text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> input_ = self.history.get_workflow_input()
for values in input_.values():
for k,v in values.items():
if 'decider_spec' in k:
return floto.specs.DeciderSpec.from_json(v)<|fim_prefix|># repo: diogoaurelio/floto path: /floto/decider/dynamic_dec... | code_fim | medium | {
"lang": "python",
"repo": "diogoaurelio/floto",
"path": "/floto/decider/dynamic_decider.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: scbedd/azure-sdk-for-python path: /sdk/agrifood/azure-agrifood-farming/azure/agrifood/farming/aio/operations/_attachments_operations.py
farmer.
:param farmer_id: ID of the associated farmer.
:type farmer_id: str
:param resource_ids: Resource Ids of the resource.
... | code_fim | hard | {
"lang": "python",
"repo": "scbedd/azure-sdk-for-python",
"path": "/sdk/agrifood/azure-agrifood-farming/azure/agrifood/farming/aio/operations/_attachments_operations.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> delete.metadata = {'url': '/farmers/{farmerId}/attachments/{attachmentId}'} # type: ignore
async def download(
self,
farmer_id: str,
attachment_id: str,
**kwargs: Any
) -> IO:
"""Downloads and returns attachment as response for the given input filePath... | code_fim | hard | {
"lang": "python",
"repo": "scbedd/azure-sdk-for-python",
"path": "/sdk/agrifood/azure-agrifood-farming/azure/agrifood/farming/aio/operations/_attachments_operations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> t.add([Note(0, (1, 4)), Note(1, (1, 4)), Note(-1, (1, 4))])
assert list(t) == [
(Signature(0, 1), Note(0, (1, 4))),
(Signature(1, 4), Note(-1, (1, 4))),
(Signature(1, 4), Note(0, (1, 4))),
(Signature(1, 4), Note(1, (1, 4))),
]
t.add(Note(42, (8, 1)), (13, 1... | code_fim | hard | {
"lang": "python",
"repo": "Aozhi/melodia",
"path": "/tests/melodia/core/test_track.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Aozhi/melodia path: /tests/melodia/core/test_track.py
import random
import pytest
from melodia.core import Track, Signature, Note
def random_track():
track = Track(signature=(random.randint(0, 100), 16))
for _ in range(random.randint(100, 300)):
note = Note(random.randint(-10... | code_fim | hard | {
"lang": "python",
"repo": "Aozhi/melodia",
"path": "/tests/melodia/core/test_track.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MLDL/uninas path: /uninas/optimization/estimators/net.py
"""
common estimator (metric) utils to rank different networks (architecture subsets of a super network)
"""
import torch
from uninas.methods.abstract import AbstractMethod
from uninas.models.networks.uninas.search import SearchUninasNetwo... | code_fim | hard | {
"lang": "python",
"repo": "MLDL/uninas",
"path": "/uninas/optimization/estimators/net.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@Register.hpo_estimator(requires_trainer=True, requires_method=True)
class NetValueEstimator(AbstractNetEstimator):
"""
An Estimator for a value returned by forward passes (loss, accuracy, ...)
"""
def __init__(self, *args_, **kwargs_):
# can set self.net_kwargs to account for pa... | code_fim | hard | {
"lang": "python",
"repo": "MLDL/uninas",
"path": "/uninas/optimization/estimators/net.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: coolsnake/JupyterNotebook path: /new_algs/Graph+algorithms/Dijkstra's+algorithm/digraph.py
from math import inf
from terminaltables import AsciiTable
from timeit import default_timer as timer
# This method takes in the node set, the set of predecesors to each node, and
# their distance to each n... | code_fim | hard | {
"lang": "python",
"repo": "coolsnake/JupyterNotebook",
"path": "/new_algs/Graph+algorithms/Dijkstra's+algorithm/digraph.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> start = timer()
# initializing the 2D distance matrix
node_list = list(self.node_set)
dis_matrix = []
for row_index in range(len(node_list)):
temp_row = []
for column_index in range(len(node_list)):
tail = node_list[row_index... | code_fim | hard | {
"lang": "python",
"repo": "coolsnake/JupyterNotebook",
"path": "/new_algs/Graph+algorithms/Dijkstra's+algorithm/digraph.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> hl = len(haystack)
nl = len(needle)
if nl == 0:
return 0
for i in range(hl-nl+1):
if haystack[i] == needle[0]:
for i2 in range(0,nl):
if needle[i2] != haystack[i+i2]:
break
... | code_fim | hard | {
"lang": "python",
"repo": "we1are1adc/leetcodeRecord",
"path": "/28.实现-str-str.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: we1are1adc/leetcodeRecord path: /28.实现-str-str.py
#
# @lc app=leetcode.cn id=28 lang=python3
#
# [28] 实现 strStr()
#
<|fim_suffix|> hl = len(haystack)
nl = len(needle)
if nl == 0:
return 0
for i in range(hl-nl+1):
if haystack[i] == needle[0]:... | code_fim | hard | {
"lang": "python",
"repo": "we1are1adc/leetcodeRecord",
"path": "/28.实现-str-str.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: idapython/src path: /tools/inject_pydoc.py
node.findall("enumvalue") if get_enums else None
if brief_node is None and \
detailed_node is None and \
enum_nodes is None:
return None
plist = []
for pnode in node.findall("param"):
... | code_fim | hard | {
"lang": "python",
"repo": "idapython/src",
"path": "/tools/inject_pydoc.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> visitor = pydoc_visitor_t(self.classes, self.functions, self.variables)
for pydoc in pydocs:
try:
log_verb("swig_pydoc_collector_t: parsing clob %s" % pydoc)
tree = ast.parse(pydoc)
except Exception as ex:
message = e... | code_fim | hard | {
"lang": "python",
"repo": "idapython/src",
"path": "/tools/inject_pydoc.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not indent and parse_prototypes:
for re in (self.RE_PROTO1, self.RE_PROTO2):
m = re.match(line)
if m:
self.parts = m.groups()
return self.PAT_PROTO
return self.PAT_TEXT
def _rest_after_colon(self, ... | code_fim | hard | {
"lang": "python",
"repo": "idapython/src",
"path": "/tools/inject_pydoc.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ktp-forked-repos/py-algorithms path: /py_algorithms/data_structures/tree_node.py
from typing import Any
class TreeNode:
__slots__ = '_left', '_right', '_element'
<|fim_suffix|> return "#<{} e={} left={} right={}>" \
.format(self.__class__.__name__, self.element, self.lef... | code_fim | hard | {
"lang": "python",
"repo": "ktp-forked-repos/py-algorithms",
"path": "/py_algorithms/data_structures/tree_node.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def set_left(self, node: 'TreeNode') -> 'TreeNode':
self._left = node
return self
@property
def right(self) -> 'TreeNode':
return self._right
def set_right(self, node: 'TreeNode') -> 'TreeNode':
self._right = node
return self
@property
def... | code_fim | medium | {
"lang": "python",
"repo": "ktp-forked-repos/py-algorithms",
"path": "/py_algorithms/data_structures/tree_node.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def right(self) -> 'TreeNode':
return self._right
def set_right(self, node: 'TreeNode') -> 'TreeNode':
self._right = node
return self
@property
def element(self) -> Any:
return self._element
def __repr__(self):
return "#<{} e={} ... | code_fim | medium | {
"lang": "python",
"repo": "ktp-forked-repos/py-algorithms",
"path": "/py_algorithms/data_structures/tree_node.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JIAWea/rxbpn path: /rxbpn/observer/bufferobserver.py
import threading
from typing import Optional
from rx.core import typing
from rxbp.acknowledgement.ack import Ack
from rxbp.acknowledgement.acksubject import AckSubject
from rxbp.acknowledgement.continueack import ContinueAck, continue_ack
from... | code_fim | hard | {
"lang": "python",
"repo": "JIAWea/rxbpn",
"path": "/rxbpn/observer/bufferobserver.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> next_raw_state = RawBufferedStates.OnErrorOrDownStreamStopped()
with self.lock:
prev_state = self.state
self.state = next_raw_state
prev_meas_state = prev_state.get_measured_state(has_elements=False)
if not isinstance(prev_meas_state, BufferedStat... | code_fim | hard | {
"lang": "python",
"repo": "JIAWea/rxbpn",
"path": "/rxbpn/observer/bufferobserver.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jiji-online/neptune-cli path: /neptune/internal/common/utils/paths.py
#
# Copyright (c) 2016, deepsense.io
#
# 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 | medium | {
"lang": "python",
"repo": "jiji-online/neptune-cli",
"path": "/neptune/internal/common/utils/paths.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> abs_path = os.path.abspath(path)
norm_abs_path = normalize_path(abs_path)
return norm_abs_path
def make_path(dst, verbose=False):
mkpath(dst, verbose=verbose)
return dst<|fim_prefix|># repo: jiji-online/neptune-cli path: /neptune/internal/common/utils/paths.py
#
# Copyright (c) 2016... | code_fim | medium | {
"lang": "python",
"repo": "jiji-online/neptune-cli",
"path": "/neptune/internal/common/utils/paths.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return str(Path(p).resolve())
def getcwd():
return resolve(os.getcwd())
def join_paths(path, *paths):
joined_path = os.path.join(path, *paths)
norm_joined_path = normalize_path(joined_path)
return norm_joined_path
def absolute_path(path):
abs_path = os.path.abspath(path)
... | code_fim | hard | {
"lang": "python",
"repo": "jiji-online/neptune-cli",
"path": "/neptune/internal/common/utils/paths.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # save model, just in case
if rank == 0:
model_ref.save('temp')
return model, optimizer, scheduler, writer
if __name__ == "__main__":
"""
some test's
"""
# torch.cuda.empty_cache()
tnz = torch.empty(3, 15).random_(0, 4)
print(tnz)<|fim_prefix|># repo: muska... | code_fim | hard | {
"lang": "python",
"repo": "muskanmahajan486/pubtrends-review",
"path": "/pysrc/review/train/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # loss
loss = criter(
draft_logprobs,
target_ids,
)
# backward
grad_norm = backward_step(loss, optimizer, model, optimizer.clip_value, amp_enabled=cfg.amp_enabled)
grad_norm = 0 if (math.isinf(grad_norm) or math.isnan(grad_norm)) els... | code_fim | hard | {
"lang": "python",
"repo": "muskanmahajan486/pubtrends-review",
"path": "/pysrc/review/train/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: muskanmahajan486/pubtrends-review path: /pysrc/review/train/train.py
import math
import torch
import torch.distributed as distrib
import torch.nn as nn
from torch.optim.optimizer import Optimizer
from tqdm import tqdm
import pysrc.review.config as cfg
from pysrc.review.utils import get_enc_lr, ... | code_fim | hard | {
"lang": "python",
"repo": "muskanmahajan486/pubtrends-review",
"path": "/pysrc/review/train/train.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NeverLeft/DjangoAXF path: /App/migrations/0005_auto_20180526_1052.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.10 on 2018-05-26 10:52
from __future__ import unicode_literals
from django.db import migrations
<|fim_suffix|>
dependencies = [
('App', '0004_foodtype'),
]
... | code_fim | easy | {
"lang": "python",
"repo": "NeverLeft/DjangoAXF",
"path": "/App/migrations/0005_auto_20180526_1052.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.RenameField(
model_name='foodtype',
old_name='chiletypenames',
new_name='childypenames',
),
]<|fim_prefix|># repo: NeverLeft/DjangoAXF path: /App/migrations/0005_auto_20180526_1052.py
# -*- coding: utf-8 -*-
# Generated... | code_fim | medium | {
"lang": "python",
"repo": "NeverLeft/DjangoAXF",
"path": "/App/migrations/0005_auto_20180526_1052.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('App', '0004_foodtype'),
]
operations = [
migrations.RenameField(
model_name='foodtype',
old_name='chiletypenames',
new_name='childypenames',
),
]<|fim_prefix|># repo: NeverLeft/DjangoAXF path: /App/migrations/... | code_fim | easy | {
"lang": "python",
"repo": "NeverLeft/DjangoAXF",
"path": "/App/migrations/0005_auto_20180526_1052.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Transformation(object):
def __init__(self, is_gray, k_90_rotate):
self.gray = is_gray
self.k_90_rotate = k_90_rotate
def __call__(self, x):
res_x = x
if self.gray:
if x.shape[2] == 1:
pass # input is gray
elif x.shape[2... | code_fim | hard | {
"lang": "python",
"repo": "wogong/pt-tiae",
"path": "/transformations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wogong/pt-tiae path: /transformations.py
import abc
import itertools
import numpy as np
from keras.preprocessing.image import apply_affine_transform
from scipy.ndimage.interpolation import rotate as rt
import keras.backend as K
class AbstractTransformer(abc.ABC):
def __init__(self):
... | code_fim | hard | {
"lang": "python",
"repo": "wogong/pt-tiae",
"path": "/transformations.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for line in self.lines_fast:
f = line.lstrip().split()
if (len(f) < 2):
continue
if (f[1] == 'PtfmFile' and self.ptfm_file == None):
self.ptfm_file = f[0][1:-1]
if (f[1] == 'TwrFile' and self.twr_file == None):
... | code_fim | hard | {
"lang": "python",
"repo": "xiaoyao79/AeroelasticSE",
"path": "/src/AeroelasticSE/runFAST.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Write the new platform file
Parameters
self.lines_ptfm are the unmodified lines of the platform file
fstDict may contain location of WAMITFile, also may contain "PlatformDir" to change angle of platform
"""
if self.ptfm_file == None:
return... | code_fim | hard | {
"lang": "python",
"repo": "xiaoyao79/AeroelasticSE",
"path": "/src/AeroelasticSE/runFAST.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xiaoyao79/AeroelasticSE path: /src/AeroelasticSE/runFAST.py
one:
hdr, out = self.parseFASTout(directory)
if (out == None):
fname = self.runname + '.out'
sys.stderr.write("output param %s does not exist in %s\n" % (paramname, fname))
... | code_fim | hard | {
"lang": "python",
"repo": "xiaoyao79/AeroelasticSE",
"path": "/src/AeroelasticSE/runFAST.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>for object in object_class:
pre = []
rec = []
for item in th:
print("class: %d"%object)
print("th: %f"%item)
full_one(item,object)
pre_path = prefix + '/' + 'pre_' + str(object) + '.npy'
rec_path = prefix + '/' + 'rec_' + str(object) + '.npy'
np.save(pre_p... | code_fim | hard | {
"lang": "python",
"repo": "Spritea/pytorch-semseg-fp16-one-titan",
"path": "/get_score/full_para_multiclass.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def full_one(th,object):
running_metrics_val.reset()
pool=ThreadPool(26)
pool.starmap(backbone,zip(range(len(Tensor_Str)),itertools.repeat(th),itertools.repeat(object)))
pool.close()
pool.join()
acc, cls_pre, cls_rec, cls_f1, cls_iu, hist = running_metrics_val.get_scores()
pr... | code_fim | hard | {
"lang": "python",
"repo": "Spritea/pytorch-semseg-fp16-one-titan",
"path": "/get_score/full_para_multiclass.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Spritea/pytorch-semseg-fp16-one-titan path: /get_score/full_para_multiclass.py
import cv2 as cv
from get_score import util
import numpy as np
import time
from pathlib import Path
import natsort
from get_score.metrics_my import runningScore
from tqdm import tqdm
from multiprocessing.dummy import ... | code_fim | hard | {
"lang": "python",
"repo": "Spritea/pytorch-semseg-fp16-one-titan",
"path": "/get_score/full_para_multiclass.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nphard001/ADL-Final path: /fashion_retrieval/__init__.py
from fashion_retrieval import ranker
from fashion_retriev<|fim_suffix|>
from fashion_retrieval import model
from fashion_retrieval import sim_user
from fashion_retrieval import train_rl<|fim_middle|>al import syn_user
from fashion_retrieval... | code_fim | easy | {
"lang": "python",
"repo": "nphard001/ADL-Final",
"path": "/fashion_retrieval/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
from fashion_retrieval import model
from fashion_retrieval import sim_user
from fashion_retrieval import train_rl<|fim_prefix|># repo: nphard001/ADL-Final path: /fashion_retrieval/__init__.py
from fashion_retrieval import ranker
from fashion_retriev<|fim_middle|>al import syn_user
from fashion_retrieval... | code_fim | easy | {
"lang": "python",
"repo": "nphard001/ADL-Final",
"path": "/fashion_retrieval/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>al import sim_user
from fashion_retrieval import train_rl<|fim_prefix|># repo: nphard001/ADL-Final path: /fashion_retrieval/__init__.py
from fashion_retrieval import ranker
from fashion_retriev<|fim_middle|>al import syn_user
from fashion_retrieval import train_sl
from fashion_retrieval import model
from... | code_fim | medium | {
"lang": "python",
"repo": "nphard001/ADL-Final",
"path": "/fashion_retrieval/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jlmasson/taller7-bootstrap path: /docs/recetas/css/arena.py
n = int(input("Ingrese número de filas: "))
c = input("Ingrese caracter: ")
for i in range(1, n+1):
for j in range(1, n+1):
if i == 1 or i == n:
print(<|fim_suffix|>i and j < n + 1 - i:
print(c, end="")
else:
print(" ", en... | code_fim | medium | {
"lang": "python",
"repo": "jlmasson/taller7-bootstrap",
"path": "/docs/recetas/css/arena.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>i and j < n + 1 - i:
print(c, end="")
else:
print(" ", end="")
print()<|fim_prefix|># repo: jlmasson/taller7-bootstrap path: /docs/recetas/css/arena.py
n = int(input("Ingrese número de filas: "))
c = input("Ingrese caracter: ")
fo<|fim_middle|>r i in range(1, n+1):
for j in range(1, n+1):
if... | code_fim | medium | {
"lang": "python",
"repo": "jlmasson/taller7-bootstrap",
"path": "/docs/recetas/css/arena.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if current_user.is_merchant():
return redirect(url_for('merchant.index'))
elif current_user.is_admin():
return redirect(url_for('admin.index'))
elif current_user.is_vendor():
return redirect(url_for('vendor.index'))
else:
return redirect(url_for('account.lo... | code_fim | easy | {
"lang": "python",
"repo": "msgpo/reading-terminal-market",
"path": "/app/main/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: msgpo/reading-terminal-market path: /app/main/views.py
from flask import redirect, url_for
from . import main
from flask.ext.login import current_user
<|fim_suffix|> if current_user.is_merchant():
return redirect(url_for('merchant.index'))
elif current_user.is_admin():
ret... | code_fim | easy | {
"lang": "python",
"repo": "msgpo/reading-terminal-market",
"path": "/app/main/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> W = np.asarray(
np.random.uniform(
low=-4.*np.sqrt(6. / (n_in + n_out)),
high=4.*np.sqrt(6. / (n_in + n_out)),
size=(n_in, n_out)
),
dtype=theano.config.floatX
)
return W
def init_norm(n_in, n_out):
W = np.asarray(np.random.randn(n_in, n_out)*0.1, dtype=theano.config.floatX)
return... | code_fim | hard | {
"lang": "python",
"repo": "miradel51/biLSTM-theano",
"path": "/src/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: miradel51/biLSTM-theano path: /src/utils.py
import theano
import numpy as np
def init_ortho(size):
return np.concatenate(
[ ortho_matrix( size ),
ortho_matrix( size ),
ortho_matrix( size ),
ortho_matrix( size ), ], axis=1).astype(theano.config.floatX)
def init_uniform(n_in, ... | code_fim | medium | {
"lang": "python",
"repo": "miradel51/biLSTM-theano",
"path": "/src/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return False
if __name__ == '__main__':
nums = [0]
k = 0
print check_sub_array_sum(nums, k)<|fim_prefix|># repo: tonylixu/devops path: /algorithm/523-continuous-subarray-sum/solution2.py
def check_sub_array_sum(nums, k):
# Key is reminder, value is index
dmap = {0:-1}
total = ... | code_fim | medium | {
"lang": "python",
"repo": "tonylixu/devops",
"path": "/algorithm/523-continuous-subarray-sum/solution2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tonylixu/devops path: /algorithm/523-continuous-subarray-sum/solution2.py
def check_sub_array_sum(nums, k):
# Key is reminder, value is index
dmap = {0:-1}
total = 0
<|fim_suffix|> return False
if __name__ == '__main__':
nums = [0]
k = 0
print check_sub_array_sum(nums... | code_fim | hard | {
"lang": "python",
"repo": "tonylixu/devops",
"path": "/algorithm/523-continuous-subarray-sum/solution2.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NULLCT/LOMC path: /src/data/970.py
import sys
sys.setrecursionlimit(10**8)
from typing import NamedTuple
from operator import itemgetter, attrgetter
from collections import defaultdict, deque, Counter
from itertools import combinations, combinations_with_replacement, permutations
import heapq
im... | code_fim | medium | {
"lang": "python",
"repo": "NULLCT/LOMC",
"path": "/src/data/970.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> seen = [False] * N
score = [-1] * N
score[0] = 0
stack = [0]
while stack:
v = stack.pop()
seen[v] = True
for u in Edge[v]:
if seen[u]:
continue
score[u] = score[v] + 1
stack.append(u)
for _ in range(Q):
... | code_fim | hard | {
"lang": "python",
"repo": "NULLCT/LOMC",
"path": "/src/data/970.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>freeSpace = TOTAL_SIZE - root.folderSize()
neededClearance = NEEDED_FREE - freeSpace
foldersBySize = sorted(allFolders, key=lambda x : x.folderSize())
for f in foldersBySize:
if f.folderSize() >= neededClearance:
print("Folder to delete and size:", f.name, f.folderSize())
break
# def example_... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/Reactors",
"path": "/coding-languages-frameworks/code-garden-advent-of-code-2022/day7.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>root = Folder("/")
workingDir = root
allFolders = [root]
for line in data[1:]:
if line.startswith("$"):
# is a command
if line.startswith("$ cd"):
destination = line.split(" ")[2]
if destination == "..":
workingDir = workingDir.parent
... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/Reactors",
"path": "/coding-languages-frameworks/code-garden-advent-of-code-2022/day7.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: microsoft/Reactors path: /coding-languages-frameworks/code-garden-advent-of-code-2022/day7.py
data = [x.strip() for x in open("day7-example.txt").readlines()]
class Folder:
def __init__(self, name, parent=None):
self.name = name
self.subfolders = {}
self.files = {}
... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/Reactors",
"path": "/coding-languages-frameworks/code-garden-advent-of-code-2022/day7.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#IMPORTING SequenceMatcher FROM difflib
from difflib import SequenceMatcher
#CALCULATING OVERALL SIMILARITY SCORE
score = SequenceMatcher(None, concat1, concat2)
#OUTPUT
print("Similarity of the two given files is:")
print(score.ratio())<|fim_prefix|># repo: Tomnearly30/CS590-CLS-project path... | code_fim | hard | {
"lang": "python",
"repo": "Tomnearly30/CS590-CLS-project",
"path": "/compare.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Tomnearly30/CS590-CLS-project path: /compare.py
#-----sequenceCompare-----
#This is used to find the similarity percentage of two fasta files
#ACCEPTING INPUT FILES
import sys
file1 = sys.argv[1]
file2 = sys.argv[2]
#OPENING FIRST FILE AND EXCLUDING LABELS
with open(file1) as f:
fa... | code_fim | medium | {
"lang": "python",
"repo": "Tomnearly30/CS590-CLS-project",
"path": "/compare.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#OPENING SECOND FILE AND EXCLUDING LABELS
with open(file2) as f:
fasta2 = f.readlines()
i=0
while i < len(fasta2):
if fasta2[i].find(">hsa") > -1:
fasta2.pop(i)
i=i+1
#REMOVING SPACES AND CONCATENATING SECOND FILE
fasta2 = [x.strip() for x in fasta2]
concat2 = "".join(fasta2)... | code_fim | medium | {
"lang": "python",
"repo": "Tomnearly30/CS590-CLS-project",
"path": "/compare.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>print('测试 chip')
get_similar_tokens('chip', 3, glove)
print('测试 china')
get_similar_tokens('china', 3, glove)
print('求类比词，比如 man vs women 等于 son vs daughter')
def get_analogy(token_a, token_b, token_c, embed):
vecs = [embed.vectors[embed.stoi[t]] for t in [token_a, token_b, token_c]]
x = vecs[1... | code_fim | hard | {
"lang": "python",
"repo": "ZixuanKe/deep-learning-note",
"path": "/d2l/50_similar_words.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ZixuanKe/deep-learning-note path: /d2l/50_similar_words.py
import torch
import torchtext.vocab as vocab
print('查看已支持的预训练模型')
print(vocab.pretrained_aliases.keys())
print('下载 glove.6B.50d，比较大 800m，会下载全部 glove，但其实我们要的是 100m')
# 下载地址 http://nlp.stanford.edu/data/glove.6B.zip
glove = vocab.GloVe(na... | code_fim | hard | {
"lang": "python",
"repo": "ZixuanKe/deep-learning-note",
"path": "/d2l/50_similar_words.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: smly/nips17_adversarial_attack path: /defense/defense_xgb.py
# -*- coding: utf-8 -*-
import sys
import re
from collections import Counter
import numpy as np
import pandas as pd
import torch
from torch.autograd import Variable
from torchvision.models.densenet import densenet121
import torch.nn.fu... | code_fim | hard | {
"lang": "python",
"repo": "smly/nips17_adversarial_attack",
"path": "/defense/defense_xgb.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return f(input_, self.params)
def _predict_top5(model_i, probs, num_inst, num_classes, st_idx):
probs = F.softmax(probs)
probs = probs.data.cpu().numpy().reshape(
(num_inst, num_classes))
topk_preds = []
topk_probs = []
for k in range(5):
top1_preds = probs.a... | code_fim | hard | {
"lang": "python",
"repo": "smly/nips17_adversarial_attack",
"path": "/defense/defense_xgb.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yehengchen/Object-Detection-and-Tracking path: /OneStage/yolo/tools/video2frame.py
import cv2
image_folder = './mask_face'
video_name = './cut_test.m4v'
vc = <|fim_suffix|>else:
rval=False
while rval:
rval,frame=vc.read()
cv2.imwrite('./mask_face/IMG_'+str(c)+'.jpg',frame)
c=c+1... | code_fim | medium | {
"lang": "python",
"repo": "yehengchen/Object-Detection-and-Tracking",
"path": "/OneStage/yolo/tools/video2frame.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>mask_face/IMG_'+str(c)+'.jpg',frame)
c=c+1
cv2.waitKey(1)
vc.release()<|fim_prefix|># repo: yehengchen/Object-Detection-and-Tracking path: /OneStage/yolo/tools/video2frame.py
import cv2
image_folder = './mask_face'
video_name = './cut_test.m4v'
vc = <|fim_middle|>cv2.VideoCapture(video_name)
c ... | code_fim | medium | {
"lang": "python",
"repo": "yehengchen/Object-Detection-and-Tracking",
"path": "/OneStage/yolo/tools/video2frame.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Query API
search_result = CargoTimeSeries().search(
# We're only interested in movements into China
filter_destinations=china,
# We're looking at daily imports
timeseries_frequency="day",
# We want 'b' for barrels here
timeseries_unit="b",
... | code_fim | medium | {
"lang": "python",
"repo": "amirvortexa/python-sdk",
"path": "/docs/examples/5_chinese_daily_imports.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Find Crude/Condensates ID
crude_condensates = [
p.id
for p in Products().search(term="Crude/Condensates").to_list()
if p.name == "Crude/Condensates"
]
# Query API
search_result = CargoTimeSeries().search(
# We're only interested in movements into Chin... | code_fim | medium | {
"lang": "python",
"repo": "amirvortexa/python-sdk",
"path": "/docs/examples/5_chinese_daily_imports.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: amirvortexa/python-sdk path: /docs/examples/5_chinese_daily_imports.py
"""
Let's retrieve the daily sum of Chinese Crude/Condensate imports, over the last year.
The below script returns:
| | key | value | count |
|----:|:-------------------------|---------:|-------... | code_fim | hard | {
"lang": "python",
"repo": "amirvortexa/python-sdk",
"path": "/docs/examples/5_chinese_daily_imports.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # calculate surface energy and mass balance
sp.surface_physics.surface_energy_and_mass_balance(state,par,bnd,t,y)
# write output for last year
if y == nyears-1:
y1['tsurf'][:,t] = state.tsurf
y1['alb'][:,t] = state.alb
y1['swnet'][:,t] =... | code_fim | hard | {
"lang": "python",
"repo": "mkrapp/semic",
"path": "/f2py/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># populate validation data
y2['tsurf'] = vali[:,0:nx].T
y2['alb'] = vali[:,nx:2*nx].T
y2['swnet'] = vali[:,2*nx:3*nx].T
y2['smb'] = vali[:,3*nx:4*nx].T
y2['melt'] = vali[:,4*nx:5*nx].T
y2['acc'] = vali[:,5*nx:6*nx].T
y2['shf'] = vali[:,6*nx:7*nx].T
y2['lhf'] = vali[:,7*nx:].T
# loop nyears ove... | code_fim | hard | {
"lang": "python",
"repo": "mkrapp/semic",
"path": "/f2py/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mkrapp/semic path: /f2py/test.py
import numpy as np
import matplotlib.pyplot as plt
import SurfacePhysics as sp
# read data
pre = 'transect'
forc = np.loadtxt('../example/data/'+pre+'_input.txt')
vali = np.loadtxt('../example/data/'+pre+'_output.txt')
var_names = ['tsurf', 'alb', 'swnet', 'smb',... | code_fim | hard | {
"lang": "python",
"repo": "mkrapp/semic",
"path": "/f2py/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hanlsin/udacity_PFwithPy path: /inheritance/inheritance.py
class Parent():
""" This is a parent class to learn how to use inheritance of classes"""
def __init__(self, last_name, eye_color):
<|fim_suffix|> print("Last Name: " + self.last_name)
print("Eye Color: " + self.eye... | code_fim | medium | {
"lang": "python",
"repo": "hanlsin/udacity_PFwithPy",
"path": "/inheritance/inheritance.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>billy_cyrus.show_info()
miley_cyrus = Child("Cyrus", "Blue", 3)
print(miley_cyrus.last_name)
print(miley_cyrus.number_of_toys)
miley_cyrus.show_info()<|fim_prefix|># repo: hanlsin/udacity_PFwithPy path: /inheritance/inheritance.py
class Parent():
""" This is a parent class to learn how to use inher... | code_fim | hard | {
"lang": "python",
"repo": "hanlsin/udacity_PFwithPy",
"path": "/inheritance/inheritance.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: martindurant/gcsfs path: /gcsfs/__init__.py
from ._version import get_versions
<|fim_suffix|>__all__ = ["GCSFileSystem", "GCSMap"]<|fim_middle|>__version__ = get_versions()["version"]
del get_versions
from .core import GCSFileSystem
from .mapping import GCSMap
| code_fim | medium | {
"lang": "python",
"repo": "martindurant/gcsfs",
"path": "/gcsfs/__init__.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>__all__ = ["GCSFileSystem", "GCSMap"]<|fim_prefix|># repo: martindurant/gcsfs path: /gcsfs/__init__.py
from ._version import get_versions
<|fim_middle|>__version__ = get_versions()["version"]
del get_versions
from .core import GCSFileSystem
from .mapping import GCSMap
| code_fim | medium | {
"lang": "python",
"repo": "martindurant/gcsfs",
"path": "/gcsfs/__init__.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='category',
name='description',
field=models.TextField(verbose_name='Description'),
),
]<|fim_prefix|># repo: joeig/memodrop path: /categories/migrations/0008_auto_20180331_1348.py
# -*- coding: u... | code_fim | medium | {
"lang": "python",
"repo": "joeig/memodrop",
"path": "/categories/migrations/0008_auto_20180331_1348.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: joeig/memodrop path: /categories/migrations/0008_auto_20180331_1348.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.10 on 2018-03-31 13:48
from __future__ import unicode_literals
from django.db import migrations, models
<|fim_suffix|>
dependencies = [
('categories', '0007_aut... | code_fim | easy | {
"lang": "python",
"repo": "joeig/memodrop",
"path": "/categories/migrations/0008_auto_20180331_1348.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
('categories', '0007_auto_20180318_2307'),
]
operations = [
migrations.AlterField(
model_name='category',
name='description',
field=models.TextField(verbose_name='Description'),
),
]<|fim_prefix|># repo: joeig/m... | code_fim | medium | {
"lang": "python",
"repo": "joeig/memodrop",
"path": "/categories/migrations/0008_auto_20180331_1348.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>urlpatterns += patterns('',
url(r'^admin/', include(admin.site.urls)),
url(r'^accounts/', include('allauth.urls')),
)
urlpatterns = += patterns('',
url(r'^$', 'appmodel_site.views.showcase', name='showcase'),
url(r'demo$', TemplateView.as_view(template_name="static/info/demo.html")),
)<|f... | code_fim | medium | {
"lang": "python",
"repo": "paulocheque/python-django-bootstrap",
"path": "/toolbox/management/commands/appmodel/urls.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: paulocheque/python-django-bootstrap path: /toolbox/management/commands/appmodel/urls.py
from django.conf.urls import patterns, include, url
from django.contrib import admin
from django.views.generic import TemplateView
from tastypie.api import Api
<|fim_suffix|>v1_api = Api(api_name='v1')
v1_ap... | code_fim | medium | {
"lang": "python",
"repo": "paulocheque/python-django-bootstrap",
"path": "/toolbox/management/commands/appmodel/urls.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Send the Experiment Description to the Main node and start the Experiment.
:param experiment_description: Dict. Experiment Description that will be sent to the Main node.
:param wait_for_results: If ``False`` - client will only send an Experiment Description and r... | code_fim | hard | {
"lang": "python",
"repo": "ITS-Zah/BRISE2",
"path": "/benchmark/shared_tools.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def chown_files_in_dir(directory):
for root, dirs, files in os.walk(directory):
for f in files:
os.chown(os.path.abspath(os.path.join(root, f)),
int(os.environ['host_uid']), int(os.environ['host_gid']))
break # do not traverse recursively
def check... | code_fim | hard | {
"lang": "python",
"repo": "ITS-Zah/BRISE2",
"path": "/benchmark/shared_tools.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ITS-Zah/BRISE2 path: /benchmark/shared_tools.py
import sys
import pickle
import random
import requests
import datetime
import socketio # high-level transport protocol
import logging
import socket # low-level (3-4th levels of OSI model), binding IP and port
import json
import time
import re
impor... | code_fim | hard | {
"lang": "python",
"repo": "ITS-Zah/BRISE2",
"path": "/benchmark/shared_tools.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GuyRoosevelt/Minecraft-Dungeons-The-Awakening path: /enemies.py
class Enemy:
def __init__(self):
raise NotImplementedError("Do not create raw Enemy objects.")
def __str__(self):
return self.name
def is_alive(self):
return self.hp > 0
class Vindicat... | code_fim | medium | {
"lang": "python",
"repo": "GuyRoosevelt/Minecraft-Dungeons-The-Awakening",
"path": "/enemies.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class RedstoneGolem(Enemy):
def __init__(self):
self.name = "Redstone Golem"
self.hp = 150
self.damage = 7
class TrainingDummy(Enemy):
def __init__(self):
self.name = "Training Dummy"
self.hp = float('inf')
self.damage = 0<|fim_prefix|># repo: GuyR... | code_fim | hard | {
"lang": "python",
"repo": "GuyRoosevelt/Minecraft-Dungeons-The-Awakening",
"path": "/enemies.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: adobe-type-tools/opentype-svg path: /tests/shared_utils_test.py
# Copyright 2018 Adobe. All rights reserved.
import os
import shutil
import sys
import tempfile
import unittest
from io import StringIO
from opentypesvg import utils as shared_utils
class SharedUtilsTest(unittest.TestCase):
... | code_fim | hard | {
"lang": "python",
"repo": "adobe-type-tools/opentype-svg",
"path": "/tests/shared_utils_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.reset_stream(stream)
shared_utils.final_message(2)
self.assertEqual(stream.getvalue().strip(), '2 SVG files saved.')
def test_create_folder(self):
folder_path = 'new_folder'
shared_utils.create_folder(folder_path)
self.assertTrue(os.path.isdir(fold... | code_fim | hard | {
"lang": "python",
"repo": "adobe-type-tools/opentype-svg",
"path": "/tests/shared_utils_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def verbosePref(self):
"""Return setting of owner's verbosePref at level specified in its PreferenceEntry.level
:param level:
:return:
"""
# If the level of the object is below the Preference level,
# recursively calls base (super) class... | code_fim | hard | {
"lang": "python",
"repo": "PrincetonUniversity/PsyNeuLink",
"path": "/psyneulink/core/globals/preferences/basepreferenceset.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @verbosePref.setter
def verbosePref(self, setting):
"""Assign setting to owner's verbosePref
:param setting:
:return:
"""
self.set_preference(candidate_info=setting, pref_ivar_name=VERBOSE_PREF)
@property
def paramValidationPref(self):
"""Re... | code_fim | hard | {
"lang": "python",
"repo": "PrincetonUniversity/PsyNeuLink",
"path": "/psyneulink/core/globals/preferences/basepreferenceset.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PrincetonUniversity/PsyNeuLink path: /psyneulink/core/globals/preferences/basepreferenceset.py
referencesDict = {
PREFERENCE_SET_NAME: TYPE_DEFAULT_PREFERENCES,
VERBOSE_PREF: PreferenceEntry(False, PreferenceLevel.TYPE),
PARAM_VALIDATION_PREF: PreferenceEntry(True, PreferenceLevel.TYP... | code_fim | hard | {
"lang": "python",
"repo": "PrincetonUniversity/PsyNeuLink",
"path": "/psyneulink/core/globals/preferences/basepreferenceset.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> driver.click_xpath(hamburger)
driver.wait_for_xpath_to_appear(dashboard)<|fim_prefix|># repo: skyportal/skyportal path: /skyportal/tests/frontend/test_frontpage.py
def test_foldable_sidebar(driver):
driver.get('/')
dashboard = '//p[contains(text(),"Dashboard")]'
sidebar_text = driver.... | code_fim | medium | {
"lang": "python",
"repo": "skyportal/skyportal",
"path": "/skyportal/tests/frontend/test_frontpage.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: skyportal/skyportal path: /skyportal/tests/frontend/test_frontpage.py
def test_foldable_sidebar(driver):
driver.get('/')
dashboard = '//p[contains(text(),"Dashboard")]'
sidebar_text = driver.wait_for_xpath(dashboard)
assert sidebar_text.is_displayed()
<|fim_suffix|> driver.cli... | code_fim | medium | {
"lang": "python",
"repo": "skyportal/skyportal",
"path": "/skyportal/tests/frontend/test_frontpage.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aihill/google-landmarks path: /prepare_train_data.py
#!/usr/bin/python3.6
""" Parses data, builds train/dev datasets, bakes data into big files. """
from typing import *
import os
from shutil import copyfile
import numpy as np, pandas as pd # type: ignore
from tqdm import tqdm ... | code_fim | hard | {
"lang": "python",
"repo": "aihill/google-landmarks",
"path": "/prepare_train_data.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # print("copy '%s' to '%s'" % (src, dst))
os.makedirs(directory, exist_ok=True)
try:
copyfile(src, dst, follow_symlinks=True)
except FileNotFoundError:
pass<|fim_prefix|># repo: aihill/google-landmarks path: /prepare_train_data.py
#!/usr/bin/python... | code_fim | hard | {
"lang": "python",
"repo": "aihill/google-landmarks",
"path": "/prepare_train_data.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @classmethod
def dict_to_list(cls, deductions):
deductions_list = []
for deduction in deductions:
deductions_list.append({"payee": deduction, "points": deductions[deduction]})
return deductions_list
transactions = UserTransactions()
class TransactionsException... | code_fim | hard | {
"lang": "python",
"repo": "utkarshban/take-home-test",
"path": "/src/user_transactions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: utkarshban/take-home-test path: /src/user_transactions.py
import heapq
from collections import defaultdict
class UserTransactions:
def __init__(self):
self.transactions_heap = []
self.payer_points = defaultdict(int)
self.total_user_points = 0
def add_transaction(s... | code_fim | hard | {
"lang": "python",
"repo": "utkarshban/take-home-test",
"path": "/src/user_transactions.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> listofnumbers = [0,1,2,3,4,5,6,7,8,9,10,11,12]
userinput = int(input("give me a number between 0,12"))
numgreat = 0
numequal = 0
numsmall = 0
for element in listofnumbers:
if(element > userinput):
numgreat+=1
elif(element == userinput):
num... | code_fim | hard | {
"lang": "python",
"repo": "cs-fullstack-2019-spring/python-arraycollections-cw-tdude0175",
"path": "/array_cw1.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> nicknamelist ={"Jonathan":"John",
"Michael":"Mike",
"William":"Bill",
"Robert":"Rob"}
for x in nicknamelist:
print(f"{x} {nicknamelist[x]}")
print(nicknamelist["William"])
# Create an array of 5 numbers. Using a loop, print the elements in the array reverse ord... | code_fim | hard | {
"lang": "python",
"repo": "cs-fullstack-2019-spring/python-arraycollections-cw-tdude0175",
"path": "/array_cw1.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cs-fullstack-2019-spring/python-arraycollections-cw-tdude0175 path: /array_cw1.py
def main():
# problem1()
# problem2()
# problem3()
# problem4()
problem5()
# Create a function with the variable below. After you create the variable do the instructions below that.
#
# arrayFo... | code_fim | hard | {
"lang": "python",
"repo": "cs-fullstack-2019-spring/python-arraycollections-cw-tdude0175",
"path": "/array_cw1.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>['m2'] == 5.
metrics = metrics.reset()
metrics = metrics.update(m1=1., m2=1.)
assert metrics['m1'] == 1.
assert metrics['m2'] == 1.
metrics = metrics.reset()
with pytest.raises(ZeroDivisionError):
metrics['m1']<|fim_prefix|># repo: n2cholas/htn-ml-productivity-workshop pat... | code_fim | medium | {
"lang": "python",
"repo": "n2cholas/htn-ml-productivity-workshop",
"path": "/src/tests/test_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: n2cholas/htn-ml-productivity-workshop path: /src/tests/test_utils.py
import pytest
from utils import MetricsGroup
def test_metrics_group():
metrics = MetricsGroup('m1', 'm2')
met<|fim_suffix|>assert metrics['m2'] == 1.
metrics = metrics.reset()
with pytest.raises(ZeroDivisionEr... | code_fim | hard | {
"lang": "python",
"repo": "n2cholas/htn-ml-productivity-workshop",
"path": "/src/tests/test_utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>assert metrics['m2'] == 1.
metrics = metrics.reset()
with pytest.raises(ZeroDivisionError):
metrics['m1']<|fim_prefix|># repo: n2cholas/htn-ml-productivity-workshop path: /src/tests/test_utils.py
import pytest
from utils import MetricsGroup
def test_metrics_group():
metrics = Metri... | code_fim | hard | {
"lang": "python",
"repo": "n2cholas/htn-ml-productivity-workshop",
"path": "/src/tests/test_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mofhu/algorithm-workbook path: /chap3/run.py
from sys import argv
import os
script, source = argv
<|fim_suffix|>subprocess.run(["clang", source, '-Wall', '-o', source[:-3]+'o']) # clang -o
if source[:-3]+'in' in os.listdir():
print(script, source, "<", source[:-3] + 'in')
subprocess.r... | code_fim | easy | {
"lang": "python",
"repo": "mofhu/algorithm-workbook",
"path": "/chap3/run.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if source[:-3]+'in' in os.listdir():
print(script, source, "<", source[:-3] + 'in')
subprocess.run(["./"+ source[:-3]+'o'],
stdin=open(source[:-3]+'in')) # delete .cpp and add .in
else:
print(script, source)
subprocess.run(["./"+ source[:-3]+'o'])<|fim_prefix|># repo: m... | code_fim | medium | {
"lang": "python",
"repo": "mofhu/algorithm-workbook",
"path": "/chap3/run.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.