text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> start_date = now + timedelta(days=-7)
term.first_day_quarter = start_date.date()
self.assertEquals(term.get_week_of_term(), 2, "7 days in")
self.assertEquals(term.get_week_of_term_for_date(now),
2, "7 days in")
start_date = now + timedelta... | code_fim | hard | {
"lang": "python",
"repo": "uw-it-aca/uw-restclients-sws",
"path": "/uw_sws/tests/test_term.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: uw-it-aca/uw-restclients-sws path: /uw_sws/tests/test_term.py
Equals(term.get_bod_reg_period1_start(),
datetime(2012, 11, 2, 0, 0, 0))
self.assertEquals(term.get_bod_reg_period2_start(),
datetime(2012, 11, 26, 0, 0, 0))
self.as... | code_fim | hard | {
"lang": "python",
"repo": "uw-it-aca/uw-restclients-sws",
"path": "/uw_sws/tests/test_term.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: uw-it-aca/uw-restclients-sws path: /uw_sws/tests/test_term.py
rter = "spring"
expected_year = 2013
self.assertEquals(term.year, expected_year,
"Return {} for the current year".format(
expected_year))
self.assertEqua... | code_fim | hard | {
"lang": "python",
"repo": "uw-it-aca/uw-restclients-sws",
"path": "/uw_sws/tests/test_term.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> ### Inputs
_button_a = digitalio.DigitalInOut(board.BUTTON_A)
_button_a.switch_to_input(pull=digitalio.Pull.UP)
_button_b = digitalio.DigitalInOut(board.BUTTON_B)
_button_b.switch_to_input(pull=digitalio.Pull.UP)
button_left = lambda: not _button_a.value
button_right = lambda: ... | code_fim | hard | {
"lang": "python",
"repo": "dglaude/circuitpython-examples",
"path": "/clue/clue-bar-hammer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>### TOTAL_ROUNDS = 5
TOTAL_ROUNDS = 3
CRYPTO_ALGO = "chacha20"
KEY_SIZE = 8 ### in bytes
KEY_ENLARGE = 256 // KEY_SIZE // 8
def evaluateRound(mine, yours):
"""Determine who won the game based on the two strings mine and yours.
Returns three booleans (win, draw, void)."""
### Return with... | code_fim | hard | {
"lang": "python",
"repo": "dglaude/circuitpython-examples",
"path": "/clue/clue-bar-hammer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dglaude/circuitpython-examples path: /clue/clue-bar-hammer.py
### Trying to recreate MemoryError with broadcastAndReceive
### v2 introduces variable buffer sizes
### Tested with CLUE and Circuit Playground Bluefruit Alpha with TFT Gizmo
### using CircuitPython and 5.3.0
### copy this file to C... | code_fim | hard | {
"lang": "python",
"repo": "dglaude/circuitpython-examples",
"path": "/clue/clue-bar-hammer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 0x14d/PDPK path: /data_provider/synthetic_data_provider.py
"""
This module provides the class `SyntheticDataProvider`
"""
# pylint: disable=too-many-arguments, no-self-use, unused-argument, unused-variable, too-many-locals
from __future__ import annotations
from collections import defaultdict
... | code_fim | hard | {
"lang": "python",
"repo": "0x14d/PDPK",
"path": "/data_provider/synthetic_data_provider.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Parses a synthetic dataset to a list of AIPE experiments
Parameters:
dataset (GeneratedDataset): Synthetic dataset
Returns:
List of all generated experiments parsed to the AIPE format
"""
parsed_experiments: List[dei.ExperimentF... | code_fim | hard | {
"lang": "python",
"repo": "0x14d/PDPK",
"path": "/data_provider/synthetic_data_provider.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _parse_synthetic_experiment(
self,
experiment: GeneratedExperiment,
experiment_series: GeneratedExperimentSeries,
) -> dei.ExperimentFromDb:
"""
Parses a synthetic experiment to the AIPE format
Parameters:
experiment (GeneratedExperi... | code_fim | hard | {
"lang": "python",
"repo": "0x14d/PDPK",
"path": "/data_provider/synthetic_data_provider.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: angelosalatino/cso-classifier path: /cso_classifier/semanticmodule.py
import warnings
from kneed import KneeLocator
from rapidfuzz.distance import Levenshtein
from nltk import everygrams
class Semantic:
""" A simple abstraction layer for using the Semantic module of the CSO classifier """
... | code_fim | hard | {
"lang": "python",
"repo": "angelosalatino/cso-classifier",
"path": "/cso_classifier/semanticmodule.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Args:
gram (string): the n-gram found (joined)
grams (list): list of tokens to be analysed and founf in the model
Returns:
list_of_matched_topics (list): containing of all found topics
"""
identified_topics = list()
f... | code_fim | hard | {
"lang": "python",
"repo": "angelosalatino/cso-classifier",
"path": "/cso_classifier/semanticmodule.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> list_of_merged_topics = {}
for gram in grams:
if self.model.check_word_in_model(gram):
list_of_matched_topics_t = self.model.get_words_from_model(gram)
for topic_item in list_of_matched_topics_t:
temp_... | code_fim | hard | {
"lang": "python",
"repo": "angelosalatino/cso-classifier",
"path": "/cso_classifier/semanticmodule.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wairton/mr-ear path: /music.py
SHARP_NOTES = ['C', 'C#', 'D', 'D#', 'E', 'F', 'F#', 'G', 'G#', 'A', 'A#', 'B']
ATTR_SHARP_NOTES = ['C', 'CS', 'D', 'DS', 'E', 'F', 'FS', 'G', 'GS', 'A', 'AS', 'B']
ATTR_FLAT_NOTES = ['C', 'DF', 'D', 'EF', 'E', 'F', 'GF', 'G', 'AF', 'A', 'BF', 'B']
FLAT_NOTES = ['C'... | code_fim | hard | {
"lang": "python",
"repo": "wairton/mr-ear",
"path": "/music.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self._base
@base.setter
def base(self, value):
if not self._is_base_valid(value):
raise Exception('{} is not a valid note'.format(value))
self._base = value
def __lt__(self, other):
return Reference.reference_to_code(self) < Reference.refere... | code_fim | hard | {
"lang": "python",
"repo": "wairton/mr-ear",
"path": "/music.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def octave(self):
return self._octave
@octave.setter
def octave(self, value):
if 0 > value or 8 < value:
raise Exception('{} is not a valid octave'.format(value))
self._octave = value
def _is_base_valid(self, base):
return base.lo... | code_fim | hard | {
"lang": "python",
"repo": "wairton/mr-ear",
"path": "/music.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: phildini/django-patronage path: /patronage/migrations/0007_auto_20180926_1723.py
# Generated by Django 2.1.1 on 2018-09-26 17:23
from django.conf import settings
from django.db import migrations, models
<|fim_suffix|> operations = [
migrations.RemoveField(
model_name='ti... | code_fim | medium | {
"lang": "python",
"repo": "phildini/django-patronage",
"path": "/patronage/migrations/0007_auto_20180926_1723.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('patronage', '0006_auto_20180926_1720'),
]
operations = [
migrations.RemoveField(
model_name='tier',
name='creator',
),
migrations.AddField(
... | code_fim | medium | {
"lang": "python",
"repo": "phildini/django-patronage",
"path": "/patronage/migrations/0007_auto_20180926_1723.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Jacob-Lisner/Pneumathorax_Segmentation path: /basicAnalysis.py
import os
import pandas as pd
import json
import numpy as np
import pydicom as dicom
from sklearn.neural_network import MLPClassifier
import tensorflow as tf
from tensorflow.keras import datasets, layers, models
def main():
... | code_fim | hard | {
"lang": "python",
"repo": "Jacob-Lisner/Pneumathorax_Segmentation",
"path": "/basicAnalysis.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
yTest = yFull[batch_size:2*batch_size]
xTest = np.zeros((batch_size,width,height,1))
for i in range(0,batch_size):
img = dicom.read_file("./train_images/"+files[i+batch_size]+".dcm")
xTest[i,:,:,:] = np.reshape(img.pixel_array, (width,height,1)).astype(float)/255.0
... | code_fim | hard | {
"lang": "python",
"repo": "Jacob-Lisner/Pneumathorax_Segmentation",
"path": "/basicAnalysis.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def _send_all(recipients, **kwargs):
for recipient in recipients:
_send_single(recipient, **kwargs)
def _send_single(recipient, template_path, extra_context, from_email,
fail_silently, extra_headers):
context = {}
context.update(extra_context)
context["STATIC_U... | code_fim | hard | {
"lang": "python",
"repo": "cuu508/templated-emails",
"path": "/templated_emails/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cuu508/templated-emails path: /templated_emails/utils.py
import logging
import threading
from django.core.mail import EmailMultiAlternatives
from django.conf import settings
from django.template import TemplateDoesNotExist
from django.template.loader import render_to_string
from django.contrib.a... | code_fim | hard | {
"lang": "python",
"repo": "cuu508/templated-emails",
"path": "/templated_emails/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert f'{fixture_barcode_bingo75} {fixture_barcode_bingo75_2} {app.utiliz.count_range_barcode_in_util_menu()}' \
in app.utiliz.barcode_in_util_menu()
app.utiliz.two_delete_barcode(fixture_barcode_bingo75, fixture_barcode_bingo75_2)
app.utiliz.comeback_main_page()<|fim_prefix|># repo:... | code_fim | hard | {
"lang": "python",
"repo": "FearFactor1/SPA",
"path": "/test/Utilizations/bingo-75/test_add_two_barcode_bingo_75_current_draw_keyboard.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FearFactor1/SPA path: /test/Utilizations/bingo-75/test_add_two_barcode_bingo_75_current_draw_keyboard.py
# Добавить два билета на утилизацию по игре бинго 75 с помощью экранной клавиатуры
def test_add_two_barcode_bingo_75_current_draw_keyboard_range(app,
... | code_fim | hard | {
"lang": "python",
"repo": "FearFactor1/SPA",
"path": "/test/Utilizations/bingo-75/test_add_two_barcode_bingo_75_current_draw_keyboard.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>pp.utiliz.modal_one_input_ticket_barcode_keyboard(fixture_barcode_bingo75)
app.utiliz.click_two_input_in_keyboard()
app.utiliz.modal_two_input_ticket_barcode_keyboard(fixture_barcode_bingo75_2)
app.utiliz.modal_ticket_barcode_add()
app.utiliz.barcode_in_util_menu()
assert f'{fixture_ba... | code_fim | hard | {
"lang": "python",
"repo": "FearFactor1/SPA",
"path": "/test/Utilizations/bingo-75/test_add_two_barcode_bingo_75_current_draw_keyboard.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>model = dict(
generator=dict(out_size=256, fp16_enabled=True),
discriminator=dict(in_size=256, fp16_enabled=False, num_fp16_scales=4),
)
train_cfg = dict(max_iters=800000)
optim_wrapper = dict(
generator=dict(type='AmpOptimWrapper', loss_scale=512),
discriminator=dict(type='AmpOptimWrapper... | code_fim | medium | {
"lang": "python",
"repo": "open-mmlab/mmagic",
"path": "/configs/styleganv2/stylegan2_c2-PL-R1_8xb4-fp16-globalG-partialD-no-scaler-800kiters_ffhq-256x256.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: open-mmlab/mmagic path: /configs/styleganv2/stylegan2_c2-PL-R1_8xb4-fp16-globalG-partialD-no-scaler-800kiters_ffhq-256x256.py
"""Config for the `config-f` setting in StyleGAN2."""
<|fim_suffix|>model = dict(
generator=dict(out_size=256, fp16_enabled=True),
discriminator=dict(in_size=256,... | code_fim | medium | {
"lang": "python",
"repo": "open-mmlab/mmagic",
"path": "/configs/styleganv2/stylegan2_c2-PL-R1_8xb4-fp16-globalG-partialD-no-scaler-800kiters_ffhq-256x256.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> level_attr = dict(standard_name="level", uints="hPa")
lat_attr = dict(standard_name="lat", uints="degrees north")
lon_attr = dict(standard_name="lon", uints="degrees east")
ds = xr.Dataset({
"temperature":(dims,temps,temp_attr),
"precipitation":... | code_fim | hard | {
"lang": "python",
"repo": "go1me/python_creat_or_read_netcdf_demo",
"path": "/python_netcdf.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> temp_attr = dict(standard_name="air_potential_tempeature", uints="f")
prcp_attr = dict(standard_name="convective_precipitation_flux", uints="mm")
level_attr = dict(standard_name="level", uints="hPa")
lat_attr = dict(standard_name="lat", uints="degrees north")
lon... | code_fim | hard | {
"lang": "python",
"repo": "go1me/python_creat_or_read_netcdf_demo",
"path": "/python_netcdf.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: go1me/python_creat_or_read_netcdf_demo path: /python_netcdf.py
import time
import numpy as np
import pandas as pd
from netCDF4 import Dataset
class pyton_netcdf(object):
def __init__(self):
pass
def creat_netcdf_by_netcdf4(self,file_name_nc):
ntimes = 5
nlevels ... | code_fim | hard | {
"lang": "python",
"repo": "go1me/python_creat_or_read_netcdf_demo",
"path": "/python_netcdf.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alinamachidon/seq2seq_temporal_attention path: /code/S2S_att.py
import chainer
from chainer.links import Linear, Bilinear, EmbedID
from chainer.functions import array, batch_matmul, reshape
from chainer.functions.activation.lstm import lstm
from chainer.functions.activation.tanh import tanh
from... | code_fim | hard | {
"lang": "python",
"repo": "alinamachidon/seq2seq_temporal_attention",
"path": "/code/S2S_att.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def encode(self, frame, prev_word, state, dropout_flag=False, dropout_ratio=0.0):
state = self.enc(frame, prev_word, state, dropout_flag, dropout_ratio)
self.a_list.append(state['h1'])
return state
def decode(self, frame, prev_word, state, batch_size, xp):
if self.... | code_fim | hard | {
"lang": "python",
"repo": "alinamachidon/seq2seq_temporal_attention",
"path": "/code/S2S_att.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def check_ge_wrapper(self, *args):
for arg in args:
if isinstance(arg, numbers.Real) and arg < value:
raise ValueError("Value must be greater than or equal to " + str(value))
return func(self, *args)
return check_ge_wrapper
re... | code_fim | hard | {
"lang": "python",
"repo": "Computational-Fluid-Dynamics/Fluid-Simulation-for-Computer-Graphics",
"path": "/src/pyfluid/method_decorators.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Computational-Fluid-Dynamics/Fluid-Simulation-for-Computer-Graphics path: /src/pyfluid/method_decorators.py
import numbers
from .fluidsimulationsavestate import FluidSimulationSaveState
from .vector3 import Vector3
from .gridindex import GridIndex
def ijk_or_gridindex(func):
def ijk_or_grid... | code_fim | hard | {
"lang": "python",
"repo": "Computational-Fluid-Dynamics/Fluid-Simulation-for-Computer-Graphics",
"path": "/src/pyfluid/method_decorators.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
from scipy import sparse
import matplotlib.pyplot as plt
from tick.plot import plot_history
import numpy as np
from tick.linear_model import SimuLogReg, ModelLogReg
from tick.simulation import weights_sparse_gauss
from tick.solver import SVRG
from tick.prox import ProxElasticNet
seed = 1398
np.random.s... | code_fim | medium | {
"lang": "python",
"repo": "andro2157/tick",
"path": "/examples/plot_asynchronous_stochastic_solver.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andro2157/tick path: /examples/plot_asynchronous_stochastic_solver.py
"""
==============================
Asynchronous stochastic solver
==============================
This example illustrates the convergence speed of the asynchronous version of
SVRG solver. This solver called KroMagnon has been ... | code_fim | hard | {
"lang": "python",
"repo": "andro2157/tick",
"path": "/examples/plot_asynchronous_stochastic_solver.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def check_subseq_range(subseq_range):
"""Check that a range of sequences to extract is well defined
This function check:
- The range is correctly built: 2 integer values separated by a -
- The second value is higher than the first one
:param download: range for subsequences (limit ... | code_fim | hard | {
"lang": "python",
"repo": "nick-youngblut/enasearch",
"path": "/enasearch/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> free_text_search, query, result, display, download=None, file=None
):
"""Search ENA data and get all results (not size limited)
This function
- Extracts the number of possible results for the query
- Extracts the all the results of the query (by potentially running several
time... | code_fim | hard | {
"lang": "python",
"repo": "nick-youngblut/enasearch",
"path": "/enasearch/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nick-youngblut/enasearch path: /enasearch/__init__.py
download of data from ENA
:param download: download option to specify that records are to be saved in a file (used with file option, accessible with get_download_options)
:param file: filepath to save the content of the data (used wit... | code_fim | hard | {
"lang": "python",
"repo": "nick-youngblut/enasearch",
"path": "/enasearch/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
('newsletter', '0011_auto_20170127_1807'),
]
operations = [
migrations.AlterField(
model_name='list',
name='provider',
field=models.CharField(max_length=32, default='mailerlite', editable=False),
),
]<|fim_prefi... | code_fim | medium | {
"lang": "python",
"repo": "rogerhil/flaviabernardes",
"path": "/flaviabernardes/flaviabernardes/newsletter/migrations/0012_auto_20170402_1535.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rogerhil/flaviabernardes path: /flaviabernardes/flaviabernardes/newsletter/migrations/0012_auto_20170402_1535.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
<|fim_suffix|> dependencies = [
('newsletter', '0011_auto_2017012... | code_fim | easy | {
"lang": "python",
"repo": "rogerhil/flaviabernardes",
"path": "/flaviabernardes/flaviabernardes/newsletter/migrations/0012_auto_20170402_1535.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MarsPain/BiDAF_test_tf0.12 path: /test.py
# test1
# import tensorflow as tf
#
# # temp = tf.tile([1,2,3],[2])
# # temp2 = tf.tile([[1,2],[3,4],[5,6]],[2,3])
# #
# # with tf.Session() as sess:
# # print(sess.run(temp))
# # print(sess.run(temp2))
#
# t1 = [[[1, 2, 3], [1, 2, 3], [1, 2, 3]],... | code_fim | medium | {
"lang": "python",
"repo": "MarsPain/BiDAF_test_tf0.12",
"path": "/test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>a = tf.random_normal((100, 100))
b = tf.random_normal((100, 500))
c = tf.matmul(a, b)
sess = tf.InteractiveSession()
sess.run(c)
# test3
# import tensorflow as tf
#
# with tf.device('gpu'):
# a = tf.constant([1.0, 2.0, 3.0], shape=[3], name='a')
# b = tf.constant([1.0, 2.0, 3.0], shape=[3], name=... | code_fim | medium | {
"lang": "python",
"repo": "MarsPain/BiDAF_test_tf0.12",
"path": "/test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: isneverdead/heroku-test path: /duck.py
from selenium import webdriver
import os
chrome_options = webdriver.ChromeOptions()
chrome_options.binary_location = os.environ.get("GOOGLE_CHROME_BIN")
chrome_options.add_argument("--headless")
chrome_options.add_argument("--disable-dev-shm-usage")
chrome_... | code_fim | hard | {
"lang": "python",
"repo": "isneverdead/heroku-test",
"path": "/duck.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#print (search_box)
#search_box.send_keys(Keys.RETURN)
#submit = driver.get_element_by_id("search_button_homepage")
#submit.click()<|fim_prefix|># repo: isneverdead/heroku-test path: /duck.py
from selenium import webdriver
import os
chrome_options = webdriver.ChromeOptions()
chrome_options.binary_locati... | code_fim | hard | {
"lang": "python",
"repo": "isneverdead/heroku-test",
"path": "/duck.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def resize(self, tensor, size):
h, w = size
h0, w0 = tensor.shape[2:]
if h0==h and w0==w:
return tensor
assert h0%h==0 and w0%w==0
sh, sw = h0//h, w0//w
out = nn.functional.avg_pool2d(tensor, kernel_size=(sh,sw), stride=(sh,sw))
retur... | code_fim | hard | {
"lang": "python",
"repo": "yilmazdoga/lifting-2d-stylegan-for-3d-aware-face-generation",
"path": "/models/perc_loss.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yilmazdoga/lifting-2d-stylegan-for-3d-aware-face-generation path: /models/perc_loss.py
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
EPS = 1e-7
class PerceptualLoss(nn.Module):
def __init__(self, requires_grad=False, loss_type='l2', n_scale=1, slice_in... | code_fim | hard | {
"lang": "python",
"repo": "yilmazdoga/lifting-2d-stylegan-for-3d-aware-face-generation",
"path": "/models/perc_loss.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DigitalGlobe/gbdxtools path: /gbdxtools/images/landsat_image.py
from gbdxtools.images.base import RDABaseImage
from gbdxtools.images.drivers import RDADaskImageDriver
from gbdxtools.images.util.image import reproject_params
from gbdxtools.rda.error import IncompatibleOptions
from gbdxtools.rda.in... | code_fim | hard | {
"lang": "python",
"repo": "DigitalGlobe/gbdxtools",
"path": "/gbdxtools/images/landsat_image.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self.options["band_type"]
@property
def _rgb_bands(self):
return [3,2,1]
@property
def _ndvi_bands(self):
return [4,3]
@property
def _ndwi_bands(self):
return[2,4]
@classmethod
def _build_graph(cls, _id, band_type="MS", proj=None, ... | code_fim | hard | {
"lang": "python",
"repo": "DigitalGlobe/gbdxtools",
"path": "/gbdxtools/images/landsat_image.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: easyopsapis/easyops-api-python path: /webshell_sdk/api/task/task_client.py
# -*- coding: utf-8 -*-
import os
import sys
import webshell_sdk.api.task.create_sync_task_pb2
import webshell_sdk.utils.http_util
import google.protobuf.json_format
class TaskClient(object):
def __init__(self, se... | code_fim | hard | {
"lang": "python",
"repo": "easyopsapis/easyops-api-python",
"path": "/webshell_sdk/api/task/task_client.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> rsp_obj = webshell_sdk.utils.http_util.do_api_request(
method="POST",
src_name="logic.webshell_sdk",
dst_name=route_name,
server_ip=server_ip,
server_port=self._server_port,
host=self._host,
uri=uri,
pa... | code_fim | hard | {
"lang": "python",
"repo": "easyopsapis/easyops-api-python",
"path": "/webshell_sdk/api/task/task_client.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ray-project/ray path: /doc/source/serve/doc_code/fault_tolerance/sleepy_pid.py
# flake8: noqa
# __start__
# File name: sleepy_pid.py
from ray import serve
<|fim_suffix|> return os.getpid()
app = SleepyPid.bind()
# __end__<|fim_middle|>
@serve.deployment
class SleepyPid:
def __init... | code_fim | medium | {
"lang": "python",
"repo": "ray-project/ray",
"path": "/doc/source/serve/doc_code/fault_tolerance/sleepy_pid.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> import os
return os.getpid()
app = SleepyPid.bind()
# __end__<|fim_prefix|># repo: ray-project/ray path: /doc/source/serve/doc_code/fault_tolerance/sleepy_pid.py
# flake8: noqa
# __start__
# File name: sleepy_pid.py
from ray import serve
<|fim_middle|>@serve.deployment
class Sleepy... | code_fim | medium | {
"lang": "python",
"repo": "ray-project/ray",
"path": "/doc/source/serve/doc_code/fault_tolerance/sleepy_pid.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Aidan-Bharath/code_and_stuffs path: /vert_shear.py
from __future__ import division
import numpy as np
import matplotlib
import netCDF4 as net
from datetime import datetime
from datetime import timedelta
import matplotlib.pyplot as plt
import matplotlib.tri as Tri
import matplotlib.ticker as ticke... | code_fim | hard | {
"lang": "python",
"repo": "Aidan-Bharath/code_and_stuffs",
"path": "/vert_shear.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> matplotlib.rcParams['contour.negative_linestyle'] = 'solid'
for i in range(vel.shape[0]):
grid = Tri.Triangulation(lon,lat,triangles=nv)
fig = plt.figure()
plt.rc('font',size='22')
ax = fig.add_subplot(111,aspect=(1.0/np.cos(np.mean(lat)*np.pi/180.0)))
CS =... | code_fim | hard | {
"lang": "python",
"repo": "Aidan-Bharath/code_and_stuffs",
"path": "/vert_shear.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: parttimehacker/sensor-testbed path: /testbed.py
#!/usr/bin/python3
""" testbed for temperature, humidity, pressure and gas sensors """
# MIT License
#
# Copyright (c) 2019 Dave Wilson
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associat... | code_fim | hard | {
"lang": "python",
"repo": "parttimehacker/sensor-testbed",
"path": "/testbed.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>try:
HUMIDITY_SI7021_FEED = AIO.feeds("testsi7021humidity")
except RequestError: # Doesn't exist, create a new feed
FEED = Feed(name="testsi7021humidity")
HUMIDITY_SI7021_FEED = AIO.create_feed(FEED)
try:
TEMPERATURE_DHT22_FEED = AIO.feeds("testdht22temperature")
except RequestError: # Do... | code_fim | hard | {
"lang": "python",
"repo": "parttimehacker/sensor-testbed",
"path": "/testbed.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>"""
# config.py
import os
from pathlib import Path # pathlib is seriously awesome!
from inspect import currentframe, getframeinfo
fname = getframeinfo(currentframe()).filename # current file name
data_dir = Path(fname).resolve().parent.parent.parent / 'data' / 'raw'
data_files = os.listdir(data_dir)... | code_fim | medium | {
"lang": "python",
"repo": "jmsung/anaphase_promoting_complex",
"path": "/apc/apc/.ipynb_checkpoints/config-checkpoint.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jmsung/anaphase_promoting_complex path: /apc/apc/.ipynb_checkpoints/config-checkpoint.py
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 13 11:30:05 2019
<|fim_suffix|>import os
from pathlib import Path # pathlib is seriously awesome!
from inspect import currentframe, getframeinfo
fname = getf... | code_fim | medium | {
"lang": "python",
"repo": "jmsung/anaphase_promoting_complex",
"path": "/apc/apc/.ipynb_checkpoints/config-checkpoint.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rwchakra/apotoma path: /outlier_exposure_temp_folder/generate_adv.py
import numpy as np
import tensorflow as tf
from tensorflow.keras.models import load_model
import foolbox
badge_size = 500
model = load_model('./model/model_outexp_cifar.h5')
root = '/Users/rwiddhichakraborty/PycharmProjects/The... | code_fim | hard | {
"lang": "python",
"repo": "rwchakra/apotoma",
"path": "/outlier_exposure_temp_folder/generate_adv.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>advs = np.concatenate(adv).reshape((-1, 32, 32, 3))
# np.save(root+'/cifar10_base_model_adv.npy', advs)
# np.save(root+'/cifar10_base_model_adv_labels.npy', adv_labels)<|fim_prefix|># repo: rwchakra/apotoma path: /outlier_exposure_temp_folder/generate_adv.py
import numpy as np
import tensorflow as tf
fro... | code_fim | hard | {
"lang": "python",
"repo": "rwchakra/apotoma",
"path": "/outlier_exposure_temp_folder/generate_adv.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ssanderson/pstats-view path: /pstatsviewer/viewer.py
"""
A viewer for Stats objects.
"""
import os
from IPython.display import display
from ipywidgets import interactive, IntSlider
import matplotlib.pyplot as plt
import pandas as pd
from pstats import Stats
from qgrid.grid import show_grid
from ... | code_fim | hard | {
"lang": "python",
"repo": "ssanderson/pstats-view",
"path": "/pstatsviewer/viewer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _interact(count, sort_by):
data = self._get_timing_data(count, sort_by, fields)
self._show_timing_data(
data.ix[::-1, sort_by],
sort_by,
**mpl_kwargs
)
return interactive(
_interact,
... | code_fim | hard | {
"lang": "python",
"repo": "ssanderson/pstats-view",
"path": "/pstatsviewer/viewer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def compare_table(self, other, lsuffix='_l', rsuffix='_r'):
left = self.timings[self.default_view_fields]
right = other.timings[self.default_view_fields]
return self._show_table(
left.join(
right,
lsuffix=lsuffix,
rs... | code_fim | hard | {
"lang": "python",
"repo": "ssanderson/pstats-view",
"path": "/pstatsviewer/viewer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OpposedOak/mypyladies_sqlite path: /data_sources.py
"""Links to data sources on chmi pages"""
average_temperature_prefix = "https://www.chmi.cz/files/portal/docs/meteo/ok/denni_data/T-AVG/"
source_files = {
"Jihocesky": [
"C2BYNO01_T_N.csv.zip",
... | code_fim | hard | {
"lang": "python",
"repo": "OpposedOak/mypyladies_sqlite",
"path": "/data_sources.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ],
"Ustecky":[
"U1SNEZ01_T_N.csv.zip",
"U2VARN01_T_N.csv.zip",
],
}<|fim_prefix|># repo: OpposedOak/mypyladies_sqlite path: /data_sources.py
"""Links to data sources on chmi pages""... | code_fim | hard | {
"lang": "python",
"repo": "OpposedOak/mypyladies_sqlite",
"path": "/data_sources.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> elif n not in lista:
lista.append(n)
print('Adicionado.')
r = input('Continuar? [S/N] ')
if r.lower() == 'n':
print(lista)
break<|fim_prefix|># repo: beatrizflorenccio/Studies-Python path: /Exercicios/listas_num.py
#MaBe
lista = []
while Tru... | code_fim | medium | {
"lang": "python",
"repo": "beatrizflorenccio/Studies-Python",
"path": "/Exercicios/listas_num.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: beatrizflorenccio/Studies-Python path: /Exercicios/listas_num.py
#MaBe
lista = []
while True:
n = int(input('Digite um valor: '))
<|fim_suffix|> elif n not in lista:
lista.append(n)
print('Adicionado.')
r = input('Continuar? [S/N] ')
if r.lower() == 'n'... | code_fim | medium | {
"lang": "python",
"repo": "beatrizflorenccio/Studies-Python",
"path": "/Exercicios/listas_num.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> nums2[j]])
if j + 1 < n: heapq.heappush(heap, (nums1[i] + nums2[j + 1], i, j + 1))
return res<|fim_prefix|># repo: jxhangithub/leetcode path: /solutions/python3/373.py
class Solution:
def kSmallestPairs(self, nums1, nums2, k):
if not nums1 or not nums2: return []
... | code_fim | hard | {
"lang": "python",
"repo": "jxhangithub/leetcode",
"path": "/solutions/python3/373.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jxhangithub/leetcode path: /solutions/python3/373.py
class Solution:
def kSmallestPairs(self, nums1, nums2, k):
if not nums1 or not nums2: return []
n, res, cnt, heap = len(nums2), [], 0, [(nums1[i] + nums2[0], i, 0) for i in range(len(nums1))]
while h<|fim_suffix|> nu... | code_fim | hard | {
"lang": "python",
"repo": "jxhangithub/leetcode",
"path": "/solutions/python3/373.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>while 1:
a = 1
break
print a
if 0:
# this is only an error if the code gets hit:
print not_defined<|fim_prefix|># repo: jmgc/pyston path: /test/tests/20.py
# Programs are well-defined even if they contain potentially-undefined variables
# The exceptions are well-defined too, but I don't ... | code_fim | medium | {
"lang": "python",
"repo": "jmgc/pyston",
"path": "/test/tests/20.py",
"mode": "spm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jmgc/pyston path: /test/tests/20.py
# Programs are well-defined even if they contain potentially-undefined variables
# The exceptions are well-defined too, but I don't support that yet
<|fim_suffix|>if 0:
# this is only an error if the code gets hit:
print not_defined<|fim_middle|>if 1:
... | code_fim | medium | {
"lang": "python",
"repo": "jmgc/pyston",
"path": "/test/tests/20.py",
"mode": "psm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> queryset = Persona.objects.all()
serializer_class = PersonaSerializer<|fim_prefix|># repo: jhonnyperalta/trivago-serve path: /core/views/persona_view.py
from ..models import Persona
from rest_framework import serializers, viewsets
from rest_framework import permissions
from django.db.models impor... | code_fim | medium | {
"lang": "python",
"repo": "jhonnyperalta/trivago-serve",
"path": "/core/views/persona_view.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jhonnyperalta/trivago-serve path: /core/views/persona_view.py
from ..models import Persona
from rest_framework import serializers, viewsets
from rest_framework import permissions
from django.db.models import Q
from operator import __or__ as OR
from functools import reduce
class PersonaSerializ... | code_fim | medium | {
"lang": "python",
"repo": "jhonnyperalta/trivago-serve",
"path": "/core/views/persona_view.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == '__main__':
s = Solution()
print s.maxScoreWords(["dog","cat","dad","good"], ["a","a","c","d","d","d","g","o","o"], [1,0,9,5,0,0,3,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0])
print s.maxScoreWords(["xxxz","ax","bx","cx"], ["z","a","b","c","x","x","x"], [4,4,4,0,0,0,0,0,0,0,0,0,0,0,... | code_fim | hard | {
"lang": "python",
"repo": "windard/leeeeee",
"path": "/maximum-score-words-formed-by-letters.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for key, value in data.items():
if l_data.get(key, 0) < value:
return False
return True
def count_score(self, total, score):
count = 0
for w in total:
for t in w:
count += score[ord(t) - ord('a')]
return c... | code_fim | hard | {
"lang": "python",
"repo": "windard/leeeeee",
"path": "/maximum-score-words-formed-by-letters.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: windard/leeeeee path: /maximum-score-words-formed-by-letters.py
# coding=utf-8
class Solution(object):
def maxScoreWords(self, words, letters, score):
"""
:type words: List[str]
:type letters: List[str]
:type score: List[int]
:rtype: int
"""
... | code_fim | hard | {
"lang": "python",
"repo": "windard/leeeeee",
"path": "/maximum-score-words-formed-by-letters.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if(model_manager.is_valid()):
num_steps = int(T/sampling_dt)
# Get the OD Matrix form Model Manager
# OD Matrix can also be initialized from another source, as long as it fits the OD_Matrix class format
OD_Matrix = model_manager.get_OD_Matrix(num_st... | code_fim | hard | {
"lang": "python",
"repo": "ugirumurera/TA_solver",
"path": "/python/Runner_OTM.py",
"mode": "spm",
"license": "BSD-3-Clause-LBNL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ugirumurera/TA_solver path: /python/Runner_OTM.py
from __future__ import division
import os
import inspect
from Model_Manager.OTM_Model_Manager import OTM_Model_Manager_class
from Java_Connection import Java_Connection
from Solvers.Solver_Class import Solver_class
import argparse
from Data_Types.... | code_fim | hard | {
"lang": "python",
"repo": "ugirumurera/TA_solver",
"path": "/python/Runner_OTM.py",
"mode": "psm",
"license": "BSD-3-Clause-LBNL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pezzdoge/BrightID-AntiSybil path: /anti_sybil/tests/24_hours_test.py
import xmltodict
import requests
import os
from anti_sybil import algorithms
from anti_sybil.utils import *
BACKUP_URL = 'http://storage.googleapis.com/brightid-backups/'
OUTPUT_FOLDER = './outputs/24_hours_test/'
def main():... | code_fim | hard | {
"lang": "python",
"repo": "pezzdoge/BrightID-AntiSybil",
"path": "/anti_sybil/tests/24_hours_test.py",
"mode": "psm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_suffix|> outputs.append(generate_output(
ranker.graph, 'SybilRank\n{}'.format(l[1])))
draw_graph(ranker.graph, os.path.join(
OUTPUT_FOLDER, 'graph{}.html'.format(i)))
write_output_file(outputs, os.path.join(
OUTPUT_FOLDER, 'result.csv'))
for n in scores_dic:... | code_fim | hard | {
"lang": "python",
"repo": "pezzdoge/BrightID-AntiSybil",
"path": "/anti_sybil/tests/24_hours_test.py",
"mode": "spm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_handle_sns_message():
responder = MagicMock()
responder.return_value = True
message_consumer = handle_sns_message(responder)
message_consumer({
"Records": [{
'Sns': {
'Message': "message"
}
}]
}, {})
responder.ass... | code_fim | hard | {
"lang": "python",
"repo": "joelstevenson/xavier",
"path": "/tests/test_aws_sns.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: joelstevenson/xavier path: /tests/test_aws_sns.py
import pytest
from unittest.mock import patch, MagicMock
from xavier.aws.sns import publish_sns_message, handle_sns_message
def test_publish_sns_event():
TEST_ARN = 'arn:abc'
TEST_MESSAGE = "message"
with patch('xavier.aws.sns.send... | code_fim | hard | {
"lang": "python",
"repo": "joelstevenson/xavier",
"path": "/tests/test_aws_sns.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> responder = MagicMock()
responder.return_value = True
message_consumer = handle_sns_message(responder)
message_consumer({
"Records": [{
'Sns': {
'Message': "message"
}
}]
}, {})
responder.assert_called_once_with("message")<... | code_fim | hard | {
"lang": "python",
"repo": "joelstevenson/xavier",
"path": "/tests/test_aws_sns.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Abhinavl3v3l/drishtypy_2 path: /data/does_augmentation.py
import albumentations as A
from torchvision import transforms
import numpy as np
from drishtypy.data.data_utils import find_stats
from albumentations.pytorch import ToTensor
import cv2
'''
# A.Resize(input_size,input_size),
# A.CoarseDropo... | code_fim | hard | {
"lang": "python",
"repo": "Abhinavl3v3l/drishtypy_2",
"path": "/data/does_augmentation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> train_transforms = AlbumCompose(train_albumentation_transform)
# Test Phase transformation
test_transforms = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(tuple(mean), tuple(stdev))
])
return train_transforms, test_transforms<|fim_prefix|># repo: Ab... | code_fim | hard | {
"lang": "python",
"repo": "Abhinavl3v3l/drishtypy_2",
"path": "/data/does_augmentation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def get_data_transform(path):
mean, stdev = find_stats(path)
input_size = 32
train_albumentation_transform = A.Compose([
# CoarseDropout(max_holes=3, max_height=8, max_width=8, min_holes=None, min_height=None, min_width=None,
# fill_value=[i * 255 for i in mea... | code_fim | medium | {
"lang": "python",
"repo": "Abhinavl3v3l/drishtypy_2",
"path": "/data/does_augmentation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mtshrmn/horrible-downloader path: /test/test_parser.py
import os
import sys
import pytest
from httmock import urlmatch, HTTMock
# from urllib.parse import parse_qs
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from HorribleDownloader import Parser
TEST_DIR_PAT... | code_fim | hard | {
"lang": "python",
"repo": "mtshrmn/horrible-downloader",
"path": "/test/test_parser.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for batch in batches:
assert batch["title"] == title
has_magnet = []
for resolution in "480", "720", "1080":
assert resolution in batch
has_magnet.append("Magnet" in batch[resolution])
assert has_magnet == sorted(has_magnet, reverse=True)
... | code_fim | hard | {
"lang": "python",
"repo": "mtshrmn/horrible-downloader",
"path": "/test/test_parser.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for code in self.code_blocks:
try:
yield self.execute_code(code, event=event_dict)
except Exception as e:
self.log.exception('Code execution error: %s', e)
for job in self.jobs:
... | code_fim | hard | {
"lang": "python",
"repo": "daniel-covelli/jaffle",
"path": "/jaffle/app/watchdog/handler.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: daniel-covelli/jaffle path: /jaffle/app/watchdog/handler.py
# -*- coding: utf-8 -*-
from pathlib import Path
from tornado import gen
from watchdog.events import PatternMatchingEventHandler
def _event_to_dict(event):
"""
Converts an Watchdog filesystem event to a dict.
Parameters
... | code_fim | hard | {
"lang": "python",
"repo": "daniel-covelli/jaffle",
"path": "/jaffle/app/watchdog/handler.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self._timeout = None
self._in_throttle = False
def on_any_event(self, event):
"""
Event handler for Watchdog filesystem events.
Executes the handling in the main ioloop.
Parameters
----------
event : watchdog.events.FileSystemEvent
... | code_fim | hard | {
"lang": "python",
"repo": "daniel-covelli/jaffle",
"path": "/jaffle/app/watchdog/handler.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Do not save self.replay_buffer since it's a duplicate and seems to
# cause joblib recursion issues.
return dict(
train_replay_buffer=self.train_replay_buffer,
validation_replay_buffer=self.validation_replay_buffer,
fraction_paths_in_train=self.... | code_fim | hard | {
"lang": "python",
"repo": "google-research/DBAP-algorithm",
"path": "/third_party/rlkit_library/rlkit/data_management/split_buffer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def terminate_episode(self, *args, **kwargs):
self.replay_buffer.terminate_episode(*args, **kwargs)
self._randomly_set_replay_buffer()
def _randomly_set_replay_buffer(self):
if random.random() <= self.fraction_paths_in_train:
self.replay_buffer = self.train_rep... | code_fim | hard | {
"lang": "python",
"repo": "google-research/DBAP-algorithm",
"path": "/third_party/rlkit_library/rlkit/data_management/split_buffer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: google-research/DBAP-algorithm path: /third_party/rlkit_library/rlkit/data_management/split_buffer.py
# Copyright 2021 Google LLC
#
# 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 L... | code_fim | hard | {
"lang": "python",
"repo": "google-research/DBAP-algorithm",
"path": "/third_party/rlkit_library/rlkit/data_management/split_buffer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def rotated_array_search_recursive(input_list, number, begin_index, end_index):
current_index = (begin_index + end_index) // 2
begin = input_list[begin_index]
mid = input_list[current_index]
end = input_list[end_index]
if mid > begin and mid > end:
# left is sorted and right... | code_fim | hard | {
"lang": "python",
"repo": "qiyangjie/Udacity-Data-Structures-Algorithm-Projects",
"path": "/project3/rotated_array_search.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_function(test_case):
input_list = test_case[0]
number = test_case[1]
if linear_search(input_list, number) == rotated_array_search(input_list, number):
print("Pass")
else:
print("Fail")
if __name__ == '__main__':
test_function([[6, 7, 8, 9, 10, 1, 2, 3, 4], 6... | code_fim | hard | {
"lang": "python",
"repo": "qiyangjie/Udacity-Data-Structures-Algorithm-Projects",
"path": "/project3/rotated_array_search.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: qiyangjie/Udacity-Data-Structures-Algorithm-Projects path: /project3/rotated_array_search.py
def ordered_array_search_recursive(input_list, number, begin_index, end_index):
if input_list[begin_index] == number:
return begin_index
if end_index - begin_index <= 0:
return -... | code_fim | hard | {
"lang": "python",
"repo": "qiyangjie/Udacity-Data-Structures-Algorithm-Projects",
"path": "/project3/rotated_array_search.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for buffer, transition in zip(self.buffers, transition_list):
buffer.extend([transition])
def build_controller(self):
return A2CController(self.envs.observation_space.shape[0],
self.envs.action_space.n,
**self._controller_args,
... | code_fim | hard | {
"lang": "python",
"repo": "abilashananthula/torchrl",
"path": "/examples/a2c.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: abilashananthula/torchrl path: /examples/a2c.py
from kondo import Spec
import torch
from torchrl.experiments import BaseExperiment
from torchrl.utils.storage import TransitionTupleDataset
from torchrl.contrib.controllers import A2CController
class A2CExperiment(BaseExperiment):
def __init__(s... | code_fim | hard | {
"lang": "python",
"repo": "abilashananthula/torchrl",
"path": "/examples/a2c.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> buffer.truncate()
all_transitions = [torch.cat(t, dim=0) for t in all_transitions]
all_returns = torch.cat(all_returns, dim=0)
return self.controller.learn(*all_transitions, all_returns)
@staticmethod
def spec_list():
return [
Spec(
group='a2c',
... | code_fim | hard | {
"lang": "python",
"repo": "abilashananthula/torchrl",
"path": "/examples/a2c.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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