite... | Generates batches of paramaters that respect
SQLite's MAX_VARIABLE_NUMBER | _db_batch_generator | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _db_full_result_to_vec(self, result, put_cache=True):
"""Converts a full database result to a vector."""
result_key = result[0]
if self._query_is_cached(result_key):
return (result_key, self.query(result_key))
else:
vec = self._db_result_to_vec(result[1:])
... | Converts a full database result to a vector. | _db_full_result_to_vec | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _vector_for_key(self, key):
"""Queries the database for a single key."""
result = self._db().execute(
"""
SELECT *
FROM `magnitude`
WHERE key = ?
ORDER BY key = ? COLLATE BINARY DESC
LIMIT 1;""",
... | Queries the database for a single key. | _vector_for_key | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _vectors_for_keys(self, keys):
"""Queries the database for multiple keys."""
unseen_keys = tuple(key for key in keys
if not self._query_is_cached(key))
unseen_keys_map = {}
if len(unseen_keys) > 0:
unseen_keys_map = {self._key_t(k): i for i, k ... | Queries the database for multiple keys. | _vectors_for_keys | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _key_for_index(self, index, return_vector=True):
"""Queries the database the key at a single index."""
columns = "key"
if return_vector:
columns = "*"
result = self._db().execute(
"""
SELECT """ + columns + """
FROM `magnitude`
... | Queries the database the key at a single index. | _key_for_index | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _keys_for_indices(self, indices, return_vector=True):
"""Queries the database for the keys of multiple indices."""
unseen_indices = tuple(int(index + 1) for index in indices
if self._key_for_index_cached._cache.get(((index,), # noqa
... | Queries the database for the keys of multiple indices. | _keys_for_indices | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def query(self, q, pad_to_length=None,
pad_left=None, truncate_left=None):
"""Handles a query of keys which could be a single key, a
1-D list of keys, or a 2-D list of keys.
"""
pad_to_length = pad_to_length or self.pad_to_length
pad_left = pad_left or self.pad_left... | Handles a query of keys which could be a single key, a
1-D list of keys, or a 2-D list of keys.
| query | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def index(self, q, return_vector=True):
"""Gets a key for an index or multiple indices."""
if isinstance(q, list) or isinstance(q, tuple):
return self._keys_for_indices(q, return_vector=return_vector)
else:
return self._key_for_index_cached(q, return_vector=return_vector) | Gets a key for an index or multiple indices. | index | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _query_numpy(self, key):
"""Returns the query for a key, forcibly converting the
resulting vector to a numpy array.
"""
key_is_ndarray = isinstance(key, np.ndarray)
key_is_list = isinstance(key, list)
key_len_ge_0 = key_is_list and len(key) > 0
key_0_is_number... | Returns the query for a key, forcibly converting the
resulting vector to a numpy array.
| _query_numpy | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _query_is_cached(self, key):
"""Checks if the query been cached by Magnitude."""
return ((self._vector_for_key_cached._cache.get((key,)) is not None) or ( # noqa
self._out_of_vocab_vector_cached._cache.get((key,)) is not None)) | Checks if the query been cached by Magnitude. | _query_is_cached | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def distance(self, key, q):
"""Calculates the distance from key to the key(s) in q."""
a = self._query_numpy(key)
if not isinstance(q, list):
b = self._query_numpy(q)
return np.linalg.norm(a - b)
else:
return [np.linalg.norm(a - self._query_numpy(b)) f... | Calculates the distance from key to the key(s) in q. | distance | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def similarity(self, key, q):
"""Calculates the similarity from key to the key(s) in q."""
a = self._query_numpy(key)
if not isinstance(q, list):
b = self._query_numpy(q)
return np.inner(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))
else:
bs = [self.... | Calculates the similarity from key to the key(s) in q. | similarity | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def most_similar_to_given(self, key, q):
"""Calculates the most similar key in q to key."""
distances = self.distance(key, q)
min_index, _ = min(enumerate(distances), key=operator.itemgetter(1))
return q[min_index] | Calculates the most similar key in q to key. | most_similar_to_given | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def doesnt_match(self, q):
"""Given a set of keys, figures out which key doesn't
match the rest.
"""
mean_vector = np.mean(self._query_numpy([[sq] for sq in q]), axis=0)
mean_unit_vector = mean_vector / np.linalg.norm(mean_vector)
distances = [np.linalg.norm(mean_unit_vec... | Given a set of keys, figures out which key doesn't
match the rest.
| doesnt_match | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _db_query_similarity(
self,
positive,
negative,
min_similarity=None,
topn=10,
exclude_keys=set(),
return_similarities=False,
method='distance',
effort=1.0):
"""Runs a database query to find vectors cl... | Runs a database query to find vectors close to vector. | _db_query_similarity | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def most_similar(self, positive, negative=[], topn=10, min_similarity=None,
return_similarities=True):
"""Finds the topn most similar vectors under or equal
to max distance.
"""
positive, negative = self._handle_pos_neg_args(positive, negative)
return self._... | Finds the topn most similar vectors under or equal
to max distance.
| most_similar | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def most_similar_cosmul(self, positive, negative=[], topn=10,
min_similarity=None, return_similarities=True):
"""Finds the topn most similar vectors under or equal to max
distance using 3CosMul:
[Levy and Goldberg](http://www.aclweb.org/anthology/W14-1618)
"""... | Finds the topn most similar vectors under or equal to max
distance using 3CosMul:
[Levy and Goldberg](http://www.aclweb.org/anthology/W14-1618)
| most_similar_cosmul | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def most_similar_approx(
self,
positive,
negative=[],
topn=10,
min_similarity=None,
return_similarities=True,
effort=1.0):
"""Approximates the topn most similar vectors under or equal to max
distance using Annoy:
... | Approximates the topn most similar vectors under or equal to max
distance using Annoy:
https://github.com/spotify/annoy
| most_similar_approx | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def closer_than(self, key, q, topn=None):
"""Finds all keys closer to key than q is to key."""
epsilon = (10.0 / 10**6)
min_similarity = self.similarity(key, q) + epsilon
return self.most_similar(key, topn=topn, min_similarity=min_similarity,
return_simi... | Finds all keys closer to key than q is to key. | closer_than | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def get_vectors_mmap(self):
"""Gets a numpy.memmap of all vectors, blocks if it is still
being built.
"""
if self._all_vectors is None:
while True:
if not self.setup_for_mmap:
self._setup_for_mmap()
try:
... | Gets a numpy.memmap of all vectors, blocks if it is still
being built.
| get_vectors_mmap | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def get_approx_index_chunks(self):
"""Gets decompressed chunks of the AnnoyIndex of the vectors from
the database."""
try:
db = self._db(force_new=True)
with lz4.frame.LZ4FrameDecompressor() as decompressor:
chunks = db.execute(
"""
... | Gets decompressed chunks of the AnnoyIndex of the vectors from
the database. | get_approx_index_chunks | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def get_approx_index(self):
"""Gets an AnnoyIndex of the vectors from the database."""
chunks = self.get_approx_index_chunks()
if self._approx_index is None:
while True:
if not self.setup_for_mmap:
self._setup_for_mmap()
try:
... | Gets an AnnoyIndex of the vectors from the database. | get_approx_index | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _iter(self, put_cache):
"""Yields keys and vectors for all vectors in the store."""
try:
db = self._db(force_new=True)
results = db.execute(
"""
SELECT *
FROM `magnitude`
""")
for result in re... | Yields keys and vectors for all vectors in the store. | _iter | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def __getitem__(self, q):
"""Performs the index method when indexed."""
if isinstance(q, slice):
return self.index(list(range(*q.indices(self.length))),
return_vector=True)
else:
return self.index(q, return_vector=True) | Performs the index method when indexed. | __getitem__ | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _take(self, q, multikey, i):
"""Selects only the i'th element from the inner-most axis and
reduces the dimensions of the tensor q by 1.
"""
if multikey == -1:
return q
else:
cut = np.take(q, [i], axis=multikey)
result = np.reshape(cut, np.s... | Selects only the i'th element from the inner-most axis and
reduces the dimensions of the tensor q by 1.
| _take | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _hstack(self, l, use_numpy):
"""Horizontally stacks NumPy arrays or Python lists"""
if use_numpy:
return np.concatenate(l, axis=-1)
else:
return list(chain.from_iterable(l)) | Horizontally stacks NumPy arrays or Python lists | _hstack | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _dstack(self, l, use_numpy):
"""Depth stacks NumPy arrays or Python lists"""
if use_numpy:
return np.concatenate(l, axis=-1)
else:
return [self._hstack((l3[example] for l3 in l),
use_numpy=use_numpy) for example in xrange(len(l[0]))] ... | Depth stacks NumPy arrays or Python lists | _dstack | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def query(self, q, pad_to_length=None,
pad_left=None, truncate_left=None):
"""Handles a query of keys which could be a single key, a
1-D list of keys, or a 2-D list of keys.
"""
# Check if keys are specified for each concatenated model
multikey = -1
if isin... | Handles a query of keys which could be a single key, a
1-D list of keys, or a 2-D list of keys.
| query | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def batchify(X, y, batch_size): # noqa: N803
""" Creates an iterator that chunks `X` and `y` into batches
that each contain `batch_size` elements and loops forever"""
X_batch_generator = cycle([X[i: i + batch_size] # noqa: N806
for i in xrange(0, len(X), batc... | Creates an iterator that chunks `X` and `y` into batches
that each contain `batch_size` elements and loops forever | batchify | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def class_encoding():
"""Creates a set of functions to add a new class, convert a
class into an integer, and the integer back to a class."""
class_to_int_map = {}
int_to_class_map = None
def add_class(c):
global int_to_class_map
int_to_class_map = None
... | Creates a set of functions to add a new class, convert a
class into an integer, and the integer back to a class. | class_encoding | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def to_categorical(y, num_classes=None):
"""Converts a class vector (integers) to binary class matrix.
"""
y = np.array(y, dtype='int')
input_shape = y.shape
if input_shape and input_shape[-1] == 1 and len(input_shape) > 1:
input_shape = tuple(input_shape[:-1])
... | Converts a class vector (integers) to binary class matrix.
| to_categorical | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src2/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src2/__init__.py | MIT |
def _sqlite_try_max_variable_number(num):
""" Tests whether SQLite can handle num variables """
db = sqlite3.connect(':memory:')
try:
db.cursor().execute(
"SELECT 1 IN (" + ",".join(["?"] * num) + ")",
([0] * num)
).fetchall()
return num
except BaseExcepti... | Tests whether SQLite can handle num variables | _sqlite_try_max_variable_number | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def __new__(cls, *args, **kwargs):
""" Returns a concatenated magnitude object, if Magnitude parameters """
if len(args) > 0 and isinstance(args[0], Magnitude):
obj = object.__new__(ConcatenatedMagnitude, *args, **kwargs)
obj.__init__(*args, **kwargs)
else:
ob... | Returns a concatenated magnitude object, if Magnitude parameters | __new__ | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _db(self, force_new=False):
"""Returns a cursor to the database. Each thread gets its
own cursor.
"""
identifier = threading.current_thread().ident
conn_exists = identifier in self._cursors
if not conn_exists or force_new:
if self.fd:
if os... | Returns a cursor to the database. Each thread gets its
own cursor.
| _db | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _key_t(self, key):
"""Transforms a key to lower case depending on case
sensitivity.
"""
if self.case_insensitive and (isinstance(key, str) or
isinstance(key, unicode)):
return key.lower()
return key | Transforms a key to lower case depending on case
sensitivity.
| _key_t | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _oov_key_t(self, key):
"""Transforms a key for out-of-vocabulary lookup.
"""
is_str = isinstance(key, str) or isinstance(key, unicode)
if is_str:
key = Magnitude.BOW + self._key_t(key) + Magnitude.EOW
return is_str, self._key_shrunk_2(key)
return is_st... | Transforms a key for out-of-vocabulary lookup.
| _oov_key_t | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _oov_english_stem_english_ixes(self, key):
"""Strips away common English prefixes and suffixes."""
key_lower = key.lower()
start_idx = 0
end_idx = 0
for p in Magnitude.ENGLISH_PREFIXES:
if key_lower[:len(p)] == p:
start_idx = len(p)
... | Strips away common English prefixes and suffixes. | _oov_english_stem_english_ixes | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _oov_stem(self, key):
"""Strips away common prefixes and suffixes."""
if self.language == 'en':
return self._oov_english_stem_english_ixes(key)
return key | Strips away common prefixes and suffixes. | _oov_stem | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _db_query_similar_keys_vector(self, key, orig_key, topn=3):
"""Finds similar keys in the database and gets the mean vector."""
def _sql_escape_single(s):
return s.replace("'", "''")
def _sql_escape_fts(s):
return ''.join("\\" + c if c in Magnitude.FTS_SPECIAL
... | Finds similar keys in the database and gets the mean vector. | _db_query_similar_keys_vector | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _seed(self, val):
"""Returns a unique seed for val and the (optional) namespace."""
if self._namespace:
return xxhash.xxh32(self._namespace + Magnitude.RARE_CHAR +
val.encode('utf-8')).intdigest()
else:
return xxhash.xxh32(val.encode('u... | Returns a unique seed for val and the (optional) namespace. | _seed | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _out_of_vocab_vector(self, key):
"""Generates a random vector based on the hash of the key."""
orig_key = key
is_str, key = self._oov_key_t(key)
if not is_str:
seed = self._seed(type(key).__name__)
Magnitude.OOV_RNG_LOCK.acquire()
np.random.seed(se... | Generates a random vector based on the hash of the key. | _out_of_vocab_vector | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _db_batch_generator(self, params):
""" Generates batches of paramaters that respect
SQLite's MAX_VARIABLE_NUMBER """
if len(params) <= Magnitude.SQLITE_MAX_VARIABLE_NUMBER:
yield params
else:
it = iter(params)
for batch in \
ite... | Generates batches of paramaters that respect
SQLite's MAX_VARIABLE_NUMBER | _db_batch_generator | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _db_full_result_to_vec(self, result, put_cache=True):
"""Converts a full database result to a vector."""
result_key = result[0]
if self._query_is_cached(result_key):
return (result_key, self.query(result_key))
else:
vec = self._db_result_to_vec(result[1:])
... | Converts a full database result to a vector. | _db_full_result_to_vec | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _vector_for_key(self, key):
"""Queries the database for a single key."""
result = self._db().execute(
"""
SELECT *
FROM `magnitude`
WHERE key = ?
ORDER BY key = ? COLLATE BINARY DESC
LIMIT 1;""",
... | Queries the database for a single key. | _vector_for_key | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _vectors_for_keys(self, keys):
"""Queries the database for multiple keys."""
unseen_keys = tuple(key for key in keys
if not self._query_is_cached(key))
unseen_keys_map = {}
if len(unseen_keys) > 0:
unseen_keys_map = {self._key_t(k): i for i, k ... | Queries the database for multiple keys. | _vectors_for_keys | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _key_for_index(self, index, return_vector=True):
"""Queries the database the key at a single index."""
columns = "key"
if return_vector:
columns = "*"
result = self._db().execute(
"""
SELECT """ + columns + """
FROM `magnitude`
... | Queries the database the key at a single index. | _key_for_index | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _keys_for_indices(self, indices, return_vector=True):
"""Queries the database for the keys of multiple indices."""
unseen_indices = tuple(int(index + 1) for index in indices
if self._key_for_index_cached._cache.get(((index,), # noqa
... | Queries the database for the keys of multiple indices. | _keys_for_indices | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def query(self, q, pad_to_length=None,
pad_left=None, truncate_left=None):
"""Handles a query of keys which could be a single key, a
1-D list of keys, or a 2-D list of keys.
"""
pad_to_length = pad_to_length or self.pad_to_length
pad_left = pad_left or self.pad_left... | Handles a query of keys which could be a single key, a
1-D list of keys, or a 2-D list of keys.
| query | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def index(self, q, return_vector=True):
"""Gets a key for an index or multiple indices."""
if isinstance(q, list) or isinstance(q, tuple):
return self._keys_for_indices(q, return_vector=return_vector)
else:
return self._key_for_index_cached(q, return_vector=return_vector) | Gets a key for an index or multiple indices. | index | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _query_numpy(self, key):
"""Returns the query for a key, forcibly converting the
resulting vector to a numpy array.
"""
key_is_ndarray = isinstance(key, np.ndarray)
key_is_list = isinstance(key, list)
key_len_ge_0 = key_is_list and len(key) > 0
key_0_is_number... | Returns the query for a key, forcibly converting the
resulting vector to a numpy array.
| _query_numpy | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _query_is_cached(self, key):
"""Checks if the query been cached by Magnitude."""
return ((self._vector_for_key_cached._cache.get((key,)) is not None) or ( # noqa
self._out_of_vocab_vector_cached._cache.get((key,)) is not None)) | Checks if the query been cached by Magnitude. | _query_is_cached | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def distance(self, key, q):
"""Calculates the distance from key to the key(s) in q."""
a = self._query_numpy(key)
if not isinstance(q, list):
b = self._query_numpy(q)
return np.linalg.norm(a - b)
else:
return [np.linalg.norm(a - self._query_numpy(b)) f... | Calculates the distance from key to the key(s) in q. | distance | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def similarity(self, key, q):
"""Calculates the similarity from key to the key(s) in q."""
a = self._query_numpy(key)
if not isinstance(q, list):
b = self._query_numpy(q)
return np.inner(a, b) / (np.linalg.norm(a) * np.linalg.norm(b))
else:
bs = [self.... | Calculates the similarity from key to the key(s) in q. | similarity | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def most_similar_to_given(self, key, q):
"""Calculates the most similar key in q to key."""
distances = self.distance(key, q)
min_index, _ = min(enumerate(distances), key=operator.itemgetter(1))
return q[min_index] | Calculates the most similar key in q to key. | most_similar_to_given | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def doesnt_match(self, q):
"""Given a set of keys, figures out which key doesn't
match the rest.
"""
mean_vector = np.mean(self._query_numpy([[sq] for sq in q]), axis=0)
mean_unit_vector = mean_vector / np.linalg.norm(mean_vector)
distances = [np.linalg.norm(mean_unit_vec... | Given a set of keys, figures out which key doesn't
match the rest.
| doesnt_match | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _db_query_similarity(
self,
positive,
negative,
min_similarity=None,
topn=10,
exclude_keys=set(),
return_similarities=False,
method='distance',
effort=1.0):
"""Runs a database query to find vectors cl... | Runs a database query to find vectors close to vector. | _db_query_similarity | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def most_similar(self, positive, negative=[], topn=10, min_similarity=None,
return_similarities=True):
"""Finds the topn most similar vectors under or equal
to max distance.
"""
positive, negative = self._handle_pos_neg_args(positive, negative)
return self._... | Finds the topn most similar vectors under or equal
to max distance.
| most_similar | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def most_similar_cosmul(self, positive, negative=[], topn=10,
min_similarity=None, return_similarities=True):
"""Finds the topn most similar vectors under or equal to max
distance using 3CosMul:
[Levy and Goldberg](http://www.aclweb.org/anthology/W14-1618)
"""... | Finds the topn most similar vectors under or equal to max
distance using 3CosMul:
[Levy and Goldberg](http://www.aclweb.org/anthology/W14-1618)
| most_similar_cosmul | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def most_similar_approx(
self,
positive,
negative=[],
topn=10,
min_similarity=None,
return_similarities=True,
effort=1.0):
"""Approximates the topn most similar vectors under or equal to max
distance using Annoy:
... | Approximates the topn most similar vectors under or equal to max
distance using Annoy:
https://github.com/spotify/annoy
| most_similar_approx | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def closer_than(self, key, q, topn=None):
"""Finds all keys closer to key than q is to key."""
epsilon = (10.0 / 10**6)
min_similarity = self.similarity(key, q) + epsilon
return self.most_similar(key, topn=topn, min_similarity=min_similarity,
return_simi... | Finds all keys closer to key than q is to key. | closer_than | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def get_vectors_mmap(self):
"""Gets a numpy.memmap of all vectors, blocks if it is still
being built.
"""
if self._all_vectors is None:
while True:
if not self.setup_for_mmap:
self._setup_for_mmap()
try:
... | Gets a numpy.memmap of all vectors, blocks if it is still
being built.
| get_vectors_mmap | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def get_approx_index_chunks(self):
"""Gets decompressed chunks of the AnnoyIndex of the vectors from
the database."""
try:
db = self._db(force_new=True)
with lz4.frame.LZ4FrameDecompressor() as decompressor:
chunks = db.execute(
"""
... | Gets decompressed chunks of the AnnoyIndex of the vectors from
the database. | get_approx_index_chunks | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def get_approx_index(self):
"""Gets an AnnoyIndex of the vectors from the database."""
chunks = self.get_approx_index_chunks()
if self._approx_index is None:
while True:
if not self.setup_for_mmap:
self._setup_for_mmap()
try:
... | Gets an AnnoyIndex of the vectors from the database. | get_approx_index | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _iter(self, put_cache):
"""Yields keys and vectors for all vectors in the store."""
try:
db = self._db(force_new=True)
results = db.execute(
"""
SELECT *
FROM `magnitude`
""")
for result in re... | Yields keys and vectors for all vectors in the store. | _iter | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def __getitem__(self, q):
"""Performs the index method when indexed."""
if isinstance(q, slice):
return self.index(list(range(*q.indices(self.length))),
return_vector=True)
else:
return self.index(q, return_vector=True) | Performs the index method when indexed. | __getitem__ | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _take(self, q, multikey, i):
"""Selects only the i'th element from the inner-most axis and
reduces the dimensions of the tensor q by 1.
"""
if multikey == -1:
return q
else:
cut = np.take(q, [i], axis=multikey)
result = np.reshape(cut, np.s... | Selects only the i'th element from the inner-most axis and
reduces the dimensions of the tensor q by 1.
| _take | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _hstack(self, l, use_numpy):
"""Horizontally stacks NumPy arrays or Python lists"""
if use_numpy:
return np.concatenate(l, axis=-1)
else:
return list(chain.from_iterable(l)) | Horizontally stacks NumPy arrays or Python lists | _hstack | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def _dstack(self, l, use_numpy):
"""Depth stacks NumPy arrays or Python lists"""
if use_numpy:
return np.concatenate(l, axis=-1)
else:
return [self._hstack((l3[example] for l3 in l),
use_numpy=use_numpy) for example in xrange(len(l[0]))] ... | Depth stacks NumPy arrays or Python lists | _dstack | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def query(self, q, pad_to_length=None,
pad_left=None, truncate_left=None):
"""Handles a query of keys which could be a single key, a
1-D list of keys, or a 2-D list of keys.
"""
# Check if keys are specified for each concatenated model
multikey = -1
if isin... | Handles a query of keys which could be a single key, a
1-D list of keys, or a 2-D list of keys.
| query | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def batchify(X, y, batch_size): # noqa: N803
""" Creates an iterator that chunks `X` and `y` into batches
that each contain `batch_size` elements and loops forever"""
X_batch_generator = cycle([X[i: i + batch_size] # noqa: N806
for i in xrange(0, len(X), batc... | Creates an iterator that chunks `X` and `y` into batches
that each contain `batch_size` elements and loops forever | batchify | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def class_encoding():
"""Creates a set of functions to add a new class, convert a
class into an integer, and the integer back to a class."""
class_to_int_map = {}
int_to_class_map = None
def add_class(c):
global int_to_class_map
int_to_class_map = None
... | Creates a set of functions to add a new class, convert a
class into an integer, and the integer back to a class. | class_encoding | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def to_categorical(y, num_classes=None):
"""Converts a class vector (integers) to binary class matrix.
"""
y = np.array(y, dtype='int')
input_shape = y.shape
if input_shape and input_shape[-1] == 1 and len(input_shape) > 1:
input_shape = tuple(input_shape[:-1])
... | Converts a class vector (integers) to binary class matrix.
| to_categorical | python | plasticityai/magnitude | pymagnitude/third_party/_pysqlite/src3/__init__.py | https://github.com/plasticityai/magnitude/blob/master/pymagnitude/third_party/_pysqlite/src3/__init__.py | MIT |
def get_size(obj, seen=None):
"""Recursively finds size of objects
Source: https://goshippo.com/blog/measure-real-size-any-python-object/
"""
size = sys.getsizeof(obj)
if seen is None:
seen = set()
obj_id = id(obj)
if obj_id in seen:
return 0
# Important mark as seen *... | Recursively finds size of objects
Source: https://goshippo.com/blog/measure-real-size-any-python-object/
| get_size | python | plasticityai/magnitude | tests/benchmark.py | https://github.com/plasticityai/magnitude/blob/master/tests/benchmark.py | MIT |
def get_channel_dim(input_tensor, data_format='INVALID'):
"""Returns the number of channels in the input tensor."""
shape = input_tensor.get_shape().as_list()
assert data_format != 'INVALID'
assert len(shape) == 4
if data_format == 'NHWC':
return int(shape[3])
elif data_format == 'NCHW':
return int(... | Returns the number of channels in the input tensor. | get_channel_dim | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def block_build(self, input_tensors, is_training, lengths=None, hparams=None):
"""Builds a block for phoenix.
Args:
input_tensors: A list of input tensors.
is_training: Whether we are training. Used for regularization.
lengths: The lengths of the input sequences in the batch.
hparams: T... | Builds a block for phoenix.
Args:
input_tensors: A list of input tensors.
is_training: Whether we are training. Used for regularization.
lengths: The lengths of the input sequences in the batch.
hparams: The training HParams.
Returns:
output_tensors: A list of the output tensors.... | block_build | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def is_input_order_important(self):
"""Is the order of the entries in the input tensor important.
Returns:
A bool specifying if the order of the entries in the input is important.
Examples where the order is important: Input for a cnn layer.
(e.g., pixels an image). Examples when the order is... | Is the order of the entries in the input tensor important.
Returns:
A bool specifying if the order of the entries in the input is important.
Examples where the order is important: Input for a cnn layer.
(e.g., pixels an image). Examples when the order is not important:
Input for a dense lay... | is_input_order_important | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def __init__(self,
max_output_size=100,
max_number_of_parameters=None,
apply_batch_norm=False,
residual_connection_type=None,
**kwargs):
"""Initializes a new FullyConnectedBlock instance.
Args:
max_output_size: The maximum number ... | Initializes a new FullyConnectedBlock instance.
Args:
max_output_size: The maximum number of output neurons.
max_number_of_parameters: The maximum number of parameters allowed.
apply_batch_norm: Whether to apply batch normalization to the layer.
residual_connection_type: The ResidualConnect... | __init__ | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def _add_residual_connection(self, input_tensor, output_tensor):
"""Creates the residual connection between the input and the output."""
if self._residual_connection_type == ResidualConnectionType.NONE:
return output_tensor
in_shape = input_tensor.shape[-1]
out_shape = output_tensor.shape[-1]
... | Creates the residual connection between the input and the output. | _add_residual_connection | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def block_build(self, input_tensors, is_training, lengths=None, hparams=None):
"""Applies 2d max pooling on the input tensor."""
input_tensor = input_tensors[-1]
if input_tensor.get_shape().as_list()[2] < self._pool_size:
return input_tensors
max_pool = tf.keras.layers.MaxPool2D(
pool_siz... | Applies 2d max pooling on the input tensor. | block_build | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def block_build(self, input_tensors, is_training, lengths=None, hparams=None):
"""Returns a ReLU activated output of a residual unit with 2 sub layers."""
input_tensor = input_tensors[-1]
net1 = tf.keras.layers.Conv2D(
get_channel_dim(input_tensor),
kernel_size=self._kernel_size,
nam... | Returns a ReLU activated output of a residual unit with 2 sub layers. | block_build | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def block_build(self, input_tensors, is_training, lengths=None, hparams=None):
"""Custom (wide) convolution block with some pooling."""
# Guard so that we won't have zero channels
input_tensor = input_tensors[-1]
if get_channel_dim(input_tensor) < 6:
return input_tensors
reduced = tf.keras.la... | Custom (wide) convolution block with some pooling. | block_build | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def block_build(self, input_tensors, is_training, lengths=None, hparams=None):
"""Builds a basic rnn block.
Args:
input_tensors: A tf.Tensor with the input.
is_training: Whether we are training. Used for regularization.
lengths: The lengths of the input sequences in the batch.
hparams: ... | Builds a basic rnn block.
Args:
input_tensors: A tf.Tensor with the input.
is_training: Whether we are training. Used for regularization.
lengths: The lengths of the input sequences in the batch.
hparams: hparams for the build.
Returns:
output tensor
| block_build | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def block_build(self, input_tensors, is_training, lengths=None, hparams=None):
"""Builds a one dimensional convolutional block.
Args:
input_tensors: A tf.Tensor with the input.
is_training: Whether we are training. Used for regularization.
lengths: The lengths of the input sequences in the ba... | Builds a one dimensional convolutional block.
Args:
input_tensors: A tf.Tensor with the input.
is_training: Whether we are training. Used for regularization.
lengths: The lengths of the input sequences in the batch.
hparams: hparams for the build.
Returns:
output tensor
| block_build | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def block_build(self, input_tensors, is_training, lengths=None, hparams=None):
"""Builds as LSTM block.
Args:
input_tensors: A list of tf.Tensors with the input.
is_training: Whether we are training. Used for regularization.
lengths: The lengths of the input sequences in the batch.
hpar... | Builds as LSTM block.
Args:
input_tensors: A list of tf.Tensors with the input.
is_training: Whether we are training. Used for regularization.
lengths: The lengths of the input sequences in the batch.
hparams: hparams for the build.
Returns:
output tensor
| block_build | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def block_build(self, input_tensors, is_training, lengths=None, hparams=None):
"""Builds as LSTM block.
Args:
input_tensors: A list of tf.Tensors with the input.
is_training: Whether we are training. Used for regularization.
lengths: The lengths of the input sequences in the batch.
hpar... | Builds as LSTM block.
Args:
input_tensors: A list of tf.Tensors with the input.
is_training: Whether we are training. Used for regularization.
lengths: The lengths of the input sequences in the batch.
hparams: hparams for the build.
Returns:
output tensor
| block_build | python | google/model_search | model_search/block.py | https://github.com/google/model_search/blob/master/model_search/block.py | Apache-2.0 |
def search_space(blocks_to_use=None):
"""Returns required search space for all blocks."""
search_space = ms_hparameters.Hyperparameters()
for block_type in BlockType:
if block_type == BlockType.EMPTY_BLOCK:
continue
if blocks_to_use is None or block_type.name in blocks_to_use:
ta... | Returns required search space for all blocks. | search_space | python | google/model_search | model_search/block_builder.py | https://github.com/google/model_search/blob/master/model_search/block_builder.py | Apache-2.0 |
def replay_is_training_a_tower(self, my_id):
"""Returns True if we are training a new tower in a replay run.
Example:
1. In adaptive ensembling, every trial is training one new tower, so the
return value is always True.
2. In a non-adaptive ensembling, every trial except the last one is
... | Returns True if we are training a new tower in a replay run.
Example:
1. In adaptive ensembling, every trial is training one new tower, so the
return value is always True.
2. In a non-adaptive ensembling, every trial except the last one is
training a new tower, whereas the last trial just e... | replay_is_training_a_tower | python | google/model_search | model_search/controller.py | https://github.com/google/model_search/blob/master/model_search/controller.py | Apache-2.0 |
Subsets and Splits
Django Code with Docstrings
Filters Python code examples from Django repository that contain Django-related code, helping identify relevant code snippets for understanding Django framework usage patterns.
SQL Console for Shuu12121/python-treesitter-filtered-datasetsV2
Retrieves specific code examples from the Flask repository but doesn't provide meaningful analysis or patterns beyond basic data retrieval.
HTTPX Repo Code and Docstrings
Retrieves specific code examples from the httpx repository, which is useful for understanding how particular libraries are used but doesn't provide broader analytical insights about the dataset.
Requests Repo Docstrings & Code
Retrieves code examples with their docstrings and file paths from the requests repository, providing basic filtering but limited analytical value beyond finding specific code samples.
Quart Repo Docstrings & Code
Retrieves code examples with their docstrings from the Quart repository, providing basic code samples but offering limited analytical value for understanding broader patterns or relationships in the dataset.