uid stringlengths 24 24 | split stringclasses 1
value | category stringclasses 2
values | content stringlengths 5 482k | signature stringlengths 1 14k | suffix stringlengths 1 482k | prefix stringlengths 9 14k | prefix_token_count int64 3 5.01k | prefix_token_budget int64 64 256 | element_token_count int64 1 292k | signature_token_count int64 1 5.01k | prefix_context_token_count int64 0 255 | repo stringlengths 7 112 | path stringlengths 4 208 | language stringclasses 1
value | name stringlengths 1 218 | qualname stringlengths 1 218 | start_line int64 1 26.7k | end_line int64 1 26.7k | signature_start_line int64 1 26.7k | signature_end_line int64 1 26.7k | source_hash stringlengths 40 40 | source_dataset stringclasses 1
value | source_split stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
a424dadc65a2a0e9c32061df | train | class | class rollup(ColumnElement):
def __init__(self, *elements):
self.elements = [_clause_element_as_expr(e) for e in elements]
| class rollup(ColumnElement):
| def __init__(self, *elements):
self.elements = [_clause_element_as_expr(e) for e in elements]
| 2013
@author: peterb
'''
from sqlalchemy.sql.expression import ColumnElement, _clause_element_as_expr
from sqlalchemy.ext.compiler import compiles
from sqlalchemy.ext.mutable import Mutable
from sqlalchemy.types import TypeDecorator, VARCHAR
from blueshed.utils.utils import dumps, loads
class rollup(ColumnElement):
| 64 | 64 | 33 | 6 | 57 | blueshed/blueshed-py | src/blueshed/model_helpers/sql_extensions.py | Python | rollup | rollup | 15 | 17 | 15 | 15 | 79d30299684949ad193670d0c9258d3d841579d0 | bigcode/the-stack | train |
b997bd187dd756e42491b9ce | train | class | class JSONEncodedDict(TypeDecorator):
"Represents an immutable structure as a json-encoded string."
impl = VARCHAR
def process_bind_param(self, value, dialect):
if value is not None:
value = dumps(value)
return value
def process_result_value(self, value, dialect):
... | class JSONEncodedDict(TypeDecorator):
| "Represents an immutable structure as a json-encoded string."
impl = VARCHAR
def process_bind_param(self, value, dialect):
if value is not None:
value = dumps(value)
return value
def process_result_value(self, value, dialect):
if value is not None:
valu... | ) for e in elements]
@compiles(rollup, "mysql")
def _mysql_rollup(element, compiler, **kw):
return "%s WITH ROLLUP" % (', '.join([compiler.process(e, **kw) for e in element.elements]))
class JSONEncodedDict(TypeDecorator):
| 63 | 64 | 82 | 7 | 56 | blueshed/blueshed-py | src/blueshed/model_helpers/sql_extensions.py | Python | JSONEncodedDict | JSONEncodedDict | 24 | 37 | 24 | 24 | 7cc30af0cdc433865200b5c591264ab56492176a | bigcode/the-stack | train |
369b311b23c10e03f9927d8a | train | function | @compiles(rollup, "mysql")
def _mysql_rollup(element, compiler, **kw):
return "%s WITH ROLLUP" % (', '.join([compiler.process(e, **kw) for e in element.elements]))
| @compiles(rollup, "mysql")
def _mysql_rollup(element, compiler, **kw):
| return "%s WITH ROLLUP" % (', '.join([compiler.process(e, **kw) for e in element.elements]))
| blueshed.utils.utils import dumps, loads
class rollup(ColumnElement):
def __init__(self, *elements):
self.elements = [_clause_element_as_expr(e) for e in elements]
@compiles(rollup, "mysql")
def _mysql_rollup(element, compiler, **kw):
| 64 | 64 | 50 | 22 | 42 | blueshed/blueshed-py | src/blueshed/model_helpers/sql_extensions.py | Python | _mysql_rollup | _mysql_rollup | 19 | 21 | 19 | 20 | 310f8a5dba044d9398e43ff7b2180a8f43848629 | bigcode/the-stack | train |
2ba6adb2415baf200b1317b3 | train | class | class Controller:
def __init__(self):
"""Initialise the controller. This sets up the command line argument parsing etc."""
self._parser = argparse.ArgumentParser(description='Run securify.')
self._parser.add_argument('-t', '--truffle',
action="store_true",
... | class Controller:
| def __init__(self):
"""Initialise the controller. This sets up the command line argument parsing etc."""
self._parser = argparse.ArgumentParser(description='Run securify.')
self._parser.add_argument('-t', '--truffle',
action="store_true",
... | the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language govern... | 99 | 99 | 331 | 3 | 95 | eluanshi7/securifyresearch | scripts/controller.py | Python | Controller | Controller | 28 | 68 | 28 | 28 | 91915eabb20e630f49016413764249d99ea9c9a6 | bigcode/the-stack | train |
bf7e4c5a448f09a2710a69ae | train | function | def return_get_res(url, cookies=None, proxies=None, headers=None, encoding='utf-8'):
if not headers:
headers = DEFAULT_HEADERS
# read settings from ini file
use_proxy = return_config_string(['代理', '是否使用代理？'])
# prioritize passed in proxies
if use_proxy == '是' and not proxies:
proxi... | def return_get_res(url, cookies=None, proxies=None, headers=None, encoding='utf-8'):
| if not headers:
headers = DEFAULT_HEADERS
# read settings from ini file
use_proxy = return_config_string(['代理', '是否使用代理？'])
# prioritize passed in proxies
if use_proxy == '是' and not proxies:
proxies = return_config_string(['代理', '代理IP及端口'])
res = requests.get(url, headers=hea... | pass
#print('not using proxy for requests')
res = requests.post(url, data, headers=headers, cookies=cookies, proxies=proxies)
res.encoding = encoding
return res
def return_get_res(url, cookies=None, proxies=None, headers=None, encoding='utf-8'):
| 64 | 64 | 120 | 21 | 42 | jadjz/JAVOneStop | JavHelper/core/requester_proxy.py | Python | return_get_res | return_get_res | 28 | 41 | 28 | 28 | 5b2caf82d559439b5f197a174f46b442da626a57 | bigcode/the-stack | train |
f3a8e28fd87f8c99b299c0de | train | function | def return_html_text(url, cookies=None, proxies=None, encoding='utf-8'):
# read settings from ini file
use_proxy = return_config_string(['代理', '是否使用代理？'])
# prioritize passed in proxies
if use_proxy == '是' and not proxies:
proxies = return_config_string(['代理', '代理IP及端口'])
res = requests.ge... | def return_html_text(url, cookies=None, proxies=None, encoding='utf-8'):
# read settings from ini file
| use_proxy = return_config_string(['代理', '是否使用代理？'])
# prioritize passed in proxies
if use_proxy == '是' and not proxies:
proxies = return_config_string(['代理', '代理IP及端口'])
res = requests.get(url, cookies=cookies, proxies=proxies)
res.encoding = encoding
return res.text
| 代理', '代理IP及端口'])
res = requests.get(url, headers=headers, cookies=cookies, proxies=proxies)
res.encoding = encoding
return res
def return_html_text(url, cookies=None, proxies=None, encoding='utf-8'):
# read settings from ini file
| 64 | 64 | 104 | 26 | 37 | jadjz/JAVOneStop | JavHelper/core/requester_proxy.py | Python | return_html_text | return_html_text | 44 | 54 | 44 | 45 | e90c7a6625288b9a953524f9c36e41c6f2a77f33 | bigcode/the-stack | train |
bbed105cbf851235b335c159 | train | function | def return_post_res(url, data=None, cookies=None, proxies=None, headers=None, encoding='utf-8'):
if not headers:
headers = DEFAULT_HEADERS
# read settings from ini file
use_proxy = return_config_string(['代理', '是否使用代理？'])
# prioritize passed in proxies
if use_proxy == '是' and not proxies:
... | def return_post_res(url, data=None, cookies=None, proxies=None, headers=None, encoding='utf-8'):
| if not headers:
headers = DEFAULT_HEADERS
# read settings from ini file
use_proxy = return_config_string(['代理', '是否使用代理？'])
# prioritize passed in proxies
if use_proxy == '是' and not proxies:
proxies = return_config_string(['代理', '代理IP及端口'])
else:
pass
#print('n... | Mac OS X 10_15_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.88 Safari/537.36'
}
def return_post_res(url, data=None, cookies=None, proxies=None, headers=None, encoding='utf-8'):
| 64 | 64 | 141 | 24 | 40 | jadjz/JAVOneStop | JavHelper/core/requester_proxy.py | Python | return_post_res | return_post_res | 10 | 26 | 10 | 10 | 6c0db84d53f6dffdd2d63c11950f14163b90bc0b | bigcode/the-stack | train |
50d5fc08acfff8519cfd7221 | train | function | def FMotionStart(builder): builder.StartObject(3)
| def FMotionStart(builder): | builder.StartObject(3)
| (self):
o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8))
if o != 0:
return self._tab.Get(flatbuffers.number_types.Float64Flags, o + self._tab.Pos)
return 0.0
def FMotionStart(builder): | 64 | 64 | 12 | 7 | 56 | sintefneodroid/schema | FBSSchemaGenerator/build/python/FMotion.py | Python | FMotionStart | FMotionStart | 42 | 42 | 42 | 42 | 1f2e13b3748b5539c5f97643f8608f7ae40992c7 | bigcode/the-stack | train |
4867d96d46ec7d3ecdd96b40 | train | function | def FMotionAddActuatorName(builder, actuatorName): builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(actuatorName), 0)
| def FMotionAddActuatorName(builder, actuatorName): | builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(actuatorName), 0)
| def FMotionStart(builder): builder.StartObject(3)
def FMotionAddActorName(builder, actorName): builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(actorName), 0)
def FMotionAddActuatorName(builder, actuatorName): | 64 | 64 | 41 | 13 | 51 | sintefneodroid/schema | FBSSchemaGenerator/build/python/FMotion.py | Python | FMotionAddActuatorName | FMotionAddActuatorName | 44 | 44 | 44 | 44 | 086fe26a1a5360a2395d61322c60730d584e089d | bigcode/the-stack | train |
0beeb07e85c95ee0bde615af | train | function | def FMotionAddStrength(builder, strength): builder.PrependFloat64Slot(2, strength, 0.0)
| def FMotionAddStrength(builder, strength): | builder.PrependFloat64Slot(2, strength, 0.0)
| _types.UOffsetTFlags.py_type(actorName), 0)
def FMotionAddActuatorName(builder, actuatorName): builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(actuatorName), 0)
def FMotionAddStrength(builder, strength): | 64 | 64 | 25 | 10 | 54 | sintefneodroid/schema | FBSSchemaGenerator/build/python/FMotion.py | Python | FMotionAddStrength | FMotionAddStrength | 45 | 45 | 45 | 45 | ca7924a33d7736e6209d87dfab9a01843fc57408 | bigcode/the-stack | train |
06ce67a01ac5f1de34d46b26 | train | function | def FMotionAddActorName(builder, actorName): builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(actorName), 0)
| def FMotionAddActorName(builder, actorName): | builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(actorName), 0)
| tab.Offset(8))
if o != 0:
return self._tab.Get(flatbuffers.number_types.Float64Flags, o + self._tab.Pos)
return 0.0
def FMotionStart(builder): builder.StartObject(3)
def FMotionAddActorName(builder, actorName): | 64 | 64 | 39 | 12 | 52 | sintefneodroid/schema | FBSSchemaGenerator/build/python/FMotion.py | Python | FMotionAddActorName | FMotionAddActorName | 43 | 43 | 43 | 43 | 9a756498e750182d5106052c5e184f80b7b4f392 | bigcode/the-stack | train |
875f171d7375be97136888ab | train | function | def FMotionEnd(builder): return builder.EndObject()
| def FMotionEnd(builder): | return builder.EndObject()
| actuatorName): builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(actuatorName), 0)
def FMotionAddStrength(builder, strength): builder.PrependFloat64Slot(2, strength, 0.0)
def FMotionEnd(builder): | 64 | 64 | 11 | 7 | 57 | sintefneodroid/schema | FBSSchemaGenerator/build/python/FMotion.py | Python | FMotionEnd | FMotionEnd | 46 | 46 | 46 | 46 | 2a7d5a006a5aa9a93ba000c9eb8bc1b5a162174d | bigcode/the-stack | train |
9921c56b3520d9535a81e2a0 | train | class | class FMotion(object):
__slots__ = ['_tab']
@classmethod
def GetRootAsFMotion(cls, buf, offset):
n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
x = FMotion()
x.Init(buf, n + offset)
return x
# FMotion
def Init(self, buf, pos):
self._tab ... | class FMotion(object):
| __slots__ = ['_tab']
@classmethod
def GetRootAsFMotion(cls, buf, offset):
n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset)
x = FMotion()
x.Init(buf, n + offset)
return x
# FMotion
def Init(self, buf, pos):
self._tab = flatbuffers.table.Tab... | # automatically generated by the FlatBuffers compiler, do not modify
# namespace: Reaction
import flatbuffers
class FMotion(object):
| 27 | 81 | 271 | 5 | 21 | sintefneodroid/schema | FBSSchemaGenerator/build/python/FMotion.py | Python | FMotion | FMotion | 7 | 40 | 7 | 7 | bffed7de8eba07db1d3861cc40b583c88b8d1eb2 | bigcode/the-stack | train |
8b70fec9a4c29742208d5e9f | train | function | @pytest.fixture
def tf_v_ae_mnist(request):
# load and preprocess MNIST data
(X_train, _), (X_test, _) = tf.keras.datasets.mnist.load_data()
X = X_train.reshape(60000, input_dim)[:1000] # only train on 1000 instances
X = X.astype(np.float32)
X /= 255
# init model, predict with untrained model,... | @pytest.fixture
def tf_v_ae_mnist(request):
# load and preprocess MNIST data
| (X_train, _), (X_test, _) = tf.keras.datasets.mnist.load_data()
X = X_train.reshape(60000, input_dim)[:1000] # only train on 1000 instances
X = X.astype(np.float32)
X /= 255
# init model, predict with untrained model, train and predict with trained model
model = request.param
X_recon_untra... | _dim, activation=tf.nn.sigmoid)
]
)
ae = AE(encoder_net, decoder_net)
vae = VAE(encoder_net, decoder_net, latent_dim)
tests = [ae, vae]
@pytest.fixture
def tf_v_ae_mnist(request):
# load and preprocess MNIST data
| 64 | 64 | 209 | 21 | 43 | Clusks/alibi-detect | alibi_detect/models/tests/test_autoencoder.py | Python | tf_v_ae_mnist | tf_v_ae_mnist | 33 | 49 | 33 | 35 | 654fe70472fab421c6fe566b2a4f0c652cb9a091 | bigcode/the-stack | train |
61df679e62fc3386e1bdae59 | train | function | @pytest.mark.parametrize('tf_v_ae_mnist', tests, indirect=True)
def test_ae_vae(tf_v_ae_mnist):
pass
| @pytest.mark.parametrize('tf_v_ae_mnist', tests, indirect=True)
def test_ae_vae(tf_v_ae_mnist):
| pass
| .weights[1].numpy()).any()
assert np.sum((X - X_recon_untrained)**2) > np.sum((X - X_recon)**2)
@pytest.mark.parametrize('tf_v_ae_mnist', tests, indirect=True)
def test_ae_vae(tf_v_ae_mnist):
| 64 | 64 | 32 | 29 | 35 | Clusks/alibi-detect | alibi_detect/models/tests/test_autoencoder.py | Python | test_ae_vae | test_ae_vae | 52 | 54 | 52 | 53 | f7b09224c5b88341ab21827da077dd6f53031e48 | bigcode/the-stack | train |
3b0988eb8ad4b5685ae42251 | train | function | @pytest.fixture
def tf_v_aegmm_mnist(request):
# load and preprocess MNIST data
(X_train, _), (X_test, _) = tf.keras.datasets.mnist.load_data()
X = X_train.reshape(60000, input_dim)[:1000] # only train on 1000 instances
X = X.astype(np.float32)
X /= 255
# init model, predict with untrained mod... | @pytest.fixture
def tf_v_aegmm_mnist(request):
# load and preprocess MNIST data
| (X_train, _), (X_test, _) = tf.keras.datasets.mnist.load_data()
X = X_train.reshape(60000, input_dim)[:1000] # only train on 1000 instances
X = X.astype(np.float32)
X /= 255
# init model, predict with untrained model, train and predict with trained model
model, loss_fn = tests[request.param]
... | , gmm_density_net, n_gmm, latent_dim)
tests = [(aegmm, loss_aegmm), (vaegmm, loss_vaegmm)]
n_tests = len(tests)
@pytest.fixture
def tf_v_aegmm_mnist(request):
# load and preprocess MNIST data
| 64 | 64 | 216 | 22 | 42 | Clusks/alibi-detect | alibi_detect/models/tests/test_autoencoder.py | Python | tf_v_aegmm_mnist | tf_v_aegmm_mnist | 72 | 88 | 72 | 74 | b8944baeb8cba279a144c3c021551a52d508707f | bigcode/the-stack | train |
ed3b7289665da710506f075b | train | function | @pytest.mark.parametrize('tf_v_aegmm_mnist', list(range(n_tests)), indirect=True)
def test_aegmm_vaegmm(tf_v_aegmm_mnist):
pass
| @pytest.mark.parametrize('tf_v_aegmm_mnist', list(range(n_tests)), indirect=True)
def test_aegmm_vaegmm(tf_v_aegmm_mnist):
| pass
| epochs=5, verbose=False, batch_size=1000)
assert (model_weights != model.weights[1].numpy()).any()
@pytest.mark.parametrize('tf_v_aegmm_mnist', list(range(n_tests)), indirect=True)
def test_aegmm_vaegmm(tf_v_aegmm_mnist):
| 64 | 64 | 39 | 36 | 28 | Clusks/alibi-detect | alibi_detect/models/tests/test_autoencoder.py | Python | test_aegmm_vaegmm | test_aegmm_vaegmm | 91 | 93 | 91 | 92 | 81461758df5f3a9ef892bc3247595eba345ad83c | bigcode/the-stack | train |
9e321ed5048bf1afbe866913 | train | function | @pytest.fixture
def tf_seq2seq_sine(request):
# create artificial sine time series
X = np.sin(np.linspace(-50, 50, 10000)).astype(np.float32)
# init model
decoder_net_, n_features = tests_seq2seq[request.param]
encoder_net = EncoderLSTM(latent_dim)
threshold_net = tf.keras.Sequential(
[... | @pytest.fixture
def tf_seq2seq_sine(request):
# create artificial sine time series
| X = np.sin(np.linspace(-50, 50, 10000)).astype(np.float32)
# init model
decoder_net_, n_features = tests_seq2seq[request.param]
encoder_net = EncoderLSTM(latent_dim)
threshold_net = tf.keras.Sequential(
[
InputLayer(input_shape=(seq_len, latent_dim)),
Dense(10, activ... | egmm_vaegmm(tf_v_aegmm_mnist):
pass
seq_len = 10
tests_seq2seq = [(DecoderLSTM(latent_dim, 1, None), 1),
(DecoderLSTM(latent_dim, 2, None), 2)]
n_tests = len(tests_seq2seq)
@pytest.fixture
def tf_seq2seq_sine(request):
# create artificial sine time series
| 90 | 90 | 300 | 20 | 70 | Clusks/alibi-detect | alibi_detect/models/tests/test_autoencoder.py | Python | tf_seq2seq_sine | tf_seq2seq_sine | 102 | 130 | 102 | 104 | df99d754a7baebdaaf2e6ec65ffb34aa4680695a | bigcode/the-stack | train |
8b66ee82d4f5e0fb735607f4 | train | function | @pytest.mark.parametrize('tf_seq2seq_sine', list(range(n_tests)), indirect=True)
def test_seq2seq(tf_seq2seq_sine):
pass
| @pytest.mark.parametrize('tf_seq2seq_sine', list(range(n_tests)), indirect=True)
def test_seq2seq(tf_seq2seq_sine):
| pass
| 1].numpy()).any()
assert np.sum((X - X_recon_untrained)**2) > np.sum((X - X_recon)**2)
@pytest.mark.parametrize('tf_seq2seq_sine', list(range(n_tests)), indirect=True)
def test_seq2seq(tf_seq2seq_sine):
| 64 | 64 | 34 | 31 | 33 | Clusks/alibi-detect | alibi_detect/models/tests/test_autoencoder.py | Python | test_seq2seq | test_seq2seq | 133 | 135 | 133 | 134 | 0536d0b7459651a68ab46e4749c760f6936f20a8 | bigcode/the-stack | train |
40617d3973e4be264ef02da6 | train | function | def plot_confusion_matrix(X, Y, figsize=(10, 6), cmap=plt.cm.Greens):
Y_pred = model.predict(X)
Y_pred = np.argmax(Y_pred, axis=1)
Y_true = np.argmax(Y, axis=1)
cm = confusion_matrix(Y_true, Y_pred)
plt.figure(figsize=figsize)
ax = sns.heatmap(cm, cmap=cmap, annot=True, square=True)
ax.set_... | def plot_confusion_matrix(X, Y, figsize=(10, 6), cmap=plt.cm.Greens):
| Y_pred = model.predict(X)
Y_pred = np.argmax(Y_pred, axis=1)
Y_true = np.argmax(Y, axis=1)
cm = confusion_matrix(Y_true, Y_pred)
plt.figure(figsize=figsize)
ax = sns.heatmap(cm, cmap=cmap, annot=True, square=True)
ax.set_ylabel('Actual', fontsize=30)
ax.set_xlabel('Predicted', fontsize=... | sklearn.metrics import confusion_matrix
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
import seaborn as sns
from keras.models import load_model
SEED = 42
def plot_confusion_matrix(X, Y, figsize=(10, 6), cmap=plt.cm.Greens):
| 64 | 64 | 122 | 24 | 39 | AlphaHelix456/Digit-Recognizer | run.py | Python | plot_confusion_matrix | plot_confusion_matrix | 12 | 22 | 12 | 12 | 7a8eeb63d88cc9b74c1bcb625ec3e7eb732a5358 | bigcode/the-stack | train |
3436794a15755d9d96c0683d | train | function | def pytest_configure(config):
config.addinivalue_line("markers", "slow: mark test as slow to run")
config.addinivalue_line("markers", "release: mark test as only relevant for a release")
| def pytest_configure(config):
| config.addinivalue_line("markers", "slow: mark test as slow to run")
config.addinivalue_line("markers", "release: mark test as only relevant for a release")
| def pytest_addoption(parser):
parser.addoption(
"--runslow", action="store_true", default=False, help="run slow tests"
)
parser.addoption(
"--runrelease", action="store_true", default=False, help="run release tests"
)
def pytest_configure(config):
| 64 | 64 | 48 | 6 | 58 | anoburn/mspypeline | test/conftest.py | Python | pytest_configure | pytest_configure | 15 | 17 | 15 | 15 | 5241c277cd7b9776d6220807484ab2779b0d53ca | bigcode/the-stack | train |
84d26303bbc6ef31881f42a9 | train | function | def pytest_addoption(parser):
parser.addoption(
"--runslow", action="store_true", default=False, help="run slow tests"
)
parser.addoption(
"--runrelease", action="store_true", default=False, help="run release tests"
)
| def pytest_addoption(parser):
| parser.addoption(
"--runslow", action="store_true", default=False, help="run slow tests"
)
parser.addoption(
"--runrelease", action="store_true", default=False, help="run release tests"
)
| import pytest
from .mock_data import MockData
def pytest_addoption(parser):
| 17 | 64 | 58 | 6 | 10 | anoburn/mspypeline | test/conftest.py | Python | pytest_addoption | pytest_addoption | 6 | 12 | 6 | 6 | 580e37d1d45e615725923a9d3ebeeadf7e8a7148 | bigcode/the-stack | train |
86019ad347060b7a21e290a1 | train | function | def pytest_collection_modifyitems(config, items):
# if config.getoption("--runslow"):
# # --runslow given in cli: do not skip slow tests
# return
skip_slow = pytest.mark.skip(reason="need --runslow option to run")
for item in items:
if "slow" in item.keywords and not config.getoption... | def pytest_collection_modifyitems(config, items):
# if config.getoption("--runslow"):
# # --runslow given in cli: do not skip slow tests
# return
| skip_slow = pytest.mark.skip(reason="need --runslow option to run")
for item in items:
if "slow" in item.keywords and not config.getoption("--runslow"):
item.add_marker(skip_slow)
skip_release = pytest.mark.skip(reason="need --release option to run")
for item in items:
if "r... | ")
config.addinivalue_line("markers", "release: mark test as only relevant for a release")
def pytest_collection_modifyitems(config, items):
# if config.getoption("--runslow"):
# # --runslow given in cli: do not skip slow tests
# return
| 64 | 64 | 138 | 41 | 23 | anoburn/mspypeline | test/conftest.py | Python | pytest_collection_modifyitems | pytest_collection_modifyitems | 20 | 32 | 20 | 23 | 62fb2403cbc7c0ea095039154c0f0a8d66b81535 | bigcode/the-stack | train |
ae05d620bd651faace703f64 | train | class | class ImageAttribute:
def __init__(self, parent=None):
self.name = None
self.kernel = None
self.ramdisk = None
self.attrs = {}
def startElement(self, name, attrs, connection):
if name == 'blockDeviceMapping':
self.attrs['block_device_mapping'] = BlockDeviceM... | class ImageAttribute:
| def __init__(self, parent=None):
self.name = None
self.kernel = None
self.ramdisk = None
self.attrs = {}
def startElement(self, name, attrs, connection):
if name == 'blockDeviceMapping':
self.attrs['block_device_mapping'] = BlockDeviceMapping()
re... | group_names)
def reset_launch_attributes(self):
return self.connection.reset_image_attribute(self.id,
'launchPermission')
def get_kernel(self):
img_attrs =self.connection.get_image_attrib... | 88 | 88 | 294 | 4 | 83 | bopopescu/drawquest-web | common/boto/ec2/image.py | Python | ImageAttribute | ImageAttribute | 284 | 324 | 284 | 285 | bbbc27218800a2084f0a9a3a6bac78218271098d | bigcode/the-stack | train |
d7ed9f35d3fc55dbd7faf92f | train | class | class ProductCodes(list):
def startElement(self, name, attrs, connection):
pass
def endElement(self, name, value, connection):
if name == 'productCode':
self.append(value)
| class ProductCodes(list):
| def startElement(self, name, attrs, connection):
pass
def endElement(self, name, value, connection):
if name == 'productCode':
self.append(value)
| , TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
# IN THE SOFTWARE.
from boto.ec2.ec2object import EC2Object, TaggedEC2Object
from boto.ec2.blockdevicemapping import BlockDeviceMapping
class ProductCodes(list):
| 64 | 64 | 45 | 5 | 58 | bopopescu/drawquest-web | common/boto/ec2/image.py | Python | ProductCodes | ProductCodes | 26 | 33 | 26 | 27 | 2e3fcc086a3a33a8f66735766aae09eea0d46c9e | bigcode/the-stack | train |
86c0f9a64ccdeac81c7cd273 | train | class | class Image(TaggedEC2Object):
"""
Represents an EC2 Image
"""
def __init__(self, connection=None):
TaggedEC2Object.__init__(self, connection)
self.id = None
self.location = None
self.state = None
self.ownerId = None # for backwards compatibility
self... | class Image(TaggedEC2Object):
| """
Represents an EC2 Image
"""
def __init__(self, connection=None):
TaggedEC2Object.__init__(self, connection)
self.id = None
self.location = None
self.state = None
self.ownerId = None # for backwards compatibility
self.owner_id = None
self.... | merge, publish, dis-
# tribute, sublicense, and/or sell copies of the Software, and to permit
# persons to whom the Software is furnished to do so, subject to the fol-
# lowing conditions:
#
# The above copyright notice and this permission notice shall be included
# in all copies or substantial portions of the Softwar... | 255 | 256 | 1,860 | 8 | 247 | bopopescu/drawquest-web | common/boto/ec2/image.py | Python | Image | Image | 35 | 282 | 35 | 35 | 7439907e4595e4d948bdfbd1a735952afea1656b | bigcode/the-stack | train |
3f406993108f0d8a8a8d5647 | train | function | def get_mean_and_std(dataset):
'''Compute the mean and std value of dataset.'''
dataloader = trainloader = torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=True, num_workers=2)
mean = torch.zeros(3)
std = torch.zeros(3)
print('==> Computing mean and std..')
for inputs, targets in data... | def get_mean_and_std(dataset):
| '''Compute the mean and std value of dataset.'''
dataloader = trainloader = torch.utils.data.DataLoader(dataset, batch_size=1, shuffle=True, num_workers=2)
mean = torch.zeros(3)
std = torch.zeros(3)
print('==> Computing mean and std..')
for inputs, targets in dataloader:
for i in range(... | import errno
import math
import os
import sys
import time
import torch
import torch.nn as nn
import torch.nn.init as init
__all__ = ['get_mean_and_std', 'init_params', 'mkdir_p', 'AverageMeter']
def get_mean_and_std(dataset):
| 60 | 64 | 136 | 7 | 53 | TanayNarshana/rethinking-network-pruning | cifar/weight-level/utils/misc.py | Python | get_mean_and_std | get_mean_and_std | 14 | 27 | 14 | 14 | efead26f510dfdde238ee6b8363e7ea588c9d1fd | bigcode/the-stack | train |
4ebc7f108a0a3c9ed495047a | train | function | def get_conv_zero_param(model):
total = 0
for m in model.modules():
if isinstance(m, nn.Conv2d):
total += torch.sum(m.weight.data.eq(0))
return total
| def get_conv_zero_param(model):
| total = 0
for m in model.modules():
if isinstance(m, nn.Conv2d):
total += torch.sum(m.weight.data.eq(0))
return total
| in dataloader:
for i in range(3):
mean[i] += inputs[:,i,:,:].mean()
std[i] += inputs[:,i,:,:].std()
mean.div_(len(dataset))
std.div_(len(dataset))
return mean, std
def get_conv_zero_param(model):
| 64 | 64 | 46 | 7 | 56 | TanayNarshana/rethinking-network-pruning | cifar/weight-level/utils/misc.py | Python | get_conv_zero_param | get_conv_zero_param | 29 | 34 | 29 | 29 | 9b871b91711ec26928bc7b4529818d29b7e5d87c | bigcode/the-stack | train |
a4932036c8d4b2efca9c44da | train | function | def mkdir_p(path):
'''make dir if not exist'''
try:
os.makedirs(path)
except OSError as exc: # Python >2.5
if exc.errno == errno.EEXIST and os.path.isdir(path):
pass
else:
raise
| def mkdir_p(path):
| '''make dir if not exist'''
try:
os.makedirs(path)
except OSError as exc: # Python >2.5
if exc.errno == errno.EEXIST and os.path.isdir(path):
pass
else:
raise
| nn.BatchNorm2d):
init.constant(m.weight, 1)
init.constant(m.bias, 0)
elif isinstance(m, nn.Linear):
init.normal(m.weight, std=1e-3)
if m.bias:
init.constant(m.bias, 0)
def mkdir_p(path):
| 64 | 64 | 61 | 5 | 59 | TanayNarshana/rethinking-network-pruning | cifar/weight-level/utils/misc.py | Python | mkdir_p | mkdir_p | 51 | 59 | 51 | 51 | 6f4425b7b1627d355fb0eb09249fbe6d33ec3937 | bigcode/the-stack | train |
1912b8403e13420d3673821e | train | function | def init_params(net):
'''Init layer parameters.'''
for m in net.modules():
if isinstance(m, nn.Conv2d):
init.kaiming_normal(m.weight, mode='fan_out')
if m.bias:
init.constant(m.bias, 0)
elif isinstance(m, nn.BatchNorm2d):
init.constant(m.weight... | def init_params(net):
| '''Init layer parameters.'''
for m in net.modules():
if isinstance(m, nn.Conv2d):
init.kaiming_normal(m.weight, mode='fan_out')
if m.bias:
init.constant(m.bias, 0)
elif isinstance(m, nn.BatchNorm2d):
init.constant(m.weight, 1)
init.... | std.div_(len(dataset))
return mean, std
def get_conv_zero_param(model):
total = 0
for m in model.modules():
if isinstance(m, nn.Conv2d):
total += torch.sum(m.weight.data.eq(0))
return total
def init_params(net):
| 64 | 64 | 121 | 5 | 58 | TanayNarshana/rethinking-network-pruning | cifar/weight-level/utils/misc.py | Python | init_params | init_params | 36 | 49 | 36 | 36 | 491478a4c24fe5001c8e3424a4cc36043f8ab8b7 | bigcode/the-stack | train |
b4e2cfe886ceb9a6c03c5de3 | train | class | class AverageMeter(object):
"""Computes and stores the average and current value
Imported from https://github.com/pytorch/examples/blob/master/imagenet/main.py#L247-L262
"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
... | class AverageMeter(object):
| """Computes and stores the average and current value
Imported from https://github.com/pytorch/examples/blob/master/imagenet/main.py#L247-L262
"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
d... | _p(path):
'''make dir if not exist'''
try:
os.makedirs(path)
except OSError as exc: # Python >2.5
if exc.errno == errno.EEXIST and os.path.isdir(path):
pass
else:
raise
class AverageMeter(object):
| 64 | 64 | 126 | 5 | 58 | TanayNarshana/rethinking-network-pruning | cifar/weight-level/utils/misc.py | Python | AverageMeter | AverageMeter | 61 | 78 | 61 | 61 | b09043b96d0d5b9ad491d96ee123de9c2f531368 | bigcode/the-stack | train |
2071e5073d71520fdbfd92b6 | train | class | class EzFlask:
def __init__(self):
self.app = flask.Flask('')
@self.app.route('/')
def _index():
return _get_html('index.html')
@self.app.route('/<path>')
def _get(path):
return _get_html(escape(path))
def run(self):
... | class EzFlask:
| def __init__(self):
self.app = flask.Flask('')
@self.app.route('/')
def _index():
return _get_html('index.html')
@self.app.route('/<path>')
def _get(path):
return _get_html(escape(path))
def run(self):
self.app.run(ho... | '\
'If you entered the URL manually please check your spelling and try again.</p> '
def _get_html(path):
try:
with open(path, 'r') as file:
return file.read()
except FileNotFoundError:
return PNF
class EzFlask:
| 64 | 64 | 92 | 5 | 58 | SmartMozart/ezflask | ezflask.py | Python | EzFlask | EzFlask | 16 | 29 | 16 | 16 | e5965f5be8e402252894eb42a670be8b005c83dc | bigcode/the-stack | train |
1bd3d205918f65a7aa735aaf | train | function | def _get_html(path):
try:
with open(path, 'r') as file:
return file.read()
except FileNotFoundError:
return PNF
| def _get_html(path):
| try:
with open(path, 'r') as file:
return file.read()
except FileNotFoundError:
return PNF
| PNF = '<!DOCTYPE html><title>404 Not Found</title><h1>Not Found</h1><p>The requested URL was not found on the server. '\
'If you entered the URL manually please check your spelling and try again.</p> '
def _get_html(path):
| 63 | 64 | 37 | 6 | 57 | SmartMozart/ezflask | ezflask.py | Python | _get_html | _get_html | 8 | 13 | 8 | 8 | 3992222bfc65ca22d2dab6fedb90639c0bd7c53d | bigcode/the-stack | train |
5ecf37a95a1404bfd018064a | train | class | class IsUserlandTest(fixtures.MappedTest):
@classmethod
def define_tables(cls, metadata):
Table(
"foo",
metadata,
Column("id", Integer, primary_key=True),
Column("someprop", Integer),
)
def _test(self, value, instancelevel=None):
class... | class IsUserlandTest(fixtures.MappedTest):
@classmethod
| def define_tables(cls, metadata):
Table(
"foo",
metadata,
Column("id", Integer, primary_key=True),
Column("someprop", Integer),
)
def _test(self, value, instancelevel=None):
class Foo:
someprop = value
m = self.mapper(... | ):
self.value = "foobar"
return self.value
self.mapper(H1, ht1)
self.mapper(H2, ht1)
h1 = H1()
h1.value = "Asdf"
h1.value = "asdf asdf" # ding
h2 = H2()
h2.value = "Asdf"
h2.value = "asdf asdf" # ding
class IsUserlandTe... | 106 | 106 | 354 | 15 | 90 | brussee/sqlalchemy | test/orm/test_mapper.py | Python | IsUserlandTest | IsUserlandTest | 2,519 | 2,575 | 2,519 | 2,520 | d856623fd9bde48c05774e0a1c0f6595b9e7be9e | bigcode/the-stack | train |
2fd69242d62508d4d4ad5d15 | train | class | class ORMLoggingTest(_fixtures.FixtureTest):
def setup_test(self):
self.buf = logging.handlers.BufferingHandler(100)
for log in [logging.getLogger("sqlalchemy.orm")]:
log.addHandler(self.buf)
self.mapper = registry().map_imperatively
def teardown_test(self):
for log... | class ORMLoggingTest(_fixtures.FixtureTest):
| def setup_test(self):
self.buf = logging.handlers.BufferingHandler(100)
for log in [logging.getLogger("sqlalchemy.orm")]:
log.addHandler(self.buf)
self.mapper = registry().map_imperatively
def teardown_test(self):
for log in [logging.getLogger("sqlalchemy.orm")]:
... | eq_(Foo.bars.__doc__, "bar relationship")
eq_(Foo.hoho.__doc__, "syn of col4")
eq_(Bar.col1.__doc__, "primary key column")
eq_(Bar.foo.__doc__, "foo relationship")
class ORMLoggingTest(_fixtures.FixtureTest):
| 64 | 64 | 191 | 10 | 54 | brussee/sqlalchemy | test/orm/test_mapper.py | Python | ORMLoggingTest | ORMLoggingTest | 2,771 | 2,795 | 2,771 | 2,771 | de92d69c49768de70bd6a145e38d2f7fb41e9260 | bigcode/the-stack | train |
34b1ad17e8ab9e28d47f4718 | train | class | class MagicNamesTest(fixtures.MappedTest):
@classmethod
def define_tables(cls, metadata):
Table(
"cartographers",
metadata,
Column(
"id", Integer, primary_key=True, test_needs_autoincrement=True
),
Column("name", String(50)),
... | class MagicNamesTest(fixtures.MappedTest):
@classmethod
| def define_tables(cls, metadata):
Table(
"cartographers",
metadata,
Column(
"id", Integer, primary_key=True, test_needs_autoincrement=True
),
Column("name", String(50)),
Column("alias", String(50)),
Column("q... | class Foo:
someprop = value
m = self.mapper(Foo, self.tables.foo)
is_(Foo.someprop.property.columns[0], self.tables.foo.c.someprop)
assert self.tables.foo.c.someprop in m._columntoproperty
def test_string(self):
self._test("someprop")
def test_unicode(self):
... | 205 | 205 | 685 | 14 | 191 | brussee/sqlalchemy | test/orm/test_mapper.py | Python | MagicNamesTest | MagicNamesTest | 2,578 | 2,704 | 2,578 | 2,579 | c34721052ff748cab7706e6578bc233ea1b8e6c3 | bigcode/the-stack | train |
e0c76354f9e6462d8f7f9aec | train | class | class RequirementsTest(fixtures.MappedTest):
"""Tests the contract for user classes."""
@classmethod
def define_tables(cls, metadata):
Table(
"ht1",
metadata,
Column(
"id", Integer, primary_key=True, test_needs_autoincrement=True
),
... | class RequirementsTest(fixtures.MappedTest):
| """Tests the contract for user classes."""
@classmethod
def define_tables(cls, metadata):
Table(
"ht1",
metadata,
Column(
"id", Integer, primary_key=True, test_needs_autoincrement=True
),
Column("value", String(10)),
... | name"), (["foo"], (), ()))
# using it with an ORM operation, raises
assert_raises(
sa.orm.exc.UnmappedClassError, fixture_session().add, Sub()
)
def test_unmapped_subclass_error_premap(self):
users = self.tables.users
class Base:
pass
self.... | 256 | 256 | 1,820 | 9 | 247 | brussee/sqlalchemy | test/orm/test_mapper.py | Python | RequirementsTest | RequirementsTest | 2,262 | 2,516 | 2,262 | 2,263 | 582865c1ab18cf1c29cfafd61d78dd63643c12fb | bigcode/the-stack | train |
6a8687473742ef7142f72fdb | train | class | class DocumentTest(fixtures.TestBase):
def setup_test(self):
self.mapper = registry().map_imperatively
def test_doc_propagate(self):
metadata = MetaData()
t1 = Table(
"t1",
metadata,
Column(
"col1", Integer, primary_key=True, doc="pri... | class DocumentTest(fixtures.TestBase):
| def setup_test(self):
self.mapper = registry().map_imperatively
def test_doc_propagate(self):
metadata = MetaData()
t1 = Table(
"t1",
metadata,
Column(
"col1", Integer, primary_key=True, doc="primary key column"
),
... | t,
)
def test_indirect_stateish(self):
maps = self.tables.maps
for reserved in (
sa.orm.instrumentation.ClassManager.STATE_ATTR,
sa.orm.instrumentation.ClassManager.MANAGER_ATTR,
):
class M:
pass
... | 129 | 129 | 433 | 8 | 121 | brussee/sqlalchemy | test/orm/test_mapper.py | Python | DocumentTest | DocumentTest | 2,707 | 2,768 | 2,707 | 2,707 | 2da2d0973c2700f033dcde772a99312d3c54e20a | bigcode/the-stack | train |
da2623fd8da2c0d532be94fd | train | class | class MapperTest(_fixtures.FixtureTest, AssertsCompiledSQL):
__dialect__ = "default"
def test_decl_attributes(self):
"""declarative mapper() now sets up some of the convenience
attributes"""
Address, addresses, users, User = (
self.classes.Address,
self.tables.a... | class MapperTest(_fixtures.FixtureTest, AssertsCompiledSQL):
| __dialect__ = "default"
def test_decl_attributes(self):
"""declarative mapper() now sets up some of the convenience
attributes"""
Address, addresses, users, User = (
self.classes.Address,
self.tables.addresses,
self.tables.users,
self.cla... | sqlalchemy.orm import aliased
from sqlalchemy.orm import attributes
from sqlalchemy.orm import backref
from sqlalchemy.orm import class_mapper
from sqlalchemy.orm import clear_mappers
from sqlalchemy.orm import column_property
from sqlalchemy.orm import composite
from sqlalchemy.orm import configure_mappers
from sqlal... | 256 | 256 | 13,363 | 14 | 241 | brussee/sqlalchemy | test/orm/test_mapper.py | Python | MapperTest | MapperTest | 50 | 2,259 | 50 | 50 | 4eed6f8aa66034bff4aa0f49666e38fdf5a076ef | bigcode/the-stack | train |
51e5c724dfdfd1e7cbd4e90c | train | class | class RegistryConfigDisposeTest(fixtures.TestBase):
"""test the cascading behavior of registry configure / dispose."""
@testing.fixture
def threeway_fixture(self):
reg1 = registry()
reg2 = registry()
reg3 = registry()
ab = bc = True
@reg1.mapped
class A:
... | class RegistryConfigDisposeTest(fixtures.TestBase):
| """test the cascading behavior of registry configure / dispose."""
@testing.fixture
def threeway_fixture(self):
reg1 = registry()
reg2 = registry()
reg3 = registry()
ab = bc = True
@reg1.mapped
class A:
__tablename__ = "a"
id = Colum... | self.mapper(User, users)
self.mapper(
Address,
addresses,
properties={
"user": relationship(
User,
comparator_factory=MyFactory,
backref=backref(
"addresses", comparato... | 256 | 256 | 1,106 | 10 | 246 | brussee/sqlalchemy | test/orm/test_mapper.py | Python | RegistryConfigDisposeTest | RegistryConfigDisposeTest | 2,960 | 3,112 | 2,960 | 2,960 | 49e2fd09bc8fda855f09c06ebae6902fc565824b | bigcode/the-stack | train |
3f2828e3d6179087bc8766c9 | train | class | class ConfigureOrNotConfigureTest(_fixtures.FixtureTest, AssertsCompiledSQL):
__dialect__ = "default"
@testing.combinations((True,), (False,))
def test_no_mapper_configure_w_selects_etc(self, use_legacy_query):
Address, addresses, users, User = (
self.classes.Address,
self.t... | class ConfigureOrNotConfigureTest(_fixtures.FixtureTest, AssertsCompiledSQL):
| __dialect__ = "default"
@testing.combinations((True,), (False,))
def test_no_mapper_configure_w_selects_etc(self, use_legacy_query):
Address, addresses, users, User = (
self.classes.Address,
self.tables.addresses,
self.tables.users,
self.classes.User,... | ._dispose_called)
is_true(am._dispose_called)
@testing.combinations((True,), (False,), argnames="cascade")
def test_clear_cascade_not_on_dependents(
self, threeway_configured_fixture, cascade
):
reg1, reg2, reg3 = threeway_configured_fixture
A, B, C = (
reg1._cla... | 256 | 256 | 875 | 17 | 239 | brussee/sqlalchemy | test/orm/test_mapper.py | Python | ConfigureOrNotConfigureTest | ConfigureOrNotConfigureTest | 3,115 | 3,247 | 3,115 | 3,115 | 9588fedcdbfbdb35cd470471e0864ef4228c28ae | bigcode/the-stack | train |
8b316711f8249e617aecd127 | train | class | class ComparatorFactoryTest(_fixtures.FixtureTest, AssertsCompiledSQL):
def test_kwarg_accepted(self):
users, Address = self.tables.users, self.classes.Address
class DummyComposite:
def __init__(self, x, y):
pass
from sqlalchemy.orm.interfaces import PropCompara... | class ComparatorFactoryTest(_fixtures.FixtureTest, AssertsCompiledSQL):
| def test_kwarg_accepted(self):
users, Address = self.tables.users, self.classes.Address
class DummyComposite:
def __init__(self, x, y):
pass
from sqlalchemy.orm.interfaces import PropComparator
class MyFactory(PropComparator):
pass
... | ars.__doc__, "bar relationship")
eq_(Foo.hoho.__doc__, "syn of col4")
eq_(Bar.col1.__doc__, "primary key column")
eq_(Bar.foo.__doc__, "foo relationship")
class ORMLoggingTest(_fixtures.FixtureTest):
def setup_test(self):
self.buf = logging.handlers.BufferingHandler(100)
fo... | 256 | 256 | 986 | 15 | 241 | brussee/sqlalchemy | test/orm/test_mapper.py | Python | ComparatorFactoryTest | ComparatorFactoryTest | 2,798 | 2,957 | 2,798 | 2,798 | 44fab69222bd0f62f3821cc85c741f4051a57dae | bigcode/the-stack | train |
909952b02a83d8759c95d70c | train | class | class CreateDemandRequest(RpcRequest):
def __init__(self):
RpcRequest.__init__(self, 'Ecs', '2014-05-26', 'CreateDemand','ecs')
self.set_method('POST')
if hasattr(self, "endpoint_map"):
setattr(self, "endpoint_map", endpoint_data.getEndpointMap())
if hasattr(self, "endpoint_regional"):
setattr(self, ... | class CreateDemandRequest(RpcRequest):
| def __init__(self):
RpcRequest.__init__(self, 'Ecs', '2014-05-26', 'CreateDemand','ecs')
self.set_method('POST')
if hasattr(self, "endpoint_map"):
setattr(self, "endpoint_map", endpoint_data.getEndpointMap())
if hasattr(self, "endpoint_regional"):
setattr(self, "endpoint_regional", endpoint_data.getEn... | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 204 | 244 | 816 | 8 | 195 | yndu13/aliyun-openapi-python-sdk | aliyun-python-sdk-ecs/aliyunsdkecs/request/v20140526/CreateDemandRequest.py | Python | CreateDemandRequest | CreateDemandRequest | 23 | 108 | 23 | 24 | 9cf1bc1c53751187fc12504302471d82cde74bb9 | bigcode/the-stack | train |
f0593825b55b03aafc8a6d46 | train | class | class Proj2012DownloaderMiddleware:
# Not all methods need to be defined. If a method is not defined,
# scrapy acts as if the downloader middleware does not modify the
# passed objects.
@classmethod
def from_crawler(cls, crawler):
# This method is used by Scrapy to create your spiders.
... | class Proj2012DownloaderMiddleware:
# Not all methods need to be defined. If a method is not defined,
# scrapy acts as if the downloader middleware does not modify the
# passed objects.
@classmethod
| def from_crawler(cls, crawler):
# This method is used by Scrapy to create your spiders.
s = cls()
crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
return s
def process_request(self, request, spider):
# Called for each request that goes through the d... |
# that it doesn’t have a response associated.
# Must return only requests (not items).
for r in start_requests:
yield r
def spider_opened(self, spider):
spider.logger.info('Spider opened: %s' % spider.name)
class Proj2012DownloaderMiddleware:
# Not all methods need... | 105 | 105 | 350 | 48 | 57 | miccaldas/new_rss | support_files/scraping/entries/proj_2012/proj_2012/middlewares.py | Python | Proj2012DownloaderMiddleware | Proj2012DownloaderMiddleware | 59 | 103 | 59 | 64 | 0eeb0866be1cdaf3057d3b72116eab6b5c813490 | bigcode/the-stack | train |
85cf3c073c965de1d74ce997 | train | class | class Proj2012SpiderMiddleware:
# Not all methods need to be defined. If a method is not defined,
# scrapy acts as if the spider middleware does not modify the
# passed objects.
@classmethod
def from_crawler(cls, crawler):
# This method is used by Scrapy to create your spiders.
s = ... | class Proj2012SpiderMiddleware:
# Not all methods need to be defined. If a method is not defined,
# scrapy acts as if the spider middleware does not modify the
# passed objects.
@classmethod
| def from_crawler(cls, crawler):
# This method is used by Scrapy to create your spiders.
s = cls()
crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
return s
def process_spider_input(self, response, spider):
# Called for each response that goes throug... | # Define here the models for your spider middleware
#
# See documentation in:
# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
from scrapy import signals
# useful for handling different item types with a single interface
from itemadapter import is_item, ItemAdapter
class Proj2012SpiderMiddleware:
... | 107 | 107 | 357 | 48 | 58 | miccaldas/new_rss | support_files/scraping/entries/proj_2012/proj_2012/middlewares.py | Python | Proj2012SpiderMiddleware | Proj2012SpiderMiddleware | 12 | 56 | 12 | 17 | f08e46fe7f42cbc86b639dd3a435b67af3a49bc7 | bigcode/the-stack | train |
943dd1bfa0eff9576373e3a7 | train | class | class EditModelTemplateTagTest(ToolbarTestBase):
urls = 'cms.test_utils.project.placeholderapp_urls'
edit_fields_rx = "(\?|&)edit_fields=%s"
def tearDown(self):
Example1.objects.all().delete()
MultilingualExample1.objects.all().delete()
super(EditModelTemplateTagTest, self).tear... | class EditModelTemplateTagTest(ToolbarTestBase):
| urls = 'cms.test_utils.project.placeholderapp_urls'
edit_fields_rx = "(\?|&)edit_fields=%s"
def tearDown(self):
Example1.objects.all().delete()
MultilingualExample1.objects.all().delete()
super(EditModelTemplateTagTest, self).tearDown()
def test_anon(self):
user = s... | %s' % get_cms_setting('CMS_TOOLBAR_URL__EDIT_ON'))
toolbar = response.context['request'].toolbar
admin_menu = toolbar.get_or_create_menu(ADMIN_MENU_IDENTIFIER)
self.assertEquals(admin_menu.find_first(AjaxItem, name=menu_name).item.on_success, '/')
# Published page with ... | 255 | 256 | 8,518 | 12 | 242 | donce/django-cms | cms/tests/toolbar.py | Python | EditModelTemplateTagTest | EditModelTemplateTagTest | 479 | 1,270 | 479 | 479 | cd009274987ffda2011f80126557def076d0de3f | bigcode/the-stack | train |
5a96341551143ced05ce390a | train | class | class CharPkFrontendPlaceholderAdminTest(ToolbarTestBase):
def get_admin(self):
admin.autodiscover()
return admin.site._registry[CharPksExample]
def test_url_char_pk(self):
"""
Tests whether the frontend admin matches the edit_fields url with alphanumeric pks
"""
... | class CharPkFrontendPlaceholderAdminTest(ToolbarTestBase):
| def get_admin(self):
admin.autodiscover()
return admin.site._registry[CharPksExample]
def test_url_char_pk(self):
"""
Tests whether the frontend admin matches the edit_fields url with alphanumeric pks
"""
ex = CharPksExample(
char_1='one',
... | response,
'<div class="cms_plugin cms_plugin-cms-page-get_page_title-%s cms_render_model">%s</div>' % (
page.pk, page.get_page_title(language)))
self.assertContains(
response,
'<div class="cms_plugin cms_plugin-cms-page-get_menu_title-%s cms_render_model">%s<... | 187 | 187 | 624 | 13 | 174 | donce/django-cms | cms/tests/toolbar.py | Python | CharPkFrontendPlaceholderAdminTest | CharPkFrontendPlaceholderAdminTest | 1,273 | 1,347 | 1,273 | 1,274 | 0da08f0796f9531bed3f576530892a57fc9d3da0 | bigcode/the-stack | train |
8fd52715ce584ee6b11df8b9 | train | class | class ToolbarTestBase(CMSTestCase):
def get_page_request(self, page, user, path=None, edit=False, lang_code='en'):
path = path or page and page.get_absolute_url()
if edit:
path += '?%s' % get_cms_setting('CMS_TOOLBAR_URL__EDIT_ON')
request = RequestFactory().get(path)
req... | class ToolbarTestBase(CMSTestCase):
| def get_page_request(self, page, user, path=None, edit=False, lang_code='en'):
path = path or page and page.get_absolute_url()
if edit:
path += '?%s' % get_cms_setting('CMS_TOOLBAR_URL__EDIT_ON')
request = RequestFactory().get(path)
request.session = {}
request.us... | detail_view_multi_unfiltered)
from cms.test_utils.testcases import (CMSTestCase,
URL_CMS_PAGE_ADD, URL_CMS_PAGE_CHANGE)
from cms.test_utils.util.context_managers import UserLoginContext
from cms.utils.conf import get_cms_sett... | 81 | 81 | 273 | 10 | 70 | donce/django-cms | cms/tests/toolbar.py | Python | ToolbarTestBase | ToolbarTestBase | 36 | 70 | 36 | 36 | dc879eda92d1ff00f1fd0a22be157ad9e065c6cd | bigcode/the-stack | train |
a60744896a2817612435e2d2 | train | class | @override_settings(CMS_PERMISSION=False)
class ToolbarTests(ToolbarTestBase):
def test_no_page_anon(self):
request = self.get_page_request(None, self.get_anon(), '/')
toolbar = CMSToolbar(request)
toolbar.populate()
toolbar.post_template_populate()
items = toolbar.get_left_i... | @override_settings(CMS_PERMISSION=False)
class ToolbarTests(ToolbarTestBase):
| def test_no_page_anon(self):
request = self.get_page_request(None, self.get_anon(), '/')
toolbar = CMSToolbar(request)
toolbar.populate()
toolbar.post_template_populate()
items = toolbar.get_left_items() + toolbar.get_right_items()
self.assertEqual(len(items), 0)
... | = path or page and page.get_absolute_url()
if edit:
path += '?%s' % get_cms_setting('CMS_TOOLBAR_URL__EDIT_ON')
request = RequestFactory().get(path)
request.session = {}
request.user = user
request.LANGUAGE_CODE = lang_code
if edit:
request.GET = ... | 256 | 256 | 4,376 | 17 | 238 | donce/django-cms | cms/tests/toolbar.py | Python | ToolbarTests | ToolbarTests | 73 | 476 | 73 | 75 | 278b68465c045b352704814c0441153b02598c1f | bigcode/the-stack | train |
0728555de3f935e5df506f5e | train | class | class ToolbarAPITests(TestCase):
def test_find_item(self):
api = ToolbarAPIMixin()
first = api.add_link_item('First', 'http://www.example.org')
second = api.add_link_item('Second', 'http://www.example.org')
all_links = api.find_items(LinkItem)
self.assertEqual(len(all_links),... | class ToolbarAPITests(TestCase):
| def test_find_item(self):
api = ToolbarAPIMixin()
first = api.add_link_item('First', 'http://www.example.org')
second = api.add_link_item('Second', 'http://www.example.org')
all_links = api.find_items(LinkItem)
self.assertEqual(len(all_links), 2)
result = api.find_fir... | """
page = create_page('Test', 'col_two.html', 'en', published=True)
ex = Example1(
char_1='one',
char_2='two',
char_3='tree',
char_4='four'
)
ex.save()
superuser = self.get_superuser()
request = self.get_page_reques... | 124 | 124 | 416 | 8 | 116 | donce/django-cms | cms/tests/toolbar.py | Python | ToolbarAPITests | ToolbarAPITests | 1,350 | 1,392 | 1,350 | 1,350 | 05ac2d1a985bf7a52bbf19a8b1df155f2df97b35 | bigcode/the-stack | train |
b6486581ec9093b6f5e21e76 | train | class | class Draco(CMakePackage):
"""Draco is an object-oriented component library geared towards numerically
intensive, radiation (particle) transport applications built for parallel
computing hardware. It consists of semi-independent packages and a robust
build system. """
homepage = "https://github.com... | class Draco(CMakePackage):
| """Draco is an object-oriented component library geared towards numerically
intensive, radiation (particle) transport applications built for parallel
computing hardware. It consists of semi-independent packages and a robust
build system. """
homepage = "https://github.com/lanl/draco"
url = "htt... | # Copyright 2013-2020 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack import *
class Draco(CMakePackage):
| 60 | 256 | 1,224 | 6 | 54 | xiki-tempula/spack | var/spack/repos/builtin/packages/draco/package.py | Python | Draco | Draco | 9 | 75 | 9 | 9 | 48f751f9d59f5da1016fa18e244a2a0d87dfab00 | bigcode/the-stack | train |
142072a4fe9a32ce1b857780 | train | function | def boundary(T):
"""
Returns the boundary edges of the given input topology
Parameters
----------
T : LongTensor
the input topology tensor
Returns
-------
LongTensor
the boundary edge tensor
"""
E = poly2edge(T)[0]
_, j, e = unique(torch.sort(E, 1)[0]... | def boundary(T):
| """
Returns the boundary edges of the given input topology
Parameters
----------
T : LongTensor
the input topology tensor
Returns
-------
LongTensor
the boundary edge tensor
"""
E = poly2edge(T)[0]
_, j, e = unique(torch.sort(E, 1)[0], ByRows=True)
... | import torch
from ..utility.unique import *
from ..utility.accumarray import *
from .poly2edge import *
def boundary(T):
| 30 | 64 | 106 | 4 | 26 | mauriziokovacic/ACME | ACME/topology/boundary.py | Python | boundary | boundary | 7 | 25 | 7 | 7 | a706db3074da46274536ea9b26bdb86cf75da7b9 | bigcode/the-stack | train |
8659669bf9c862659367d3d0 | train | class | class TapeOperationRecorder(QuantumTape):
"""A template and quantum function inspector,
allowing easy introspection of operators that have been
applied without requiring a QNode.
**Example**:
The OperationRecorder is a context manager. Executing templates
or quantum functions stores ap... | class TapeOperationRecorder(QuantumTape):
| """A template and quantum function inspector,
allowing easy introspection of operators that have been
applied without requiring a QNode.
**Example**:
The OperationRecorder is a context manager. Executing templates
or quantum functions stores applied operators in the
recorder, which... | See the License for the specific language governing permissions and
# limitations under the License.
"""
This subpackage contains various quantum tapes, which track, queue,
validate, execute, and differentiate quantum circuits.
"""
import contextlib
import inspect
import functools
from unittest import mock
i... | 173 | 174 | 582 | 8 | 165 | DanielPolatajko/pennylane | pennylane/tape/__init__.py | Python | TapeOperationRecorder | TapeOperationRecorder | 44 | 117 | 44 | 44 | f55bd50798409ad68c9126209f30463e0b5674a2 | bigcode/the-stack | train |
7b7e774f621690d161921a1e | train | function | def TapeTemplateDecorator(func):
"""Register a quantum template with PennyLane.
This decorator wraps the given function and makes it return a list of all queued Operations.
**Example:**
When defining a :doc:`template </introduction/templates>`, simply decorate
the template function with t... | def TapeTemplateDecorator(func):
| """Register a quantum template with PennyLane.
This decorator wraps the given function and makes it return a list of all queued Operations.
**Example:**
When defining a :doc:`template </introduction/templates>`, simply decorate
the template function with this decorator.
.. code-bloc... | \n"
for op in self.ops:
output += repr(op) + "\n"
output += "\n"
output += "Observables\n"
output += "==========\n"
for op in self.obs:
output += repr(op) + "\n"
return output
@property
def queue(self):
return self.... | 85 | 86 | 288 | 6 | 78 | DanielPolatajko/pennylane | pennylane/tape/__init__.py | Python | TapeTemplateDecorator | TapeTemplateDecorator | 120 | 163 | 120 | 120 | ef2e59d2dd0e50ac57aa71c693094df2edb82775 | bigcode/the-stack | train |
9be1f8ee8f12372aeb34a3bc | train | function | def disable_tape():
"""Disable tape mode.
This function may be called at any time after :func:`~.enable_tape` has been executed
in order to disable tape mode.
Tape mode is an experimental new mode of PennyLane. QNodes created in tape mode have support for
in-QNode classical processing, diff... | def disable_tape():
| """Disable tape mode.
This function may be called at any time after :func:`~.enable_tape` has been executed
in order to disable tape mode.
Tape mode is an experimental new mode of PennyLane. QNodes created in tape mode have support for
in-QNode classical processing, differentiable quantum de... | ._queuing.OperationRecorder", TapeOperationRecorder),
mock.patch("pennylane.template", TapeTemplateDecorator),
]
with contextlib.ExitStack() as stack:
for m in mocks:
stack.enter_context(m)
_mock_stack.append(stack.pop_all())
def disable_tape():
| 63 | 64 | 147 | 5 | 58 | DanielPolatajko/pennylane | pennylane/tape/__init__.py | Python | disable_tape | disable_tape | 219 | 234 | 219 | 219 | 5344a852de09f1129f93f77b5afb7631ac5b958c | bigcode/the-stack | train |
e990c2fafe211ed7c8d529d6 | train | function | def enable_tape():
"""Enable tape mode.
Tape mode is an experimental new mode of PennyLane. QNodes created in tape mode have support for
in-QNode classical processing, differentiable quantum decompositions, returning the quantum
state, less restrictive QNode signatures, and various other improveme... | def enable_tape():
| """Enable tape mode.
Tape mode is an experimental new mode of PennyLane. QNodes created in tape mode have support for
in-QNode classical processing, differentiable quantum decompositions, returning the quantum
state, less restrictive QNode signatures, and various other improvements.
For more... | ml.device('default.qubit', wires=2)
@qml.qnode(dev)
def circuit():
qml.inv(bell_state_preparation(wires=[0, 1]))
return qml.expval(qml.PauliZ(0) @ qml.PauliZ(1))
Args:
func (callable): A template function
Returns:
callable: The wrapper functi... | 139 | 139 | 464 | 5 | 133 | DanielPolatajko/pennylane | pennylane/tape/__init__.py | Python | enable_tape | enable_tape | 166 | 216 | 166 | 166 | 30a54b955210fa55a4328cc2a270d9269ea41fb5 | bigcode/the-stack | train |
d3bdb9522d34ac5c843eeaaf | train | function | def tape_mode_active():
"""Returns whether tape mode is enabled."""
return inspect.isclass(qml.QNode) and issubclass(qml.QNode, qml.tape.QNode)
| def tape_mode_active():
| """Returns whether tape mode is enabled."""
return inspect.isclass(qml.QNode) and issubclass(qml.QNode, qml.tape.QNode)
| signatures, and various other improvements.
For more details on tape mode, see :mod:`~.tape`.
"""
if not _mock_stack:
warnings.warn("Tape mode is not currently enabled.", UserWarning)
else:
_mock_stack.pop().close()
def tape_mode_active():
| 64 | 64 | 41 | 5 | 59 | DanielPolatajko/pennylane | pennylane/tape/__init__.py | Python | tape_mode_active | tape_mode_active | 237 | 239 | 237 | 237 | 87cb2a731c5f7f00729e756dba80c01afe1476cf | bigcode/the-stack | train |
bf6dea86225ab8833c798f65 | train | class | class WaveletTest(parameterized.TestCase, tf.test.TestCase):
def setUp(self):
super(WaveletTest, self).setUp()
np.random.seed(0)
def _assert_pyramids_close(self, x0, x1, epsilon):
"""A helper function for assering that two wavelet pyramids are close."""
if isinstance(x0, tuple) or isinstance(x0, l... | class WaveletTest(parameterized.TestCase, tf.test.TestCase):
| def setUp(self):
super(WaveletTest, self).setUp()
np.random.seed(0)
def _assert_pyramids_close(self, x0, x1, epsilon):
"""A helper function for assering that two wavelet pyramids are close."""
if isinstance(x0, tuple) or isinstance(x0, list):
assert isinstance(x1, (list, tuple))
assert ... | # coding=utf-8
# Copyright 2019 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 205 | 256 | 3,996 | 14 | 191 | rmitra/google-research | robust_loss/wavelet_test.py | Python | WaveletTest | WaveletTest | 29 | 367 | 29 | 30 | 1d92c9a42e66f31c1057ff465c217ce09ce7aef1 | bigcode/the-stack | train |
67ea1f5750e6b7b14976210f | train | function | def load_model(model_file):
torch.set_default_tensor_type('torch.cuda.FloatTensor')
set_cfg('yolact_plus_resnet50_config')
net = Yolact()
net.load_weights(model_file)
net.eval()
return net
| def load_model(model_file):
| torch.set_default_tensor_type('torch.cuda.FloatTensor')
set_cfg('yolact_plus_resnet50_config')
net = Yolact()
net.load_weights(model_file)
net.eval()
return net
| import sys
import cv2
import rbcompiler.api_v2 as rb
import pyRbRuntime as rt
import numpy as np
# register pyruntime op
import sg.dcn
import torch
from yolact import Yolact
from data import set_cfg
def load_model(model_file):
| 61 | 64 | 52 | 6 | 54 | aksenventwo/yolact | export_sg.py | Python | load_model | load_model | 14 | 20 | 14 | 14 | 9c6d2bb937f868cfeb78c43db1b83e96257cbb40 | bigcode/the-stack | train |
324de6a19b30b60b23925115 | train | function | def export_sg(net):
# generate sg
sg = rb.gen_sg_from_pytorch(net, input_shape=[1, 3, 550, 550])
rb.save_sg(sg, 'yolact_plus.sg')
| def export_sg(net):
# generate sg
| sg = rb.gen_sg_from_pytorch(net, input_shape=[1, 3, 550, 550])
rb.save_sg(sg, 'yolact_plus.sg')
|
def load_model(model_file):
torch.set_default_tensor_type('torch.cuda.FloatTensor')
set_cfg('yolact_plus_resnet50_config')
net = Yolact()
net.load_weights(model_file)
net.eval()
return net
def export_sg(net):
# generate sg
| 64 | 64 | 52 | 11 | 52 | aksenventwo/yolact | export_sg.py | Python | export_sg | export_sg | 22 | 25 | 22 | 23 | 055f58d77fe595dab7f5e82245438fcfadbf65a7 | bigcode/the-stack | train |
db59dc804438aaae261c8b9a | train | class | class DoorSettings(AutoFormSettings):
spec = OrderedDict([
("direction", {"type": "choice", "choices": ["north", "south", "east", "west"],
"tooltip": "Set the direction to this door from currently"
" selected tile"}),
("prefix", {"type": "str", "tooltip": ... | class DoorSettings(AutoFormSettings):
| spec = OrderedDict([
("direction", {"type": "choice", "choices": ["north", "south", "east", "west"],
"tooltip": "Set the direction to this door from currently"
" selected tile"}),
("prefix", {"type": "str", "tooltip": "Set the word that should precede "
... | ": "Enable/disable wall to the south"}),
("east", {"type": "bool", "tooltip": "Enable/disable wall to the east"}),
("west", {"type": "bool", "tooltip": "Enable/disable wall to the west"})
])
class DoorSettings(AutoFormSettings):
| 64 | 64 | 189 | 8 | 56 | eriknyquist/text_map_builder_gui | text_game_map_maker/forms.py | Python | DoorSettings | DoorSettings | 21 | 33 | 21 | 21 | e4fe38d65ca61762052eb62676ae6064f1c5b995 | bigcode/the-stack | train |
b0c2d7159c718b3d15da5972 | train | class | class AutoFormSettings(object):
def __init__(self):
if not hasattr(self, "spec"):
raise RuntimeError("%s instance has no 'spec' attribute"
% self.__class__.__name__)
for attrname in self.spec.keys():
setattr(self, attrname, None)
| class AutoFormSettings(object):
| def __init__(self):
if not hasattr(self, "spec"):
raise RuntimeError("%s instance has no 'spec' attribute"
% self.__class__.__name__)
for attrname in self.spec.keys():
setattr(self, attrname, None)
| from collections import OrderedDict
class AutoFormSettings(object):
| 12 | 64 | 62 | 6 | 5 | eriknyquist/text_map_builder_gui | text_game_map_maker/forms.py | Python | AutoFormSettings | AutoFormSettings | 4 | 11 | 4 | 4 | 5267cef85a79d0f10293e35ea40ab26f7f7f244f | bigcode/the-stack | train |
ba72d76332d11d4c26cc192a | train | class | class TileSettings(AutoFormSettings):
spec = OrderedDict([
('tile_id', {'type': 'str', 'label': 'tile ID', "tooltip": "Unique "
"identifier for programmatic access to this tile"}),
('name', {'type': 'str', 'tooltip': "Short string used to describe this "
"tile to... | class TileSettings(AutoFormSettings):
| spec = OrderedDict([
('tile_id', {'type': 'str', 'label': 'tile ID', "tooltip": "Unique "
"identifier for programmatic access to this tile"}),
('name', {'type': 'str', 'tooltip': "Short string used to describe this "
"tile to the player from afar, e.g. 'a scary r... | or 'an' (e.g. 'a' "
"wooden door, 'an' oak door)"}),
("name", {"type": "str", "tooltip": "name of this door, e.g. "
"'wooden door' or 'oak door'"}),
("tile_id", {"type": "str", "label": "tile ID", "tooltip": "unique "
"identifier for programmatic ... | 173 | 173 | 579 | 8 | 165 | eriknyquist/text_map_builder_gui | text_game_map_maker/forms.py | Python | TileSettings | TileSettings | 53 | 93 | 53 | 53 | 0cbe1d0eba49037eb489e839f75d3d3c11d68398 | bigcode/the-stack | train |
3f654ee2a8d1a9879fc10395 | train | class | class WallSettings(AutoFormSettings):
spec = OrderedDict([
("north", {"type": "bool", "tooltip": "Enable/disable wall to the north"}),
("south", {"type": "bool", "tooltip": "Enable/disable wall to the south"}),
("east", {"type": "bool", "tooltip": "Enable/disable wall to the east"}),
... | class WallSettings(AutoFormSettings):
| spec = OrderedDict([
("north", {"type": "bool", "tooltip": "Enable/disable wall to the north"}),
("south", {"type": "bool", "tooltip": "Enable/disable wall to the south"}),
("east", {"type": "bool", "tooltip": "Enable/disable wall to the east"}),
("west", {"type": "bool", "tooltip": ... | def __init__(self):
if not hasattr(self, "spec"):
raise RuntimeError("%s instance has no 'spec' attribute"
% self.__class__.__name__)
for attrname in self.spec.keys():
setattr(self, attrname, None)
class WallSettings(AutoFormSettings):
| 64 | 64 | 104 | 8 | 56 | eriknyquist/text_map_builder_gui | text_game_map_maker/forms.py | Python | WallSettings | WallSettings | 13 | 19 | 13 | 13 | c2092044394592a7b5c1bcf719ed977b89397511 | bigcode/the-stack | train |
19307a16c70fb8837656e9bf | train | class | class KeypadDoorSettings(AutoFormSettings):
spec = OrderedDict([
("direction", {"type": "choice", "choices": ["north", "south", "east", "west"],
"tooltip": "Set the direction to this door from currently"
" selected tile"}),
("prefix", {"type": "str", "tool... | class KeypadDoorSettings(AutoFormSettings):
| spec = OrderedDict([
("direction", {"type": "choice", "choices": ["north", "south", "east", "west"],
"tooltip": "Set the direction to this door from currently"
" selected tile"}),
("prefix", {"type": "str", "tooltip": "Set the word that should precede "
... | type": "str", "tooltip": "name of this door, e.g. "
"'wooden door' or 'oak door'"}),
("tile_id", {"type": "str", "label": "tile ID", "tooltip": "unique "
"identifier for programmatic access to this door"})
])
class KeypadDoorSettings(AutoFormSettings):
| 77 | 77 | 259 | 10 | 67 | eriknyquist/text_map_builder_gui | text_game_map_maker/forms.py | Python | KeypadDoorSettings | KeypadDoorSettings | 35 | 51 | 35 | 35 | 16bd928be781dbd94c8758a3166a86a316ff9f88 | bigcode/the-stack | train |
cbcb41f9c53836ed4955bd7a | train | class | class IsisSRTunnelList(Base):
"""ISIS MPLS SR Tunnel
The IsisSRTunnelList class encapsulates a required isisSRTunnelList resource which will be retrieved from the server every time the property is accessed.
"""
__slots__ = ()
_SDM_NAME = 'isisSRTunnelList'
_SDM_ATT_MAP = {
'Active': 'ac... | class IsisSRTunnelList(Base):
| """ISIS MPLS SR Tunnel
The IsisSRTunnelList class encapsulates a required isisSRTunnelList resource which will be retrieved from the server every time the property is accessed.
"""
__slots__ = ()
_SDM_NAME = 'isisSRTunnelList'
_SDM_ATT_MAP = {
'Active': 'active',
'Count': 'count... | ight
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or se... | 256 | 256 | 1,709 | 8 | 247 | OpenIxia/ixnetwork_restpy | uhd_restpy/testplatform/sessions/ixnetwork/topology/isissrtunnellist_4c3217e504788bc35135af392bfa9c40.py | Python | IsisSRTunnelList | IsisSRTunnelList | 27 | 228 | 27 | 27 | 19cfee74451b9730c2c7daf1ec67b097a6898e8c | bigcode/the-stack | train |
9b36176c6cd9ba459eb1ba63 | train | class | class StoryEditorTests(BaseStoryEditorControllerTests):
def test_can_not_access_story_editor_page_with_invalid_story_id(self):
self.login(self.ADMIN_EMAIL)
new_story_id = story_services.get_new_story_id()
self.get_html_response(
'%s/%s' % (
feconf.STORY_EDITOR_... | class StoryEditorTests(BaseStoryEditorControllerTests):
| def test_can_not_access_story_editor_page_with_invalid_story_id(self):
self.login(self.ADMIN_EMAIL)
new_story_id = story_services.get_new_story_id()
self.get_html_response(
'%s/%s' % (
feconf.STORY_EDITOR_URL_PREFIX, new_story_id),
expected_status_in... | category='Mathematics', language_code='en',
correctness_feedback_enabled=True)
json_response = self.get_json(
'%s/%s' % (
feconf.VALIDATE_STORY_EXPLORATIONS_URL_PREFIX, self.story_id),
params={
'comma_separated_exp_ids': '15,0'
})
... | 256 | 256 | 3,146 | 10 | 246 | TheoLipeles/oppia | core/controllers/story_editor_test.py | Python | StoryEditorTests | StoryEditorTests | 165 | 581 | 165 | 166 | cafb11cadf0e6969914f0ba06847da8de90ea479 | bigcode/the-stack | train |
6b04bee4b6ab799f38fcd63d | train | class | class StoryPublicationTests(BaseStoryEditorControllerTests):
def test_put_can_not_publish_story_with_invalid_story_id(self):
self.login(self.ADMIN_EMAIL)
new_story_id = story_services.get_new_story_id()
csrf_token = self.get_new_csrf_token()
self.put_json(
'%s/%s' % (
... | class StoryPublicationTests(BaseStoryEditorControllerTests):
| def test_put_can_not_publish_story_with_invalid_story_id(self):
self.login(self.ADMIN_EMAIL)
new_story_id = story_services.get_new_story_id()
csrf_token = self.get_new_csrf_token()
self.put_json(
'%s/%s' % (
feconf.STORY_PUBLISH_HANDLER, new_story_id),
... | self.admin_id = self.get_user_id_from_email(self.ADMIN_EMAIL)
self.new_user_id = self.get_user_id_from_email(self.NEW_USER_EMAIL)
self.set_admins([self.ADMIN_USERNAME])
self.admin = user_services.get_user_actions_info(self.admin_id)
self.topic_id = topic_fetchers.get_new_topic_... | 174 | 174 | 582 | 10 | 164 | TheoLipeles/oppia | core/controllers/story_editor_test.py | Python | StoryPublicationTests | StoryPublicationTests | 53 | 125 | 53 | 54 | 5ea819e16211a43d23c04c3b161c9daad45727f1 | bigcode/the-stack | train |
494455ada97161f1d3e8e578 | train | class | class ValidateExplorationsHandlerTests(BaseStoryEditorControllerTests):
def test_validation_error_messages(self):
# Check that admins can publish a story.
self.login(self.ADMIN_EMAIL)
self.save_new_valid_exploration(
'0', self.admin_id, title='Title 1',
category='Mat... | class ValidateExplorationsHandlerTests(BaseStoryEditorControllerTests):
| def test_validation_error_messages(self):
# Check that admins can publish a story.
self.login(self.ADMIN_EMAIL)
self.save_new_valid_exploration(
'0', self.admin_id, title='Title 1',
category='Mathematics', language_code='en',
correctness_feedback_enabled=T... | _id:
self.assertEqual(reference.story_is_published, False)
self.logout()
# Check that non-admins cannot publish a story.
self.put_json(
'%s/%s' % (
feconf.STORY_PUBLISH_HANDLER, self.story_id),
{'new_story_status_is_public': True}, csrf_t... | 92 | 92 | 308 | 13 | 79 | TheoLipeles/oppia | core/controllers/story_editor_test.py | Python | ValidateExplorationsHandlerTests | ValidateExplorationsHandlerTests | 128 | 162 | 128 | 129 | 83fef7943093dba3dba7c8471db8111181b5d615 | bigcode/the-stack | train |
168af8332fff7384aa9ff536 | train | class | class BaseStoryEditorControllerTests(test_utils.GenericTestBase):
def setUp(self):
"""Completes the sign-up process for the various users."""
super(BaseStoryEditorControllerTests, self).setUp()
self.signup(self.ADMIN_EMAIL, self.ADMIN_USERNAME)
self.signup(self.NEW_USER_EMAIL, self.... | class BaseStoryEditorControllerTests(test_utils.GenericTestBase):
| def setUp(self):
"""Completes the sign-up process for the various users."""
super(BaseStoryEditorControllerTests, self).setUp()
self.signup(self.ADMIN_EMAIL, self.ADMIN_USERNAME)
self.signup(self.NEW_USER_EMAIL, self.NEW_USER_USERNAME)
self.admin_id = self.get_user_id_from_e... | __future__ import unicode_literals # pylint: disable=import-only-modules
from core.domain import story_domain
from core.domain import story_services
from core.domain import topic_fetchers
from core.domain import user_services
from core.tests import test_utils
import feconf
class BaseStoryEditorControllerTests(test_u... | 69 | 69 | 232 | 12 | 56 | TheoLipeles/oppia | core/controllers/story_editor_test.py | Python | BaseStoryEditorControllerTests | BaseStoryEditorControllerTests | 28 | 50 | 28 | 29 | 61072c8735cf89391be947b1c403cfe11ce17474 | bigcode/the-stack | train |
c4e67c6725db893830996c6b | train | function | def test_predict(test_df):
filters = ['col1 in [0, 2, 4]']
model_exp = 'col1 ~ col2'
fit = regression.fit_model(test_df, filters, model_exp)
predicted = regression.predict(
test_df.query('col1 in [1, 3]'), None, fit)
expected = pd.Series([1., 3.], index=['b', 'd'])
pdt.assert_series_equa... | def test_predict(test_df):
| filters = ['col1 in [0, 2, 4]']
model_exp = 'col1 ~ col2'
fit = regression.fit_model(test_df, filters, model_exp)
predicted = regression.predict(
test_df.query('col1 in [1, 3]'), None, fit)
expected = pd.Series([1., 3.], index=['b', 'd'])
pdt.assert_series_equal(predicted, expected)
| ', 'x', 'y']
return test_df
def test_fit_model(test_df):
filters = []
model_exp = 'col1 ~ col2'
fit = regression.fit_model(test_df, filters, model_exp)
assert isinstance(fit, RegressionResultsWrapper)
def test_predict(test_df):
| 64 | 64 | 103 | 6 | 58 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_predict | test_predict | 44 | 51 | 44 | 44 | 2f56f96c21488b70eb1194e83234feb627c70c37 | bigcode/the-stack | train |
572a31e2200f810e3187919c | train | class | class TestRegressionModelYAMLFit(TestRegressionModelYAMLNotFit):
def setup_method(self, method):
super(TestRegressionModelYAMLFit, self).setup_method(method)
self.model.fit(test_df())
self.expected_dict['fitted'] = True
self.expected_dict['fit_rsquared'] = 1.0
self.expected... | class TestRegressionModelYAMLFit(TestRegressionModelYAMLNotFit):
| def setup_method(self, method):
super(TestRegressionModelYAMLFit, self).setup_method(method)
self.model.fit(test_df())
self.expected_dict['fitted'] = True
self.expected_dict['fit_rsquared'] = 1.0
self.expected_dict['fit_rsquared_adj'] = 1.0
self.expected_dict['fit_p... | _file = tempfile.NamedTemporaryFile(suffix='.yaml').name
self.model.to_yaml(str_or_buffer=test_file)
with open(test_file) as f:
assert_dict_specs_equal(yaml.safe_load(f), self.expected_dict)
model = regression.RegressionModel.from_yaml(str_or_buffer=test_file)
assert isinst... | 94 | 94 | 314 | 15 | 79 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | TestRegressionModelYAMLFit | TestRegressionModelYAMLFit | 244 | 275 | 244 | 244 | cc534be1fbbda442a8d97c332d7e45b173891550 | bigcode/the-stack | train |
365ab1af25875f2aea67c15a | train | function | def test_predict_with_nans():
df = pd.DataFrame(
{'col1': range(5),
'col2': [5, 6, pd.np.nan, 8, 9]},
index=['a', 'b', 'c', 'd', 'e'])
with pytest.raises(ModelEvaluationError):
regression.fit_model(df, None, 'col1 ~ col2')
fit = regression.fit_model(df.loc[['a', 'b', 'e']]... | def test_predict_with_nans():
| df = pd.DataFrame(
{'col1': range(5),
'col2': [5, 6, pd.np.nan, 8, 9]},
index=['a', 'b', 'c', 'd', 'e'])
with pytest.raises(ModelEvaluationError):
regression.fit_model(df, None, 'col1 ~ col2')
fit = regression.fit_model(df.loc[['a', 'b', 'e']], None, 'col1 ~ col2')
pr... | test_df.query('col1 in [1, 3]'), None, fit, ytransform=yt)
expected = pd.Series([0.5, 1.5], index=['b', 'd'])
pdt.assert_series_equal(predicted, expected)
def test_predict_with_nans():
| 64 | 64 | 140 | 7 | 57 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_predict_with_nans | test_predict_with_nans | 66 | 80 | 66 | 66 | c821538f89deac07d580eee5d4036493d0298902 | bigcode/the-stack | train |
e6bbd4cd2581b926539d2c76 | train | class | class TestRegressionModelYAMLNotFit(object):
def setup_method(self, method):
fit_filters = ['col1 in [0, 2, 4]']
predict_filters = ['col1 in [1, 3]']
model_exp = 'col1 ~ col2'
ytransform = np.log1p
name = 'test hedonic'
self.model = regression.RegressionModel(
... | class TestRegressionModelYAMLNotFit(object):
| def setup_method(self, method):
fit_filters = ['col1 in [0, 2, 4]']
predict_filters = ['col1 in [1, 3]']
model_exp = 'col1 ~ col2'
ytransform = np.log1p
name = 'test hedonic'
self.model = regression.RegressionModel(
fit_filters, predict_filters, model_exp... | .sort_index(), groupby_df.col1,
check_dtype=False, check_names=False)
def assert_dict_specs_equal(j1, j2):
j1_params = j1.pop('fit_parameters')
j2_params = j2.pop('fit_parameters')
assert j1 == j2
if j1_params and j2_params:
pdt.assert_series_equal(
pd.Series(j1_params['C... | 125 | 125 | 417 | 10 | 114 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | TestRegressionModelYAMLNotFit | TestRegressionModelYAMLNotFit | 188 | 241 | 188 | 188 | d80947a8a187209f78a290c9c3b465017b4d866c | bigcode/the-stack | train |
3a1364eb890177eb105714f9 | train | function | def test_SegmentedRegressionModel_yaml(groupby_df):
seg = regression.SegmentedRegressionModel(
'group', fit_filters=['col1 not in [2]'],
predict_filters=['group != "z"'], default_model_expr='col1 ~ col2',
min_segment_size=5000, name='test_seg')
seg.add_segment('x')
seg.add_segment('y... | def test_SegmentedRegressionModel_yaml(groupby_df):
| seg = regression.SegmentedRegressionModel(
'group', fit_filters=['col1 not in [2]'],
predict_filters=['group != "z"'], default_model_expr='col1 ~ col2',
min_segment_size=5000, name='test_seg')
seg.add_segment('x')
seg.add_segment('y', 'np.exp(col2) ~ np.exp(col1)', np.log)
expec... | seg.add_segment('x', 'col1 ~ col2')
seg.add_segment('y', 'np.exp(col2) ~ np.exp(col1)', np.log)
assert set(seg.columns_used()) == {'col1', 'col2', 'group'}
fits = seg.fit(groupby_df)
assert 'x' in fits and 'y' in fits
assert isinstance(fits['x'], RegressionResultsWrapper)
test_data = pd.Da... | 193 | 194 | 649 | 12 | 181 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_SegmentedRegressionModel_yaml | test_SegmentedRegressionModel_yaml | 338 | 408 | 338 | 338 | e229927e33bc355676c704673547531882a2aa81 | bigcode/the-stack | train |
15297b9340a99dcc0ed4c787 | train | function | def test_SegmentedRegressionModel_removes_gone_segments(groupby_df):
seg = regression.SegmentedRegressionModel(
'group', default_model_expr='col1 ~ col2')
seg.add_segment('a')
seg.add_segment('b')
seg.add_segment('c')
seg.fit(groupby_df)
assert sorted(seg._group.models.keys()) == ['x',... | def test_SegmentedRegressionModel_removes_gone_segments(groupby_df):
| seg = regression.SegmentedRegressionModel(
'group', default_model_expr='col1 ~ col2')
seg.add_segment('a')
seg.add_segment('b')
seg.add_segment('c')
seg.fit(groupby_df)
assert sorted(seg._group.models.keys()) == ['x', 'y']
| _dict['models']['y'].pop('fit_rsquared_adj'), float)
assert actual_dict == expected_dict
new_seg = regression.SegmentedRegressionModel.from_yaml(seg.to_yaml())
assert new_seg.fitted is True
def test_SegmentedRegressionModel_removes_gone_segments(groupby_df):
| 64 | 64 | 84 | 16 | 47 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_SegmentedRegressionModel_removes_gone_segments | test_SegmentedRegressionModel_removes_gone_segments | 411 | 420 | 411 | 411 | ff85615e831e0dae6bc328d3367fd1f485f39391 | bigcode/the-stack | train |
90774459a1d8fd4af5d25b8a | train | function | def test_predict_ytransform(test_df):
def yt(x):
return x / 2.
filters = ['col1 in [0, 2, 4]']
model_exp = 'col1 ~ col2'
fit = regression.fit_model(test_df, filters, model_exp)
predicted = regression.predict(
test_df.query('col1 in [1, 3]'), None, fit, ytransform=yt)
expected = p... | def test_predict_ytransform(test_df):
| def yt(x):
return x / 2.
filters = ['col1 in [0, 2, 4]']
model_exp = 'col1 ~ col2'
fit = regression.fit_model(test_df, filters, model_exp)
predicted = regression.predict(
test_df.query('col1 in [1, 3]'), None, fit, ytransform=yt)
expected = pd.Series([0.5, 1.5], index=['b', 'd'])... | )
predicted = regression.predict(
test_df.query('col1 in [1, 3]'), None, fit)
expected = pd.Series([1., 3.], index=['b', 'd'])
pdt.assert_series_equal(predicted, expected)
def test_predict_ytransform(test_df):
| 64 | 64 | 125 | 8 | 56 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_predict_ytransform | test_predict_ytransform | 54 | 63 | 54 | 54 | 07b3098defac3c6d2432b83ef96ed2316e3827b1 | bigcode/the-stack | train |
c04a255972f4109b2f4d21c8 | train | function | def test_SegmentedRegressionModel_explicit(groupby_df):
seg = regression.SegmentedRegressionModel(
'group', fit_filters=['col1 not in [2]'],
predict_filters=['group != "z"'])
seg.add_segment('x', 'col1 ~ col2')
seg.add_segment('y', 'np.exp(col2) ~ np.exp(col1)', np.log)
assert set(seg.co... | def test_SegmentedRegressionModel_explicit(groupby_df):
| seg = regression.SegmentedRegressionModel(
'group', fit_filters=['col1 not in [2]'],
predict_filters=['group != "z"'])
seg.add_segment('x', 'col1 ~ col2')
seg.add_segment('y', 'np.exp(col2) ~ np.exp(col1)', np.log)
assert set(seg.columns_used()) == {'col1', 'col2', 'group'}
fits = s... | group': ['x', 'y'], 'col2': [0.5, 10.5]})
predicted = seg.predict(test_data)
pdt.assert_series_equal(predicted.sort_index(), pd.Series([-4.5, 5.5]))
def test_SegmentedRegressionModel_explicit(groupby_df):
| 67 | 68 | 229 | 13 | 54 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_SegmentedRegressionModel_explicit | test_SegmentedRegressionModel_explicit | 316 | 335 | 316 | 316 | 87008f2a2ed46f496ca32ac9e77d41819df2ae67 | bigcode/the-stack | train |
ffabfbf2783c8475424c565f | train | function | def test_fit_from_cfg(test_df):
fit_filters = ['col1 in [0, 2, 4]']
predict_filters = ['col1 in [1, 3]']
model_exp = 'col1 ~ col2'
ytransform = np.log
name = 'test hedonic'
model = regression.RegressionModel(
fit_filters, predict_filters, model_exp, ytransform, name)
cfgname = temp... | def test_fit_from_cfg(test_df):
| fit_filters = ['col1 in [0, 2, 4]']
predict_filters = ['col1 in [1, 3]']
model_exp = 'col1 ~ col2'
ytransform = np.log
name = 'test hedonic'
model = regression.RegressionModel(
fit_filters, predict_filters, model_exp, ytransform, name)
cfgname = tempfile.NamedTemporaryFile(suffix='... | group', default_model_expr='col1 ~ col2')
seg.add_segment('a')
seg.add_segment('b')
seg.add_segment('c')
seg.fit(groupby_df)
assert sorted(seg._group.models.keys()) == ['x', 'y']
def test_fit_from_cfg(test_df):
| 64 | 64 | 149 | 8 | 56 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_fit_from_cfg | test_fit_from_cfg | 423 | 437 | 423 | 423 | 7d878e2ba18b9acb7e5afc574b7a6578b4723765 | bigcode/the-stack | train |
be986c1f2316451897284ca8 | train | function | def test_RegressionModel(test_df):
fit_filters = ['col1 in [0, 2, 4]']
predict_filters = ['col1 in [1, 3]']
model_exp = 'col1 ~ col2'
def ytransform(x):
return x / 2.
name = 'test hedonic'
model = regression.RegressionModel(
fit_filters, predict_filters, model_exp, ytransform,... | def test_RegressionModel(test_df):
| fit_filters = ['col1 in [0, 2, 4]']
predict_filters = ['col1 in [1, 3]']
model_exp = 'col1 ~ col2'
def ytransform(x):
return x / 2.
name = 'test hedonic'
model = regression.RegressionModel(
fit_filters, predict_filters, model_exp, ytransform, name)
assert model.fit_filters... | pdt.assert_series_equal(wrapper.params, fit.params, check_names=False)
pdt.assert_series_equal(wrapper.bse, fit.bse, check_names=False)
pdt.assert_series_equal(wrapper.tvalues, fit.tvalues, check_names=False)
assert wrapper.rsquared == fit.rsquared
assert wrapper.rsquared_adj == fit.rsquared_adj
def... | 82 | 82 | 275 | 8 | 73 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_RegressionModel | test_RegressionModel | 109 | 142 | 109 | 109 | 7e580ea48fcf83748d757957e7dab9f16b269897 | bigcode/the-stack | train |
4f9ff149efb6b3e6842fcbf9 | train | function | def test_SegmentedRegressionModel(groupby_df):
seg = regression.SegmentedRegressionModel(
'group', default_model_expr='col1 ~ col2')
assert seg.fitted is False
fits = seg.fit(groupby_df)
assert seg.fitted is True
assert 'x' in fits and 'y' in fits
assert isinstance(fits['x'], Regression... | def test_SegmentedRegressionModel(groupby_df):
| seg = regression.SegmentedRegressionModel(
'group', default_model_expr='col1 ~ col2')
assert seg.fitted is False
fits = seg.fit(groupby_df)
assert seg.fitted is True
assert 'x' in fits and 'y' in fits
assert isinstance(fits['x'], RegressionResultsWrapper)
test_data = pd.DataFrame({... | quared
assert params.rsquared_adj == fit.rsquared_adj
def test_SegmentedRegressionModel_raises(groupby_df):
seg = regression.SegmentedRegressionModel('group')
with pytest.raises(ValueError):
seg.fit(groupby_df)
def test_SegmentedRegressionModel(groupby_df):
| 64 | 64 | 148 | 11 | 53 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_SegmentedRegressionModel | test_SegmentedRegressionModel | 300 | 313 | 300 | 300 | 4a09427945b4a068a241552183eefc4e39676355 | bigcode/the-stack | train |
41941839debf106a7c04fdbd | train | function | def test_model_fit_to_table(test_df):
filters = []
model_exp = 'col1 ~ col2'
fit = regression.fit_model(test_df, filters, model_exp)
params = regression._model_fit_to_table(fit)
pdt.assert_series_equal(
params['Coefficient'], fit.params, check_names=False)
pdt.assert_series_equal(params... | def test_model_fit_to_table(test_df):
| filters = []
model_exp = 'col1 ~ col2'
fit = regression.fit_model(test_df, filters, model_exp)
params = regression._model_fit_to_table(fit)
pdt.assert_series_equal(
params['Coefficient'], fit.params, check_names=False)
pdt.assert_series_equal(params['Std. Error'], fit.bse, check_names=F... | (test_df))
testing.assert_frames_equal(
model.fit_parameters, self.model.fit_parameters)
assert model.fit_parameters.rsquared == \
self.model.fit_parameters.rsquared
assert model.fit_parameters.rsquared_adj == \
self.model.fit_parameters.rsquared_adj
def test_... | 64 | 64 | 131 | 9 | 54 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_model_fit_to_table | test_model_fit_to_table | 278 | 290 | 278 | 278 | c1b3bb3adebd1102197f81db7daa17d8255db548 | bigcode/the-stack | train |
1f32277339eccdf7c1d0095e | train | function | def assert_dict_specs_equal(j1, j2):
j1_params = j1.pop('fit_parameters')
j2_params = j2.pop('fit_parameters')
assert j1 == j2
if j1_params and j2_params:
pdt.assert_series_equal(
pd.Series(j1_params['Coefficient']),
pd.Series(j2_params['Coefficient']))
else:
... | def assert_dict_specs_equal(j1, j2):
| j1_params = j1.pop('fit_parameters')
j2_params = j2.pop('fit_parameters')
assert j1 == j2
if j1_params and j2_params:
pdt.assert_series_equal(
pd.Series(j1_params['Coefficient']),
pd.Series(j2_params['Coefficient']))
else:
assert j1_params is None
as... | ['y'], RegressionResultsWrapper)
predicted = hmg.predict(groupby_df)
assert isinstance(predicted, pd.Series)
pdt.assert_series_equal(
predicted.sort_index(), groupby_df.col1,
check_dtype=False, check_names=False)
def assert_dict_specs_equal(j1, j2):
| 64 | 64 | 97 | 11 | 53 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | assert_dict_specs_equal | assert_dict_specs_equal | 173 | 185 | 173 | 173 | 2119b1bd28fb45da88d3846db55ee9119e365d63 | bigcode/the-stack | train |
1711614465df114d8b41421a | train | function | @pytest.fixture
def test_df():
return pd.DataFrame(
{'col1': range(5),
'col2': range(5, 10)},
index=['a', 'b', 'c', 'd', 'e'])
| @pytest.fixture
def test_df():
| return pd.DataFrame(
{'col1': range(5),
'col2': range(5, 10)},
index=['a', 'b', 'c', 'd', 'e'])
|
import pytest
import statsmodels.formula.api as smf
import yaml
from pandas.util import testing as pdt
from statsmodels.regression.linear_model import RegressionResultsWrapper
from .. import regression
from ...exceptions import ModelEvaluationError
from ...utils import testing
@pytest.fixture
def test_df():
| 64 | 64 | 51 | 7 | 56 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_df | test_df | 23 | 28 | 23 | 24 | afc76eef9c74aac425ec59931057ddcda64ee1e9 | bigcode/the-stack | train |
b0d319f314d8d9b6886b9843 | train | function | def test_FakeRegressionResults(test_df):
model_exp = 'col1 ~ col2'
model = smf.ols(formula=model_exp, data=test_df)
fit = model.fit()
fit_parameters = regression._model_fit_to_table(fit)
wrapper = regression._FakeRegressionResults(
model_exp, fit_parameters, fit.rsquared, fit.rsquared_adj)... | def test_FakeRegressionResults(test_df):
| model_exp = 'col1 ~ col2'
model = smf.ols(formula=model_exp, data=test_df)
fit = model.fit()
fit_parameters = regression._model_fit_to_table(fit)
wrapper = regression._FakeRegressionResults(
model_exp, fit_parameters, fit.rsquared, fit.rsquared_adj)
test_predict = pd.DataFrame({'col2'... | .isnan(predict.loc['c'])
def test_rhs():
assert regression._rhs('col1 + col2') == 'col1 + col2'
assert regression._rhs('col3 ~ col1 + col2') == 'col1 + col2'
def test_FakeRegressionResults(test_df):
| 64 | 64 | 197 | 9 | 55 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_FakeRegressionResults | test_FakeRegressionResults | 88 | 106 | 88 | 88 | 899c1189034bea27790ddd82dadd4463afe8f557 | bigcode/the-stack | train |
3b858c2b150c6cd9349bb8b1 | train | function | def test_rhs():
assert regression._rhs('col1 + col2') == 'col1 + col2'
assert regression._rhs('col3 ~ col1 + col2') == 'col1 + col2'
| def test_rhs():
| assert regression._rhs('col1 + col2') == 'col1 + col2'
assert regression._rhs('col3 ~ col1 + col2') == 'col1 + col2'
| ~ col2')
fit = regression.fit_model(df.loc[['a', 'b', 'e']], None, 'col1 ~ col2')
predict = regression.predict(
df.loc[['c', 'd']], None, fit)
assert np.isnan(predict.loc['c'])
def test_rhs():
| 63 | 64 | 47 | 4 | 59 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_rhs | test_rhs | 83 | 85 | 83 | 83 | b5f94cb0277d711f5c4c9a454475333fe3e11a1c | bigcode/the-stack | train |
bf99e68dc02189c20b5e8ad8 | train | function | def test_SegmentedRegressionModel_raises(groupby_df):
seg = regression.SegmentedRegressionModel('group')
with pytest.raises(ValueError):
seg.fit(groupby_df)
| def test_SegmentedRegressionModel_raises(groupby_df):
| seg = regression.SegmentedRegressionModel('group')
with pytest.raises(ValueError):
seg.fit(groupby_df)
| '], fit.bse, check_names=False)
pdt.assert_series_equal(params['T-Score'], fit.tvalues, check_names=False)
assert params.rsquared == fit.rsquared
assert params.rsquared_adj == fit.rsquared_adj
def test_SegmentedRegressionModel_raises(groupby_df):
| 64 | 64 | 39 | 13 | 50 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_SegmentedRegressionModel_raises | test_SegmentedRegressionModel_raises | 293 | 297 | 293 | 293 | 389a21ddb2823aeb4e1d42e4d5c40fc7cb59f01c | bigcode/the-stack | train |
7d17ccf35ca1e107fb888209 | train | function | def test_fit_from_cfg_segmented(groupby_df):
seg = regression.SegmentedRegressionModel(
'group', fit_filters=['col1 not in [2]'],
predict_filters=['group != "z"'], default_model_expr='col1 ~ col2',
min_segment_size=5000, name='test_seg')
seg.add_segment('x')
cfgname = tempfile.Named... | def test_fit_from_cfg_segmented(groupby_df):
| seg = regression.SegmentedRegressionModel(
'group', fit_filters=['col1 not in [2]'],
predict_filters=['group != "z"'], default_model_expr='col1 ~ col2',
min_segment_size=5000, name='test_seg')
seg.add_segment('x')
cfgname = tempfile.NamedTemporaryFile(suffix='.yaml').name
seg.to... | TemporaryFile(suffix='.yaml').name
model.to_yaml(cfgname)
regression.RegressionModel.fit_from_cfg(test_df, cfgname, debug=True)
regression.RegressionModel.predict_from_cfg(test_df, cfgname)
os.remove(cfgname)
def test_fit_from_cfg_segmented(groupby_df):
| 64 | 64 | 156 | 11 | 53 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_fit_from_cfg_segmented | test_fit_from_cfg_segmented | 440 | 452 | 440 | 440 | bf869742c125fab6478ae58fd6869982a929e759 | bigcode/the-stack | train |
b19e6560170f008f0b896ab7 | train | function | def test_fit_model(test_df):
filters = []
model_exp = 'col1 ~ col2'
fit = regression.fit_model(test_df, filters, model_exp)
assert isinstance(fit, RegressionResultsWrapper)
| def test_fit_model(test_df):
| filters = []
model_exp = 'col1 ~ col2'
fit = regression.fit_model(test_df, filters, model_exp)
assert isinstance(fit, RegressionResultsWrapper)
| 10)},
index=['a', 'b', 'c', 'd', 'e'])
@pytest.fixture
def groupby_df(test_df):
test_df['group'] = ['x', 'y', 'x', 'x', 'y']
return test_df
def test_fit_model(test_df):
| 64 | 64 | 46 | 7 | 56 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_fit_model | test_fit_model | 37 | 41 | 37 | 37 | a50b27046a136d0c6597a1becb3ed0119267d934 | bigcode/the-stack | train |
6e3558354b185894c8e18d0f | train | function | @pytest.fixture
def groupby_df(test_df):
test_df['group'] = ['x', 'y', 'x', 'x', 'y']
return test_df
| @pytest.fixture
def groupby_df(test_df):
| test_df['group'] = ['x', 'y', 'x', 'x', 'y']
return test_df
| testing
@pytest.fixture
def test_df():
return pd.DataFrame(
{'col1': range(5),
'col2': range(5, 10)},
index=['a', 'b', 'c', 'd', 'e'])
@pytest.fixture
def groupby_df(test_df):
| 63 | 64 | 37 | 10 | 53 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | groupby_df | groupby_df | 31 | 34 | 31 | 32 | 4cc6e585abf70fbd798528bb70cb76d763592147 | bigcode/the-stack | train |
317d86913cdc646d8d21e114 | train | function | def test_RegressionModelGroup(groupby_df):
model_exp = 'col1 ~ col2'
hmg = regression.RegressionModelGroup('group')
xmodel = regression.RegressionModel(None, None, model_exp, name='x')
hmg.add_model(xmodel)
assert isinstance(hmg.models['x'], regression.RegressionModel)
hmg.add_model_from_para... | def test_RegressionModelGroup(groupby_df):
| model_exp = 'col1 ~ col2'
hmg = regression.RegressionModelGroup('group')
xmodel = regression.RegressionModel(None, None, model_exp, name='x')
hmg.add_model(xmodel)
assert isinstance(hmg.models['x'], regression.RegressionModel)
hmg.add_model_from_params('y', None, None, model_exp)
assert i... | ResultsWrapper)
predicted = model.predict(test_df)
expected = pd.Series([0.5, 1.5], index=['b', 'd'])
pdt.assert_series_equal(predicted, expected)
# make sure this doesn't cause an error
model.report_fit()
def test_RegressionModelGroup(groupby_df):
| 69 | 69 | 233 | 10 | 59 | tin6150/urbansim | urbansim/models/tests/test_regression.py | Python | test_RegressionModelGroup | test_RegressionModelGroup | 145 | 170 | 145 | 145 | b5f4f58ae08a24dd899719b17d98ac72a70a2fc6 | bigcode/the-stack | train |
96f37600e0de4bc1288803ba | train | class | class Connection(apsw.Connection, ContextManagerMixin):
def __init__(self, filename: Union[PathLike, str], *args):
super().__init__(str(filename), *args)
| class Connection(apsw.Connection, ContextManagerMixin):
| def __init__(self, filename: Union[PathLike, str], *args):
super().__init__(str(filename), *args)
| self.cursor()
try:
c.execute("BEGIN TRANSACTION")
yield c
except Exception:
c.execute("ROLLBACK TRANSACTION")
raise
else:
c.execute("COMMIT TRANSACTION")
finally:
c.close()
class Connection(apsw.Connection, ContextM... | 64 | 64 | 41 | 11 | 53 | jack1142/SinbadCogs-1 | mlog/apsw_wrapper.py | Python | Connection | Connection | 50 | 52 | 50 | 50 | 20a23d1dbbd9ddcfffd4f53cb038af4e72fd09f4 | bigcode/the-stack | train |
fa012486ecaf67a151495138 | train | class | class ContextManagerMixin(ProvidesCursor):
@contextmanager
def with_cursor(self) -> Generator[apsw.Cursor, None, None]:
c = self.cursor()
try:
yield c
finally:
c.close()
@contextmanager
def transaction(self) -> Generator[apsw.Cursor, None, None]:
... | class ContextManagerMixin(ProvidesCursor):
@contextmanager
| def with_cursor(self) -> Generator[apsw.Cursor, None, None]:
c = self.cursor()
try:
yield c
finally:
c.close()
@contextmanager
def transaction(self) -> Generator[apsw.Cursor, None, None]:
c = self.cursor()
try:
c.execute("BEGIN TRA... | point, but I'm being
lazy in the short term here.
"""
if TYPE_CHECKING:
from typing_extensions import Protocol
else:
Protocol = object
class ProvidesCursor(Protocol):
def cursor(self) -> apsw.Cursor:
...
class ContextManagerMixin(ProvidesCursor):
@contextmanager
| 64 | 64 | 127 | 13 | 51 | jack1142/SinbadCogs-1 | mlog/apsw_wrapper.py | Python | ContextManagerMixin | ContextManagerMixin | 26 | 47 | 26 | 27 | 784d775a56ff8a7df19b75bc8fc41e3c542445b3 | bigcode/the-stack | train |
84e469c85f0c51c036988c2c | train | class | class ProvidesCursor(Protocol):
def cursor(self) -> apsw.Cursor:
...
| class ProvidesCursor(Protocol):
| def cursor(self) -> apsw.Cursor:
...
| TYPE_CHECKING, Generator, Union
import apsw
"""
This should be moved into a pip installable lib at some point, but I'm being
lazy in the short term here.
"""
if TYPE_CHECKING:
from typing_extensions import Protocol
else:
Protocol = object
class ProvidesCursor(Protocol):
| 64 | 64 | 18 | 6 | 57 | jack1142/SinbadCogs-1 | mlog/apsw_wrapper.py | Python | ProvidesCursor | ProvidesCursor | 21 | 23 | 21 | 21 | 60e17ba2f41a2ce351f322c4df2e0917f99db28c | bigcode/the-stack | train |
83736f3d651bf07ce8cefcf3 | train | function | def is_windows() -> bool:
"""Guess if windows"""
platform_string = platform.system()
return os.name == "nt" or platform_string == "Windows" or "_NT" in platform_string
| def is_windows() -> bool:
| """Guess if windows"""
platform_string = platform.system()
return os.name == "nt" or platform_string == "Windows" or "_NT" in platform_string
| not, several tools don't make sense to run
https://stackoverflow.com/a/39956572/33264
"""
try:
_ = git.Repo(path).git_dir
return True
except git.exc.InvalidGitRepositoryError:
return False
def is_windows() -> bool:
| 64 | 64 | 43 | 7 | 56 | matthewdeanmartin/pydoc_fork | navio_tasks/system_info.py | Python | is_windows | is_windows | 27 | 30 | 27 | 27 | 47dd625857be88f5ac708018d45e6bf7736aee9c | bigcode/the-stack | train |
27c25fe73887c528395b2400 | train | function | def is_powershell() -> bool:
"""
Check if parent process or other ancestor process is powershell
"""
# ref https://stackoverflow.com/a/55598796/33264
# Get the parent process name.
try:
process_name = psutil.Process(os.getppid()).name()
grand_process_name = psutil.Process(os.get... | def is_powershell() -> bool:
| """
Check if parent process or other ancestor process is powershell
"""
# ref https://stackoverflow.com/a/55598796/33264
# Get the parent process name.
try:
process_name = psutil.Process(os.getppid()).name()
grand_process_name = psutil.Process(os.getppid()).parent().name()
... | except git.exc.InvalidGitRepositoryError:
return False
def is_windows() -> bool:
"""Guess if windows"""
platform_string = platform.system()
return os.name == "nt" or platform_string == "Windows" or "_NT" in platform_string
def is_powershell() -> bool:
| 64 | 64 | 207 | 9 | 54 | matthewdeanmartin/pydoc_fork | navio_tasks/system_info.py | Python | is_powershell | is_powershell | 33 | 53 | 33 | 33 | 4150f05617d6edabb3c740fd4bf7b26aa031c577 | bigcode/the-stack | train |
c1fb938b57df63df0e284d91 | train | function | def is_git_repo(path: str) -> bool:
"""
Are we in a git repo if not, several tools don't make sense to run
https://stackoverflow.com/a/39956572/33264
"""
try:
_ = git.Repo(path).git_dir
return True
except git.exc.InvalidGitRepositoryError:
return False
| def is_git_repo(path: str) -> bool:
| """
Are we in a git repo if not, several tools don't make sense to run
https://stackoverflow.com/a/39956572/33264
"""
try:
_ = git.Repo(path).git_dir
return True
except git.exc.InvalidGitRepositoryError:
return False
| """
Infering what machine we are on.
"""
import os
import platform
import re
import socket
import git
import psutil
from navio_tasks.utils import inform
def is_git_repo(path: str) -> bool:
| 48 | 64 | 78 | 11 | 36 | matthewdeanmartin/pydoc_fork | navio_tasks/system_info.py | Python | is_git_repo | is_git_repo | 15 | 24 | 15 | 15 | e023ef2b9af6d3b21a966f9ad9baf02ca5e5367d | bigcode/the-stack | train |
1bf4de2611bcff32ebe46058 | train | function | def check_is_aws() -> bool:
"""
Look at domain name to see if this is an ec2 machine
"""
# HACK: environment variable checking is much, much faster & reliable.
name = socket.getfqdn()
return "ip-" in name and ".ec2.internal" in name
| def check_is_aws() -> bool:
| """
Look at domain name to see if this is an ec2 machine
"""
# HACK: environment variable checking is much, much faster & reliable.
name = socket.getfqdn()
return "ip-" in name and ".ec2.internal" in name
| .fullmatch("pwsh|pwsh.exe|powershell.exe", grand_process_name)
)
except psutil.NoSuchProcess:
inform("Can't tell if this is powershell, assuming not.")
is_that_shell = False
return is_that_shell
def check_is_aws() -> bool:
| 64 | 64 | 68 | 9 | 54 | matthewdeanmartin/pydoc_fork | navio_tasks/system_info.py | Python | check_is_aws | check_is_aws | 56 | 62 | 56 | 56 | d750226bed3d9b45474f421bb0f8e8cf6411d7ea | bigcode/the-stack | train |
7d96d6b21b5237d57d703a0f | train | function | def process_TCGA_MAF(maf_file, save_path, filetype='matrix', gene_naming='Symbol', verbose=False):
loadtime = time.time()
# Load MAF File
TCGA_MAF = pd.read_csv(maf_file,sep='\t',low_memory=False)
# Get all patient somatic mutation (sm) pairs from MAF file
if gene_naming=='Entrez':
TCGA_sm = TCGA_MAF.groupby(['T... | def process_TCGA_MAF(maf_file, save_path, filetype='matrix', gene_naming='Symbol', verbose=False):
| loadtime = time.time()
# Load MAF File
TCGA_MAF = pd.read_csv(maf_file,sep='\t',low_memory=False)
# Get all patient somatic mutation (sm) pairs from MAF file
if gene_naming=='Entrez':
TCGA_sm = TCGA_MAF.groupby(['Tumor_Sample_Barcode', 'Entrez_Gene_Id']).size()
else:
TCGA_sm = TCGA_MAF.groupby(['Tumor_Sample_... | data[data[score_col]>q_score][data.columns[[nodeA_col, nodeB_col, score_col]]]
data_filt.columns = ['nodeA', 'nodeB', 'edgeScore']
if verbose:
print(data_filt.shape[0], '/', data.shape[0], 'edges retained')
data_filt.to_csv(save_path, sep='\t', header=False, index=False)
return
# Convert and save MAF from Broa... | 204 | 204 | 680 | 27 | 177 | decarlin/pyNBS_3 | pyNBS/data_import_tools.py | Python | process_TCGA_MAF | process_TCGA_MAF | 176 | 221 | 176 | 176 | 1d7c239adf764a9b4036ccc431790abd849368c5 | bigcode/the-stack | train |
565ddf0583701307e2f8fadd | train | function | def load_binary_mutation_data(filename, filetype='list', delimiter='\t', verbose=True):
# Load binary mutation data from file
if filetype=='list':
f = open(filename)
binary_mat_lines = f.read().splitlines()
binary_mat_data = [(line.split('\t')[0], line.split('\t')[1]) for line in binary_mat_lines]
binary_mat_... | def load_binary_mutation_data(filename, filetype='list', delimiter='\t', verbose=True):
# Load binary mutation data from file
| if filetype=='list':
f = open(filename)
binary_mat_lines = f.read().splitlines()
binary_mat_data = [(line.split('\t')[0], line.split('\t')[1]) for line in binary_mat_lines]
binary_mat_index = pd.MultiIndex.from_tuples(binary_mat_data, names=['Tumor_Sample_Barcode', 'Gene_Name'])
binary_mat_2col = pd.DataFram... | 1st column is sample/patient, 2nd column is one gene mutated in that patient
# Line example in 'list' file: 'Patient ID','Gene Mutated'
def load_binary_mutation_data(filename, filetype='list', delimiter='\t', verbose=True):
# Load binary mutation data from file
| 66 | 66 | 221 | 29 | 37 | decarlin/pyNBS_3 | pyNBS/data_import_tools.py | Python | load_binary_mutation_data | load_binary_mutation_data | 34 | 49 | 34 | 35 | a77bec761395f6a25e939790eba0eb8626134eb7 | bigcode/the-stack | train |
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