text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>
# alist = [54,26,45,32,87,23,55,3,67,23,23]
# bubble_sort(alist)
# print alist
alist=[20,30,40,90,50,60,70,80,100,110]
short_bubble_sort(alist)
print(alist)<|fim_prefix|># repo: jsz1/algorithms-and-data-structures path: /search/bubblesort.py
def bubble_sort(alist):
for num in range(len(alist)-1,0,-... | code_fim | hard | {
"lang": "python",
"repo": "jsz1/algorithms-and-data-structures",
"path": "/search/bubblesort.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># alist = [54,26,45,32,87,23,55,3,67,23,23]
# bubble_sort(alist)
# print alist
alist=[20,30,40,90,50,60,70,80,100,110]
short_bubble_sort(alist)
print(alist)<|fim_prefix|># repo: jsz1/algorithms-and-data-structures path: /search/bubblesort.py
def bubble_sort(alist):
for num in range(len(alist)-1,0,-1... | code_fim | hard | {
"lang": "python",
"repo": "jsz1/algorithms-and-data-structures",
"path": "/search/bubblesort.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jsz1/algorithms-and-data-structures path: /search/bubblesort.py
def bubble_sort(alist):
for num in range(len(alist)-1,0,-1):
for i in range(num):
if alist[i] > alist[i+1]:
temp = alist[i]
alist[i] = alist[i+1]
alist[i+1] = te... | code_fim | hard | {
"lang": "python",
"repo": "jsz1/algorithms-and-data-structures",
"path": "/search/bubblesort.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wurunduk/crashday-trk-blender-io path: /props/props.py
import bpy
class CDTRKProps(bpy.types.PropertyGroup):
author : bpy.props.StringProperty (
name = 'Author',
default = 'Author'
)
comment : bpy.props.StringProperty (
name ... | code_fim | hard | {
"lang": "python",
"repo": "wurunduk/crashday-trk-blender-io",
"path": "/props/props.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> width : bpy.props.IntProperty (
name = 'Width',
default = 5,
min = 3,
max = 90,
soft_max = 40
)
height : bpy.props.IntProperty (
name = 'Height',
default = 5,
min ... | code_fim | hard | {
"lang": "python",
"repo": "wurunduk/crashday-trk-blender-io",
"path": "/props/props.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KorewaLidesu/VoiceLab path: /Voicelab/toolkits/Voicelab/ScaleIntensityNode.py
from Voicelab.pipeline.Node import Node
from parselmouth.praat import call
from Voicelab.toolkits.Voicelab.VoicelabNode import VoicelabNode
# MANIPULATE PITCH NODE
# WARIO pipeline node for manipulating the pitch of a... | code_fim | medium | {
"lang": "python",
"repo": "KorewaLidesu/VoiceLab",
"path": "/Voicelab/toolkits/Voicelab/ScaleIntensityNode.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.args = {
"value": 70, # Positive number
"method": ("RMS (dB)", ["RMS (dB)", "Peak (-1, 1)"])
# todo check for legal values
}
# process: WARIO hook called once for each voice file.
def process(self):
value = self.args["value"]
... | code_fim | medium | {
"lang": "python",
"repo": "KorewaLidesu/VoiceLab",
"path": "/Voicelab/toolkits/Voicelab/ScaleIntensityNode.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NVIDIA/apex path: /apex/contrib/test/layer_norm/test_fast_layer_norm.py
import unittest
import torch
SKIP_TEST = None
try:
from apex.contrib.layer_norm.layer_norm import FastLayerNorm
import fast_layer_norm as fln
except ImportError as e:
SKIP_TEST = e
class GPUTimer:
def __in... | code_fim | hard | {
"lang": "python",
"repo": "NVIDIA/apex",
"path": "/apex/contrib/test/layer_norm/test_fast_layer_norm.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_run_benchmark(self):
for (S, B, hidden_size, runs) in (
(512, 32, 768, 1000),
(512, 32, 1024, 1000),
(512, 8, 4096, 1000),
(512, 8, 5120, 1000),
(512, 8, 6144, 1000),
(256, 2, 20480, 500),
(256, 2, 256... | code_fim | hard | {
"lang": "python",
"repo": "NVIDIA/apex",
"path": "/apex/contrib/test/layer_norm/test_fast_layer_norm.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> stream = torch.cuda.Stream()
with torch.cuda.stream(stream):
timer = GPUTimer(stream)
# warmup
for r in range(runs):
z, mu, rsigma = fln.ln_fwd(x, gamma, beta, epsilon)
timer.start()
for r in range(runs):
z, mu, rsigma = fln.ln_fwd... | code_fim | hard | {
"lang": "python",
"repo": "NVIDIA/apex",
"path": "/apex/contrib/test/layer_norm/test_fast_layer_norm.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|># Finally, define the route.
route = aws.apigatewayv2.Route("route",
api_id=api.id,
route_key="POST /uploads",
target=integration.id.apply(lambda id: f"integrations/{id}"),
)
# Define a role and policy allowing Lambda functions to log to CloudWatch.
lambda_role = aws.iam.Role("lambda-role",
... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/examples",
"path": "/aws-py-apigatewayv2-eventbridge/__main__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># Create an EventBridge target associating the event rule with the function.
lambda_target = aws.cloudwatch.EventTarget("lambda-target",
arn=lambda_function.arn,
rule=rule.name,
event_bus_name=bus.name,
)
# Give EventBridge permission to invoke the function.
lambda_permission = aws.lambda_.Pe... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/examples",
"path": "/aws-py-apigatewayv2-eventbridge/__main__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pulumi/examples path: /aws-py-apigatewayv2-eventbridge/__main__.py
# Copyright 2016-2022, Pulumi Corporation. All rights reserved.
import json
import pulumi
import pulumi_aws as aws
# Create an HTTP API.
api = aws.apigatewayv2.Api("example",
protocol_type="HTTP"
)
# Create a stage and set... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/examples",
"path": "/aws-py-apigatewayv2-eventbridge/__main__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Coldwave96/PentestingTools path: /padding.py
2Db3Db4Db5Db6Db7Db8Db9"
"Dc0Dc1Dc2Dc3Dc4Dc5Dc6Dc7Dc8Dc9Dd0Dd1Dd2Dd3Dd4Dd5Dd6Dd7Dd8Dd9De0De1De2De3De4De5De"
"6De7De8De9Df0Df1Df2Df3Df4Df5Df6Df7Df8Df9Dg0Dg1Dg2Dg3Dg4Dg5Dg6Dg7Dg8Dg9Dh0Dh1Dh2D"
"h3Dh4Dh5Dh6Dh7Dh8Dh9Di0Di1Di2Di3Di4Di5Di6Di7Di8Di... | code_fim | hard | {
"lang": "python",
"repo": "Coldwave96/PentestingTools",
"path": "/padding.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>2Vr3Vr4Vr5Vr6Vr7Vr8Vr9Vs0Vs1Vs2Vs3Vs4Vs5Vs6Vs7Vs8Vs9Vt0Vt1Vt2V"
"t3Vt4Vt5Vt6Vt7Vt8Vt9Vu0Vu1Vu2Vu3Vu4Vu5Vu6Vu7Vu8Vu9Vv0Vv1Vv2Vv3Vv4Vv5Vv6Vv7Vv8Vv9"
"Vw0Vw1Vw2Vw3Vw4Vw5Vw6Vw7Vw8Vw9Vx0Vx1Vx2Vx3Vx4Vx5Vx6Vx7Vx8Vx9Vy0Vy1Vy2Vy3Vy4Vy5Vy"
"6Vy7Vy8Vy9Vz0Vz1Vz2Vz3Vz4Vz5Vz6Vz7Vz8Vz9Wa0Wa1Wa2Wa3Wa4Wa5Wa6Wa... | code_fim | hard | {
"lang": "python",
"repo": "Coldwave96/PentestingTools",
"path": "/padding.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Coldwave96/PentestingTools path: /padding.py
e4Ee5Ee6Ee7Ee8Ee9Ef0Ef1Ef2E"
"f3Ef4Ef5Ef6Ef7Ef8Ef9Eg0Eg1Eg2Eg3Eg4Eg5Eg6Eg7Eg8Eg9Eh0Eh1Eh2Eh3Eh4Eh5Eh6Eh7Eh8Eh9"
"Ei0Ei1Ei2Ei3Ei4Ei5Ei6Ei7Ei8Ei9Ej0Ej1Ej2Ej3Ej4Ej5Ej6Ej7Ej8Ej9Ek0Ek1Ek2Ek3Ek4Ek5Ek"
"6Ek7Ek8Ek9El0El1El2El3El4El5El6El7El8El9Em0E... | code_fim | hard | {
"lang": "python",
"repo": "Coldwave96/PentestingTools",
"path": "/padding.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def sort_numbers(numbers: List[Number]) -> List[Number]:
return sorted(numbers, key=lambda n: (n.rem, -n.remBy2, n.secondaryValue))
def solve_problem():
size, div = read_configuration()
while size != 0 and div != 0:
numbers = read_list(size, div)
result = [number.value for n... | code_fim | medium | {
"lang": "python",
"repo": "hiroshisiq/problem_solving",
"path": "/problems/urionlinejudge/uri_1252_sort_sort_and_sort.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hiroshisiq/problem_solving path: /problems/urionlinejudge/uri_1252_sort_sort_and_sort.py
#!/usr/bin/env python3
from typing import Tuple, List
class Number:
def __init__(self, value: int, div: int):
self.value = str(value) # true value
self.... | code_fim | medium | {
"lang": "python",
"repo": "hiroshisiq/problem_solving",
"path": "/problems/urionlinejudge/uri_1252_sort_sort_and_sort.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lahwran/tree-of-life path: /treeoflife/test/test_parseutil.py
from __future__ import unicode_literals, print_function
from treeoflife import parseutil
import parsley
def test_grammar():
<|fim_suffix|> grammar = """
source :arg = othergrammar.target(arg):t ' derp' -> t + 10
... | code_fim | medium | {
"lang": "python",
"repo": "lahwran/tree-of-life",
"path": "/treeoflife/test/test_parseutil.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> grammar = """
source :arg = othergrammar.target(arg):t ' derp' -> t + 10
"""
bindings = {
"othergrammar": MyOtherGrammar
}
assert MyGrammar("herp derp").source(1000) == 1110
assert MyGrammar("herk derk").source(1000, optional=True) is None
... | code_fim | medium | {
"lang": "python",
"repo": "lahwran/tree-of-life",
"path": "/treeoflife/test/test_parseutil.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
# Create new Container in the Service
await container_client.create_container()
# Get the BlobClient
blob_client = container_client.get_blob_client("myappendblob")
# Upload content to the append blob
with open(SOURCE_FI... | code_fim | hard | {
"lang": "python",
"repo": "elraikhm/azure-sdk-for-python",
"path": "/sdk/storage/azure-storage-blob/tests/test_blob_samples_hello_world_async.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: elraikhm/azure-sdk-for-python path: /sdk/storage/azure-storage-blob/tests/test_blob_samples_hello_world_async.py
# coding: utf-8
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT Licens... | code_fim | hard | {
"lang": "python",
"repo": "elraikhm/azure-sdk-for-python",
"path": "/sdk/storage/azure-storage-blob/tests/test_blob_samples_hello_world_async.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @record
def test_block_blob_sample_async(self):
if TestMode.need_recording_file(self.test_mode):
return
loop = asyncio.get_event_loop()
loop.run_until_complete(self._test_block_blob_sample_async())
async def _test_page_blob_sample_async(self):
# Ins... | code_fim | hard | {
"lang": "python",
"repo": "elraikhm/azure-sdk-for-python",
"path": "/sdk/storage/azure-storage-blob/tests/test_blob_samples_hello_world_async.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>?P<id_classifield>\d+)/$', viewClassifield),
)<|fim_prefix|># repo: saraivaufc/Journal path: /newspaper/urls/user/classifield.py
from django.conf.urls import patterns, include, url
from newspaper.views.user import viewCla<|fim_middle|>ssifield
urlpatterns = patterns('',
url(r'^( | code_fim | easy | {
"lang": "python",
"repo": "saraivaufc/Journal",
"path": "/newspaper/urls/user/classifield.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: saraivaufc/Journal path: /newspaper/urls/user/classifield.py
from django.conf.urls import patterns, include<|fim_suffix|>ssifield
urlpatterns = patterns('',
url(r'^(?P<id_classifield>\d+)/$', viewClassifield),
)<|fim_middle|>, url
from newspaper.views.user import viewCla | code_fim | easy | {
"lang": "python",
"repo": "saraivaufc/Journal",
"path": "/newspaper/urls/user/classifield.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Aimini/hm-51 path: /test/generate/autotest/56_57_ANL_A_Ri.py
#########################################################
# 2020-01-23 12:41:37
# AI
# ins: ANL A, @Ri
#########################################################
from .common.INS_XXX_A_Ri import XXX_A_Ri
from ..asmconst import *
class... | code_fim | easy | {
"lang": "python",
"repo": "Aimini/hm-51",
"path": "/test/generate/autotest/56_57_ANL_A_Ri.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def op_func(self, B):
A = self.ram.get_direct(SFR_A.x)
self.ram.set_direct(SFR_A.x, A & B)
p = ANL_A_Ri().gen(0xFF, 15, 1)<|fim_prefix|># repo: Aimini/hm-51 path: /test/generate/autotest/56_57_ANL_A_Ri.py
#########################################################
# 2020-01-23... | code_fim | medium | {
"lang": "python",
"repo": "Aimini/hm-51",
"path": "/test/generate/autotest/56_57_ANL_A_Ri.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_complete(self):
left = Node(data=2, left=Node(data=1), right=Node(data=3))
right = Node(data=6, left=Node(data=5), right=Node(data=7))
tree = Node(data=4, left=left, right=right)
is_balanced, tree_min, tree_max = balanced(tree)
self.assertTrue(is_balanc... | code_fim | hard | {
"lang": "python",
"repo": "jpventura/Craftsman",
"path": "/ctci/ctci-is-binary-search-tree.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jpventura/Craftsman path: /ctci/ctci-is-binary-search-tree.py
#!/usr/bin/env python3
import math
import unittest
class Node:
def __init__(self, data, left=None, right=None):
self.data = data
self.left = left
self.right = right
def balanced(tree):
if tree is No... | code_fim | hard | {
"lang": "python",
"repo": "jpventura/Craftsman",
"path": "/ctci/ctci-is-binary-search-tree.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chardorn/unc-racecar path: /src/pure_pursuit/src/obstacle_bloating.py
#!/usr/bin/env python
# This script probably won't end up being used--it still doesn't guarantee
# a straight-line path that avoids obstacles, and it's too slow. However, we'll
# preserve it for reference.
import rospy
import ... | code_fim | hard | {
"lang": "python",
"repo": "chardorn/unc-racecar",
"path": "/src/pure_pursuit/src/obstacle_bloating.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> while not rospy.core.is_shutdown_requested():
laser_data = rospy.client.wait_for_message('scan', LaserScan)
prev_time = time.clock() # calculate loop time
print "Got " + str(len(laser_data.ranges)) + " laser points"
start = time.time()
bloated_data = get_all_bl... | code_fim | hard | {
"lang": "python",
"repo": "chardorn/unc-racecar",
"path": "/src/pure_pursuit/src/obstacle_bloating.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> html = ClassificationSummary(df, None)._repr_html_()
# render html http://htmledit.squarefree.com/
print(html)
self.assertIn("data:image/png;base64", html)
def test_regression_summary(self):
df = pd.DataFrame({"a": np.random.random(10), "b": np.random.random(... | code_fim | hard | {
"lang": "python",
"repo": "jcoffi/pandas-ml-quant",
"path": "/pandas-ml-utils/pandas_ml_utils_test/ml/data/test__summary.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> html = RegressionSummary(df, None)._repr_html_()
# render html http://htmledit.squarefree.com/
print(html)
self.assertIn("data:image/png;base64", html)<|fim_prefix|># repo: jcoffi/pandas-ml-quant path: /pandas-ml-utils/pandas_ml_utils_test/ml/data/test__summary.py
from u... | code_fim | medium | {
"lang": "python",
"repo": "jcoffi/pandas-ml-quant",
"path": "/pandas-ml-utils/pandas_ml_utils_test/ml/data/test__summary.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jcoffi/pandas-ml-quant path: /pandas-ml-utils/pandas_ml_utils_test/ml/data/test__summary.py
from unittest import TestCase
import pandas as pd
from pandas_ml_utils import ClassificationSummary, RegressionSummary
import numpy as np
from pandas_ml_utils.constants import *
class TestSummary(TestCas... | code_fim | medium | {
"lang": "python",
"repo": "jcoffi/pandas-ml-quant",
"path": "/pandas-ml-utils/pandas_ml_utils_test/ml/data/test__summary.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: esslushy/Cheat path: /Deck.py
from Card import Card
import random
suits = ['Hearts', 'Clubs', 'Diamonds', 'Spades']
class Deck():
def __init__(self, empty=False):
<|fim_suffix|> def shuffle(self):
random.shuffle(self.cards)
def draw(self, num=1):
drawnCards = []
... | code_fim | hard | {
"lang": "python",
"repo": "esslushy/Cheat",
"path": "/Deck.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> random.shuffle(self.cards)
def draw(self, num=1):
drawnCards = []
for i in range(num):
drawnCards.append(self.cards[i])
self.cards.remove(self.cards[i])
if(len(drawnCards) == 1):
return drawnCards[0]
else:
return ... | code_fim | hard | {
"lang": "python",
"repo": "esslushy/Cheat",
"path": "/Deck.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> drawnCards = []
for i in range(num):
drawnCards.append(self.cards[i])
self.cards.remove(self.cards[i])
if(len(drawnCards) == 1):
return drawnCards[0]
else:
return drawnCards
def __str__(self):
return self.cards<|f... | code_fim | hard | {
"lang": "python",
"repo": "esslushy/Cheat",
"path": "/Deck.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # optional lowercase
if lower:
corpus = map(lambda x: x.lower(), corpus)
return corpus
def get_vocab_counts(corpus):
''' Reads in a list of sentences, returns a list of tuples of (word, probability, count)
sorted by descending frequency. This is a reimplementation of 'amitta... | code_fim | hard | {
"lang": "python",
"repo": "shamilcm/cynical",
"path": "/python_cynical_wrapper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shamilcm/cynical path: /python_cynical_wrapper.py
e're also expecting that this data is already tokenized (unless you want to run
selection on non-tokenized data for some weird reason.)
'''
#Check that the cyncial_perl_script exists and can be executed.
# Uncomment if you're us... | code_fim | hard | {
"lang": "python",
"repo": "shamilcm/cynical",
"path": "/python_cynical_wrapper.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shamilcm/cynical path: /python_cynical_wrapper.py
_lines, seed_lines=[],
batch_mode=False, keep_boring=True,
save_memory=True, lower=True, debug=True,
min_count=3, max_count=10000, num_lines=0,
outdir='/tmp/cynical_out', save_ou... | code_fim | hard | {
"lang": "python",
"repo": "shamilcm/cynical",
"path": "/python_cynical_wrapper.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ccj5351/hmr_rgbd path: /src/datasets/surreal_to_tfrecords.py
'Number of shards in training TFRecord files.')
tf.app.flags.DEFINE_integer('validation_shards', 1000,
'Number of shards in validation TFRecord files.')
"""
# save to h5 file or sa... | code_fim | hard | {
"lang": "python",
"repo": "ccj5351/hmr_rgbd",
"path": "/src/datasets/surreal_to_tfrecords.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for d in subdirs: # for each sequence, e.g., d =
ppl_num_valid = 0
cur_dir = join(img_dir, d)
sequences = [s for s in listdir(cur_dir) if isfile(join(cur_dir,s)) and ".mp4" in s]
for s in sequences: # for each video in the sequence
s_name = s.split(".")[0]
... | code_fim | hard | {
"lang": "python",
"repo": "ccj5351/hmr_rgbd",
"path": "/src/datasets/surreal_to_tfrecords.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
#do_transform = False
do_transform = True # already test, this value must be TRUE;
if do_transform:
# <========= LOAD SMPL MODEL BASED ON GENDER
if info_dict['gender'][0] == 0: # f
m = load_model('/... | code_fim | hard | {
"lang": "python",
"repo": "ccj5351/hmr_rgbd",
"path": "/src/datasets/surreal_to_tfrecords.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rjleveque/shoaling_paper_figures path: /japan2011/maketopo.py
"""
Need to edit based on
/Users/rjl/git/GeoClaw_MOST_comparisons/topo/PacificDEMs/*4min.tt3
"""
from __future__ import print_function
from pylab import *
from clawpack.geoclaw import topotools
from clawpack.clawutil.data import ge... | code_fim | hard | {
"lang": "python",
"repo": "rjleveque/shoaling_paper_figures",
"path": "/japan2011/maketopo.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>etopo1_url = 'https://www.ngdc.noaa.gov/thredds/dodsC/global/ETOPO1_Ice_g_gmt4.nc'
extent = [-180, -110, 20, 60]
print('Attempting to read etopo1 data from\n %s' % etopo1_url)
etopo = topotools.read_netcdf(path=etopo1_url, extent=extent,
coarsen=1, verbose=True)
fname = 'eto... | code_fim | medium | {
"lang": "python",
"repo": "rjleveque/shoaling_paper_figures",
"path": "/japan2011/maketopo.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def main():
clf = KMeans(3)
train_x = [
[1, 1], [0.9, 1.2], [1.3, 0.8],
[8, 8], [8.1, 7.9], [8.2, 7.8],
[9, 0], [9, 0.2], [9.2, 0.3]
]
train_x = np.array(train_x)
clf.fit(train_x)
print(clf.clusters)
print(clf.predict_one(np.array([9, 9])))
if __name__... | code_fim | easy | {
"lang": "python",
"repo": "KLabp/ML-by-Python",
"path": "/tests/test_kmeans.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KLabp/ML-by-Python path: /tests/test_kmeans.py
import os
import sys
sys.path.insert(0, os.path.abspath('.'))
<|fim_suffix|>
def main():
clf = KMeans(3)
train_x = [
[1, 1], [0.9, 1.2], [1.3, 0.8],
[8, 8], [8.1, 7.9], [8.2, 7.8],
[9, 0], [9, 0.2], [9.2, 0.3]
]
... | code_fim | easy | {
"lang": "python",
"repo": "KLabp/ML-by-Python",
"path": "/tests/test_kmeans.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def main():
clf = KMeans(3)
train_x = [
[1, 1], [0.9, 1.2], [1.3, 0.8],
[8, 8], [8.1, 7.9], [8.2, 7.8],
[9, 0], [9, 0.2], [9.2, 0.3]
]
train_x = np.array(train_x)
clf.fit(train_x)
print(clf.clusters)
print(clf.predict_one(np.array([9, 9])))
if __name_... | code_fim | easy | {
"lang": "python",
"repo": "KLabp/ML-by-Python",
"path": "/tests/test_kmeans.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sourabhv/FlapPyBird path: /src/utils/sounds.py
import sys
import pygame
class Sounds:
die: pygame.mixer.Sound
hit: pygame.mixer.Sound
point: pygame.mixer.Sound
swoosh: pygame.mixer.Sound
wing: pygame.mixer.Sound
<|fim_suffix|> self.die = pygame.mixer.Sound(f"assets/... | code_fim | medium | {
"lang": "python",
"repo": "sourabhv/FlapPyBird",
"path": "/src/utils/sounds.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.die = pygame.mixer.Sound(f"assets/audio/die.{ext}")
self.hit = pygame.mixer.Sound(f"assets/audio/hit.{ext}")
self.point = pygame.mixer.Sound(f"assets/audio/point.{ext}")
self.swoosh = pygame.mixer.Sound(f"assets/audio/swoosh.{ext}")
self.wing = pygame.mixer.Sou... | code_fim | medium | {
"lang": "python",
"repo": "sourabhv/FlapPyBird",
"path": "/src/utils/sounds.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: uvenil/PythonKurs201806 path: /___Python/Angela/PyKurs/p02_datenstrukturen/m04_worterbuch_invertieren.py
d = {"Tisch": "table",
"Stuhl": "chair",
"Schreibtisch": "desk"}
# Ziel: Weiteres Woerterbuch aufbauen, das als Schluessel englische Begriffe enthaelt
# print(d.items())
<|f... | code_fim | hard | {
"lang": "python",
"repo": "uvenil/PythonKurs201806",
"path": "/___Python/Angela/PyKurs/p02_datenstrukturen/m04_worterbuch_invertieren.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># 3. Ansatz
e = {}
for key, value in d.items():
e[value] = key<|fim_prefix|># repo: uvenil/PythonKurs201806 path: /___Python/Angela/PyKurs/p02_datenstrukturen/m04_worterbuch_invertieren.py
d = {"Tisch": "table",
"Stuhl": "chair",
"Schreibtisch": "desk"}
# Ziel: Weiteres Woerterbuch ... | code_fim | medium | {
"lang": "python",
"repo": "uvenil/PythonKurs201806",
"path": "/___Python/Angela/PyKurs/p02_datenstrukturen/m04_worterbuch_invertieren.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vokal/s3same path: /s3same/iam.py
import json
from botocore.exceptions import ClientError
IAMName = 's3same_travis'
def _policy_string(bucket):
return json.dumps({
"Version": "2012-10-17",
"Statement": [
{
"Action": [
"s3:ListB... | code_fim | hard | {
"lang": "python",
"repo": "vokal/s3same",
"path": "/s3same/iam.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
users = list(_users_in_group(iam))
except ClientError as e:
if e.response['Error']['Code'] != 'NoSuchEntity':
raise
users = []
for user in users:
username = user.get('UserName')
if not username:
continue
for key in _k... | code_fim | hard | {
"lang": "python",
"repo": "vokal/s3same",
"path": "/s3same/iam.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def credentials_for_new_user(iam, username, bucket=IAMName):
_create_group_if_needed(iam, bucket)
try:
iam.create_user(UserName=username)
except ClientError as e:
if e.response['Error']['Code'] != 'EntityAlreadyExists':
raise
iam.add_user_to_group(UserName=usern... | code_fim | hard | {
"lang": "python",
"repo": "vokal/s3same",
"path": "/s3same/iam.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mlgig/sktime path: /sktime/base/tests/test_base_sktime.py
# -*- coding: utf-8 -*-
# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Tests for BaseObject universal base class that require sktime or sklearn imports."""
__author__ = ["fkiraly"]
def test_get_fitted_params_... | code_fim | hard | {
"lang": "python",
"repo": "mlgig/sktime",
"path": "/sktime/base/tests/test_base_sktime.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> from sktime.datasets import load_airline
from sktime.forecasting.trend import TrendForecaster
y = load_airline()
pipe = make_pipeline(StandardScaler(), LinearRegression())
f = TrendForecaster(pipe)
f.fit(y)
params = f.get_fitted_params()
assert "regressor" in params.keys... | code_fim | hard | {
"lang": "python",
"repo": "mlgig/sktime",
"path": "/sktime/base/tests/test_base_sktime.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> Raises
------
AssertionError if logic behind get_fitted_params is incorrect, logic tested:
calling get_fitted_params on obj sktime component returns expected nested params
"""
from sklearn.linear_model import LinearRegression
from sklearn.pipeline import make_pipeline
f... | code_fim | hard | {
"lang": "python",
"repo": "mlgig/sktime",
"path": "/sktime/base/tests/test_base_sktime.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nodejs/node-addon-api path: /test/addon_build/tpl/binding.gyp
{
'target_defaults': {
'include_dirs': [
"<!(node -p \"require('node-addon-api').include_dir\")"
],
'variables': {
'NAPI_VERSION%': "<!(node -p \"process.versions.napi\")",
'disable_deprecated': "<!(no... | code_fim | hard | {
"lang": "python",
"repo": "nodejs/node-addon-api",
"path": "/test/addon_build/tpl/binding.gyp",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>_DISABLE_CPP_EXCEPTIONS' ],
'cflags': [ '-fno-exceptions' ],
'cflags_cc': [ '-fno-exceptions' ],
'msvs_settings': {
'VCCLCompilerTool': {
'ExceptionHandling': 0,
'EnablePREfast': 'true',
},
},
'xcode_settings': {
'CLANG_CXX_LIBRARY'... | code_fim | hard | {
"lang": "python",
"repo": "nodejs/node-addon-api",
"path": "/test/addon_build/tpl/binding.gyp",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: livsik/strawberry_py path: /xcode/xc_build.py
import re
from os import getcwd
from datetime import datetime
from calendar import timegm
from time import sleep
from commander import Commander
from command_output_pipe_base import CommandOutputPipeBase
from pretty_output_pipe import PrettyOutputPip... | code_fim | hard | {
"lang": "python",
"repo": "livsik/strawberry_py",
"path": "/xcode/xc_build.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def build(self, clean, run, device, result_formatter):
if self.verbose:
pipe_type = PrettyOutputPipe
else:
pipe_type = ProgressOutputPipe
if clean:
pipe = pipe_type()
if result_formatter:
result_formatter.start(pipe)
Log.msg("Cleaning \"{0}\"".format(sel... | code_fim | hard | {
"lang": "python",
"repo": "livsik/strawberry_py",
"path": "/xcode/xc_build.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: forkode/ok_kafka path: /ok_kafka/default_serializer.py
import json
from datetime import date, datetime
from decimal import Decimal
from typing import Any, Union
from uuid import UUID
from ok_kafka.local_types import JSONType
__all__ = ['serialize', 'deserialize']
class UniversalEncoder(json.J... | code_fim | hard | {
"lang": "python",
"repo": "forkode/ok_kafka",
"path": "/ok_kafka/default_serializer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def deserialize(value, topic): # type: (bytes, str) -> JSONType
return json.loads(value, parse_float=Decimal)<|fim_prefix|># repo: forkode/ok_kafka path: /ok_kafka/default_serializer.py
import json
from datetime import date, datetime
from decimal import Decimal
from typing import Any, Union
from uui... | code_fim | hard | {
"lang": "python",
"repo": "forkode/ok_kafka",
"path": "/ok_kafka/default_serializer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: edouard-lopez/parlr path: /tests/test_learner.py
# -*- coding: utf-8 -*-
import logging
from parlr import Learner
import server
import json
import unittest
logger = logging.getLogger(__name__)
class LearnerTestCase(unittest.TestCase):
def setUp(self):
self.app = server.app.test_cl... | code_fim | hard | {
"lang": "python",
"repo": "edouard-lopez/parlr",
"path": "/tests/test_learner.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> response = self.app.put('/learners/1',
data=json.dumps({'username': 'Édouard Lopez', 'level': 1, 'known_characters': [1,2]}),
content_type='application/json')
self.assertEqual(200, response.status_code)<|fim_prefix|># repo: ed... | code_fim | hard | {
"lang": "python",
"repo": "edouard-lopez/parlr",
"path": "/tests/test_learner.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: maxbates/molecular-design-toolkit path: /moldesign/helpers/logs.py
from __future__ import print_function, absolute_import, division
from future.builtins import *
from future import standard_library
standard_library.install_aliases()
# Copyright 2017 Autodesk Inc.
#
# Licensed under the Apache Lic... | code_fim | hard | {
"lang": "python",
"repo": "maxbates/molecular-design-toolkit",
"path": "/moldesign/helpers/logs.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> ke = kinetic_energy(properties['momenta'], mol.masses)
t = kinetic_temperature(ke, mol.dynamic_dof)
print(self.ROW_FORMAT.format(properties['time'].defunits_value(),
properties['potential_energy'].defunits_value(),
... | code_fim | hard | {
"lang": "python",
"repo": "maxbates/molecular-design-toolkit",
"path": "/moldesign/helpers/logs.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if os.path.exists(dest):
logger.info(
'Project {0} already available locally in {1}, performing an update.'.format(slug, dest))
try:
RepoCloner.pull(dest)
RepoCloner.update_submodules(dest)
... | code_fim | hard | {
"lang": "python",
"repo": "collab-uniba/szz-mpi",
"path": "/githubutils/clone_projects.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: collab-uniba/szz-mpi path: /githubutils/clone_projects.py
import getopt
import logging
import os
import sys
from gitutils.repo import RepoCloner
from loggingcfg import initialize_logger
from utils import utility
def start(argv):
project_file = 'project-list.txt'
destination_dir = './gi... | code_fim | hard | {
"lang": "python",
"repo": "collab-uniba/szz-mpi",
"path": "/githubutils/clone_projects.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return {
"$gte": value
}
def get_value(self, field, value):
return field.to_son(value)<|fim_prefix|># repo: parthi82/tailow path: /tailow/operators/gt.py
from tailow.operators.base import Operator
class GTOperator(Operator):
""" Greater than operator """
... | code_fim | hard | {
"lang": "python",
"repo": "parthi82/tailow",
"path": "/tailow/operators/gt.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: parthi82/tailow path: /tailow/operators/gt.py
from tailow.operators.base import Operator
class GTOperator(Operator):
""" Greater than operator """
def to_query(self, field_name, value):
return {
"$gt": value
}
def get_value(self, field, value):
<|fim_su... | code_fim | medium | {
"lang": "python",
"repo": "parthi82/tailow",
"path": "/tailow/operators/gt.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# combine the info files
data_list = [pd.read_csv(os.path.join(input_dir, read + '.csv'))
for read in read_list]
compiled_data = pd.concat(data_list)
compiled_data['name'] = compiled_data['name'].apply(str.lower)
compiled_data = compiled_data[['name', 'latitude', 'longitude']]
compiled_data... | code_fim | medium | {
"lang": "python",
"repo": "garygsw/twitter-crowd-flow",
"path": "/compile_places_info.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: garygsw/twitter-crowd-flow path: /compile_places_info.py
'''compile_places_info.py.
Compile the places latitude and longitudes.
'''
import os
import math
import pandas as pd
# Input parameters
read_list = ['sg_factual_places', 'sg_manual_names', 'sg_mrt_names']
input_dir = 'places-info'
output... | code_fim | hard | {
"lang": "python",
"repo": "garygsw/twitter-crowd-flow",
"path": "/compile_places_info.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alexge50/Matrix-API path: /web-api/main.py
from flask import Flask, request, jsonify
import matrix
app = Flask(__name__)
@app.route('/')
def hello():
return 'Hello, World!'
<|fim_suffix|> return jsonify(matrix.multiply(first_matrix, second_matrix))<|fim_middle|>@app.route('/multiply',... | code_fim | hard | {
"lang": "python",
"repo": "alexge50/Matrix-API",
"path": "/web-api/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return jsonify(matrix.multiply(first_matrix, second_matrix))<|fim_prefix|># repo: alexge50/Matrix-API path: /web-api/main.py
from flask import Flask, request, jsonify
import matrix
app = Flask(__name__)
@app.route('/')
def hello():
return 'Hello, World!'
@app.route('/multiply', methods=['POS... | code_fim | hard | {
"lang": "python",
"repo": "alexge50/Matrix-API",
"path": "/web-api/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>d(int(input('введите число: ')))
print(array[n] ** n)<|fim_prefix|># repo: MakarFadeev/PythonTasks path: /LISTS2/NUMBER4.py
numbers = int(input('сколько чисел вы хотите ввести?<|fim_middle|> '))
n = int(input('введите число (любое!): ')) - 1
array = []
for i in range(0, numbers):
array.appen | code_fim | medium | {
"lang": "python",
"repo": "MakarFadeev/PythonTasks",
"path": "/LISTS2/NUMBER4.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MakarFadeev/PythonTasks path: /LISTS2/NUMBER4.py
numbers = int(input('сколько чисел вы хотите ввести?<|fim_suffix|>rray = []
for i in range(0, numbers):
array.append(int(input('введите число: ')))
print(array[n] ** n)<|fim_middle|> '))
n = int(input('введите число (любое!): ')) - 1
a | code_fim | easy | {
"lang": "python",
"repo": "MakarFadeev/PythonTasks",
"path": "/LISTS2/NUMBER4.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>0.07}, 5: {'A': -0.017, 'C': -0.179, 'E': -0.012, 'D': 0.11, 'G': -0.028, 'F': -0.033, 'I': -0.01, 'H': 0.079, 'K': -0.036, 'M': 0.0, 'L': -0.151, 'N': 0.135, 'Q': 0.221, 'P': -0.01, 'S': -0.013, 'R': -0.136, 'T': 0.256, 'W': -0.023, 'V': -0.121, 'Y': -0.031}, 6: {'A': -0.001, 'C': -0.0, 'E': 0.0, 'D': 0.... | code_fim | hard | {
"lang": "python",
"repo": "FRED-2/Fred2",
"path": "/Fred2/Data/pssms/smm/mat/B_45_01_10.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>002, 'N': 0.011, 'Q': 0.037, 'P': 0.001, 'S': 0.013, 'R': -0.024, 'T': -0.009, 'W': -0.019, 'V': 0.001, 'Y': -0.025}, 8: {'A': -0.028, 'C': 0.015, 'E': -0.062, 'D': 0.097, 'G': 0.088, 'F': -0.008, 'I': -0.011, 'H': 0.046, 'K': 0.051, 'M': 0.114, 'L': -0.087, 'N': -0.044, 'Q': -0.017, 'P': -0.066, 'S': -0.... | code_fim | hard | {
"lang": "python",
"repo": "FRED-2/Fred2",
"path": "/Fred2/Data/pssms/smm/mat/B_45_01_10.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FRED-2/Fred2 path: /Fred2/Data/pssms/smm/mat/B_45_01_10.py
B_45_01_10 = {0: {'A': -0.639, 'C': -0.412, 'E': -0.297, 'D': 0.548, 'G': 0.267, 'F': 0.132, 'I': -0.105, 'H': 0.19, 'K': 0.169, 'M': -0.566, 'L': 0.327, 'N': -0.066, 'Q': -0.356, 'P': 0.695, 'S': -0.341, 'R': -0.106, 'T': -0.06, 'W': 0.2... | code_fim | hard | {
"lang": "python",
"repo": "FRED-2/Fred2",
"path": "/Fred2/Data/pssms/smm/mat/B_45_01_10.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KarboniteKream/advent-of-code path: /2019/04.py
import util
def part1(low, high):
def is_valid(number):
digits = str(number)
valid = False
for i in range(5):
if digits[i] > digits[i + 1]:
return False
if digits[i] == digits[i... | code_fim | hard | {
"lang": "python",
"repo": "KarboniteKream/advent-of-code",
"path": "/2019/04.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return valid
return sum(is_valid(num) for num in range(low, high + 1))
def part2(low, high):
def is_valid(number):
digits = str(number)
count = [0] * 10
count[int(digits[5])] = 1
for i in range(5):
if digits[i] > digits[i + 1]:
... | code_fim | medium | {
"lang": "python",
"repo": "KarboniteKream/advent-of-code",
"path": "/2019/04.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stickwithjosh/hypodrical path: /apps/podcast/admin.py
from apps.podcast.models import Podcast, Contributor, Episode, Category
from django.contrib import admin
<|fim_suffix|>
class EpisodeAdmin(admin.ModelAdmin):
list_display = ('title', 'episode_number', 'pub_date')
prepopulated_fields =... | code_fim | medium | {
"lang": "python",
"repo": "stickwithjosh/hypodrical",
"path": "/apps/podcast/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class EpisodeAdmin(admin.ModelAdmin):
list_display = ('title', 'episode_number', 'pub_date')
prepopulated_fields = {"slug": ("title",)}
date_hierarchy = 'pub_date'
admin.site.register(Episode, EpisodeAdmin)<|fim_prefix|># repo: stickwithjosh/hypodrical path: /apps/podcast/admin.py
from apps... | code_fim | medium | {
"lang": "python",
"repo": "stickwithjosh/hypodrical",
"path": "/apps/podcast/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> list_display = ('title', 'episode_number', 'pub_date')
prepopulated_fields = {"slug": ("title",)}
date_hierarchy = 'pub_date'
admin.site.register(Episode, EpisodeAdmin)<|fim_prefix|># repo: stickwithjosh/hypodrical path: /apps/podcast/admin.py
from apps.podcast.models import Podcast, Contri... | code_fim | medium | {
"lang": "python",
"repo": "stickwithjosh/hypodrical",
"path": "/apps/podcast/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: modin-project/modin path: /modin/core/dataframe/algebra/__init__.py
# Licensed to Modin Development Team under one or more contributor license agreements.
# See the NOTICE file distributed with this work for additional information regarding
# copyright ownership. The Modin Development Team licen... | code_fim | medium | {
"lang": "python",
"repo": "modin-project/modin",
"path": "/modin/core/dataframe/algebra/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>from .operator import Operator
from .map import Map
from .tree_reduce import TreeReduce
from .reduce import Reduce
from .fold import Fold
from .binary import Binary
from .groupby import GroupByReduce
__all__ = [
"Operator",
"Map",
"TreeReduce",
"Reduce",
"Fold",
"Binary",
"Gro... | code_fim | medium | {
"lang": "python",
"repo": "modin-project/modin",
"path": "/modin/core/dataframe/algebra/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return (self.asn, self_node_id) < (other.asn, other_node_id)
@property
def _node_data(self):
return self.nidb.raw_graph().node[self.node_id]
def dump(self):
# return str(self._node_data)
import pprint
pprint.pprint(self._node_data)
def __nonzero__... | code_fim | hard | {
"lang": "python",
"repo": "plucena24/autonetkit",
"path": "/autonetkit/nidb/node.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: plucena24/autonetkit path: /autonetkit/nidb/node.py
import functools
import logging
import string
import autonetkit.log as log
from autonetkit.log import CustomAdapter
from autonetkit.nidb.config_stanza import ConfigStanza
from autonetkit.nidb.interface import DmInterface
import autonetkit.log a... | code_fim | hard | {
"lang": "python",
"repo": "plucena24/autonetkit",
"path": "/autonetkit/nidb/node.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Public function to view interfaces
Temporary function name until Compiler/DeviceModel/Templates
move to using "proper" interfaces"""
def filter_func(interface):
"""Filter based on args and kwargs"""
return (
all(getattr(interface,... | code_fim | hard | {
"lang": "python",
"repo": "plucena24/autonetkit",
"path": "/autonetkit/nidb/node.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mandarjoshi90/pair2vec path: /embeddings/representation.py
import numpy as np
import torch
from torch.nn import Module, Linear, Dropout, Sequential, LSTM, Embedding, GRU, ReLU, Parameter
from embeddings.util import masked_softmax
from torch.autograd import Variable
from torch.nn.init import xavie... | code_fim | hard | {
"lang": "python",
"repo": "mandarjoshi90/pair2vec",
"path": "/embeddings/representation.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
self.contextualizer = LSTMContextualizer(config) if config.n_lstm_layers > 0 else lambda x : x
self.dropout = Dropout(p=config.dropout)
self.head_attention = Sequential(self.dropout, Linear(2 * config.d_lstm_hidden, 1))
self.head_transform = Sequential(self.dropout, Linear... | code_fim | hard | {
"lang": "python",
"repo": "mandarjoshi90/pair2vec",
"path": "/embeddings/representation.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>sub(r'([%s])' % escape_chars, r'\\\1', text)<|fim_prefix|># repo: codebam/telegram-bot path: /modules/escape_markdown.py
def escape_markdown(text):
"""Helper fu<|fim_middle|>nction to escape telegram markup symbols"""
escape_chars = '\*_`\['
return re. | code_fim | medium | {
"lang": "python",
"repo": "codebam/telegram-bot",
"path": "/modules/escape_markdown.py",
"mode": "spm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: codebam/telegram-bot path: /modules/escape_markdown.py
def escape_markdown(text):
"""Helper fu<|fim_suffix|>
escape_chars = '\*_`\['
return re.sub(r'([%s])' % escape_chars, r'\\\1', text)<|fim_middle|>nction to escape telegram markup symbols""" | code_fim | easy | {
"lang": "python",
"repo": "codebam/telegram-bot",
"path": "/modules/escape_markdown.py",
"mode": "psm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: anhquannguyen21/Image-Processing path: /Source/FreiChen.py
import numpy as np
import cv2
from matplotlib import pyplot as plt
from convolve_np import convolve_np
img = cv2.imread('images/jet.jpg', cv2.IMREAD_GRAYSCALE)
height = img.shape[0]
width = img.shape[1]
Hx = 1.0/(2+np.sqrt(2)... | code_fim | medium | {
"lang": "python",
"repo": "anhquannguyen21/Image-Processing",
"path": "/Source/FreiChen.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>img_out = np.sqrt(np.power(img_x, 2) + np.power(img_y, 2))
img_out = (img_out / np.max(img_out)) * 255
cv2.imwrite('images/edge_FreiChen.jpg', img_out)
plt.imshow(img_out, cmap = 'gray', interpolation = 'bicubic')
plt.xticks([]), plt.yticks([])
plt.show()<|fim_prefix|># repo: anhquannguyen21/Image-Pr... | code_fim | hard | {
"lang": "python",
"repo": "anhquannguyen21/Image-Processing",
"path": "/Source/FreiChen.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
Hy = 1.0/(2+np.sqrt(2))*np.array([[-1, -np.sqrt(2), -1],
[0, 0, 0],
[1, np.sqrt(2), 1]])
img_x = convolve_np(img, Hx)
img_y = convolve_np(img, Hy)
img_out = np.sqrt(np.power(img_x, 2) + np.power(img_y, 2))
img_out = (img_out / np.max(img_out)) * 255
cv2.imwrite('... | code_fim | medium | {
"lang": "python",
"repo": "anhquannguyen21/Image-Processing",
"path": "/Source/FreiChen.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # ### commands auto generated by Alembic - please adjust! ###
op.drop_index(op.f('ix_user_username'), table_name='user')
op.alter_column(
'user', 'username', existing_type=mysql.VARCHAR(length=64), nullable=True
)
op.alter_column(
'user', 'sex', existing_type=mysql.VARC... | code_fim | hard | {
"lang": "python",
"repo": "chinese-bbb/web-backend",
"path": "/migration-dev/versions/2c3c245b5ea6_add_flask_user_required_field.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chinese-bbb/web-backend path: /migration-dev/versions/2c3c245b5ea6_add_flask_user_required_field.py
"""
add flask_user required field.
Revision ID: 2c3c245b5ea6
Revises:
Create Date: 2019-09-08 18:06:57.170638
"""
import sqlalchemy as sa
from alembic import op
from sqlalchemy.dialects import mys... | code_fim | hard | {
"lang": "python",
"repo": "chinese-bbb/web-backend",
"path": "/migration-dev/versions/2c3c245b5ea6_add_flask_user_required_field.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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