text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> loss = entropy_loss(theta, X, Y);
x, y = idx2pos(theta, d);
origin_val = theta[x][y];
diff = get_d1_loss(theta, d, X, Y);
d2loss = get_d2_loss(theta, d, X, Y);
if abs(d2loss) > 0.0:
theta[x][y] -= diff / d2loss;
new_loss = entropy_loss(theta, X, Y);
return abs(new_l... | code_fim | hard | {
"lang": "python",
"repo": "AshuAkshi0708/Data-Science-Projects",
"path": "/Wine Dataset - Coordinate Descent/src/softmax.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: XiaoqingWang/deepcake path: /cake.py
import datetime
import json
import os,sys
import numpy as np
import tensorflow as tf
from reader import *
from config import *
from logger import *
from models import *
logger = init_log(debug = True)
def model(inputs):
if FLAGS.model == "wide":
return... | code_fim | hard | {
"lang": "python",
"repo": "XiaoqingWang/deepcake",
"path": "/cake.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># metric here
tf.get_variable_scope().reuse_variables()
accuracy_logits = model(validate_batch_features)
validate_softmax = tf.nn.softmax(accuracy_logits)
validate_batch_labels = tf.to_int64(validate_batch_labels)
correct_prediction = tf.equal(tf.argmax(validate_softmax, 1), validate_batch_labels)
accurac... | code_fim | hard | {
"lang": "python",
"repo": "XiaoqingWang/deepcake",
"path": "/cake.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>with tf.device("/cpu:0"): # better than gpu
global_step = tf.Variable(0, name='global_step', trainable=False)
train_op = optimizer.minimize(loss, global_step=global_step)
# metric here
tf.get_variable_scope().reuse_variables()
accuracy_logits = model(validate_batch_features)
validate_softmax = tf.nn.... | code_fim | hard | {
"lang": "python",
"repo": "XiaoqingWang/deepcake",
"path": "/cake.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> fig.tight_layout()
fig.savefig(os.path.join(CONFIG['IO_OPTION']['OUTPUT_ROOT'], 'roc_curve.png'), dpi=100)
def plot_fig(test_img, scores, save_dir, class_name, wav_names):
num = len(scores)
vmax = scores.max()
vmin = scores.min()
for i in tqdm(range(num), '| plot heatmap | test | ... | code_fim | hard | {
"lang": "python",
"repo": "HirokiNarita/dcase2021_task2",
"path": "/src/model_codes/PaDiM/ex8/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if mean_img_roc_auc < max_img_roc_auc:
img_scores = max_img_scores
fpr, tpr = max_fpr, max_tpr
img_roc_auc = max_img_roc_auc
else:
img_scores = mean_img_scores
fpr, tpr = mean_fpr, mean_tpr
img_roc_auc = mean_img_roc_a... | code_fim | hard | {
"lang": "python",
"repo": "HirokiNarita/dcase2021_task2",
"path": "/src/model_codes/PaDiM/ex8/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HirokiNarita/dcase2021_task2 path: /src/model_codes/PaDiM/ex8/main.py
a import DataLoader
from torchvision.models import wide_resnet50_2, resnet18
from models import ResNet38, Cnn14_16k
import datasets.mvtec as mvtec
import DCASE2021_task2
from DCASE_util import DCASE2021_Task2_Score_Calculator
... | code_fim | hard | {
"lang": "python",
"repo": "HirokiNarita/dcase2021_task2",
"path": "/src/model_codes/PaDiM/ex8/main.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def scan_victims(pkg):
print('Scaning for victims: %s' % (pkg.handler.info()['name']))
vdb = LocalDatabase()
for child in pkg.info:
if child['type'] == '.jar':
matches = vdb.match_archive(child['sha512'])
if len(matches) > 0:
cve_str = ','.join(matches)
filename = join(child['path'], ch... | code_fim | hard | {
"lang": "python",
"repo": "abn/jsnoop",
"path": "/examples/process.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: abn/jsnoop path: /examples/process.py
#! /usr/bin/env python3
import sys
from os.path import basename, join, isfile, isdir
from os import listdir
from jsnoop.package import Package
from jsnoop.plugins.victims import LocalDatabase
from optparse import OptionParser
from multiprocessing import Pool... | code_fim | medium | {
"lang": "python",
"repo": "abn/jsnoop",
"path": "/examples/process.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> time_steps: int = 8 # :math:`T`
depth: int = 2
recurrent_hidden_channels: int = 64
num_cascades: int = 8
no_parameter_sharing: bool = True<|fim_prefix|># repo: NKI-AI/direct path: /direct/nn/cirim/config.py
# coding=utf-8
# Copyright (c) DIRECT Contributors
from dataclasses import d... | code_fim | medium | {
"lang": "python",
"repo": "NKI-AI/direct",
"path": "/direct/nn/cirim/config.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NKI-AI/direct path: /direct/nn/cirim/config.py
# coding=utf-8
# Copyright (c) DIRECT Contributors
from dataclasses import dataclass
from direct.config.defaults import ModelConfig
<|fim_suffix|> time_steps: int = 8 # :math:`T`
depth: int = 2
recurrent_hidden_channels: int = 64
... | code_fim | easy | {
"lang": "python",
"repo": "NKI-AI/direct",
"path": "/direct/nn/cirim/config.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: YooInKeun/CAU_CSE_Capstone_3 path: /BeautyForMe/myvenv/Lib/site-packages/win32com/test/daodump.py
# import dao3032
# No longer imported here - callers responsibility to load
#
import win32com.client
def DumpDB(db, bDeep = 1):
# MUST be a DB object.
DumpTables(db,bDeep)
DumpRelations(... | code_fim | hard | {
"lang": "python",
"repo": "YooInKeun/CAU_CSE_Capstone_3",
"path": "/BeautyForMe/myvenv/Lib/site-packages/win32com/test/daodump.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for progid in ("DAO.DBEngine.36", "DAO.DBEngine.35", "DAO.DBEngine.30"):
try:
ob = win32com.client.gencache.EnsureDispatch(progid)
except pythoncom.com_error:
print(progid, "does not seem to be installed")
else:
TestEngine(ob)
bre... | code_fim | hard | {
"lang": "python",
"repo": "YooInKeun/CAU_CSE_Capstone_3",
"path": "/BeautyForMe/myvenv/Lib/site-packages/win32com/test/daodump.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from .stores import dl_async, export, MediaData
from .generators import dwca
from .generators import api<|fim_prefix|># repo: plantnet/gbif-dl path: /gbif_dl/__init__.py
"""
__gbif-dl__ provides easy access to media data from the GBIF database to be used for training machine learning models.
It wraps the... | code_fim | medium | {
"lang": "python",
"repo": "plantnet/gbif-dl",
"path": "/gbif_dl/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: plantnet/gbif-dl path: /gbif_dl/__init__.py
"""
__gbif-dl__ provides easy access to media data from the GBIF database to be used for training machine learning models.
It wraps the GBIF API and supports directly querying the api to obtain and download a list of urls.
Existing queries can also be o... | code_fim | medium | {
"lang": "python",
"repo": "plantnet/gbif-dl",
"path": "/gbif_dl/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SandraCoburn/graphs_guided path: /word_ladders2.py
class Queue():
def __init__(self):
self.queue = []
def enqueue(self, value):
self.queue.append(value)
def dequeue(self):
if self.size() > 0:
return self.queue.pop(0)
else:
return... | code_fim | hard | {
"lang": "python",
"repo": "SandraCoburn/graphs_guided",
"path": "/word_ladders2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> q = Queue()
visited = set()
q.enqueue([start_word])
while q.size() > 0:
current_path = q.dequeue()
current_word = current_path[-1]
if current_word == end_word:
return current_path
if current_word not in visited:
visited.add... | code_fim | hard | {
"lang": "python",
"repo": "SandraCoburn/graphs_guided",
"path": "/word_ladders2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if current_word not in visited:
visited.add(current_word)
neighbors = get_neighbors(current_word)
for neighbor in neighbors:
new_path = current_path + [neighbor]
q.enqueue(new_path)<|fim_prefix|># repo: SandraCoburn/graphs_guided... | code_fim | hard | {
"lang": "python",
"repo": "SandraCoburn/graphs_guided",
"path": "/word_ladders2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> post.self_print(contraversial=True, hide=['all_comments','selftext_html','punchline_ext'])
#self.network.show_graph()
#print(post)
return f'returning from {self}'
def create_network_edge(self, start, end, type):#, network):
if str(type) == "<class '... | code_fim | hard | {
"lang": "python",
"repo": "jaquielajoie/Reddit-NLP",
"path": "/Social_Scraper/Web_Server/Reddit/PostReader.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jaquielajoie/Reddit-NLP path: /Social_Scraper/Web_Server/Reddit/PostReader.py
import praw
from praw.models import MoreComments
import pprint
from datetime import datetime
import re
import string
import sqlite3
import nltk
from nltk.tokenize import sent_tokenize, word_tokenize
from nltk.chunk impo... | code_fim | hard | {
"lang": "python",
"repo": "jaquielajoie/Reddit-NLP",
"path": "/Social_Scraper/Web_Server/Reddit/PostReader.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #print(i, comm.author, comm.body)
#com = Comment()
#self.create_network_edge(start=ru,end=redd_comm,type=type(redd_comm), network_name=comm.submission.id)
post.self_print(contraversial=True, hide=['all_comments','selftext_html','punchlin... | code_fim | hard | {
"lang": "python",
"repo": "jaquielajoie/Reddit-NLP",
"path": "/Social_Scraper/Web_Server/Reddit/PostReader.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> index = 0
# preprocess
img = np.asarray(img, dtype=np.uint8)
prob = prob.squeeze()
key = key.squeeze()
color = [(15, 15, 240), (15, 240, 155), (240, 155, 15), (240, 15, 155), (240, 15, 240)]
for c, p in enumerate(prob):
if p > 0.5:
img = cv2.circle(img, (i... | code_fim | medium | {
"lang": "python",
"repo": "MahmudulAlam/Unified-Gesture-and-Fingertip-Detection",
"path": "/visualize.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MahmudulAlam/Unified-Gesture-and-Fingertip-Detection path: /visualize.py
import cv2
import numpy as np
from preprocess.data_generator import label_generator
def visualize(img, prob, key):
index = 0
<|fim_suffix|>
if __name__ == '__main__':
image, probability, keypoints = label_generato... | code_fim | hard | {
"lang": "python",
"repo": "MahmudulAlam/Unified-Gesture-and-Fingertip-Detection",
"path": "/visualize.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.cursor.execute("SELECT typeName FROM invtypes WHERE typeID = %s; " % type_id)
type_name = ''
for row in self.cursor:
type_name = row[0]
return type_name
def type_id_has_group_id(self, type_id):
self.cursor.execute("SELECT marketGroupID FROM inv... | code_fim | hard | {
"lang": "python",
"repo": "Marclass/EveCommon",
"path": "/EveCommon/SDEConnector.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.cursor.close()
self.connection.close()
def get_type_id_by_type_name(self, type_name):
self.cursor.execute("SELECT typeID FROM invtypes WHERE typeName = %s; " % type_name)
type_id = 0
for row in self.cursor:
type_id = row[0]
return type_... | code_fim | hard | {
"lang": "python",
"repo": "Marclass/EveCommon",
"path": "/EveCommon/SDEConnector.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Marclass/EveCommon path: /EveCommon/SDEConnector.py
import sqlite3
class SDEConnector(object):
def __init__(self, db_name='', host='127.0.0.1', port=3306, user='root', passwd=''):
self.db_name = db_name
self.host = host
self.port = port
self.user = user
... | code_fim | medium | {
"lang": "python",
"repo": "Marclass/EveCommon",
"path": "/EveCommon/SDEConnector.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ThoughtWorksInc/CD4ML-Scenarios path: /test/test_acceptance_arg_parsing.py
import datetime
import os
from pathlib import Path
from cd4ml.filenames import get_model_files
from scripts import acceptance as acceptance_script
def test_acceptance_with_model_id():
model_id = acceptance_script.pa... | code_fim | medium | {
"lang": "python",
"repo": "ThoughtWorksInc/CD4ML-Scenarios",
"path": "/test/test_acceptance_arg_parsing.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>earlier_time = int(datetime.datetime(2020, 8, 29, 12, 0, 0).timestamp())
later_time = int(datetime.datetime(2020, 8, 29, 14, 0, 0).timestamp())
def test_acceptance_with_no_arguments(tmp_path):
os.environ["CD4ML_DATA_DIR"] = str(tmp_path)
files = get_model_files('', base_data_dir=tmp_path)
b... | code_fim | medium | {
"lang": "python",
"repo": "ThoughtWorksInc/CD4ML-Scenarios",
"path": "/test/test_acceptance_arg_parsing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_acceptance_with_no_arguments(tmp_path):
os.environ["CD4ML_DATA_DIR"] = str(tmp_path)
files = get_model_files('', base_data_dir=tmp_path)
base_results_directory = files['results_folder']
earlier_folder = Path(base_results_directory, "earlier")
earlier_folder.mkdir(parents=True... | code_fim | hard | {
"lang": "python",
"repo": "ThoughtWorksInc/CD4ML-Scenarios",
"path": "/test/test_acceptance_arg_parsing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rxedu/tensorflow-tutorials path: /tensorflow_tutorials/mnist/test/mnist_test.py
# pylint: disable=import-error
# pylint: disable=missing-docstring
# pylint: disable=redefined-outer-name
import pytest
<|fim_suffix|>def test_distribution():
assert MNIST().distribution is not None
def test_en... | code_fim | hard | {
"lang": "python",
"repo": "rxedu/tensorflow-tutorials",
"path": "/tensorflow_tutorials/mnist/test/mnist_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> mnist = MNIST()
session = mnist.train(mnist_data.train)
accuracy = mnist.check_accuracy(mnist_data.test, session)
assert accuracy >= 0.91
assert accuracy <= 0.93
session.close()<|fim_prefix|># repo: rxedu/tensorflow-tutorials path: /tensorflow_tutorials/mnist/test/mnist_test.py
# ... | code_fim | hard | {
"lang": "python",
"repo": "rxedu/tensorflow-tutorials",
"path": "/tensorflow_tutorials/mnist/test/mnist_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> import numpy as np
# Circulant embedding
circ = np.zeros((2 * L, 2 * M, 2 * N, 3), dtype=np.complex128)
for i in range(0, 3):
circ[0:L, 0:M, 0:N, i] = toep[:, :, :, i]
circ[0:L, 0:M, N+1:2*N, i] = toep[0:L, 0:M, -1:0:-1, i]
circ[0:L, M+1:2*M, 0:N, i] = toep[0:L, -1... | code_fim | hard | {
"lang": "python",
"repo": "JBannister96/vines",
"path": "/vines/precondition/threeD.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JBannister96/vines path: /vines/precondition/threeD.py
def gperiodic_coeff_nop(cube):
import numpy as np
if cube in 'L':
Gp = np.array((+1.0, -1.0, -1.0, +1.0, +1.0, +1.0))
elif cube in 'M':
Gp = np.array((+1.0, -1.0, +1.0, +1.0, -1.0, +1.0))
elif cube in 'N':
... | code_fim | hard | {
"lang": "python",
"repo": "JBannister96/vines",
"path": "/vines/precondition/threeD.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
WBH15RMK_24 = [##this section is being decoded correctly
('RRC-TAPE-RECORD-ID',0,2,'pic_any'),
('WB-H15-REMARK-KEY',2,3,'pic_numeric'),
('WB-H15-REMARK-TEXT',5,70,'pic_any')
]##inherits API from 01 and h15 key from 23. Might work well as json
WBSB126_25 = ... | code_fim | hard | {
"lang": "python",
"repo": "skylerbast/TXRRC_data_harvest",
"path": "/dbf900_layouts.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: skylerbast/TXRRC_data_harvest path: /dbf900_layouts.py
LL-BORE-PLUGGED',10,8,'pic_yyyymmdd'), ##YYYYMMDD
('WB-PLUG-TOTAL-DEPTH',18,5,'pic_numeric'),
('WB-PLUG-CEMENT-COMP',23,32,'pic_any'),
('WB-PLUG-MUD-FILLED',55,1,'pic_any'),
('WB-PLUG-MUD-APPLIE... | code_fim | hard | {
"lang": "python",
"repo": "skylerbast/TXRRC_data_harvest",
"path": "/dbf900_layouts.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: skylerbast/TXRRC_data_harvest path: /dbf900_layouts.py
('WB-WELL-LOC-NEAREST-TOWN',96,13,'pic_any'),
('WB-DIST-FROM-SURVEY-LINES',137,28,'pic_any'),
('WB-DIST-DIRECT-NEAR-WELL',165,28,'pic_any')
]##should inherit API10, many wells do not have this section
WBNE... | code_fim | hard | {
"lang": "python",
"repo": "skylerbast/TXRRC_data_harvest",
"path": "/dbf900_layouts.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>def s3_sync(s3_bucket, s3_prefix, sync_path="."):
"""
Syncs a given path to an s3 prefix
Args:
s3_bucket (str): bucket name
s3_prefix (str): s3 prefix to sync to
sync_path (str, Path): path to sync to bucket:prefix
Returns:
(None)
"""
# Get bucket... | code_fim | hard | {
"lang": "python",
"repo": "apalizha/CAMD",
"path": "/camd/utils/data.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: apalizha/CAMD path: /camd/utils/data.py
# Copyright (c) 2019 Toyota Research Institute. All rights reserved.
"""
This module consolidates s3-based dataset loading
for CAMD, mostly in the form of dataframes
"""
import os
import boto3
import botocore
import requests
import pandas as pd
import n... | code_fim | hard | {
"lang": "python",
"repo": "apalizha/CAMD",
"path": "/camd/utils/data.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert last_eoe_idx is None or last_eoes[last_eoe_idx], f"last_eoe_idx:{last_eoe_idx}"
if last_eoe_idx is not None:
replace_hist_before_eoe(hist=new_act_buf, eoe_idx_in_hist=last_eoe_idx - self.start_acts_offset - 1)
replace_hist_before_eoe(hist=last_act_buf, eoe_i... | code_fim | hard | {
"lang": "python",
"repo": "trackmania-rl/tmrl",
"path": "/tmrl/custom/custom_memories.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: trackmania-rl/tmrl path: /tmrl/custom/custom_memories.py
input to the append() method of the memory
the user must define both this function and the append() method of the memory
CAUTION: prev_act is the action that comes BEFORE obs (i.e. prev_obs, prev_act(prev_obs), obs(prev_act))
""... | code_fim | hard | {
"lang": "python",
"repo": "trackmania-rl/tmrl",
"path": "/tmrl/custom/custom_memories.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: trackmania-rl/tmrl path: /tmrl/custom/custom_memories.py
==============
def last_true_in_list(li):
for i in reversed(range(len(li))):
if li[i]:
return i
return None
def replace_hist_before_eoe(hist, eoe_idx_in_hist):
"""
Pads the history hist before the End... | code_fim | hard | {
"lang": "python",
"repo": "trackmania-rl/tmrl",
"path": "/tmrl/custom/custom_memories.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.name = name
super(ShapeSystVar, self).__init__(name, pretty_name=pretty_name, on=on)
class ForHist(SystVar.ForHist):
def __init__(self, hist, systVar):
super(ShapeSystVar.ForHist, self).__init__(hist, systVar)
self.histUp = self._findVarHist("up")
... | code_fim | hard | {
"lang": "python",
"repo": "pieterdavid/mplbplot",
"path": "/cms_stacks/systematics.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pieterdavid/mplbplot path: /cms_stacks/systematics.py
"""
Systematics classes (based on plotIt)
"""
__all__ = ("HistoKey", "SystVarsForHist",
"SystVar", "ParameterizedSystVar", "ConstantSystVar", "LogNormalSystVar", "ShapeSystVar"
)
import itertools
import histo_utils as h1u... | code_fim | hard | {
"lang": "python",
"repo": "pieterdavid/mplbplot",
"path": "/cms_stacks/systematics.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> super(ParameterizedSystVar, self).__init__(name, pretty_name=pretty_name, on=on)
def nom(self, hist, i):
pass
def up(self, hist, i):
pass
def down(self, hist, i):
pass
class ForHist(SystVar.ForHist):
""" delegate everything to the corresponding syst... | code_fim | hard | {
"lang": "python",
"repo": "pieterdavid/mplbplot",
"path": "/cms_stacks/systematics.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.basic = ['homicide']<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_homicides.py
#calss header
class _HOMICIDES():
def __init__(self,):
self.name = "HOMICIDES"
self.definitions = homicide
<|fim_middle|> self.parents = []
self.childen = []
self.properties = []... | code_fim | medium | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/otherforms/_homicides.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_homicides.py
#calss header
class _HOMICIDES():
<|fim_suffix|>
self.basic = ['homicide']<|fim_middle|> def __init__(self,):
self.name = "HOMICIDES"
self.definitions = homicide
self.parents = []
self.childen = []
self.properties = [... | code_fim | medium | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/otherforms/_homicides.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return (f.LocalPath().endswith(('html'))
and (os.path.join('resources', '') not in f.LocalPath()))
for f in input_api.AffectedFiles(include_deletes=False,
file_filter=file_filter):
if not _CheckFileTimeoutMetaTags(f):
re... | code_fim | hard | {
"lang": "python",
"repo": "chromium/chromium",
"path": "/third_party/blink/web_tests/wpt_internal/prerender/PRESUBMIT.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chromium/chromium path: /third_party/blink/web_tests/wpt_internal/prerender/PRESUBMIT.py
# Copyright 2021 The Chromium Authors
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Chromium presubmit script for prerender in Web Platform Tests.
<... | code_fim | medium | {
"lang": "python",
"repo": "chromium/chromium",
"path": "/third_party/blink/web_tests/wpt_internal/prerender/PRESUBMIT.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> for f in input_api.AffectedFiles(include_deletes=False,
file_filter=file_filter):
if not _CheckFileTimeoutMetaTags(f):
results.append(
output_api.PresubmitError(
('Missing long timeout. '
... | code_fim | hard | {
"lang": "python",
"repo": "chromium/chromium",
"path": "/third_party/blink/web_tests/wpt_internal/prerender/PRESUBMIT.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Limmen/gym-idsgame path: /gym_idsgame/simulation/dao/simulation_config.py
import csv
class SimulationConfig:
def __init__(self, num_episodes: int = 10, video_fps=5,
video=False, gif_dir=None, video_dir=None, gifs=False, render=False, sleep=0.35,
log_frequen... | code_fim | hard | {
"lang": "python",
"repo": "Limmen/gym-idsgame",
"path": "/gym_idsgame/simulation/dao/simulation_config.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> :param file_path: path to the file
:return: None
"""
with open(file_path, "w") as f:
writer = csv.writer(f)
writer.writerow(["parameter", "value"])
writer.writerow(["render", str(self.render)])
writer.writerow(["sleep", str(se... | code_fim | hard | {
"lang": "python",
"repo": "Limmen/gym-idsgame",
"path": "/gym_idsgame/simulation/dao/simulation_config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class ConstantOpTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(
dtypes.bfloat16,
dtypes.complex128,
dtypes.complex64,
dtypes.double,
dtypes.float16,
dtypes.float32,
dtypes.float64,
dtypes.half,
dtypes.int16,
dtypes.int3... | code_fim | medium | {
"lang": "python",
"repo": "NVIDIA/tensorflow",
"path": "/tensorflow/python/framework/constant_op_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NVIDIA/tensorflow path: /tensorflow/python/framework/constant_op_test.py
# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
#
# 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 ... | code_fim | hard | {
"lang": "python",
"repo": "NVIDIA/tensorflow",
"path": "/tensorflow/python/framework/constant_op_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return reverse('nowait:booking_list')
def form_valid(self, form):
result = super(BookingCreateView, self).form_valid(form)
booking = form.instance
try:
booking.save_and_take_slottime(self.slottime, self.request)
except Exception as e:
ms... | code_fim | hard | {
"lang": "python",
"repo": "simodalla/mezzanine_nowait",
"path": "/nowait/views.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class BookingTypeDetailView(PageContextTitleMixin, DetailView):
model = BookingType
def get_page_title(self):
return _('%(title)s') % {'title': self.object.title.title()}
class SlottimeSelectView(PageContextTitleMixin, TemplateView):
template_name = 'nowait/slottime_select.html'
... | code_fim | hard | {
"lang": "python",
"repo": "simodalla/mezzanine_nowait",
"path": "/nowait/views.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: simodalla/mezzanine_nowait path: /nowait/views.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals, absolute_import
import logging
from datetime import datetime
from django.contrib import messages
from django.core.urlresolvers import reverse
from django.shortcuts import redirect
... | code_fim | hard | {
"lang": "python",
"repo": "simodalla/mezzanine_nowait",
"path": "/nowait/views.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return False
def has_delete_permission(self, request, obj=None):
return False<|fim_prefix|># repo: mickbad/django-extended-settings path: /extended_settings/admin.py
from django.contrib import admin
from extended_settings.models import ExtentedSettings
# ----------------------------... | code_fim | hard | {
"lang": "python",
"repo": "mickbad/django-extended-settings",
"path": "/extended_settings/admin.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> fieldsets = (
(None, {
"fields": ("name",
"key",
"value",
"updated_at",)
}),
)
def has_add_permission(self, request, obj=None):
return False
def has_delete_permission(self, request, o... | code_fim | medium | {
"lang": "python",
"repo": "mickbad/django-extended-settings",
"path": "/extended_settings/admin.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mickbad/django-extended-settings path: /extended_settings/admin.py
from django.contrib import admin
from extended_settings.models import ExtentedSettings
# ----------------------------------------------------------------------------------------------------------------------
# - Création de l'adm... | code_fim | medium | {
"lang": "python",
"repo": "mickbad/django-extended-settings",
"path": "/extended_settings/admin.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert m._tx_model_params['parameter2'] == 'P2'
assert len(m._tx_model_params.used_keys) == 2
assert 'parameter1' in m._tx_model_params.used_keys
assert 'parameter2' in m._tx_model_params.used_keys
assert m._tx_model_params.all_used
assert m._tx_model_params.get(
'missing... | code_fim | hard | {
"lang": "python",
"repo": "sebix/textX",
"path": "/tests/functional/test_metamodel/test_model_params.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sebix/textX path: /tests/functional/test_metamodel/test_model_params.py
from __future__ import unicode_literals
from textx import (metamodel_from_str)
import os.path
from pytest import raises
from textx.exceptions import TextXError
grammar = r"""
Model: 'MyModel' name=ID;
"""
text = r"""
MyMod... | code_fim | hard | {
"lang": "python",
"repo": "sebix/textX",
"path": "/tests/functional/test_metamodel/test_model_params.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> owner = serializers.PrimaryKeyRelatedField(allow_null=True, queryset=Owner.objects.all(), required=False)
driver = serializers.PrimaryKeyRelatedField(allow_null=True, queryset=Driver.objects.all(), required=False,
validators=[UniqueValidator(queryset... | code_fim | hard | {
"lang": "python",
"repo": "manibhushan05/tms",
"path": "/web/transiq/restapi/serializers/owner.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: manibhushan05/tms path: /web/transiq/restapi/serializers/owner.py
pload.bucket,
'folder': doc.s3_upload.folder,
'uuid': doc.s3_upload.uuid,
'filename': doc.s3_upload.filename,
'validity': None,
... | code_fim | hard | {
"lang": "python",
"repo": "manibhushan05/tms",
"path": "/web/transiq/restapi/serializers/owner.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> id = serializers.IntegerField(label='ID', read_only=True)
vehicle_number = serializers.CharField(write_only=True, max_length=18,
validators=[UniqueValidator(queryset=Vehicle.objects.all())])
rc_number = serializers.CharField(allow_null=True ,max_lengt... | code_fim | hard | {
"lang": "python",
"repo": "manibhushan05/tms",
"path": "/web/transiq/restapi/serializers/owner.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pablo0723/just-a-test path: /component/board/tests.py
from rest_framework.test import APIClient, APITestCase
from component.board.models import Board, TodoTask
from component.board.serializers import BoardSerializer, TodoTaskSerializer
class TestBoardViews(APITestCase):
def setUp(self):
... | code_fim | hard | {
"lang": "python",
"repo": "pablo0723/just-a-test",
"path": "/component/board/tests.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_todos_post(self):
response = self.client.post(f'/api/board/{self.board.slug}/todos/', {'board': self.board.id, 'name': 'Test 2'})
self.assertEqual(response.status_code, 201)
todo = TodoTask.objects.get(id=response.json()['id'])
serializer = TodoTaskSerializer(t... | code_fim | hard | {
"lang": "python",
"repo": "pablo0723/just-a-test",
"path": "/component/board/tests.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> response = self.client.delete(f'/api/board/boards/{self.board.id}/')
self.assertEqual(response.status_code, 204)
def test_todo_delete(self):
response = self.client.delete(f'/api/board/{self.board.slug}/todos/{self.todo.id}/')
self.assertEqual(response.status_code, 204)... | code_fim | hard | {
"lang": "python",
"repo": "pablo0723/just-a-test",
"path": "/component/board/tests.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def field_to_swagger_object(
self, field, swagger_object_type, use_references, **kwargs
):
if issubclass(type(field), NamedBase64FieldMixin):
properties = OrderedDict(
file_name=openapi.Schema(
type=openapi.TYPE_STRING,
... | code_fim | hard | {
"lang": "python",
"repo": "LeeHanYeong/drf-base64-filename",
"path": "/src/drf_base64/inspectors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self, field, swagger_object_type, use_references, **kwargs
):
if issubclass(type(field), NamedBase64FieldMixin):
properties = OrderedDict(
file_name=openapi.Schema(
type=openapi.TYPE_STRING,
description=r"Uploaded file... | code_fim | hard | {
"lang": "python",
"repo": "LeeHanYeong/drf-base64-filename",
"path": "/src/drf_base64/inspectors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LeeHanYeong/drf-base64-filename path: /src/drf_base64/inspectors.py
from collections import OrderedDict
from drf_yasg import openapi
from drf_yasg.inspectors import FieldInspector, NotHandled
<|fim_suffix|> def field_to_swagger_object(
self, field, swagger_object_type, use_references... | code_fim | hard | {
"lang": "python",
"repo": "LeeHanYeong/drf-base64-filename",
"path": "/src/drf_base64/inspectors.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: radiasoft/sirepo path: /sirepo/srunit.py
unt_key", "frameCount")))
assert c, "frame_count_key={} or frameCount={} is zero".format(
a.get("frame_count_key"),
a.get("frameCount"),
)
pkdlog("frameReport={} count={}",... | code_fim | hard | {
"lang": "python",
"repo": "radiasoft/sirepo",
"path": "/sirepo/srunit.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns:
object: Parsed JSON result
"""
op = lambda r: self.post(r, json=data)
return self.__req(
route_or_uri,
params=params,
query={},
op=op,
raw_response=raw_response,
**kwargs,
)... | code_fim | hard | {
"lang": "python",
"repo": "radiasoft/sirepo",
"path": "/sirepo/srunit.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def sr_post(self, route_or_uri, data, params=None, raw_response=False, **kwargs):
"""Posts JSON data to route_or_uri to server
File parameters are posted as::
Args:
route_or_uri (str): string name of route or uri if contains '/' (http:// or '/foo')
dat... | code_fim | hard | {
"lang": "python",
"repo": "radiasoft/sirepo",
"path": "/sirepo/srunit.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: universitas/universitas.no path: /django/apps/stories/migrations/0014_auto_20190219_1945.py
# Generated by Django 2.1.5 on 2019-02-19 18:45
from django.db import migrations, models
class Migration(migrations.Migration):
<|fim_suffix|> operations = [
migrations.AlterField(
... | code_fim | hard | {
"lang": "python",
"repo": "universitas/universitas.no",
"path": "/django/apps/stories/migrations/0014_auto_20190219_1945.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='story',
name='comment_field',
field=models.CharField(
choices=[('facebook', 'facebook'), ('disqus', 'disqus'),
('off', 'off')],
default='off',
... | code_fim | hard | {
"lang": "python",
"repo": "universitas/universitas.no",
"path": "/django/apps/stories/migrations/0014_auto_20190219_1945.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
('stories', '0013_auto_20181117_0241'),
]
operations = [
migrations.AlterField(
model_name='story',
name='comment_field',
field=models.CharField(
choices=[('facebook', 'facebook'), ('disqus', 'disqus'),
... | code_fim | hard | {
"lang": "python",
"repo": "universitas/universitas.no",
"path": "/django/apps/stories/migrations/0014_auto_20190219_1945.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> kf = KFold(n_splits=n_cv_folds, shuffle=True)
cv = kf.split(X)
elif dv_type == 'categorical':
df_eval = pd.DataFrame(columns=['model', 'eval_type', 'acc', 'auc', 'f1'])
skf = StratifiedKFold(n_splits=n_cv_folds, shuffle=True)
cv = skf.split(X, y)
# Fit to... | code_fim | hard | {
"lang": "python",
"repo": "samtashukla/mlToolbox",
"path": "/mlToolbox/pandas_helpers.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: samtashukla/mlToolbox path: /mlToolbox/pandas_helpers.py
t numpy as np
import scipy as sp
import pandas as pd
print('v5')
# Preproc stuff
###########################
from sklearn.utils import shuffle
from sklearn.preprocessing import PolynomialFeatures, StandardScaler, RobustScaler, Imputer
fro... | code_fim | hard | {
"lang": "python",
"repo": "samtashukla/mlToolbox",
"path": "/mlToolbox/pandas_helpers.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: samtashukla/mlToolbox path: /mlToolbox/pandas_helpers.py
sers/stephaniesorenson/anaconda/bin/python
import numpy as np
import scipy as sp
import pandas as pd
print('v5')
# Preproc stuff
###########################
from sklearn.utils import shuffle
from sklearn.preprocessing import PolynomialFe... | code_fim | hard | {
"lang": "python",
"repo": "samtashukla/mlToolbox",
"path": "/mlToolbox/pandas_helpers.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: darthinvader/DnDiscordBot path: /embed_creator.py
import discord
def dice_roll_embed(dice_amount, dice_types, rolls):
embed = discord.Embed(title='Dice Roll', colour=0x000080)
total_amount = 0
for da, dt, dr in zip(dice_amount, dice_types, rolls):
stringer = ''
amoun... | code_fim | medium | {
"lang": "python",
"repo": "darthinvader/DnDiscordBot",
"path": "/embed_creator.py",
"mode": "psm",
"license": "BSD-3-Clause-Clear",
"source": "the-stack-v2"
} |
<|fim_suffix|> embed = discord.Embed(title='Initiative Rolls', colour=0x000000)
for i in initiatives:
embed.add_field(name=i[0] + ' rolled:', value=str(i[1]))
return embed<|fim_prefix|># repo: darthinvader/DnDiscordBot path: /embed_creator.py
import discord
def dice_roll_embed(dice_amount, dice_ty... | code_fim | hard | {
"lang": "python",
"repo": "darthinvader/DnDiscordBot",
"path": "/embed_creator.py",
"mode": "spm",
"license": "BSD-3-Clause-Clear",
"source": "the-stack-v2"
} |
<|fim_suffix|> return Algorithm(algorithm_type=DecisionTreeRegressor,
algorithm_name="DECISION TREE REGRESSOR",
hyper_parameter_dict=param_dict,
discrete_hyper_parameter_dict=discrete_parameter_dict,
discrete_hyper_parameter_mapping=... | code_fim | hard | {
"lang": "python",
"repo": "CzakoZoltan08/AutoAI",
"path": "/AlgorithmFactories/RegressionAlgorithmFactories/DecisionTreeRegressorAlgorithmFactory.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CzakoZoltan08/AutoAI path: /AlgorithmFactories/RegressionAlgorithmFactories/DecisionTreeRegressorAlgorithmFactory.py
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 26 20:00:57 2019
@author: Zoltan
"""
from collections import OrderedDict
from sklearn.tree import DecisionTreeRegressor
from ..A... | code_fim | hard | {
"lang": "python",
"repo": "CzakoZoltan08/AutoAI",
"path": "/AlgorithmFactories/RegressionAlgorithmFactories/DecisionTreeRegressorAlgorithmFactory.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def get_algorithm():
return Algorithm(algorithm_type=DecisionTreeRegressor,
algorithm_name="DECISION TREE REGRESSOR",
hyper_parameter_dict=param_dict,
discrete_hyper_parameter_dict=discrete_parameter_dict,
discrete_hy... | code_fim | hard | {
"lang": "python",
"repo": "CzakoZoltan08/AutoAI",
"path": "/AlgorithmFactories/RegressionAlgorithmFactories/DecisionTreeRegressorAlgorithmFactory.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # fig:gg_mean_link
print('fig:gg_mean_link')
cp(src(OUT_DIR, GG, "explore", "mean_link.png")
, dst(THESIS_DIR, Chap5, GG, "mean_link.png") )
# fig:gg_prior_distrib_summaries
print('fig:gg_prior_distrib_summaries')
cp(src(OUT_DIR, GGPrior, DA, "DataAugmentation-L4x200-Adam... | code_fim | hard | {
"lang": "python",
"repo": "victor-estrade/SystGradDescent",
"path": "/update_manuscript.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: victor-estrade/SystGradDescent path: /update_manuscript.py
# coding: utf-8
from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
from __future__ import unicode_literals
import os
import shutil
import stat
OUT_DIR = "/home/estrade/Bureau/Ph... | code_fim | hard | {
"lang": "python",
"repo": "victor-estrade/SystGradDescent",
"path": "/update_manuscript.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cp(src(OUT_DIR, COMPARE, GGCalib, BEST_MSE, "GG-calib_best_average_N=2000-errplot_mse.png")
, dst(THESIS_DIR, Chap5, COMPARE, GGCalib, BEST_MSE, "GG-calib_best_average_N=2000-errplot_mse.png") )
cp(src(OUT_DIR, COMPARE, GGCalib, BEST_MSE, "GG-calib_best_average_N=2000-boxplot_mse.png")... | code_fim | hard | {
"lang": "python",
"repo": "victor-estrade/SystGradDescent",
"path": "/update_manuscript.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bbbbdragon/python-pype-lang-3 path: /pype3/macros.py
from pype3.fargs import embedded_pype,assoc,concat,l,append,dissoc,build_list,build_dict,merge,closure,_,_0,_1,deep_merge,rtrn
from pype3.fargs import is_map,is_filter,is_mirror
from pype3.helpers import dct_dissoc,dct_assoc,dct_merge,ls_extend... | code_fim | hard | {
"lang": "python",
"repo": "bbbbdragon/python-pype-lang-3",
"path": "/pype3/macros.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
return cl(ifta(is_dict,~_[key]))
def cl_app(*fArgs):
if not fArgs:
return cl([h,x],app(x))
return cl([h,x],app(*fArgs))
def consec(iterable,dct,n):
return ep((zip_consec,iterable,n),
[(get_call_or_false_core,dct,True,_)],
{_})
def consec_dct(i... | code_fim | hard | {
"lang": "python",
"repo": "bbbbdragon/python-pype-lang-3",
"path": "/pype3/macros.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
return fArgs,
def ea(*keysAndVal):
key=keysAndVal[0]
if len(keysAndVal) == 2:
val=keysAndVal[1]
return a(key,val)
return a(key,ep(_[key],ea(*keysAndVal[1:])))
def lm(callableFArg):
return (callableFArg,_)
def ifa(*fArgs):
if len(fArgs) == 1:
r... | code_fim | hard | {
"lang": "python",
"repo": "bbbbdragon/python-pype-lang-3",
"path": "/pype3/macros.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: daetsamupm/gestion-it path: /ui/mainui.py
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'main.ui'
#
# Created by: PyQt5 UI code generator 5.7
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Main(object)... | code_fim | hard | {
"lang": "python",
"repo": "daetsamupm/gestion-it",
"path": "/ui/mainui.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> _translate = QtCore.QCoreApplication.translate
Main.setWindowTitle(_translate("Main", "Gestion IT DAETSAM"))
self.tableWiFi.setSortingEnabled(True)
self.btnAccesos.setText(_translate("Main", "Ver Accesos Autorizados"))
self.btnDenegados.setText(_translate("Main", "V... | code_fim | hard | {
"lang": "python",
"repo": "daetsamupm/gestion-it",
"path": "/ui/mainui.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># __all__ += units.__all__
__all__ += _add_to_astropy_units.__all__
###############################################################################
# END<|fim_prefix|># repo: nstarman/amuse_util path: /amuse_util/units/astropy_units.py
# -*- coding: utf-8 -*-
# Docstring
"""Astropy Units.
Merge exist... | code_fim | medium | {
"lang": "python",
"repo": "nstarman/amuse_util",
"path": "/amuse_util/units/astropy_units.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nstarman/amuse_util path: /amuse_util/units/astropy_units.py
# -*- coding: utf-8 -*-
# Docstring
"""Astropy Units.
Merge existing astropy units with AMUSE-compatible additions.
"""
__author__ = "Nathaniel Starkman"
__credits__ = ["astropy"]
__all__ = []
<|fim_suffix|>######################... | code_fim | hard | {
"lang": "python",
"repo": "nstarman/amuse_util",
"path": "/amuse_util/units/astropy_units.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
###############################################################################
# END<|fim_prefix|># repo: nstarman/amuse_util path: /amuse_util/units/astropy_units.py
# -*- coding: utf-8 -*-
# Docstring
"""Astropy Units.
Merge existing astropy units with AMUSE-compatible additions.
"""
__author__ =... | code_fim | medium | {
"lang": "python",
"repo": "nstarman/amuse_util",
"path": "/amuse_util/units/astropy_units.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pavponn/machine-learning path: /labs/svm/smo.py
import random
from kernels import Kernel, calc_kernel, calculate_kernels
class SVMModel(object):
def __init__(self, n, c, xs, ys, kernel: Kernel, param):
self.alphas = [0] * n
self.b = 0
self.c = c
self.xs = xs
... | code_fim | hard | {
"lang": "python",
"repo": "pavponn/machine-learning",
"path": "/labs/svm/smo.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def update_alpha(alpha_j, e_i, e_j, y_j: int, nu: float, ll: float, h: float):
new_alpha = alpha_j - y_j * (e_i - e_j) / nu
return put_alpha_in_range(new_alpha, ll, h)
def put_alpha_in_range(alpha_j, ll, h):
if alpha_j > h:
return h
if h >= alpha_j >= ll:
return alpha_j
... | code_fim | hard | {
"lang": "python",
"repo": "pavponn/machine-learning",
"path": "/labs/svm/smo.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def build_schedule(lr: float, final_lr: float, n_epochs: int) -> Callable:
"""
Builds the schedule of which the learning rate decreases.
The schedule makes the learning rate decrease linearly.
:param lr: initial learning rate.
:param final_lr: final learning rate.
:param n_epochs:... | code_fim | hard | {
"lang": "python",
"repo": "zurk/ml-core",
"path": "/sourced/ml/core/algorithms/id_splitter/pipeline.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zurk/ml-core path: /sourced/ml/core/algorithms/id_splitter/pipeline.py
from datetime import datetime
import logging
import os
import random
from typing import Callable, Iterable, List, Tuple
import warnings
import keras
from keras import backend as kbackend
from keras.callbacks import CSVLogger,... | code_fim | hard | {
"lang": "python",
"repo": "zurk/ml-core",
"path": "/sourced/ml/core/algorithms/id_splitter/pipeline.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: daviddrysdale/python-phonenumbers path: /tools/python/allcheck.py
#!/usr/bin/env python
import sys
import re
import glob
# Use the local code in preference to any pre-installed version
sys.path.insert(0, '../../python')
import phonenumbers
import phonenumbers.geocoder
import phonenumbers.carrie... | code_fim | hard | {
"lang": "python",
"repo": "daviddrysdale/python-phonenumbers",
"path": "/tools/python/allcheck.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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