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<|fim_prefix|># repo: fengjixuchui/iWeChat path: /python/iwc_heder_inherit.py # coding=UTF-8 # 分析继承关系 import re import iwc_heder_db import os # class-dump 导出头文件所在的目录 IPA_HEADER_PATH = '/Users/wangsuyan/Desktop/baidu/reverse/header/wechat' <|fim_suffix|> dirs = os.listdir(IPA_HEADER_PATH) for file_name in dir...
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{ "lang": "python", "repo": "fengjixuchui/iWeChat", "path": "/python/iwc_heder_inherit.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: tellapart/yum-gs-iam path: /gsiam.py from google.auth import credentials from google.auth import environment_vars from google.cloud import storage import logging import os import yum import yum.config import yum.Errors import yum.plugins from yum.yumRepo import YumRepository URL_SCHEME = 'gs:...
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{ "lang": "python", "repo": "tellapart/yum-gs-iam", "path": "/gsiam.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> if repo.google_application_credentials: os.environ[environment_vars.CREDENTIALS] = repo.google_application_credentials self.bucket = bucket self.base_path = path self.name = repo.name self.basecachedir = repo.basecachedir self.gpgcheck = repo.gpgcheck self.gpgkey = repo....
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{ "lang": "python", "repo": "tellapart/yum-gs-iam", "path": "/gsiam.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> print("\nSynthesize following items:") for synthesis in crafts: display_lst = [ k + "(%s) " % synthesis["materials"][k] for k in synthesis["materials"] ] print( synthesis["ta...
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{ "lang": "python", "repo": "kyoukaya/ArkPlanner", "path": "/MaterialPlanning.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: kyoukaya/ArkPlanner path: /MaterialPlanning.py ty", "apCost", "stageCode", "stageID"]. convertion_rules: List of dictionaries recording the rules of composing. Keys of instances: ["id", "name", "level", "source", "madeof"]. """ # To count items and stag...
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{ "lang": "python", "repo": "kyoukaya/ArkPlanner", "path": "/MaterialPlanning.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: kyoukaya/ArkPlanner path: /MaterialPlanning.py ]] -= ( gold_worths[dct["item"]["itemId"]] * dct["quantity"] / float(dct["times"]) ) except (KeyError, ValueError): pass # Hardcoding: ex...
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{ "lang": "python", "repo": "kyoukaya/ArkPlanner", "path": "/MaterialPlanning.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: The-Academic-Observatory/academic-observatory-workflows path: /academic_observatory_workflows/model.py uthorList funders: FunderList publishers: PublisherList papers: PaperList fields_of_study: FieldOfStudyList repositories: RepositoryList def make_doi(doi_prefix: int): ...
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{ "lang": "python", "repo": "The-Academic-Observatory/academic-observatory-workflows", "path": "/academic_observatory_workflows/model.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> schema_path = schema_folder() with CliRunner().isolated_filesystem() as t: tables = [ Table( "repository", False, dataset_id_settings, repository, bq_find_schema(path=os.path.join(schema_path, "doi"...
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{ "lang": "python", "repo": "The-Academic-Observatory/academic-observatory-workflows", "path": "/academic_observatory_workflows/model.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> @dataclass class FieldOfStudy: """A field of study. :param id: unique identifier. :param name: the field of study name. :param level: the field of study level. """ id: int name: str = None level: int = None @dataclass class Journal: """A journal :param id: uni...
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{ "lang": "python", "repo": "The-Academic-Observatory/academic-observatory-workflows", "path": "/academic_observatory_workflows/model.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: GorgonMeducer/CMSIS_5 path: /CMSIS/DSP/cmsisdsp/sdf/nodes/host/FileSource.py ########################################### # Project: CMSIS DSP Library # Title: FileSource.py # Description: Node for creating file source # # $Date: 30 July 2021 # $Revision: V1.10.0 # # Targe...
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{ "lang": "python", "repo": "GorgonMeducer/CMSIS_5", "path": "/CMSIS/DSP/cmsisdsp/sdf/nodes/host/FileSource.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> for i in range(self._outputSize): s=self._file.readline() if (len(s)>0): a[i]=float(s) else: a[i] = 0 return(0) def __del__(self): self._file.close()<|fim_prefix|># repo: GorgonMeducer/CMSIS_5 path: /CMSIS/DSP/...
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{ "lang": "python", "repo": "GorgonMeducer/CMSIS_5", "path": "/CMSIS/DSP/cmsisdsp/sdf/nodes/host/FileSource.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> GenericSource.__init__(self,outputSize,fifoout) self._file=open(name,"r") def run(self): a=self.getWriteBuffer() for i in range(self._outputSize): s=self._file.readline() if (len(s)>0): a[i]=float(s) else: ...
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{ "lang": "python", "repo": "GorgonMeducer/CMSIS_5", "path": "/CMSIS/DSP/cmsisdsp/sdf/nodes/host/FileSource.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> a = 1 + t1 - t2 b = t3 - t1 * r1 + t2 * r1 pr_[idx] = rc_[idx] / (a * rc_[idx] + b) return pr_ def get_pr_info(lst_lbl, lst_scr): """ calculate PR info; """ rc_pt = np.linspace(0, 1, 1001) rc_pt[0] = 1e-16 prs = [] aps = [] for lbl, scr in zip(l...
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{ "lang": "python", "repo": "Sumerian-Health/azrt2021", "path": "/azrt2021/misc.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Sumerian-Health/azrt2021 path: /azrt2021/misc.py #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sat Jul 25 14:52:15 2020 @author: cxue2 """ from datetime import datetime import numpy as np from sklearn.metrics import confusion_matrix from sklearn.metrics import roc_auc_score, roc_...
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{ "lang": "python", "repo": "Sumerian-Health/azrt2021", "path": "/azrt2021/misc.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def get_pr_info(lst_lbl, lst_scr): """ calculate PR info; """ rc_pt = np.linspace(0, 1, 1001) rc_pt[0] = 1e-16 prs = [] aps = [] for lbl, scr in zip(lst_lbl, lst_scr): pr, rc, _ = precision_recall_curve(y_true=lbl, probas_pred=scr) aps.append(average_precisi...
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{ "lang": "python", "repo": "Sumerian-Health/azrt2021", "path": "/azrt2021/misc.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self.api_endpoint = api_endpoint if response_rule_provider: self.rules_provider = response_rule_provider def resolve(self, request): for response_rule in self.api_endpoint.response_rules.all(): matcher = self.rules_provider.get_matcher(response_rule.rul...
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{ "lang": "python", "repo": "aaas19920513/rest-api-mock-server", "path": "/mock_rest_app/mock_api/response_rules/resolvers.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: aaas19920513/rest-api-mock-server path: /mock_rest_app/mock_api/response_rules/resolvers.py from mock_api.response_rules import response_rules_provider class ResponseResolver(object): rules_provider = response_rules_provider <|fim_suffix|> for response_rule in self.api_endpoint.resp...
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{ "lang": "python", "repo": "aaas19920513/rest-api-mock-server", "path": "/mock_rest_app/mock_api/response_rules/resolvers.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> for response_rule in self.api_endpoint.response_rules.all(): matcher = self.rules_provider.get_matcher(response_rule.rule, response_rule.param_name, response_rule.param_value) if matcher.match(request): r...
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{ "lang": "python", "repo": "aaas19920513/rest-api-mock-server", "path": "/mock_rest_app/mock_api/response_rules/resolvers.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: simao/Polls2k11 path: /tests/tests.py # -*- coding: utf-8 -*- import os import urllib2 import unittest import simplejson as json import polls from codecs import open TEST_WIKIPEDIA_PAGE = 'tests/resources/full.html' LATEST_TEMP_FILE = "tests/latest_temp.json" __author__ = 'Simao Mata' class Te...
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{ "lang": "python", "repo": "simao/Polls2k11", "path": "/tests/tests.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def monkey_patch_urlopen(self, expected_url): ''' Substitute urllib2.urlopen by a custom function that checks that the url is equal to expected_url and returns the content of the resources/full.html file TODO: This method of testing assumes the code will use urlopen, w...
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{ "lang": "python", "repo": "simao/Polls2k11", "path": "/tests/tests.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> file_path = TEST_WIKIPEDIA_PAGE with open(file_path, 'r', 'utf-8') as fd: poll_stats = polls.get_poll_newest(fd) self.assertDictEqual(self.latest_poll, poll_stats) def monkey_patch_urlopen(self, expected_url): ''' Substitute urllib2.urlopen by a ...
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{ "lang": "python", "repo": "simao/Polls2k11", "path": "/tests/tests.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self.differences = np.append(self.differences, self.std_masses['mass values (g)']) # corresponds to Y, in g self.uncerts = np.append(self.uncerts, self.std_masses['uncertainties (' + MU_STR + 'g)']) # balance uncertainties in ug log.debug('differences:\n' + str(self.differences))...
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{ "lang": "python", "repo": "MSLNZ/Mass-Circular-Weighing", "path": "/mass_circular_weighing/routine_classes/final_mass_calc_class.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: MSLNZ/Mass-Circular-Weighing path: /mass_circular_weighing/routine_classes/final_mass_calc_class.py n file with output data; ideally an absolute path client : str name of client client_masses : dict dict of client weights Weight IDs are the stri...
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{ "lang": "python", "repo": "MSLNZ/Mass-Circular-Weighing", "path": "/mass_circular_weighing/routine_classes/final_mass_calc_class.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return items @app.post("/form/python-tuple") def post_form_param_tuple(items: tuple = Form()): return items client = TestClient(app) def test_python_list_param_as_form(): response = client.post( "/form/python-list", data={"items": ["first", "second", "third"]} ) assert re...
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{ "lang": "python", "repo": "samuelcolvin/fastapi", "path": "/tests/test_forms_from_non_typing_sequences.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: samuelcolvin/fastapi path: /tests/test_forms_from_non_typing_sequences.py from fastapi import FastAPI, Form from fastapi.testclient import TestClient app = FastAPI() @app.post("/form/python-list") def post_form_param_list(items: list = Form()): return items @app.post("/form/python-set") ...
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{ "lang": "python", "repo": "samuelcolvin/fastapi", "path": "/tests/test_forms_from_non_typing_sequences.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def test_python_set_param_as_form(): response = client.post( "/form/python-set", data={"items": ["first", "second", "third"]} ) assert response.status_code == 200, response.text assert set(response.json()) == {"first", "second", "third"} def test_python_tuple_param_as_form(): ...
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{ "lang": "python", "repo": "samuelcolvin/fastapi", "path": "/tests/test_forms_from_non_typing_sequences.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: tusharbudhwani/django-continuous-delivery path: /hooks/pre_gen_project.py #!/usr/bin/env python """Define hooks to be run before project generation.""" import sys from slugify import slugify PROJECT_SLUG = "{{ cookiecutter.project_slug }}" PROJECT_DIRNAME = "{{ cookiecutter.project_dirname }}"...
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{ "lang": "python", "repo": "tusharbudhwani/django-continuous-delivery", "path": "/hooks/pre_gen_project.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Execute intialization checks before project generation.""" check_slugs() check_identifiers() if __name__ == "__main__": main()<|fim_prefix|># repo: tusharbudhwani/django-continuous-delivery path: /hooks/pre_gen_project.py #!/usr/bin/env python """Define hooks to be run before project...
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{ "lang": "python", "repo": "tusharbudhwani/django-continuous-delivery", "path": "/hooks/pre_gen_project.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: YoshikazuArimitsu/aksdp path: /tests/test_s3file_repository.py from aksdp.data import RawData, DataFrameData from aksdp.repository import S3FileRepository, LocalFileRepository import unittest from pathlib import Path import os class TestS3FileRepository(unittest.TestCase): def setUp(self): ...
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{ "lang": "python", "repo": "YoshikazuArimitsu/aksdp", "path": "/tests/test_s3file_repository.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> repo_s3 = S3FileRepository(self.access_key_id, self.secret_access_key, self.s3file_url) data.repository = repo_s3 data.save() def test_dataframe(self): # ローカルのファイルを読んでS3に保存 repo = LocalFileRepository(Path(os.path.dirname(__file__)) / Path("titanic.csv")) ...
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{ "lang": "python", "repo": "YoshikazuArimitsu/aksdp", "path": "/tests/test_s3file_repository.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Queries the MySQL database for a specific beer by name or id""" attr = 'id' if is_id is True else 'name' query = """ SELECT `id`, `name`, `styleid`, `abv` FROM `beers` WHERE `%s` = '%s' """ % (attr, escape_string(search_term)) return mysq...
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{ "lang": "python", "repo": "stormpython/brewmaster", "path": "/brewmaster/database/lookup_beer.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: stormpython/brewmaster path: /brewmaster/database/lookup_beer.py from pymysql import escape_string from app import mysql <|fim_suffix|> """Queries the MySQL database for a specific beer by name or id""" attr = 'id' if is_id is True else 'name' query = """ SELECT `id`, `nam...
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{ "lang": "python", "repo": "stormpython/brewmaster", "path": "/brewmaster/database/lookup_beer.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: stochasticnetworkcontrol/snc path: /tests/snc/agents/hedgehog/policies/test_big_step_layered_policy.py import numpy as np from snc.agents.hedgehog.params import BigStepLayeredPolicyParams, BigStepPenaltyPolicyParams from snc.agents.hedgehog.policies.big_step_layered_policy import BigStepLayeredP...
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{ "lang": "python", "repo": "stochasticnetworkcontrol/snc", "path": "/tests/snc/agents/hedgehog/policies/test_big_step_layered_policy.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> new_state = state + (policy_obj.buffer_processing_matrix @ z_star + policy_obj.demand_rate) * horizon # critical safety stock is maintained np.testing.assert_almost_equal(new_state[2], 10) def test_full_draining_layered_policy(): env = get_simple_link_constraine...
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{ "lang": "python", "repo": "stochasticnetworkcontrol/snc", "path": "/tests/snc/agents/hedgehog/policies/test_big_step_layered_policy.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: quantumlib/ReCirq path: /recirq/fermi_hubbard/converting_sampler.py # Copyright 2020 Google # # 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 # # https://www.apache.o...
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{ "lang": "python", "repo": "quantumlib/ReCirq", "path": "/recirq/fermi_hubbard/converting_sampler.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> self, program: cirq.Circuit, params: cirq.Sweepable, repetitions: int = 1, ) -> List[cirq.Result]: program = self._convert(program) return self._sampler.run_sweep(program, params, repetitions) async def run_async(self, program: cirq....
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{ "lang": "python", "repo": "quantumlib/ReCirq", "path": "/recirq/fermi_hubbard/converting_sampler.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: lewfish/mlx path: /mlx/od/fcos/model.py from collections import defaultdict import math import torch import torch.nn as nn from torchvision import models from mlx.od.fcos.decoder import decode_batch_output from mlx.od.fcos.loss import fcos_batch_loss class FPN(nn.Module): """Feature Pyrami...
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{ "lang": "python", "repo": "lewfish/mlx", "path": "/mlx/od/fcos/model.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> u5 = self.up_conv5(c4) c3 = self.cross_conv3(self.backbone_out['layer3']) d3 = c3 + nn.functional.interpolate(d4, c3.shape[2:]) c2 = self.cross_conv2(self.backbone_out['layer2']) d2 = c2 + nn.functional.interpolate(d3, c2.shape[2:]) c1 = self.cross_conv1(...
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{ "lang": "python", "repo": "lewfish/mlx", "path": "/mlx/od/fcos/model.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: romshen/epam_python_training path: /lecture_11/homework11/tasks/task1.py """ Vasya implemented nonoptimal Enum classes. Remove duplications in variables declarations using metaclasses. from enum import Enum class ColorsEnum(Enum): RED = "RED" BLUE = "BLUE" ORANGE = "ORANGE" BLA...
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{ "lang": "python", "repo": "romshen/epam_python_training", "path": "/lecture_11/homework11/tasks/task1.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> Raises: AttributeError: if object has no attribute name; Returns: attribute, if is. """ try: return type.__getattribute__(self, name) except AttributeError as error: try: return self.__dict__["member...
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{ "lang": "python", "repo": "romshen/epam_python_training", "path": "/lecture_11/homework11/tasks/task1.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: rapidsai/cugraph path: /python/cugraph/cugraph/structure/graph_classes.py Error("Series/DataFrame contains NULL values") class Graph: """ A GPU Graph Object (Base class of other graph types) Parameters ---------- m_graph : cuGraph.MultiGraph object or None (default=None) ...
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{ "lang": "python", "repo": "rapidsai/cugraph", "path": "/python/cugraph/cugraph/structure/graph_classes.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> Returns ------- series : cudf.Series or dask_cudf.Series The internal vertex identifiers """ return self.renumber_map.to_internal_vertex_id(df, column_name) def add_internal_vertex_id( self, df, internal_column_name, ...
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{ "lang": "python", "repo": "rapidsai/cugraph", "path": "/python/cugraph/cugraph/structure/graph_classes.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def is_multipartite(self): """ Checks if Graph is multipartite. This solely relies on the user call of add_nodes_from with the partition parameter. This does not parse the graph to check if it is multipartite. NOTE: Currently not implemented and always returns...
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{ "lang": "python", "repo": "rapidsai/cugraph", "path": "/python/cugraph/cugraph/structure/graph_classes.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>numba.cuda.cudadrv.driver.Device.reset() """ deletes the context for the device. This will destroy all memory allocations, events, and streams created within the context. """ classnumba.cuda.cudadrv.driver.Stream(context, handle, finalizer, external=False) https://numba.pydata.org/numba-doc/dev/cuda-re...
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{ "lang": "python", "repo": "timtyree/care", "path": "/notebooks/lib/controller/numba_stream_processing.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: timtyree/care path: /notebooks/lib/controller/numba_stream_processing.py #TODO: utilize multiple stream processors for high throughput. # Stream Management # Streams allow concurrency of execution on a single device within a given context. Queued work items in the same stream execute sequentially...
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{ "lang": "python", "repo": "timtyree/care", "path": "/notebooks/lib/controller/numba_stream_processing.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: crisdeodates/UAV-MAVSDK-Python path: /examples/camera_params.py #!/usr/bin/env python3 import asyncio from aioconsole import ainput from mavsdk import System from mavsdk.camera import (CameraError, Mode, Option, Setting) usage_str = """ Usage: p print current (changeable) camera settings...
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{ "lang": "python", "repo": "crisdeodates/UAV-MAVSDK-Python", "path": "/examples/camera_params.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> async def observe_possible_setting_options(drone): global possible_setting_options async for settings in drone.camera.possible_setting_options(): possible_setting_options = settings def print_current_settings(): print(f"* CAM_MODE: {camera_mode}") for setting in current_settings...
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{ "lang": "python", "repo": "crisdeodates/UAV-MAVSDK-Python", "path": "/examples/camera_params.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> Args: maf: MAF to be converted. Returns: DagMaf built from the MAF. """ sorted_blocks = sort_mafblocks(maf.filecontent) dagmafnodes = [ DAGMaf.DAGMafNode(block_id=b.id, alignment=b.alignment, orient=b.orient,...
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{ "lang": "python", "repo": "meoke/pangtree", "path": "/pangtreebuild/pangenome/builders/maf2dagmaf.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: meoke/pangtree path: /pangtreebuild/pangenome/builders/maf2dagmaf.py from pangtreebuild.mafgraph.sorter import sort_mafblocks from pangtreebuild.pangenome import DAGMaf from pangtreebuild.pangenome.parameters import msa from pangtreebuild.tools import logprocess <|fim_suffix|> Args: m...
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{ "lang": "python", "repo": "meoke/pangtree", "path": "/pangtreebuild/pangenome/builders/maf2dagmaf.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Training StepFn.""" @tf.function(jit_compile=jit_compile) def step_fn(inputs): samples, labels = inputs with tf.GradientTape() as tape: logits = model(samples) loss = compute_loss(labels, logits...
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{ "lang": "python", "repo": "xiaoheilong3112/keras", "path": "/keras/distribute/ctl_correctness_test.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: xiaoheilong3112/keras path: /keras/distribute/ctl_correctness_test.py n a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT...
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{ "lang": "python", "repo": "xiaoheilong3112/keras", "path": "/keras/distribute/ctl_correctness_test.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: xiaoheilong3112/keras path: /keras/distribute/ctl_correctness_test.py ONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ==============================================================================...
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{ "lang": "python", "repo": "xiaoheilong3112/keras", "path": "/keras/distribute/ctl_correctness_test.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_braking.py #calss header class _BRAKING(): <|fim_suffix|> self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.basic = ['brake']<|fim_middle|> def __init__(self,): self.name = "BRAKING" self.definitio...
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{ "lang": "python", "repo": "cash2one/xai", "path": "/xai/brain/wordbase/otherforms/_braking.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self.basic = ['brake']<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_braking.py #calss header class _BRAKING(): def __init__(self,): <|fim_middle|> self.name = "BRAKING" self.definitions = brake self.parents = [] self.childen = [] self.properties = [] self.jso...
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{ "lang": "python", "repo": "cash2one/xai", "path": "/xai/brain/wordbase/otherforms/_braking.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ARM-software/bob-build path: /config_system/config_system/__init__.py import os import sys # The config system depends on the `ply` parser generator. On Android, this may # come as a prebuilt, but may _not_ automatically be added to PYTHONPATH. If # we're on Android (tested by checking for `envs...
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{ "lang": "python", "repo": "ARM-software/bob-build", "path": "/config_system/config_system/__init__.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>from .expr import ( format_dependency_list, ) # nopep8: E402 module level import not at top of file<|fim_prefix|># repo: ARM-software/bob-build path: /config_system/config_system/__init__.py import os import sys # The config system depends on the `ply` parser generator. On Android, this may # come ...
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{ "lang": "python", "repo": "ARM-software/bob-build", "path": "/config_system/config_system/__init__.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: soipachara43/Alcohol path: /never_หญิง.py import pandas as pd import pygal from pygal.style import DarkStyle def spirit(): """start age""" data = pd.read_csv("never_female.csv") line_graph = pygal.Pie(fill=True, interpolate='cubic', style=DarkStyle) line_graph.x_labels = data.AGE...
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{ "lang": "python", "repo": "soipachara43/Alcohol", "path": "/never_หญิง.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>", data.THIRTYTOTHIRFOUR) line_graph.add("35-39 years old", data.THIRFIVETOTHIRNINE) line_graph.add("Above 40 years old", data.ABOVEFORTY) line_graph.render_to_file("never_fe.svg") spirit()<|fim_prefix|># repo: soipachara43/Alcohol path: /never_หญิง.py import pandas as pd import pygal from py...
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{ "lang": "python", "repo": "soipachara43/Alcohol", "path": "/never_หญิง.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: alessandrobalata/pyaigym path: /qlearning_training.py from src.environment import Environment from src.action import Action from src.q_learning.q_agent import QAgent from src.q_learning.q_episode import QEpisode from src.performace import Performance from src.state import State from src.q_learnin...
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{ "lang": "python", "repo": "alessandrobalata/pyaigym", "path": "/qlearning_training.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> episodes = 1000 try: pickling_on = open(f"models/{environment_name}.pickle", "rb") q = pickle.load(pickling_on) pickling_on.close() print('loading completed') except FileNotFoundError: q = None env = Environment(environment_name) q_learn = QLea...
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{ "lang": "python", "repo": "alessandrobalata/pyaigym", "path": "/qlearning_training.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>rule mmseqs2: input: fastx_both_input output: reads='data/{seq}.mmseqs2.{db}.tsv.gz' log: log='log/mmseqs2/{seq}.{db}.log', time='time/mmseqs2/{seq}.{db}.log' params: db=mmseqs2_db, db_tsv=mmseqs2_tsv, query_db='queryDB', query_lca_db='queryLcaD...
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{ "lang": "python", "repo": "thunder123321/metax_bakeoff_2019", "path": "/rules/mmseqs2.smk", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: thunder123321/metax_bakeoff_2019 path: /rules/mmseqs2.smk MMSEQS2 = config.get('MMSEQS2', 'mmseqs') mmseqs2_base_all = expand('reports/{sample}.mmseqs2.{{db}}.tsv', sample=samples_all) MMSEQS2_ALL = expand(mmseqs2_base_all, db=['nr', 'refseqc']) rule mmseqs2_all: input: MMSEQS2_ALL MMSEQS2...
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{ "lang": "python", "repo": "thunder123321/metax_bakeoff_2019", "path": "/rules/mmseqs2.smk", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>rule mmseqs2_benchmark: input: fastx_both_input output: reads='benchmark/data/{seq}.mmseqs2.{db}.tsv.gz' log: log='benchmark/log/mmseqs2/{seq}.{db}.log', time='benchmark/time/mmseqs2/{seq}.{db}.log' params: db=mmseqs2_db, db_tsv=mmseqs2_tsv, query_db='query...
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{ "lang": "python", "repo": "thunder123321/metax_bakeoff_2019", "path": "/rules/mmseqs2.smk", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> centroids = self.client.list_all_centroids().centroids self.assertEqual(set(['centroid-1', 'centroid-3']), set(centroids)) def test_centroid_creation_already_exists(self): self.client.create_centroid('centroid-1') with self.assertRaises(ECentroidAlreadyExists): ...
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{ "lang": "python", "repo": "random-mud-pie/relevanced", "path": "/clients/python/client/relevanced_client/test/test_centroid_crud.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: random-mud-pie/relevanced path: /clients/python/client/relevanced_client/test/test_centroid_crud.py from __future__ import print_function from .common import IsolatedTestCase from .. import ( ECentroidDoesNotExist, ECentroidAlreadyExists ) class TestCentroidCrud(IsolatedTestCase): d...
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{ "lang": "python", "repo": "random-mud-pie/relevanced", "path": "/clients/python/client/relevanced_client/test/test_centroid_crud.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: alexajwhite/spatialmath-python path: /spatialmath/base/animate.py #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Mon Apr 27 12:44:45 2020 @author: corkep """ #matplotlib inline # line.set_data() # text.set_position() # quiver.set_offsets(), quiver.set_UVC() # FancyArrow.set_xy() ...
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{ "lang": "python", "repo": "alexajwhite/spatialmath-python", "path": "/spatialmath/base/animate.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def text(self, x, y, z, *args, **kwargs): h = self.ax.text3D(x, y, z, *args, **kwargs) self.displaylist.append(Animate.Text(self, h, x, y, z)) #------------------- scatter() def scatter(self, **kwargs): pass #------------------- wrappers fo...
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{ "lang": "python", "repo": "alexajwhite/spatialmath-python", "path": "/spatialmath/base/animate.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: NeilBaksi/Dental-Appointment-Bot path: /dentistAPI/app/demo/v1/api/dentists.py # -*- coding: utf-8 -*- from __future__ import absolute_import, print_function import json,os,sys from flask import request, g, jsonify <|fim_suffix|> with open(sys.path[0]+'/v1/api/dentists.json') as json_data...
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{ "lang": "python", "repo": "NeilBaksi/Dental-Appointment-Bot", "path": "/dentistAPI/app/demo/v1/api/dentists.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def get(self): with open(sys.path[0]+'/v1/api/dentists.json') as json_data: d = json.load(json_data) #return jsonify(d), 200, None return jsonify({"dentists":d['dentists']}) def post(self): with open(sys.path[0]+'/v1/api/dentists.json') as json_data: ...
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{ "lang": "python", "repo": "NeilBaksi/Dental-Appointment-Bot", "path": "/dentistAPI/app/demo/v1/api/dentists.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: renovate-bot/python-game-servers path: /samples/snippets/update_cluster.py #!/usr/bin/env python # Copyright 2020 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obta...
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{ "lang": "python", "repo": "renovate-bot/python-game-servers", "path": "/samples/snippets/update_cluster.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> request = game_server_clusters.UpdateGameServerClusterRequest( game_server_cluster=game_server_clusters.GameServerCluster( name=f"projects/{project_id}/locations/{location}/realms/{realm_id}/gameServerClusters/{cluster_id}", labels={"label-key-1": "label-value-1", "labe...
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{ "lang": "python", "repo": "renovate-bot/python-game-servers", "path": "/samples/snippets/update_cluster.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument('--project-id', help='Your cloud project ID.', required=True) parser.add_argument('--location', help='Your realm location.', required=True) parser.add_argument('--realm-id', help='Your realm ID.', required=T...
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{ "lang": "python", "repo": "renovate-bot/python-game-servers", "path": "/samples/snippets/update_cluster.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> self.check(expected, doc) def test_when_with_let(self): doc = """\ ::when: ::let: a: 1 ::get: a == 1 ::then: foo: one ::else: bar: two """ expected ...
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{ "lang": "python", "repo": "TestingIaCwithNewAccount/jinsi", "path": "/tests/test_conditionals.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: TestingIaCwithNewAccount/jinsi path: /tests/test_conditionals.py import unittest from .common import JinsiTestCase class JinsiConditionals(JinsiTestCase): def test_conditional_with_let(self): doc = """\ ::let: a: 1 ::when: ::...
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{ "lang": "python", "repo": "TestingIaCwithNewAccount/jinsi", "path": "/tests/test_conditionals.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self.check(expected, doc) def test_case_default_underscore(self): doc = """\ value: ::let: x: 17 ::case: x == 1: one x == 2: two x == 3: three ...
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{ "lang": "python", "repo": "TestingIaCwithNewAccount/jinsi", "path": "/tests/test_conditionals.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> weight_map=1./weight_map for i,data in enumerate(test_dataset): output_list=np.zeros((1,1,2*img_size[0],2*img_size[1],2*img_size[2])) label_list=np.zeros((1,1,2*img_size[0],2*img_size[1],2*img_size[2])) (inputs,labels,_,guidance,mask)=data labels3D = pt.autograd.Va...
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{ "lang": "python", "repo": "locchio/PFSeg", "path": "/train_PFSeg.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> hd_sum+=hausdorff jc_sum+=jaccard print("Finished. Total dice: ",dice_sum/len(val_dataset),'\n') print("Finished. Avg Jaccard: ",jc_sum/len(val_dataset)) print("Finished. Avg hausdorff: ",hd_sum/len(val_dataset)) return dice_sum/len(val_dataset) def TestModel(): mode...
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{ "lang": "python", "repo": "locchio/PFSeg", "path": "/train_PFSeg.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: locchio/PFSeg path: /train_PFSeg.py import torch as pt import numpy as np from model.PFSeg import PFSeg3D from medpy.metric.binary import jc,hd95 from dataset.GuidedBraTSDataset3D import GuidedBraTSDataset3D # from loss.FALoss3D import FALoss3D import cv2 from loss.TaskFusionLoss import TaskFusio...
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{ "lang": "python", "repo": "locchio/PFSeg", "path": "/train_PFSeg.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def __prune_definition(self, parsed_definition): stars = parsed_definition index = 0 while index < len(stars): delete = [] for pointer in range(index + 1, len(stars)): if self.__equals(stars[index], stars[pointer]): de...
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{ "lang": "python", "repo": "betty29/code-1", "path": "/recipes/Python/483735_Constellation_Finder/recipe-483735.py", "mode": "spm", "license": "Python-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: betty29/code-1 path: /recipes/Python/483735_Constellation_Finder/recipe-483735.py class stars: def __init__(self, owner, star_data): self.__owner = owner self.__star_data = star_data self.__stars = self.__parse() self.__set = set(self.__stars) def __parse...
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{ "lang": "python", "repo": "betty29/code-1", "path": "/recipes/Python/483735_Constellation_Finder/recipe-483735.py", "mode": "psm", "license": "Python-2.0", "source": "the-stack-v2" }
<|fim_suffix|> midi_in = rtmidi.RtMidiIn() if args.list: list_ports() else: if args.port: port = args.port else: port = choose_port() if args.keycodes: print_keycodes(port) else: config = read_config(args.config) ...
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{ "lang": "python", "repo": "Nuhddy/midi-input-mapper", "path": "/midi-input-mapper.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> midi_in.openPort(port) while True: m = midi_in.getMessage(250) if m: print_message(m) def eval_input(port): midi_in.openPort(port) while True: m = midi_in.getMessage(250) if m: note = m.getNoteNumber() if note in config:...
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{ "lang": "python", "repo": "Nuhddy/midi-input-mapper", "path": "/midi-input-mapper.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Nuhddy/midi-input-mapper path: /midi-input-mapper.py #! /usr/bin/env python3 import rtmidi import os import yaml import argparse import sys def get_args(): p = argparse.ArgumentParser(description="Map MIDI input to commands") p.add_argument("-l", "--list", action="st...
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{ "lang": "python", "repo": "Nuhddy/midi-input-mapper", "path": "/midi-input-mapper.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> rospy.sleep(0.01) if aprendendo: return 'aprendendo' return desviando(mini) # main def main(): global velocidade_saida global buffer rospy.init_node('cf_estados') # Para usar a webcam #recebedor = rospy.Subscriber("/cv_camera/image_raw/compressed", CompressedImage, roda_todo_frame, queu...
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{ "lang": "python", "repo": "wesleygas/RoR9000", "path": "/state_full.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: wesleygas/RoR9000 path: /state_full.py #! /usr/bin/env python # -*- coding:utf-8 -*- import rospy import numpy as np import tf from matplotlib import pyplot as plt import math import cv2 import time from geometry_msgs.msg import Twist, Vector3, Pose from nav_msgs.msg import Odometry from sensor_...
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{ "lang": "python", "repo": "wesleygas/RoR9000", "path": "/state_full.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # Para usar a webcam #recebedor = rospy.Subscriber("/cv_camera/image_raw/compressed", CompressedImage, roda_todo_frame, queue_size=1, buff_size = 2**24) start = rospy.get_rostime() recebedor = rospy.Subscriber("/raspicam_node/image/compressed", CompressedImage, roda_todo_frame, queue_size=10, buff_si...
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{ "lang": "python", "repo": "wesleygas/RoR9000", "path": "/state_full.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>@app.route("/") async def health(request): return json({"status": "ok"}) async def send_sms(to_addr, claim_id, body): headers = { "Authorization": "Bearer {}".format(getenv("TURN_TOKEN")), "Content-Type": "application/json", "x-turn-fallback-channel": "1", "X-Turn...
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{ "lang": "python", "repo": "praekeltfoundation/momconnect-solidarity-sms", "path": "/api.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: praekeltfoundation/momconnect-solidarity-sms path: /api.py import base64 import hmac from functools import wraps from hashlib import sha256 from os import getenv from urllib.parse import urljoin import httpx from sanic import Sanic from sanic.response import json from sanic_prometheus import mon...
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{ "lang": "python", "repo": "praekeltfoundation/momconnect-solidarity-sms", "path": "/api.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> @wraps(f) async def decorated_function(request, *args, **kwargs): try: signature = request.headers["X-Turn-Hook-Signature"] assert signature except (KeyError, AssertionError): return json({"authorization": "X-Turn-Hook-Signature header required"}...
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{ "lang": "python", "repo": "praekeltfoundation/momconnect-solidarity-sms", "path": "/api.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|>"A" and linha[j]<="Z"): linha[j] =<|fim_prefix|># repo: pufe/programa path: /2020-11-16/cripto.py n = int(input()) for i in range(n): linh<|fim_middle|>a = input() for j in range(len(linha)): c = "" if (linha[j] >=
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{ "lang": "python", "repo": "pufe/programa", "path": "/2020-11-16/cripto.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: pufe/programa path: /2020-11-16/cripto.py n = int(input()) for i in range(n): linha = input() for j in range(len(linh<|fim_suffix|>"A" and linha[j]<="Z"): linha[j] =<|fim_middle|>a)): c = "" if (linha[j] >=
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{ "lang": "python", "repo": "pufe/programa", "path": "/2020-11-16/cripto.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: pufe/programa path: /2020-11-16/cripto.py n = int(input()) for i in range(n): linh<|fim_suffix|>"A" and linha[j]<="Z"): linha[j] =<|fim_middle|>a = input() for j in range(len(linha)): c = "" if (linha[j] >=
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{ "lang": "python", "repo": "pufe/programa", "path": "/2020-11-16/cripto.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> colormap = "viridis" sc = 1/np.sum(cm, axis=1) cm_norm = sc[None].T * cm plt.figure() plt.title(title) plt.imshow(cm_norm, cmap=colormap) plt.xlabel("Predicted Label") plt.ylabel("True Label") plt.colorbar() plt.xticks(np.arange(len(cm_norm))) plt.yticks(np.ar...
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{ "lang": "python", "repo": "mandulaj/CryBabyCry", "path": "/tools.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: mandulaj/CryBabyCry path: /tools.py import os import numpy as np import pickle import matplotlib.pyplot as plt import matplotlib def zero_pad(a, length): z = np.zeros(length) offset = len(z)//2 - len(a)//2 if offset < 0: offset = 0 z[offset:offset+len(a)] = a retur...
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{ "lang": "python", "repo": "mandulaj/CryBabyCry", "path": "/tools.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: cohesity/management-sdk-python path: /cohesity_management_sdk/models/protected_objects_by_env.py # -*- coding: utf-8 -*- # Copyright 2023 Cohesity Inc. class ProtectedObjectsByEnv(object): """Implementation of the 'ProtectedObjectsByEnv' model. Number of Protected Objects by Type. ...
code_fim
hard
{ "lang": "python", "repo": "cohesity/management-sdk-python", "path": "/cohesity_management_sdk/models/protected_objects_by_env.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> """ and one val""" self.val = val self.sum += val * n self.count += n self.avg = self.sum / self.count def __str__(self): fmtstr = '{name} {val' + self.fmt + '} ({avg' + self.fmt + '})' return fmtstr.format(**self.__dict__) def wei...
code_fim
hard
{ "lang": "python", "repo": "Ascend/ModelZoo-PyTorch", "path": "/PyTorch/contrib/cv/classification/DnCNN/utils.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: Ascend/ModelZoo-PyTorch path: /PyTorch/contrib/cv/classification/DnCNN/utils.py # -*- coding: utf-8 -*- # Copyright 2020 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may o...
code_fim
hard
{ "lang": "python", "repo": "Ascend/ModelZoo-PyTorch", "path": "/PyTorch/contrib/cv/classification/DnCNN/utils.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def __str__(self): fmtstr = '{name} {val' + self.fmt + '} ({avg' + self.fmt + '})' return fmtstr.format(**self.__dict__) def weights_init_kaiming(m): """ init layers """ classname = m.__class__.__name__ if classname.find('Conv') != -1: nn.init.kaiming_normal(m...
code_fim
hard
{ "lang": "python", "repo": "Ascend/ModelZoo-PyTorch", "path": "/PyTorch/contrib/cv/classification/DnCNN/utils.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: KoxAlen/adventofcode path: /day02/script.py #Written for Python 3.4.2 data = [line.rstrip('\n') for line in open("input.txt")] totalpaper = 0 totalribbon = 0 for present in data: <|fim_suffix|> f3 = dimensions[2]*dimensions[0] extra = min(f1,f2,f3) wraplenght = 2*(dimensions[0]+dimens...
code_fim
medium
{ "lang": "python", "repo": "KoxAlen/adventofcode", "path": "/day02/script.py", "mode": "psm", "license": "WTFPL", "source": "the-stack-v2" }
<|fim_suffix|> f3 = dimensions[2]*dimensions[0] extra = min(f1,f2,f3) wraplenght = 2*(dimensions[0]+dimensions[1]) bow = dimensions[0]*dimensions[1]*dimensions[2] totalpaper += 2*(f1+f2+f3)+extra totalribbon += wraplenght+bow print(totalpaper) print(totalribbon)<|fim_prefix|># repo: KoxAlen/a...
code_fim
medium
{ "lang": "python", "repo": "KoxAlen/adventofcode", "path": "/day02/script.py", "mode": "spm", "license": "WTFPL", "source": "the-stack-v2" }