text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>def getChordType(rootNote,thirdNote,fifthNote):
intervals = (getInterval(rootNote,thirdNote),getInterval(thirdNote,fifthNote))
if (intervals == (4,3)):
return "Major"
elif (intervals == (3,4)):
return "Minor"
elif (intervals == (3,3)):
return "Diminished"
elif (intervals == (4,4)):
return "Au... | code_fim | hard | {
"lang": "python",
"repo": "PsychedelicPasta/pyFrets",
"path": "/guitarfretboard.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def _is_sym_size_node(node: Node):
return (
node.op == "call_function"
and node.target == torch.ops.aten.sym_size.default
or node.target == torch.ops.aten.sym_numel.default
or node.target == torch.ops.aten.sym_numel
or node.target == torch.ops.aten.sym_size
... | code_fim | hard | {
"lang": "python",
"repo": "pytorch/pytorch",
"path": "/torch/ao/quantization/quantizer/utils.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pytorch/pytorch path: /torch/ao/quantization/quantizer/utils.py
from typing import List, Optional
import torch
from torch.ao.quantization.quantizer.quantizer import (
QuantizationAnnotation,
QuantizationConfig,
QuantizationSpec,
)
from torch.fx import Node
__all__ = [
"get_input... | code_fim | hard | {
"lang": "python",
"repo": "pytorch/pytorch",
"path": "/torch/ao/quantization/quantizer/utils.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hmajid2301/EmotionCommotion path: /EmotionCommotion/dataset creation/audioChopper.py
import scipy.io.wavfile as wav # Reads wav file
import sys
import csv
import ntpath
import numpy as np
import pandas as pd
import os
from glob import glob
import sys
from types import *
import json
#Use soxi ... | code_fim | hard | {
"lang": "python",
"repo": "hmajid2301/EmotionCommotion",
"path": "/EmotionCommotion/dataset creation/audioChopper.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #wav.read gets the sample rate and creates an audio variable which allows use of the audio data at filepath
[sample_rate, audio] = wav.read(filepath)
print("sample rate = " + str(sample_rate))
#len(audio)/sample_rate=length of audio in seconds
#for loop to iterate over each triple
for i in range... | code_fim | hard | {
"lang": "python",
"repo": "hmajid2301/EmotionCommotion",
"path": "/EmotionCommotion/dataset creation/audioChopper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # print out current run_uuid
run_uuid = mlflow.active_run().info.run_uuid
print("MLflow Run ID: %s" % run_uuid)
# log parameters
params = self.get_params()
for k, v in params.items():
if k not in ['build_fn', 'callbac... | code_fim | hard | {
"lang": "python",
"repo": "kleysonr/snsdl",
"path": "/snsdl/keras/wrappers/mlflow_classifier.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # # save model locally
# pathdir = "keras_models/" + run_uuid
# model_dir = self.get_directory_path(pathdir, False)
# ktrain_cls.keras_save_model(model, model_dir)
# # Write out TensorFlow events as a run artifact
# print("Uploading ... | code_fim | hard | {
"lang": "python",
"repo": "kleysonr/snsdl",
"path": "/snsdl/keras/wrappers/mlflow_classifier.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kleysonr/snsdl path: /snsdl/keras/wrappers/mlflow_classifier.py
import os
import copy
import mlflow
import pandas as pd
from keras.callbacks import CSVLogger
from snsdl.keras.wrappers import BaseWrapper
class MlflowClassifier(BaseWrapper):
""" Implementation of the mlflow classifier API for ... | code_fim | hard | {
"lang": "python",
"repo": "kleysonr/snsdl",
"path": "/snsdl/keras/wrappers/mlflow_classifier.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>= int(input(f'Quantidade de gols no jogo {j+1}: '))
partidas.append(j+1)
partidas.append(g)
jogador['jogos'] = partidas
campeonato.append(jogador.copy())
print(campeonato)
for c in campeonato:
nome = c['nome']
jogos = c['jogos']
print(f'Vamos analisar o joga... | code_fim | hard | {
"lang": "python",
"repo": "felipesch92/PythonExercicios",
"path": "/ex093.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: felipesch92/PythonExercicios path: /ex093.py
# Crie um programa que gerencie o aproveitamento de um jogador
# de futebol. O programa vai ler o nome do jogador e quantas partidas
# ele jogou. Depois vai ler a quantidade de gols feitos em cada partida.
# No final, tudo isso será guardado em um dici... | code_fim | hard | {
"lang": "python",
"repo": "felipesch92/PythonExercicios",
"path": "/ex093.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>os']
print(f'Vamos analisar o jogador {nome}')
t = 0
for k, j in enumerate(jogos):
if k % 2 == 0:
print(f'No jogo {j} foram ', end='')
else:
print(f'{j} gols')
t += j
print(f'No total foram {t} gols.')<|fim_prefix|># repo: felipesch92/Pyt... | code_fim | hard | {
"lang": "python",
"repo": "felipesch92/PythonExercicios",
"path": "/ex093.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def com_adobe_cq_screens_offlinecontent_impl_bulk_offline_update_service_impl_schedule_frequency(self) -> ConfigNodePropertyString:
"""Gets the com_adobe_cq_screens_offlinecontent_impl_bulk_offline_update_service_impl_schedule_frequency of this ComAdobeCqScreensOfflinecontentImpl... | code_fim | hard | {
"lang": "python",
"repo": "shinesolutions/swagger-aem-osgi",
"path": "/clients/python-flask/generated/openapi_server/models/com_adobe_cq_screens_offlinecontent_impl_bulk_offline_update_service_impl_properties.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @com_adobe_cq_screens_offlinecontent_impl_bulk_offline_update_service_impl_schedule_frequency.setter
def com_adobe_cq_screens_offlinecontent_impl_bulk_offline_update_service_impl_schedule_frequency(self, com_adobe_cq_screens_offlinecontent_impl_bulk_offline_update_service_impl_schedule_frequency: ... | code_fim | hard | {
"lang": "python",
"repo": "shinesolutions/swagger-aem-osgi",
"path": "/clients/python-flask/generated/openapi_server/models/com_adobe_cq_screens_offlinecontent_impl_bulk_offline_update_service_impl_properties.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
browser_dict[row[0]] = (urls_id,urls,urls_title,urls_visit_count,urls_typed_count,urls_last_visit_time,urls_hidden,visits_time,visits_from_visit,visits_duration,visits_transition)
row = browser_cursor.fetchone()
browser_cursor.close()
browser_conn.close()
browser_output_file... | code_fim | hard | {
"lang": "python",
"repo": "scorelab/OpenMF",
"path": "/scripts/browser.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: scorelab/OpenMF path: /scripts/browser.py
'''
script for extracting browsers history
'''
import sys
import sqlite3
import os
import json
import datetime
import urllib
from scripts import dbm
from scripts.os_check import SEP
from scripts.utils import ROOT_DIR, mkdir
OUTPUT = ROOT_DIR
''' loca... | code_fim | hard | {
"lang": "python",
"repo": "scorelab/OpenMF",
"path": "/scripts/browser.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ultimatenhapper/zipline-reloaded path: /tests/utils/test_sentinel.py
from copy import copy, deepcopy
from pickle import loads, dumps
import sys
from weakref import ref
from zipline.utils.sentinel import sentinel
import pytest
@pytest.fixture(scope="function")
def clear_cache():
yield
se... | code_fim | hard | {
"lang": "python",
"repo": "ultimatenhapper/zipline-reloaded",
"path": "/tests/utils/test_sentinel.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_memo(self):
assert sentinel("a") is sentinel("a")
def test_copy(self):
a = sentinel("a")
assert copy(a) is a
def test_deepcopy(self):
a = sentinel("a")
assert deepcopy(a) is a
def test_repr(self):
assert repr(sentinel("a")) == "se... | code_fim | hard | {
"lang": "python",
"repo": "ultimatenhapper/zipline-reloaded",
"path": "/tests/utils/test_sentinel.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: IBM/simulai path: /tests/parallelism/test_modelpool_esn.py
2022.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LIC... | code_fim | hard | {
"lang": "python",
"repo": "IBM/simulai",
"path": "/tests/parallelism/test_modelpool_esn.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> esn_2 = EchoStateNetwork.restore(default_model_dir, "my_esn")
esn_2.fit(input_data=esn_input_data, target_data=outs)
esn_2.set_reference(esn.default_state)
esn_2.reset()
outs_2 = []
for step in range(esn_input... | code_fim | hard | {
"lang": "python",
"repo": "IBM/simulai",
"path": "/tests/parallelism/test_modelpool_esn.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: IBM/simulai path: /tests/parallelism/test_modelpool_esn.py
_data[1:]
pool_config = {
"template": "independent_series",
"n_inputs": field_train_data.shape[1] + forcings_train_data.shape[1],
"n_outputs": field_train_data.shape[1],
"n_auxiliar... | code_fim | hard | {
"lang": "python",
"repo": "IBM/simulai",
"path": "/tests/parallelism/test_modelpool_esn.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns:
array.array: New, initialized array
"""
return array.array(FLOAT_TYPECODE, *args, **kwargs)<|fim_prefix|># repo: radiasoft/pykern path: /pykern/pkarray.py
# -*- coding: utf-8 -*-
"""Wrapper for :mod:`array` to simplify and make future compatible.
Not a complete wrapper. New ... | code_fim | hard | {
"lang": "python",
"repo": "radiasoft/pykern",
"path": "/pykern/pkarray.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: radiasoft/pykern path: /pykern/pkarray.py
# -*- coding: utf-8 -*-
"""Wrapper for :mod:`array` to simplify and make future compatible.
Not a complete wrapper. New routines added as required.
<|fim_suffix|>def new_double(*args, **kwargs):
"""Creates a new double ("d") array
Args are the ... | code_fim | hard | {
"lang": "python",
"repo": "radiasoft/pykern",
"path": "/pykern/pkarray.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def new_float(*args, **kwargs):
"""Creates a new float ("f") array
Args are the same as :func:`array.array` except for typecode,
which is passed by this module.
Returns:
array.array: New, initialized array
"""
return array.array(FLOAT_TYPECODE, *args, **kwargs)<|fim_prefi... | code_fim | hard | {
"lang": "python",
"repo": "radiasoft/pykern",
"path": "/pykern/pkarray.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: eriche2016/pytorch_projects_misc path: /golden_examples/tutorials/08 - Language Model/main.py
# Some part of the code was referenced from below.
# https://github.com/pytorch/examples/tree/master/word_language_model
import torch
import torch.nn as nn
import numpy as np
from torch.autograd import... | code_fim | hard | {
"lang": "python",
"repo": "eriche2016/pytorch_projects_misc",
"path": "/golden_examples/tutorials/08 - Language Model/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Loss and Optimizer
criterion = nn.CrossEntropyLoss()
optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)
# Truncated Backpropagation
def detach(states):
return [Variable(state.data) for state in states]
# Training
for epoch in range(num_epochs):
# Initial hidden and memory sta... | code_fim | hard | {
"lang": "python",
"repo": "eriche2016/pytorch_projects_misc",
"path": "/golden_examples/tutorials/08 - Language Model/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Training
for epoch in range(num_epochs):
# Initial hidden and memory states
states = (Variable(torch.zeros(num_layers, batch_size, hidden_size)),
Variable(torch.zeros(num_layers, batch_size, hidden_size)))
for i in range(0, ids.size(1) - seq_length, seq_length):
# ... | code_fim | hard | {
"lang": "python",
"repo": "eriche2016/pytorch_projects_misc",
"path": "/golden_examples/tutorials/08 - Language Model/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GoodRx/structlog-sentry path: /test/test_sentry_processor.py
import logging
import pytest
from structlog_sentry import SentryJsonProcessor, SentryProcessor
class MockLogger:
def __init__(self, name):
self.name = name
def test_sentry_disabled():
processor = SentryProcessor(ac... | code_fim | hard | {
"lang": "python",
"repo": "GoodRx/structlog-sentry",
"path": "/test/test_sentry_processor.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_sentry_json_ignore_logger_using_event_dict_record(mocker):
m_ignore_logger = mocker.patch("structlog_sentry.ignore_logger")
m_logger = MockLogger("MockLogger")
event_data = {
"level": "info",
"event": "message",
"_record": MockLogger("RecordLogger"),
}
... | code_fim | hard | {
"lang": "python",
"repo": "GoodRx/structlog-sentry",
"path": "/test/test_sentry_processor.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@pytest.mark.parametrize("level", ["debug", "info", "warning"])
def test_sentry_log_specific_keys_as_tags(mocker, level):
m_capture_event = mocker.patch("structlog_sentry.capture_event")
event_data = {
"level": level,
"event": level + " message",
"info1": "info1",
... | code_fim | hard | {
"lang": "python",
"repo": "GoodRx/structlog-sentry",
"path": "/test/test_sentry_processor.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: home-assistant/core path: /homeassistant/components/netatmo/switch.py
"""Support for Netatmo/BTicino/Legrande switches."""
from __future__ import annotations
import logging
from typing import Any, cast
from pyatmo import modules as NaModules
from homeassistant.components.switch import SwitchEn... | code_fim | hard | {
"lang": "python",
"repo": "home-assistant/core",
"path": "/homeassistant/components/netatmo/switch.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Representation of a Netatmo switch device."""
def __init__(
self,
netatmo_device: NetatmoDevice,
) -> None:
"""Initialize the Netatmo device."""
super().__init__(netatmo_device.data_handler)
self._switch = cast(NaModules.Switch, netatmo_device.devic... | code_fim | hard | {
"lang": "python",
"repo": "home-assistant/core",
"path": "/homeassistant/components/netatmo/switch.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: netenglabs/suzieq path: /suzieq/poller/worker/services/service_manager.py
schema_dir: str,
output_queue: asyncio.Queue,
run_mode: str,
cfg: Dict,
default_interval: int = 15,
**kwargs) -> None:
"""Ins... | code_fim | hard | {
"lang": "python",
"repo": "netenglabs/suzieq",
"path": "/suzieq/poller/worker/services/service_manager.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Raises:
SqPollerConfError: raised in case of wrong service name in
'include only' or exclude list
Returns:
List[str]: the list of services to executed in the poller
"""
return self.get_service_list(service_only,
... | code_fim | hard | {
"lang": "python",
"repo": "netenglabs/suzieq",
"path": "/suzieq/poller/worker/services/service_manager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> filename: str,
svc_def: Dict,
nos: str,
cmds_desc: Union[Dict, List]):
"""Given a command description check whether initialize the textfsm
finite state machine for the output parsing... | code_fim | hard | {
"lang": "python",
"repo": "netenglabs/suzieq",
"path": "/suzieq/poller/worker/services/service_manager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Parameters
----------
d_dimensions : int
Number of dimensions to estimate the volume
norm : int, default=2
The type of ball to get the volume.
* 2 : euclidean distance
* 1 : manhattan distance
* 0 : chebyshev distance
Returns
------... | code_fim | hard | {
"lang": "python",
"repo": "superpig99/pysim",
"path": "/pysim/information/knn.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# volume of unit ball
def volume_unit_ball(d_dimensions: int, norm=2) -> float:
"""Volume of the d-dimensional unit ball
Parameters
----------
d_dimensions : int
Number of dimensions to estimate the volume
norm : int, default=2
The type of ball to get the vol... | code_fim | hard | {
"lang": "python",
"repo": "superpig99/pysim",
"path": "/pysim/information/knn.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: superpig99/pysim path: /pysim/information/knn.py
from typing import Optional, Union, Dict, List
import numpy as np
from sklearn.base import BaseEstimator
from sklearn.neighbors import NearestNeighbors
from scipy import stats
from scipy.special import gamma, psi
from sklearn.utils import check_arr... | code_fim | hard | {
"lang": "python",
"repo": "superpig99/pysim",
"path": "/pysim/information/knn.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return y/x #price per unit
def xperpound(x):
return x/8 #price per oz.
def buyxgetyfree(x,y):
return x/(x+y) #price per unit
#Finds type of custom deal
def findDeal(i):
if deals[i][0] != 0:
return 0
elif deals[i][2] != 0:
return 1
elif deals[i][4] != 0:
return 2
#Gives processed data on a cu... | code_fim | hard | {
"lang": "python",
"repo": "DevTheDev/CodeKata",
"path": "/GroceryStore.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DevTheDev/CodeKata path: /GroceryStore.py
#Grocery Store Pricer
#Stock in terms of "name":[units, price, wholesale cost]
stock = {
"can":[50, 9.45, 0.5],
"chip":[100, 6.75, 0.2],
"soda":[46, 5.00, 0.46],
"water":[30, 2.25, 0.1],
"spice":[400, 0.5, 0.05],
"milk":[49, 2.5, 0.56],
"ice cream"... | code_fim | hard | {
"lang": "python",
"repo": "DevTheDev/CodeKata",
"path": "/GroceryStore.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>#Gives processed data on a custom deal
def listCustomDeals(i):
print "There are " + str(stock[i][0]) + " units of " + str(i) + " remaining."
type = findDeal(i)
if type == 0:
p = xforydollar(deals[i][0], deals[i][1])
print "This " + str(i) + " costs us $" + str(stock[i][2]*stock[i][0]) + "."
print... | code_fim | hard | {
"lang": "python",
"repo": "DevTheDev/CodeKata",
"path": "/GroceryStore.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zmlabe/SeaIceQBO path: /Scripts/Data_Analysis/plot_FIGURE_JetStreamLocations.py
"""
Manuscript figure for regional locations of the jet
Notes
-----
Author : Zachary Labe
Date : 19 October 2018
"""
### Import modules
import numpy as np
import matplotlib.pyplot as plt
import datetime
im... | code_fim | hard | {
"lang": "python",
"repo": "zmlabe/SeaIceQBO",
"path": "/Scripts/Data_Analysis/plot_FIGURE_JetStreamLocations.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ### Begin smoothing of N days
climovarq = []
for s in range(climovar.shape[1]):
climovarqq=np.convolve(climovar[:,s], np.ones((N,))/N, mode='valid')
climovarq.append(climovarqq)
empty = np.empty((96,N-1))
empty[:] = np.nan
climovarn = np.append(empty,np.asa... | code_fim | hard | {
"lang": "python",
"repo": "zmlabe/SeaIceQBO",
"path": "/Scripts/Data_Analysis/plot_FIGURE_JetStreamLocations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def predict(self, input_text):
return np.asarray([[self.model.generate_issue_title(body[0])[1]] for body in input_text])<|fim_prefix|># repo: elsonrodriguez/examples path: /github_issue_summarization/notebooks/issue_summarization.py
"""Generates predictions using a stored model.
Uses trained model... | code_fim | hard | {
"lang": "python",
"repo": "elsonrodriguez/examples",
"path": "/github_issue_summarization/notebooks/issue_summarization.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> with open('body_pp.dpkl', 'rb') as body_file:
body_pp = dpickle.load(body_file)
with open('title_pp.dpkl', 'rb') as title_file:
title_pp = dpickle.load(title_file)
self.model = Seq2Seq_Inference(encoder_preprocessor=body_pp,
decoder_preprocessor=t... | code_fim | medium | {
"lang": "python",
"repo": "elsonrodriguez/examples",
"path": "/github_issue_summarization/notebooks/issue_summarization.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: elsonrodriguez/examples path: /github_issue_summarization/notebooks/issue_summarization.py
"""Generates predictions using a stored model.
Uses trained model files to generate a prediction.
"""
from __future__ import print_function
import numpy as np
import dill as dpickle
from keras.models imp... | code_fim | hard | {
"lang": "python",
"repo": "elsonrodriguez/examples",
"path": "/github_issue_summarization/notebooks/issue_summarization.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> model = CardQuantity
extra = 1
class DesignCardInline(admin.TabularInline):
model = DesignCard
extra = 1
class ProductCardAdmin(admin.ModelAdmin):
inlines = (QuantityInline,)
list_display = ('__unicode__', 'job_list', 'status', 'prod_notes', 'client_notes', 'contact', 'assignedus... | code_fim | medium | {
"lang": "python",
"repo": "connorbolick/wiboserver",
"path": "/wibo1/cards/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: connorbolick/wiboserver path: /wibo1/cards/admin.py
from cards.models import JobCard, ProductCard, CardQuantity, DesignCard
from django.contrib import admin
def make_archived(modeladmin, request, queryset):
for obj in queryset:
obj.archive()
make_archived.short_description = "Archive... | code_fim | medium | {
"lang": "python",
"repo": "connorbolick/wiboserver",
"path": "/wibo1/cards/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> suggestions = []
for currency in cls.currencies:
if currency.lower().startswith(prefix):
suggestions.append(currency)
return suggestions
def get_rate(symbols):
rate = _RATES.get(symbols)
if rate:
return rate
csv = urllib2.ur... | code_fim | hard | {
"lang": "python",
"repo": "csytan/pycmds",
"path": "/modules/.svn/text-base/finance.py.svn-base",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: csytan/pycmds path: /modules/.svn/text-base/finance.py.svn-base
import urllib2
import pycmds
_RATES = {}
class Currency(str):
currencies = {
'Maltese Lira (MTL)': 'MTL',
'Ukraine Hryvnia (UAH)': 'UAH',
'Rwanda Franc (RWF)': 'RWF',
'Mauritania Ougulya (MRO)... | code_fim | hard | {
"lang": "python",
"repo": "csytan/pycmds",
"path": "/modules/.svn/text-base/finance.py.svn-base",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kissmetrics/py-KISSmetrics path: /KISSmetrics/query_string.py
# -*- coding: utf-8 -*-
KEY_KEY = '_k'
PERSON_KEY = '_p'
EVENT_NAME_KEY = '_n'
TIME_KEY = '_t'
TIME_FLAG_KEY = '_d'
ALIAS_KEY = '_n'
try:
from urllib import urlencode
except ImportError:
from urllib.parse import urlencode
... | code_fim | hard | {
"lang": "python",
"repo": "kissmetrics/py-KISSmetrics",
"path": "/KISSmetrics/query_string.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> :returns: URL encoded string representing query string
:rtype: str
.. note::
When a ``timestamp`` is provided, the ``TIME_FLAG_KEY`` will
be set to ``1`` and included.
"""
if properties is None:
properties = {}
query_dict = {KEY_KEY: key, PERSON_KEY: per... | code_fim | hard | {
"lang": "python",
"repo": "kissmetrics/py-KISSmetrics",
"path": "/KISSmetrics/query_string.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if (current_output_0 == current_output_1):
print("calling bdd for output " + str(current_output_0) + " from files " + str(aigs[0] + " and " + str(aigs[1] + ":")))
print(current_expr_0)
print(current_expr_1)
p = Popen("./evalBDD " + "'" + st... | code_fim | hard | {
"lang": "python",
"repo": "gumadeiras/inf-cad-para-sistemas-digitais",
"path": "/aig_parser/aig_wrapper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gumadeiras/inf-cad-para-sistemas-digitais path: /aig_parser/aig_wrapper.py
#!/usr/bin/env python
import os
import sys
import re
import subprocess
from subprocess import Popen, PIPE
from AIGnode import AIGnode
from string import ascii_lowercase
from pprint import pprint
# usage: python wrapper.... | code_fim | hard | {
"lang": "python",
"repo": "gumadeiras/inf-cad-para-sistemas-digitais",
"path": "/aig_parser/aig_wrapper.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
p = Popen("./evalBDD " + "'" + str(current_expr_0) + "' '" + str(current_expr_1) + "'", stdout = PIPE, stderr = PIPE, shell = True)
stdout = p.communicate()[0].decode('utf-8').strip()
print(stdout)<|fim_prefix|># repo: gumadeiras/inf-cad-para-sistemas-digitais path: /aig_parser/aig_wrapper.py
#!... | code_fim | hard | {
"lang": "python",
"repo": "gumadeiras/inf-cad-para-sistemas-digitais",
"path": "/aig_parser/aig_wrapper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> issue = self.gather_ticket()
issue.owner = None
self.store_issue(issue)
self.store_new_event(issue,
"ticket owner removed",
datetime.datetime.now(),
self.gather_creator(),
self.editor_prompt("Comment"))
tkt.commands.aliases... | code_fim | hard | {
"lang": "python",
"repo": "teepark/tkt",
"path": "/tkt/plugins/claiming.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: teepark/tkt path: /tkt/plugins/claiming.py
import datetime
import re
import tkt.commands
import tkt.config
import tkt.models
tkt.models.Issue.fields.append("owner")
tkt.models.Issue.display.append("owner")
tkt.commands.Search.options.append({
'short': '-o',
'long': '--owner',
'typ... | code_fim | hard | {
"lang": "python",
"repo": "teepark/tkt",
"path": "/tkt/plugins/claiming.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Ownedby(tkt.commands.Command):
usage = "<user regex>"
usageinfo = "list the tickets owned by a particular user"
def main(self):
if not (self.parsed_args and self.parsed_args[0]):
self.fail("a search string is required")
searcher = re.compile(self.parsed_args... | code_fim | hard | {
"lang": "python",
"repo": "teepark/tkt",
"path": "/tkt/plugins/claiming.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: frank2411/cookiecutter_flasktemplate path: /{{cookiecutter.project_name}}/tests/test_rabbitmq_manager.py
import pytest
from unittest.mock import patch
from {{cookiecutter.project_name}}_api.rabbitmq_manager import RabbitMQPublisher, RabbitMQPublisherException
class TestRabbitMQPublisher:
... | code_fim | medium | {
"lang": "python",
"repo": "frank2411/cookiecutter_flasktemplate",
"path": "/{{cookiecutter.project_name}}/tests/test_rabbitmq_manager.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@patch('{{cookiecutter.project_name}}_api.rabbitmq_manager.pika.BlockingConnection')
def test_rabbitmq_publisher_fail_connection(self, mocked_connection, app):
mocked_connection.side_effect = ValueError("on connect collapsed")
with app.app_context():
with pytest.raise... | code_fim | medium | {
"lang": "python",
"repo": "frank2411/cookiecutter_flasktemplate",
"path": "/{{cookiecutter.project_name}}/tests/test_rabbitmq_manager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert publisherror.value
assert publisherror.value.message == 'Connection Problem'
@patch('{{cookiecutter.project_name}}_api.rabbitmq_manager.pika.BlockingConnection')
def test_rabbitmq_publisher_fail_publish(self, mocked_connection, app):
mocked_connection.return_value.c... | code_fim | hard | {
"lang": "python",
"repo": "frank2411/cookiecutter_flasktemplate",
"path": "/{{cookiecutter.project_name}}/tests/test_rabbitmq_manager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> request = urllib.urlopen(url % search_terms)
payload = json.loads(request.read())
feed = payload['feed']
entries = feed['entry'][0]
links = entries['link']
finalLink = links[0]['href']
print(finalLink)
index = len(sys.argv)
query = ""
for x in range(1, index):
query += sys.argv... | code_fim | hard | {
"lang": "python",
"repo": "trevor-umeda/hayate-bot",
"path": "/modules/youtube.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
url = 'http://gdata.youtube.com/feeds/api/videos?orderBy=relevance&max-results=1&alt=json&q=%s'
def SearchAndPrint(search_terms):
request = urllib.urlopen(url % search_terms)
payload = json.loads(request.read())
feed = payload['feed']
entries = feed['entry'][0]
links = entries['link']
... | code_fim | medium | {
"lang": "python",
"repo": "trevor-umeda/hayate-bot",
"path": "/modules/youtube.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: trevor-umeda/hayate-bot path: /modules/youtube.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function
import sys
import json
import urllib
from datetime import datetime, timedelta
<|fim_suffix|>def SearchAndPrint(search_terms):
reque... | code_fim | medium | {
"lang": "python",
"repo": "trevor-umeda/hayate-bot",
"path": "/modules/youtube.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Garinmckayl/researchhub-backend path: /src/paper/migrations/0039_auto_20200402_2319.py
# Generated by Django 2.2.11 on 2020-04-02 23:19
from django.db import migrations, models
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='paper',
name='doi... | code_fim | medium | {
"lang": "python",
"repo": "Garinmckayl/researchhub-backend",
"path": "/src/paper/migrations/0039_auto_20200402_2319.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='paper',
name='doi',
field=models.CharField(blank=True, default=None, max_length=255, null=True, unique=True),
),
]<|fim_prefix|># repo: Garinmckayl/researchhub-backend path: /src/paper/migrations... | code_fim | medium | {
"lang": "python",
"repo": "Garinmckayl/researchhub-backend",
"path": "/src/paper/migrations/0039_auto_20200402_2319.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: juan-edesk/delta-core path: /migrations/versions/f6a0e5e4490a_.py
"""empty message
Revision ID: f6a0e5e4490a
Revises: 7fbc4dda2333
Create Date: 2020-10-01 17:41:05.962900
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used ... | code_fim | hard | {
"lang": "python",
"repo": "juan-edesk/delta-core",
"path": "/migrations/versions/f6a0e5e4490a_.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> op.rename_table("mother_test", "test")
op.execute("ALTER SEQUENCE mother_test_id_seq RENAME TO test_id_seq")
op.execute("ALTER INDEX mother_test_pkey RENAME TO test_pkey")
op.execute(
'ALTER TABLE test RENAME CONSTRAINT "mother_test_test_resolution_id_fkey" TO "test_test_resolution... | code_fim | hard | {
"lang": "python",
"repo": "juan-edesk/delta-core",
"path": "/migrations/versions/f6a0e5e4490a_.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> op.execute(
'ALTER TABLE test_retries RENAME CONSTRAINT "test_retries_test_id_fkey" TO "test_retries_test_history_id_fkey"'
)
op.alter_column("test_retries", "test_id", new_column_name="test_history_id")
op.alter_column("test_history", "mother_test_id", new_column_name="test_id")
... | code_fim | hard | {
"lang": "python",
"repo": "juan-edesk/delta-core",
"path": "/migrations/versions/f6a0e5e4490a_.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def configure():
"""
Configure logging
Pick up the log level from the env var LOGLEVEL, otherwise default to INFO
"""
# TODO: Simple configuration of what to log and where to log it to
level_name = getenv("LOGLEVEL", "INFO")
level = getattr(logging, level_name)
logging.bas... | code_fim | medium | {
"lang": "python",
"repo": "radiac/mara",
"path": "/mara/app/logging.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: radiac/mara path: /mara/app/logging.py
import asyncio
import logging
import sys
from os import getenv
class Whitelist(logging.Filter):
def __init__(self, *whitelist):
self.whitelist = [logging.Filter(name) for name in whitelist]
def filter(self, record):
return any(f.fi... | code_fim | hard | {
"lang": "python",
"repo": "radiac/mara",
"path": "/mara/app/logging.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
args = docopt.docopt(__doc__)
# First get release version used to create the file to be converted
version_stripped = args['--release'].replace('.', '')
release_base_name = '_'.join(('h5py_wrapper', version_stripped))
try:
h5w_old = importlib.import_mo... | code_fim | medium | {
"lang": "python",
"repo": "tommybutler/mlearnpy2",
"path": "/home--tommy--mypy/mypy/bin/convert_h5file.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tommybutler/mlearnpy2 path: /home--tommy--mypy/mypy/bin/convert_h5file.py
#!/home/tommy/mypy/mypy/bin/python2
# encoding: utf8
"""
Conversion script to convert files from a previous
release version to the current version.
Usage: convert_h5file [-h|--help] [<files>...] [--save-backup] [-v|--verb... | code_fim | hard | {
"lang": "python",
"repo": "tommybutler/mlearnpy2",
"path": "/home--tommy--mypy/mypy/bin/convert_h5file.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dirpath = 'c:/RetrieveOnly100%DATAFROMSUMO_RANDOMSEED(One time)-DATASET-WithoutReplicatedVID'
for key, value in setting.items():
for percent in percentage:
for history in time_lagged_observation:
fig = plt.figure()
data = pd.read_csv(
... | code_fim | hard | {
"lang": "python",
"repo": "EEM0N/Smart-Mobility-Chula",
"path": "/Bottleneck Based Gridlock Prediction in Urban Road Network Using Long Short-Term Memory/ConfusionMatrixxAfterDefense.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EEM0N/Smart-Mobility-Chula path: /Bottleneck Based Gridlock Prediction in Urban Road Network Using Long Short-Term Memory/ConfusionMatrixxAfterDefense.py
import pandas as pd
import seaborn as sn
import matplotlib.pyplot as plt
import numpy as np
percentage = ['1%','5%','10%','15%','20%','25%'... | code_fim | hard | {
"lang": "python",
"repo": "EEM0N/Smart-Mobility-Chula",
"path": "/Bottleneck Based Gridlock Prediction in Urban Road Network Using Long Short-Term Memory/ConfusionMatrixxAfterDefense.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kryvokhyzha/examples-and-courses path: /Information-security-labs/Lab5/vulnerability1/create_reg_key.py
import winreg
from main import prepare_info_about_computer_hash
<|fim_suffix|>with reg_key:
winreg.SetValueEx(reg_key, 'Signature', 0, winreg.REG_SZ, prepare_info_about_computer_hash()... | code_fim | medium | {
"lang": "python",
"repo": "kryvokhyzha/examples-and-courses",
"path": "/Information-security-labs/Lab5/vulnerability1/create_reg_key.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>with reg_key:
winreg.SetValueEx(reg_key, 'Signature', 0, winreg.REG_SZ, prepare_info_about_computer_hash())<|fim_prefix|># repo: kryvokhyzha/examples-and-courses path: /Information-security-labs/Lab5/vulnerability1/create_reg_key.py
import winreg
from main import prepare_info_about_computer_hash
... | code_fim | medium | {
"lang": "python",
"repo": "kryvokhyzha/examples-and-courses",
"path": "/Information-security-labs/Lab5/vulnerability1/create_reg_key.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: signalfx/jaeger-client-python path: /tests/test_throttler.py
# Modified by SignalFx
# Copyright (c) 2018 Uber Technologies, Inc.
#
# 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 Li... | code_fim | hard | {
"lang": "python",
"repo": "signalfx/jaeger-client-python",
"path": "/tests/test_throttler.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_throttler_init_polling(throttler):
# noinspection PyProtectedMember
throttler._init_polling()
throttler.close()
# noinspection PyProtectedMember
throttler._init_polling()
def test_throttler_delayed_polling(throttler):
throttler.credits = {'test-operation': 0}
# noin... | code_fim | hard | {
"lang": "python",
"repo": "signalfx/jaeger-client-python",
"path": "/tests/test_throttler.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def _render_error_page(status_code, error_message=None):
templates = {
404: "errors/404.html",
410: "errors/404.html",
500: "errors/500.html",
503: "errors/500.html",
}
if status_code not in templates:
status_code = 500
return render_template(
... | code_fim | medium | {
"lang": "python",
"repo": "robot2051/dto-digitalmarketplace-buyer-frontend",
"path": "/app/main/errors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@main.app_errorhandler(500)
def internal_server_error(e):
return _render_error_page(500)
@main.app_errorhandler(503)
def service_unavailable(e):
return _render_error_page(503, e.response)
def _render_error_page(status_code, error_message=None):
templates = {
404: "errors/404.html",... | code_fim | medium | {
"lang": "python",
"repo": "robot2051/dto-digitalmarketplace-buyer-frontend",
"path": "/app/main/errors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: robot2051/dto-digitalmarketplace-buyer-frontend path: /app/main/errors.py
# coding=utf-8
from flask import render_template
from . import main
from ..api_client.error import APIError
@main.app_errorhandler(APIError)
def api_error_handler(e):
return _render_error_page(e.status_code)
@main.... | code_fim | medium | {
"lang": "python",
"repo": "robot2051/dto-digitalmarketplace-buyer-frontend",
"path": "/app/main/errors.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: antipatico/pytoyir path: /modules/cli.py
from .utils import lazyInt
def confirm(question):
print(question, "(y/N) ", end="")
return input() in ["y", "yes", "Y", "YES"]
def selectOptionsText(question, options):
<|fim_suffix|> selection = lazyInt(input(question))
if selec... | code_fim | medium | {
"lang": "python",
"repo": "antipatico/pytoyir",
"path": "/modules/cli.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> while True:
r = range(len(options))
for i in r:
print(i, options[i])
selection = lazyInt(input(question))
if selection in r:
return options[selection]<|fim_prefix|># repo: antipatico/pytoyir path: /modules/cli.py
from .utils import lazyInt
de... | code_fim | medium | {
"lang": "python",
"repo": "antipatico/pytoyir",
"path": "/modules/cli.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@bp.route("/", methods=["POST"])
def create():
return StylesheetSchema.create()
@bp.route("/", methods=["GET"])
def get_all():
return StylesheetSchema.get_all()
@bp.route("/<int:template_id>/", methods=["GET"])
def get(template_id: int):
return StylesheetSchema.get(template_id)
@bp.route... | code_fim | medium | {
"lang": "python",
"repo": "pbehnke/doku",
"path": "/doku/blueprints/api/v1/stylesheet.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pbehnke/doku path: /doku/blueprints/api/v1/stylesheet.py
from flask import Blueprint, request, jsonify
from marshmallow import ValidationError, EXCLUDE
from werkzeug.datastructures import FileStorage
from werkzeug.exceptions import BadRequest
from doku.models import db
from doku.models.document ... | code_fim | medium | {
"lang": "python",
"repo": "pbehnke/doku",
"path": "/doku/blueprints/api/v1/stylesheet.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> style: Stylesheet = get_or_404(
db.session.query(Stylesheet).filter_by(id=stylesheet_id)
)
schema = StylesheetSchema(
unknown=EXCLUDE, session=db.session, instance=style, partial=True
)
data = dict(request.form.copy())
if request.json is not None:
data.upda... | code_fim | medium | {
"lang": "python",
"repo": "pbehnke/doku",
"path": "/doku/blueprints/api/v1/stylesheet.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mindspore-ai/models path: /research/cv/DecoMR/utils/objfile.py
# Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://... | code_fim | hard | {
"lang": "python",
"repo": "mindspore-ai/models",
"path": "/research/cv/DecoMR/utils/objfile.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> material = None
for line in open(filepath, "r"):
if line.startswith('#'): continue
values = line.split()
if not values: continue
if values[0] == 'v':
# v = map(float, values[1:4])
v = [float(x) for x in values[1:4]]
vertices.appen... | code_fim | hard | {
"lang": "python",
"repo": "mindspore-ai/models",
"path": "/research/cv/DecoMR/utils/objfile.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> vertices = []
normals = []
vt_texcoords = []
faces = []
material = None
for line in open(filepath, "r"):
if line.startswith('#'): continue
values = line.split()
if not values: continue
if values[0] == 'v':
# v = map(float, values[1:4])... | code_fim | hard | {
"lang": "python",
"repo": "mindspore-ai/models",
"path": "/research/cv/DecoMR/utils/objfile.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: scooter23/grins path: /mm/editor/ViewDialog.py
__version__ = "$Id$"
# A class to handle standard geometry loading and saving for views etc.
# This works both with BasicDialog or GLDialog as base class.
# Specify this as the first base class, before the *Dialog base class.
# (Now this also define... | code_fim | hard | {
"lang": "python",
"repo": "scooter23/grins",
"path": "/mm/editor/ViewDialog.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # views can override this to return their focus node
return None
#
def globalsetfocus(self, node):
# views can override this to allow their focus to be 'pushed'
pass
#
def fixtitle(self):
# views can override this to fix their title after the
... | code_fim | hard | {
"lang": "python",
"repo": "scooter23/grins",
"path": "/mm/editor/ViewDialog.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return
name = self.geom_name
posname = name + 'winpos'
sizename = name + 'winsize'
h, v = MMAttrdefs.getattr(self.root, posname)
width, height = MMAttrdefs.getattr(self.root, sizename)
self.last_geometry = h, v, width, height
# Experimental c... | code_fim | hard | {
"lang": "python",
"repo": "scooter23/grins",
"path": "/mm/editor/ViewDialog.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> string_cap = "\n SEARCH FILES BY REGULAR EXPRESSION IN REPO '{}' (Sample expresion is {})\n".format(
repository["name"], sample_regex)
print(string_cap)
find = FindStringV3(entries=tree_entries, owner=owner, repo=repository["name"])
search_result = find.find... | code_fim | hard | {
"lang": "python",
"repo": "crazy-djactor/github_graphql_repoinfo",
"path": "/get_files.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: crazy-djactor/github_graphql_repoinfo path: /get_files.py
import threading
from queue import Queue
from findstring import *
from recursive_tree import *
from get_repo import *
import json
class SearchThread(threading.Thread):
def __init__(self, que, find_v4_in, entry, search_string, root_... | code_fim | hard | {
"lang": "python",
"repo": "crazy-djactor/github_graphql_repoinfo",
"path": "/get_files.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("\n SEARCH STRING IN FILTERED FILES IN REPO '{}' (Sample string is {})\n".format(repository["name"],
sample_search_string))
find_v4 = FindString(owner, repository["name"], [], "")
... | code_fim | hard | {
"lang": "python",
"repo": "crazy-djactor/github_graphql_repoinfo",
"path": "/get_files.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: azavea/raster-vision path: /rastervision_pytorch_backend/rastervision/pytorch_backend/pytorch_learner_backend_config.py
from typing import Optional, List
import logging
from rastervision.pipeline.config import (register_config, Field)
from rastervision.pipeline.file_system import get_tmp_dir
fro... | code_fim | hard | {
"lang": "python",
"repo": "azavea/raster-vision",
"path": "/rastervision_pytorch_backend/rastervision/pytorch_backend/pytorch_learner_backend_config.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> raise NotImplementedError()
def filter_commands(self, commands: List[str]) -> List[str]:
nochip = isinstance(self.data, GeoDataConfig)
if nochip and 'chip' in commands:
commands = [c for c in commands if c != 'chip']
return commands
def get_img_channel... | code_fim | hard | {
"lang": "python",
"repo": "azavea/raster-vision",
"path": "/rastervision_pytorch_backend/rastervision/pytorch_backend/pytorch_learner_backend_config.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> subprocess.call(self.args)
return 0
class Choice(Item):
"""asks what they would like to do, and acts accordingly"""
def __init__(self, msg="continue?", opts={'y': lambda: 0, 'n': lambda: 1}, ignorecase=True):
self.msg = self.form(msg, opts)
self.opts = _CaseInsen... | code_fim | hard | {
"lang": "python",
"repo": "Michael78912/tbip",
"path": "/tbip/uiutils/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Michael78912/tbip path: /tbip/uiutils/__init__.py
"""this package is all the cross-UI "Items" for displaying
all of the things needed in an installer, a README, License, etc...
and a tool for actually installing itself.
"""
from enum import Enum
import getpass
import sys
import subprocess
import... | code_fim | hard | {
"lang": "python",
"repo": "Michael78912/tbip",
"path": "/tbip/uiutils/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Dethada/LSCVM-Tool path: /execute.py
#!/usr/bin/env python3
from typing import List, Dict
import argparse
import common
def add(stack: List[int]):
val1: int = stack.pop()
val2: int = stack.pop()
stack.append(val1 + val2)
def mul(stack: List[int]):
val1: int = stack.pop()
v... | code_fim | hard | {
"lang": "python",
"repo": "Dethada/LSCVM-Tool",
"path": "/execute.py",
"mode": "psm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
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