dbaysal/function-class-dataset-new · Datasets at Hugging Face

ac50fc8ee863147bc6608f36

train

function

def vectorize_candidates(candidates, word_idx, sentence_size): shape = (len(candidates), sentence_size) C = [] for i, candidate in enumerate(candidates): lc = max(0, sentence_size - len(candidate)) C.append([word_idx[w] if w in word_idx else 0 for w in candidate] + [0] * lc) return Var(l...

def vectorize_candidates(candidates, word_idx, sentence_size):

shape = (len(candidates), sentence_size) C = [] for i, candidate in enumerate(candidates): lc = max(0, sentence_size - len(candidate)) C.append([word_idx[w] if w in word_idx else 0 for w in candidate] + [0] * lc) return Var(ldtype(C))

context.append(r) else: r = tokenize(line) r.append('$r') r.append('#' + str(nid)) context.append(r) else: # clear context context = [] return data def vectorize_candidates(candidates, word_id...

64

86

13

50

abhi608/task_oriented_nlp_system

memn2n_src/data_utils2.py

Python

vectorize_candidates

120

126

120

6513ed822d2ee2bf64b0abbcb5881c4034bcbbde

bigcode/the-stack

train

731888f9d296f9f4d61113b6

train

function

@app.post("/upload_img") async def upload_img(img: List[UploadFile] = File(...)): for file in img: with open(file.filename, 'wb') as buffer: shutil.copyfileobj(file.file, buffer) return {"file_name": file.filename}

@app.post("/upload_img") async def upload_img(img: List[UploadFile] = File(...)):

for file in img: with open(file.filename, 'wb') as buffer: shutil.copyfileobj(file.file, buffer) return {"file_name": file.filename}

async def upload_file(file: UploadFile = File(...)): with open(file.filename, 'wb') as buffer: shutil.copyfileobj(file.file, buffer) return {"file_name": file.filename} @app.post("/upload_img") async def upload_img(img: List[UploadFile] = File(...)):

64

58

21

43

OlegZaichuk/Fast_Api_Pyth_3.10

main.py

Python

upload_img

22

27

22

23

900c5c8d2f415d7ce800ced4ebaf38cd31c5000c

bigcode/the-stack

train

d8d4e04f670ca951bb6916ae

train

function

@app.post("/upload_file") async def upload_file(file: UploadFile = File(...)): with open(file.filename, 'wb') as buffer: shutil.copyfileobj(file.file, buffer) return {"file_name": file.filename}

@app.post("/upload_file") async def upload_file(file: UploadFile = File(...)):

with open(file.filename, 'wb') as buffer: shutil.copyfileobj(file.file, buffer) return {"file_name": file.filename}

, Path, Body, UploadFile, File import uvicorn import shutil from typing import List, Optional app = FastAPI() @app.get("/") async def read_root(): return {"Hello": "World"} @app.post("/upload_file") async def upload_file(file: UploadFile = File(...)):

63

64

49

18

45

OlegZaichuk/Fast_Api_Pyth_3.10

main.py

Python

upload_file

15

19

15

16

5a230591de016e56bca2ff2ecc98e0fa1c557594

bigcode/the-stack

train

642465f0e51f9c4f0094bc75

train

function

@app.get("/items/{item_id}") async def read_item(item_id: int, q: Optional[str] = None): return {"item_id": item_id, "q": q}

@app.get("/items/{item_id}") async def read_item(item_id: int, q: Optional[str] = None):

return {"item_id": item_id, "q": q}

(...)): for file in img: with open(file.filename, 'wb') as buffer: shutil.copyfileobj(file.file, buffer) return {"file_name": file.filename} @app.get("/items/{item_id}") async def read_item(item_id: int, q: Optional[str] = None):

64

39

25

39

OlegZaichuk/Fast_Api_Pyth_3.10

main.py

Python

read_item

30

32

30

31

c4ecfef17e9ee923efc7157d3579cd8d1a8265dd

bigcode/the-stack

train

81c57e359199a1522789f888

train

function

@app.get("/") async def read_root(): return {"Hello": "World"}

@app.get("/") async def read_root():

return {"Hello": "World"}

from fastapi import FastAPI, Query, Path, Body, UploadFile, File import uvicorn import shutil from typing import List, Optional app = FastAPI() @app.get("/") async def read_root():

45

64

16

8

37

OlegZaichuk/Fast_Api_Pyth_3.10

main.py

Python

read_root

10

12

10

11

264c7dd8e284df504cb3e2e43e684db53ec436bb

bigcode/the-stack

train

7473f26de7bb0aadb5a558b5

train

class

class GitFolderHandling(Enum): """ This enum defines way, how is .git folder handled during project build. """ DELETE_BEFORE_BUILD = 1 DELETE_AFTER_BUILD = 2 DISABLE_DELETE = 3

class GitFolderHandling(Enum):

""" This enum defines way, how is .git folder handled during project build. """ DELETE_BEFORE_BUILD = 1 DELETE_AFTER_BUILD = 2 DISABLE_DELETE = 3

from enum import Enum class GitFolderHandling(Enum):

11

64

51

6

4

inktrap/flux-ci

flux/enums.py

Python

GitFolderHandling

4

11

4

8ef3228ae2496a296aa9da159a1b8ed34cc050af

bigcode/the-stack

train

7d82db435cd89c4c726e6cd7

train

class

@pulumi.output_type class GetTableServicePropertiesResult: """ The properties of a storage account’s Table service. """ def __init__(__self__, cors=None, id=None, name=None, type=None): if cors and not isinstance(cors, dict): raise TypeError("Expected argument 'cors' to be a dict") ...

@pulumi.output_type class GetTableServicePropertiesResult:

""" The properties of a storage account’s Table service. """ def __init__(__self__, cors=None, id=None, name=None, type=None): if cors and not isinstance(cors, dict): raise TypeError("Expected argument 'cors' to be a dict") pulumi.set(__self__, "cors", cors) if id and...

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from ... import _utilities fro...

123

136

455

13

110

sebtelko/pulumi-azure-native

sdk/python/pulumi_azure_native/storage/v20210101/get_table_service_properties.py

Python

GetTableServicePropertiesResult

18

67

18

19

f0a1426032f6372231c25caca5af96782d79592d

bigcode/the-stack

train

fef49962177bdebfb38fc32f

train

function

def get_table_service_properties(account_name: Optional[str] = None, resource_group_name: Optional[str] = None, table_service_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetTableSe...

""" The properties of a storage account’s Table service. :param str account_name: The name of the storage account within the specified resource group. Storage account names must be between 3 and 24 characters in length and use numbers and lower-case letters only. :param str resource_group_name: The na...

__(self): if False: yield self return GetTableServicePropertiesResult( cors=self.cors, id=self.id, name=self.name, type=self.type) def get_table_service_properties(account_name: Optional[str] = None, resource_gr...

98

327

58

40

sebtelko/pulumi-azure-native

sdk/python/pulumi_azure_native/storage/v20210101/get_table_service_properties.py

Python

get_table_service_properties

82

108

82

85

cce0385170f35db203e085decdc3ca97b1264ced

bigcode/the-stack

train

160f18c7faf1ba4e9bdb40f8

train

class

class AwaitableGetTableServicePropertiesResult(GetTableServicePropertiesResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetTableServicePropertiesResult( cors=self.cors, id=self.id, name=self.name, ...

class AwaitableGetTableServicePropertiesResult(GetTableServicePropertiesResult): # pylint: disable=using-constant-test

def __await__(self): if False: yield self return GetTableServicePropertiesResult( cors=self.cors, id=self.id, name=self.name, type=self.type)

: """ The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts" """ return pulumi.get(self, "type") class AwaitableGetTableServicePropertiesResult(GetTableServicePropertiesResult): # pylint: disable=using-constant-test

64

69

25

39

sebtelko/pulumi-azure-native

sdk/python/pulumi_azure_native/storage/v20210101/get_table_service_properties.py

Python

AwaitableGetTableServicePropertiesResult

70

79

70

71

9134884573fabfb7fffcb56e8efc7fb64da4ec78

bigcode/the-stack

train

8813379ddd272c7a4f1c97b9

train

function

@logger('loading data') def load_data(filename: str, limit: Optional[int] = None) -> List[Example]: data = [] with open(filename) as json_data: questions = json.load(json_data)["questions"][:limit] for question in questions: tokenized_text = nltk.word_tokenize(question['text'].lower()) label = question['pag...

@logger('loading data') def load_data(filename: str, limit: Optional[int] = None) -> List[Example]:

data = [] with open(filename) as json_data: questions = json.load(json_data)["questions"][:limit] for question in questions: tokenized_text = nltk.word_tokenize(question['text'].lower()) label = question['page'] if label: data.append(Example(tokenized_text, label)) return data

_dataset.pkl' TEST_DATASET = 'test_dataset.pkl' WORD_MAPS = 'word_maps.pkl' class Example(NamedTuple): tokenized_text: List[str] label: str @logger('loading data') def load_data(filename: str, limit: Optional[int] = None) -> List[Example]:

64

97

26

37

ExSidius/qanta-codalab

src/qanta/guesser_model.py

Python

load_data

28

38

28

29

d45022160538732795e7cb6dbf1bb94fdb9d9e0d

bigcode/the-stack

train

e81819677ca8224428bf0d27

train

class

class Model(nn.Module): def __init__(self, n_classes, vocab_size, embedding_dimension=EMBEDDING_LENGTH, embedder=None, n_hidden=50, dropout_rate=.5): super(Model, self).__init__() self.n_classes = n_classes self.vocab_size = vocab_size self.n_hidden = n_hidden self.e...

class Model(nn.Module):

def __init__(self, n_classes, vocab_size, embedding_dimension=EMBEDDING_LENGTH, embedder=None, n_hidden=50, dropout_rate=.5): super(Model, self).__init__() self.n_classes = n_classes self.vocab_size = vocab_size self.n_hidden = n_hidden self.embedding_dimension = emb...

= list(labels) labels = torch.LongTensor(labels) x1 = torch.LongTensor(len(questions), max(question_lens)).zero_() for i, (question, q_len) in enumerate(zip(questions, question_lens)): x1[i, :q_len].copy_(torch.LongTensor(question)) return { 'text': x1, 'len': torch.FloatTensor(question_lens), 'labels': ...

101

339

5

96

ExSidius/qanta-codalab

src/qanta/guesser_model.py

Python

Model

144

194

144

9669cf90e41a7210f478398e7eaca73dbb3c34ab

bigcode/the-stack

train

94042771d3f32682f3839155

train

class

class QuestionDataset(Dataset): def __init__(self, examples: List[Example], word2index: Dict[str, int], num_classes: int, class2index: Optional[Dict[str, int]] = None): self.tokenized_questions = [] self.labels = [] tokenized_questions, labels = zip(*examples) self.tokenized_questions = li...

class QuestionDataset(Dataset):

def __init__(self, examples: List[Example], word2index: Dict[str, int], num_classes: int, class2index: Optional[Dict[str, int]] = None): self.tokenized_questions = [] self.labels = [] tokenized_questions, labels = zip(*examples) self.tokenized_questions = list(tokenized_questions) self.l...

] >= cutoff]) new_train = [] new_dev = [] for example in training_examples: if example.label in ans_keep: new_train.append(example) for example in dev_examples: if example.label in ans_keep: new_dev.append(example) return new_train, new_dev, len(ans_keep)/len(ans_count) class QuestionDataset(Dataset):

73

244

6

67

ExSidius/qanta-codalab

src/qanta/guesser_model.py

Python

QuestionDataset

85

117

85

b4ebb2c3fe9af851c7e60aa0c36ae723737d81f1

bigcode/the-stack

train

c4087cba3bccb7210bed5d8e

train

function

@logger('loading words') def load_words(examples: List[Example]) -> Tuple[ List[str], Dict[str, int], Dict[int, str]]: words = {kPAD, kUNK} tokenized_texts, _ = zip(*examples) for tokenized_text in tokenized_texts: for token in tokenized_text: if token not in words: words.add(token) words = list(words) ...

@logger('loading words') def load_words(examples: List[Example]) -> Tuple[ List[str], Dict[str, int], Dict[int, str]]:

words = {kPAD, kUNK} tokenized_texts, _ = zip(*examples) for tokenized_text in tokenized_texts: for token in tokenized_text: if token not in words: words.add(token) words = list(words) index2word = dict(enumerate(words)) word2index = {v: k for k, v in index2word.items()} return words, word2index, ind...

(enumerate(classes)) class2index = {v: k for k, v in index2class.items()} return class2index, index2class @logger('loading words') def load_words(examples: List[Example]) -> Tuple[ List[str], Dict[str, int], Dict[int, str]]:

64

130

32

31

ExSidius/qanta-codalab

src/qanta/guesser_model.py

Python

load_words

50

65

50

52

eb623ecfe1c361b0a3a85be00092d2e8a405b76b

bigcode/the-stack

train

7ae328f92a2ad2528f441313

train

function

@logger('clip dataset') def clip_data(training_examples, dev_examples, cutoff=2): ans_count = defaultdict(int) for example in (training_examples + dev_examples): ans_count[example.label] += 1 ans_keep = set([x for x in ans_count if ans_count[x] >= cutoff]) new_train = [] new_dev = [] for example in training_exa...

@logger('clip dataset') def clip_data(training_examples, dev_examples, cutoff=2):

ans_count = defaultdict(int) for example in (training_examples + dev_examples): ans_count[example.label] += 1 ans_keep = set([x for x in ans_count if ans_count[x] >= cutoff]) new_train = [] new_dev = [] for example in training_examples: if example.label in ans_keep: new_train.append(example) for example i...

words = list(words) index2word = dict(enumerate(words)) word2index = {v: k for k, v in index2word.items()} return words, word2index, index2word @logger('clip dataset') def clip_data(training_examples, dev_examples, cutoff=2):

64

128

19

44

ExSidius/qanta-codalab

src/qanta/guesser_model.py

Python

clip_data

68

82

68

69

4db10bbe0db751fe0004b96bed35e92c5c67b6d9

bigcode/the-stack

train

8d01c0f6b42b0353247492c2

train

function

@logger('creating class labels') def class_labels(examples: List[Example]) -> Tuple[ Dict[str, int], Dict[int, str]]: classes = set([example.label for example in examples]) index2class = dict(enumerate(classes)) class2index = {v: k for k, v in index2class.items()} return class2index, index2class

@logger('creating class labels') def class_labels(examples: List[Example]) -> Tuple[ Dict[str, int], Dict[int, str]]:

classes = set([example.label for example in examples]) index2class = dict(enumerate(classes)) class2index = {v: k for k, v in index2class.items()} return class2index, index2class

_tokenize(question['text'].lower()) label = question['page'] if label: data.append(Example(tokenized_text, label)) return data @logger('creating class labels') def class_labels(examples: List[Example]) -> Tuple[ Dict[str, int], Dict[int, str]]:

64

80

31

32

ExSidius/qanta-codalab

src/qanta/guesser_model.py

Python

class_labels

41

47

41

43

b0ebdeb779704f5d86eb7c319b0d1133b670bec0

bigcode/the-stack

train

c57bdff88994ddd2c6cfc569

train

class

class Example(NamedTuple): tokenized_text: List[str] label: str

class Example(NamedTuple):

tokenized_text: List[str] label: str

der import EMBEDDING_LENGTH, Embedder kUNK = '<unk>' kPAD = '<pad>' TRAIN_DATASET = 'train_dataset.pkl' DEV_DATASET = 'dev_dataset.pkl' TEST_DATASET = 'test_dataset.pkl' WORD_MAPS = 'word_maps.pkl' class Example(NamedTuple):

64

17

6

58

ExSidius/qanta-codalab

src/qanta/guesser_model.py

Python

Example

23

25

23

fe0c3cad3e7bc82fc9bf9b8ecbedebb8309bfcd6

bigcode/the-stack

train

0c92bdf7f63fc6e49070e0d5

train

function

def evaluate(data_loader: torch.utils.data.DataLoader, model: Model, device: torch.device) -> float: model.eval() num_examples = 0 error = 0 for i, batch in enumerate(data_loader): question_text = batch['text'].to(device) question_len = batch['len'].to(device) labels = batch['labels'].to(device) lo...

def evaluate(data_loader: torch.utils.data.DataLoader, model: Model, device: torch.device) -> float:

model.eval() num_examples = 0 error = 0 for i, batch in enumerate(data_loader): question_text = batch['text'].to(device) question_len = batch['len'].to(device) labels = batch['labels'].to(device) logits = model(question_text, question_len) top_n, top_i = logits.topk(1) num_examples += question_text.si...

0), -1) if is_prob: logits = self._softmax(logits) else: logits = self.classifier(average_embedding) return logits def evaluate(data_loader: torch.utils.data.DataLoader, model: Model, device: torch.device) -> float:

64

152

25

38

ExSidius/qanta-codalab

src/qanta/guesser_model.py

Python

evaluate

197

216

197

199

9246d168286a658afb7fa3e081c00e6add32bb18

bigcode/the-stack

train

68654591dfd18bd474af1ef6

train

function

def train(args: argparse.Namespace, model: Model, train_data_loader: torch.utils.data.DataLoader, dev_data_loader: torch.utils.data.DataLoader, accuracy: float, device: torch.device, learning_rate: float) -> float: model.train() if args.optim == 'adamax': optimizer = torch.optim.Adamax...

def train(args: argparse.Namespace, model: Model, train_data_loader: torch.utils.data.DataLoader, dev_data_loader: torch.utils.data.DataLoader, accuracy: float, device: torch.device, learning_rate: float) -> float:

model.train() if args.optim == 'adamax': optimizer = torch.optim.Adamax(model.parameters(), lr=learning_rate) elif args.optim == 'rprop': optimizer = torch.optim.Rprop(model.parameters(), lr=learning_rate) criterion = nn.CrossEntropyLoss() # print_loss_total = 0 # epoch_loss_total = 0 # start = time.time() ...

) top_n, top_i = logits.topk(1) num_examples += question_text.size(0) error += torch.nonzero(top_i.squeeze() - labels).size(0) accuracy = 1 - error / num_examples print(accuracy) return accuracy def train(args: argparse.Namespace, model: Model, train_data_loader: torch.utils.data.DataLoader, dev_...

113

378

54

58

ExSidius/qanta-codalab

src/qanta/guesser_model.py

Python

train

219

263

219

225

514e28de063a538808df2ddce0d1b66c12560e64

bigcode/the-stack

train

07487adffd59000ed4502c46

train

function

def batchify(batch: List[Tuple[List[int], int]]) -> Dict[ str, Union[torch.LongTensor, torch.FloatTensor]]: """ Create a batch of examples which includes the question text, question length and labels. """ questions, labels = zip(*batch) questions = list(questions) question_lens = [len(q) for q in questions] l...

def batchify(batch: List[Tuple[List[int], int]]) -> Dict[ str, Union[torch.LongTensor, torch.FloatTensor]]:

""" Create a batch of examples which includes the question text, question length and labels. """ questions, labels = zip(*batch) questions = list(questions) question_lens = [len(q) for q in questions] labels = list(labels) labels = torch.LongTensor(labels) x1 = torch.LongTensor(len(questions), max(question_...

[int]: return [self.word2index[word] if word in self.word2index else self.word2index[kUNK] for word in tokenized_text] def batchify(batch: List[Tuple[List[int], int]]) -> Dict[ str, Union[torch.LongTensor, torch.FloatTensor]]:

64

178

28

36

ExSidius/qanta-codalab

src/qanta/guesser_model.py

Python

batchify

120

141

120

121

f6001fd611702614e5925c0dadb78638ec0ba7ac

bigcode/the-stack

train

c93448960d2657c632f68799

train

function

def run_program_for_single_img( # pylint: disable=too-many-branches, too-many-statements image: str, resize: bool = False, size: Optional[Tuple[int, int]] = None, place: str = DEFAULT_PLACE, match_filter: Optional[str] = None, browser: Optional[mechanicalsoup.StatefulBrowser] = None, scrape...

"""Run program for single image. Args: image: image path resize: resize the image size: resized image size place: iqdb place, see `iqdb_url_dict` match_filter: whitelist matched items browser: mechanicalsoup browser instance scraper: cfscrape instance ...

=url, browser=browser, use_requests=use_requests) # if ok, will output: <Response [200]> result = list( models.ImageMatch.get_or_create_from_page(page=page, image=post_img, place=im_place)) result = [x[0] for x in result] # temp_f temp_f.close() os.remove(temp_file_name) ...

256

960

148

107

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

run_program_for_single_img

156

259

156

168

507de73dfc5e3a5ec5669368f0bea06eb6e8ceb6

bigcode/the-stack

train

4cfa06d4aa87456188464440

train

function

@click.group(cls=CustomFlaskGroup, create_app=create_app) def cli(): """Run cli. This is a management script for application."""

@click.group(cls=CustomFlaskGroup, create_app=create_app) def cli():

"""Run cli. This is a management script for application."""

% { 'app_name': 'Iqdb-tagger', 'app_version': __version__, 'version': flask_version, 'python_version': sys.version, }, color=ctx.color) ctx.exit() @click.group(cls=CustomFlaskGroup, create_app=create_app) def cli():

64

30

17

47

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

cli

354

356

354

355

eae8ad6469f005c34c295ceb2a6d630c91703ec8

bigcode/the-stack

train

0ef609bb1176c932aa0b8a86

train

function

def write_url_from_match_result(match_result, folder=None): """Write url from match result.""" netloc = urlparse(match_result.link).netloc sanitized_netloc = netloc.replace('.', '_') text_file_basename = sanitized_netloc + '.txt' text_file = os.path.join(folder, text_file_basename) if folder is not ...

def write_url_from_match_result(match_result, folder=None):

"""Write url from match result.""" netloc = urlparse(match_result.link).netloc sanitized_netloc = netloc.replace('.', '_') text_file_basename = sanitized_netloc + '.txt' text_file = os.path.join(folder, text_file_basename) if folder is not None else text_file_basename with open(text_file, 'a') a...

Init program.""" # create user data dir pathlib.Path(user_data_dir).mkdir(parents=True, exist_ok=True) pathlib.Path(thumb_folder).mkdir(parents=True, exist_ok=True) models.init_db(db_path, db_version) def write_url_from_match_result(match_result, folder=None):

64

107

12

52

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

write_url_from_match_result

88

96

88

53a1ede7bae81871ec39a492e1513576e4c11667

bigcode/the-stack

train

67588d05315d8188ed9c7840

train

function

def init_program(db_path: Optional[str] = default_db_path): """Init program.""" # create user data dir pathlib.Path(user_data_dir).mkdir(parents=True, exist_ok=True) pathlib.Path(thumb_folder).mkdir(parents=True, exist_ok=True) models.init_db(db_path, db_version)

def init_program(db_path: Optional[str] = default_db_path):

"""Init program.""" # create user data dir pathlib.Path(user_data_dir).mkdir(parents=True, exist_ok=True) pathlib.Path(thumb_folder).mkdir(parents=True, exist_ok=True) models.init_db(db_path, db_version)

in tables: res = models.ImageMatch.parse_table(table) if not res: continue additional_res = models.get_additional_result_from_table(table, res) if additional_res: yield additional_res yield res def init_program(db_path: Optional[str] = default_db_path):

64

68

14

49

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

init_program

80

85

80

2bb655b2146673f1d26946e2aa4c8b53a2f5f19d

bigcode/the-stack

train

59fbb585b99b76d7cd2b1071

train

function

def get_iqdb_result(image, iqdb_url): """Get iqdb result.""" e621_iqdb_url = 'http://iqdb.harry.lu' use_requests = iqdb_url != e621_iqdb_url if use_requests: files = {'file': open(image, 'rb')} resp = requests.post(iqdb_url, files=files, timeout=10) html_text = BeautifulSoup(resp...

def get_iqdb_result(image, iqdb_url):

"""Get iqdb result.""" e621_iqdb_url = 'http://iqdb.harry.lu' use_requests = iqdb_url != e621_iqdb_url if use_requests: files = {'file': open(image, 'rb')} resp = requests.post(iqdb_url, files=files, timeout=10) html_text = BeautifulSoup(resp.text, 'lxml') else: brows...

' DEFAULT_PLACE = 'iqdb' minsim = 75 services = ['1', '2', '3', '4', '5', '6', '10', '11'] forcegray = False log = structlog.getLogger() def get_iqdb_result(image, iqdb_url):

64

183

12

52

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

get_iqdb_result

48

64

48

003841b0add7cade8bb0248db55e08ff232bbd3b

bigcode/the-stack

train

493ede6a4829c1d23e402371

train

function

def get_custom_version(ctx, _, value): """Get version.""" if not value or ctx.resilient_parsing: return message = '%(app_name)s %(app_version)s\nFlask %(version)s\nPython %(python_version)s' click.echo(message % { 'app_name': 'Iqdb-tagger', 'app_version': __version__, 've...

def get_custom_version(ctx, _, value):

"""Get version.""" if not value or ctx.resilient_parsing: return message = '%(app_name)s %(app_version)s\nFlask %(version)s\nPython %(python_version)s' click.echo(message % { 'app_name': 'Iqdb-tagger', 'app_version': __version__, 'version': flask_version, 'python_...

"""Custom Flask Group.""" def __init__(self, **kwargs): """Class init.""" super().__init__(**kwargs) self.params[0].help = 'Show the program version' self.params[0].callback = get_custom_version def get_custom_version(ctx, _, value):

64

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9

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a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

get_custom_version

340

351

340

2e83a3c12ec7f2e3a2dd58c2679d5cf0546574a7

bigcode/the-stack

train

10a35413aa0be44839ccb2d9

train

function

@cli.command() @click.argument('tag', nargs=-1) @click.option('--access_key', help='Hydrus access key') @click.option('--hydrus_url', help='URL for hydrus client e.g. http://127.0.0.1:45869/') def search_hydrus_and_send_url(tag: List[str], access_key: Optional[str] = None, hydrus_url: Optional[str] = 'http://127.0.0.1:...

"""Search hydrus and send url.""" # compatibility search_tags = tag if Client is None: print('Hydrus package is required') return cl = Client(access_key, hydrus_url) for res_dict in get_hydrus_set(search_tags, cl): match_results = [x[0] for x in res_dict['iqdb_result']['...

@cli.command() @click.argument('tag', nargs=-1) @click.option('--access_key', help='Hydrus access key') @click.option('--hydrus_url', help='URL for hydrus client e.g. http://127.0.0.1:45869/') def search_hydrus_and_send_url(tag: List[str], access_key: Optional[str] = None, hydrus_url: Optional[str] = 'http://127.0.0.1:...

101

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207

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0

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

search_hydrus_and_send_url

491

508

491

495

723524da8006f308a9173c9106bcc40635436475

bigcode/the-stack

train

5bd994e2f9fb880791d3ec71

train

function

def parse_iqdb_result_page(page): """Parse iqdb result page.""" tables = page.select('.pages table') for table in tables: res = models.ImageMatch.parse_table(table) if not res: continue additional_res = models.get_additional_result_from_table(table, res) if additi...

def parse_iqdb_result_page(page):

"""Parse iqdb result page.""" tables = page.select('.pages table') for table in tables: res = models.ImageMatch.parse_table(table) if not res: continue additional_res = models.get_additional_result_from_table(table, res) if additional_res: yield additi...

= True browser.open(iqdb_url) html_form = browser.select_form('form') html_form.input({'file': image}) browser.submit_selected() html_text = browser.get_current_page() return parse_iqdb_result_page(html_text) def parse_iqdb_result_page(page):

64

79

9

55

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

parse_iqdb_result_page

67

77

67

28dffd6bf1a1b36ae500cd17e68e7b484c54b9ba

bigcode/the-stack

train

b4145d12e73aa8ae2f2daac6

train

class

class CustomFlaskGroup(flask_cli.FlaskGroup): """Custom Flask Group.""" def __init__(self, **kwargs): """Class init.""" super().__init__(**kwargs) self.params[0].help = 'Show the program version' self.params[0].callback = get_custom_version

class CustomFlaskGroup(flask_cli.FlaskGroup):

"""Custom Flask Group.""" def __init__(self, **kwargs): """Class init.""" super().__init__(**kwargs) self.params[0].help = 'Show the program version' self.params[0].callback = get_custom_version

_view(ModelView(ImageModel, category='DB')) # app_admin.add_view(ModelView(MatchTagRelationship, category='DB')) # routing app.add_url_rule('/thumb/<path:basename>', view_func=thumb) return app class CustomFlaskGroup(flask_cli.FlaskGroup):

64

67

12

51

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

CustomFlaskGroup

330

337

330

9ea099641ab56e38646c9a8fbdb0c5c7290b2470

bigcode/the-stack

train

2d53259a309155fbd9e9c78d

train

function

def create_app(script_info=None): """Create app.""" app = Flask(__name__) # logging if not os.path.exists(user_data_dir): os.makedirs(user_data_dir) log_dir = os.path.join(user_data_dir, 'log') if not os.path.exists(log_dir): os.makedirs(log_dir) peewee_logger = logging.getLo...

def create_app(script_info=None):

"""Create app.""" app = Flask(__name__) # logging if not os.path.exists(user_data_dir): os.makedirs(user_data_dir) log_dir = os.path.join(user_data_dir, 'log') if not os.path.exists(log_dir): os.makedirs(log_dir) peewee_logger = logging.getLogger('peewee') peewee_logger.s...

tags_verbose = [x.full_name for x in tags] match_result_tag_pairs.append((match_result, tags)) log.debug('{} tag(s) founds'.format(len(tags_verbose))) if tags and not disable_tag_print: print('\n'.join(tags_verbose)) if tags and write_tags: ...

195

653

7

188

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

create_app

267

327

267

c0314b8dac1b29570e72fcff8c4fefa4b0660607

bigcode/the-stack

train

280756093bfcb7a426209bae

train

function

def thumb(basename): """Get thumbnail.""" return send_from_directory(thumb_folder, basename)

def thumb(basename):

"""Get thumbnail.""" return send_from_directory(thumb_folder, basename)

_from_match_result(match_result, folder) except Exception as e: # pylint:disable=broad-except log.error('Error', e=str(e)) error_set.append(e) return {'error': error_set, 'match result tag pairs': match_result_tag_pairs} def thumb(basename):

64

22

6

58

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

thumb

262

264

262

32723503d2bf024ea3c6b8bdc7ea3b2f0f0a3cf3

bigcode/the-stack

train

bd1c3b27e55a8437a986f43c

train

function

@cli.command() @click.version_option() @click.option( '--place', type=click.Choice([x for x in iqdb_url_dict]), default=DEFAULT_PLACE, help='Specify iqdb place, default:{}'.format(DEFAULT_PLACE) ) @click.option( '--minimum-similarity', type=float, help='Minimum similarity.') @click.option('--resize', is...

"""Get similar image from iqdb.""" assert prog_input is not None, "Input is not a valid path" # logging log_level = None if verbose: log_level = logging.INFO if debug: log_level = logging.DEBUG if log_level: logging.basicConfig(handlers=[logging.FileHandler(os.path....

@cli.command() @click.version_option() @click.option( '--place', type=click.Choice([x for x in iqdb_url_dict]), default=DEFAULT_PLACE, help='Specify iqdb place, default:{}'.format(DEFAULT_PLACE) ) @click.option( '--minimum-similarity', type=float, help='Minimum similarity.') @click.option('--resize', is...

337

256

868

337

0

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

cli_run

359

451

359

392

fb5531a944f5a53bf8162cb9862fecea58eebcf2

bigcode/the-stack

train

94f402f3531e6dd6ecb4a0ed

train

function

def get_hydrus_set(search_tags: List[str], client: Client) -> Iterator[Dict[str, Any]]: """Get hydrus result. Args: search_tags: tags used to search hydrus client: client instance Returns: hydrus metadata and iqdb results """ # compatibility cl = client file_ids = ...

def get_hydrus_set(search_tags: List[str], client: Client) -> Iterator[Dict[str, Any]]:

"""Get hydrus result. Args: search_tags: tags used to search hydrus client: client instance Returns: hydrus metadata and iqdb results """ # compatibility cl = client file_ids = cl.search_files(search_tags) metadata_sets = cl.file_metadata(file_ids=file_ids, onl...

_set.extend([(image, x) for x in result['error']]) if error_set: log.error('Found error(s)') for x in error_set: log.error('path: ' + x[0] + '\nerror: ' + str(x[1])) def get_hydrus_set(search_tags: List[str], client: Client) -> Iterator[Dict[str, Any]]:

83

84

281

24

59

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

get_hydrus_set

454

488

454

897f9822143b5cab248049dc071e8fea122a0fbc

bigcode/the-stack

train

cb0dcf0dbf2b5113e0cd5c58

train

function

@cli.command() @click.argument('tag', nargs=-1) @click.option('--access_key', help='Hydrus access key') @click.option('--hydrus_url', help='URL for hydrus client e.g. http://127.0.0.1:45869/') @click.option('--tag_repo', help='tag repo name e.g. local tags') def search_hydrus_and_send_tag(tag: List[str], access_key: Op...

"""Search hydrus and send tag.""" # compatibility search_tags = tag if Client is None: print('Hydrus package is required') return cl = Client(access_key, hydrus_url) for res_dict in get_hydrus_set(search_tags, cl): f_hash = res_dict['metadata']['hash'] tag_sets =...

@cli.command() @click.argument('tag', nargs=-1) @click.option('--access_key', help='Hydrus access key') @click.option('--hydrus_url', help='URL for hydrus client e.g. http://127.0.0.1:45869/') @click.option('--tag_repo', help='tag repo name e.g. local tags') def search_hydrus_and_send_tag(tag: List[str], access_key: Op...

128

82

276

128

0

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

search_hydrus_and_send_tag

511

531

511

516

c888018c9f8d9956fb6a51c505e1711cfcde24d4

bigcode/the-stack

train

ff6c681f8b5f764752b14c28

train

function

def get_result_on_windows( image: str, place: str, resize: Optional[bool] = False, size: Optional[Tuple[int, int]] = None, browser: Optional[mechanicalsoup.StatefulBrowser] = None ) -> List[models.ImageMatch]: """Get result on Windows. Args: image: image path place: iqdb...

def get_result_on_windows( image: str, place: str, resize: Optional[bool] = False, size: Optional[Tuple[int, int]] = None, browser: Optional[mechanicalsoup.StatefulBrowser] = None ) -> List[models.ImageMatch]:

"""Get result on Windows. Args: image: image path place: iqdb place code resize: resize the image size: resized image size browser: browser instance Returns: matching items """ result = [] # temp_f temp_f = NamedTemporaryFile(mode='w+t', dele...

loc = urlparse(match_result.link).netloc sanitized_netloc = netloc.replace('.', '_') text_file_basename = sanitized_netloc + '.txt' text_file = os.path.join(folder, text_file_basename) if folder is not None else text_file_basename with open(text_file, 'a') as f: f.write(match_result.link) ...

145

486

60

85

a1270/iqdb_tagger

iqdb_tagger/__main__.py

Python

get_result_on_windows

99

153

99

103

1344ba51174f01a58b512982efeac24ab4d40e9e

bigcode/the-stack

train

10d760e34b3c6175256e11bb

train

function

def _select_stub_methods(gen: StubGenerator, method: ProtoServiceMethod): if method.type() is ProtoServiceMethod.Type.UNARY: return gen.unary_signature, gen.unary_stub if method.type() is ProtoServiceMethod.Type.SERVER_STREAMING: return gen.server_streaming_signature, gen.server_streaming_stub ...

def _select_stub_methods(gen: StubGenerator, method: ProtoServiceMethod):

if method.type() is ProtoServiceMethod.Type.UNARY: return gen.unary_signature, gen.unary_stub if method.type() is ProtoServiceMethod.Type.SERVER_STREAMING: return gen.server_streaming_signature, gen.server_streaming_stub if method.type() is ProtoServiceMethod.Type.CLIENT_STREAMING: ...

, output: OutputFile) -> None: """Returns the stub for this bidirectional streaming method.""" output.write_line(STUB_READER_WRITER_TODO) output.write_line('static_cast<void>(reader_writer);') def _select_stub_methods(gen: StubGenerator, method: ProtoServiceMethod):

64

148

16

48

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

_select_stub_methods

431

445

431

72f971e3070710777789cceb86cd287e41ac4ce8

bigcode/the-stack

train

fa69bb3a54c99d0398e27561

train

function

def _generate_service_and_client(gen: CodeGenerator, service: ProtoService) -> None: gen.line('// Wrapper class that namespaces server and client code for ' 'this RPC service.') gen.line(f'class {service.name()} final {{') gen.line(' public:') with gen.inde...

def _generate_service_and_client(gen: CodeGenerator, service: ProtoService) -> None:

gen.line('// Wrapper class that namespaces server and client code for ' 'this RPC service.') gen.line(f'class {service.name()} final {{') gen.line(' public:') with gen.indent(): gen.line(f'{service.name()}() = delete;') gen.line() _generate_service(gen, service) ...

_namespace) gen.line() gen.line('// Specialize MethodInfo for each RPC to provide metadata at ' 'compile time.') for service in services: _generate_info(gen, file_namespace, service) def _generate_service_and_client(gen: CodeGenerator, service: ProtoSer...

64

158

20

44

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

_generate_service_and_client

193

216

193

194

87b77a8a84b3d3a67939053da90367aa279ee75d

bigcode/the-stack

train

9d5895db83cf737db46e8466

train

function

def _service_definition_stub(service: ProtoService, output: OutputFile, stub_generator: StubGenerator) -> None: output.write_line(f'// Method definitions for {service.proto_path()}.') blank_line = False for method in service.methods(): if blank_line: output...

def _service_definition_stub(service: ProtoService, output: OutputFile, stub_generator: StubGenerator) -> None:

output.write_line(f'// Method definitions for {service.proto_path()}.') blank_line = False for method in service.methods(): if blank_line: output.write_line() else: blank_line = True signature, stub = _select_stub_methods(stub_generator, method) ou...

_line = True signature, _ = _select_stub_methods(stub_generator, method) output.write_line(signature(method, '') + ';') output.write_line('};\n') def _service_definition_stub(service: ProtoService, output: OutputFile, stub_generator: StubGenerator) -> None:

64

124

25

39

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

_service_definition_stub

537

554

537

538

7bbcf3ce19b814bde83e71c49976915289e946c8

bigcode/the-stack

train

6437641765b5a366b97681b1

train

function

def get_id(item: Union[ProtoService, ProtoServiceMethod]) -> str: name = item.proto_path() if isinstance(item, ProtoService) else item.name() return f'0x{pw_rpc.ids.calculate(name):08x}'

def get_id(item: Union[ProtoService, ProtoServiceMethod]) -> str:

name = item.proto_path() if isinstance(item, ProtoService) else item.name() return f'0x{pw_rpc.ids.calculate(name):08x}'

client stream callback and send a response as ' 'appropriate for your application') STUB_READER_WRITER_TODO = ( '// TODO: Set the client stream callback and send responses as ' 'appropriate for your application') def get_id(item: Union[ProtoService, ProtoServiceMethod]) -> str:

64

51

17

47

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

get_id

46

48

46

312a7f1915abe798278201b607d682e765af8daf

bigcode/the-stack

train

3f1762c7d1cd5af397c39d20

train

function

def generate_package(file_descriptor_proto, proto_package: ProtoNode, gen: CodeGenerator) -> None: """Generates service and client code for a package.""" assert proto_package.type() == ProtoNode.Type.PACKAGE gen.line(f'// {os.path.basename(gen.output.name())} automatically ' ...

def generate_package(file_descriptor_proto, proto_package: ProtoNode, gen: CodeGenerator) -> None:

"""Generates service and client code for a package.""" assert proto_package.type() == ProtoNode.Type.PACKAGE gen.line(f'// {os.path.basename(gen.output.name())} automatically ' f'generated by {PLUGIN_NAME} {PLUGIN_VERSION}') gen.line(f'// on {datetime.now().isoformat()}') gen.line('// ...

the Client member functions.""" @abc.abstractmethod def client_static_function(self, method: ProtoServiceMethod) -> None: """Generates method static functions that instantiate a Client.""" def method_info_specialization(self, method: ProtoServiceMethod) -> None: """Generates impl-specific...

138

139

466

22

116

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

generate_package

126

190

126

127

667cd56f3b6edcc7db5bb88f5235957bd6a58d6a

bigcode/the-stack

train

9542971f74d224e6dfc52c0e

train

function

def _generate_info(gen: CodeGenerator, namespace: str, service: ProtoService) -> None: """Generates MethodInfo for each method.""" service_id = get_id(service) info = f'struct {RPC_NAMESPACE.lstrip(":")}::internal::MethodInfo' for method in service.methods(): gen.line('templa...

def _generate_info(gen: CodeGenerator, namespace: str, service: ProtoService) -> None:

"""Generates MethodInfo for each method.""" service_id = get_id(service) info = f'struct {RPC_NAMESPACE.lstrip(":")}::internal::MethodInfo' for method in service.methods(): gen.line('template <>') gen.line(f'{info}<{namespace}::pw_rpc::{gen.name()}::' f'{service.name()}...

' 'These functions are ') gen.line('// equivalent to instantiating a Client and calling the ' 'corresponding RPC.') for method in service.methods(): _check_method_name(method) gen.client_static_function(method) gen.line() def _generate_info(gen: CodeGenerator, ...

76

255

22

54

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

_generate_info

255

285

255

256

63bdf8605c08a7905f2ddd9bb0510f1472e90724

bigcode/the-stack

train

da25ae14ada8a5f9f57b156d

train

function

def _service_declaration_stub(service: ProtoService, output: OutputFile, stub_generator: StubGenerator) -> None: output.write_line(f'// Implementation class for {service.proto_path()}.') output.write_line( f'class {service.name()} ' f': public generated::{service.na...

def _service_declaration_stub(service: ProtoService, output: OutputFile, stub_generator: StubGenerator) -> None:

output.write_line(f'// Implementation class for {service.proto_path()}.') output.write_line( f'class {service.name()} ' f': public generated::{service.name()}<{service.name()}> {{') output.write_line(' public:') with output.indent(): blank_line = False for method in se...

_definition_stub(node, output, stub_generator) output.write_line() finish_ns() output.write_line('#endif // _PW_RPC_COMPILE_GENERATED_SERVICE_STUBS') def _service_declaration_stub(service: ProtoService, output: OutputFile, stub_generator: StubGenerator) -> None:

64

153

26

38

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

_service_declaration_stub

512

534

512

513

d94d489994daecc1693d45785f5970aae726300f

bigcode/the-stack

train

6bbe24a3b50ac0f35c63c36f

train

function

def client_call_type(method: ProtoServiceMethod, prefix: str) -> str: """Returns Client ReaderWriter/Reader/Writer/Recevier for the call.""" if method.type() is ProtoServiceMethod.Type.UNARY: call_class = 'UnaryReceiver' elif method.type() is ProtoServiceMethod.Type.SERVER_STREAMING: call_cl...

def client_call_type(method: ProtoServiceMethod, prefix: str) -> str:

"""Returns Client ReaderWriter/Reader/Writer/Recevier for the call.""" if method.type() is ProtoServiceMethod.Type.UNARY: call_class = 'UnaryReceiver' elif method.type() is ProtoServiceMethod.Type.SERVER_STREAMING: call_class = 'ClientReader' elif method.type() is ProtoServiceMethod.Type...

Union[ProtoService, ProtoServiceMethod]) -> str: name = item.proto_path() if isinstance(item, ProtoService) else item.name() return f'0x{pw_rpc.ids.calculate(name):08x}' def client_call_type(method: ProtoServiceMethod, prefix: str) -> str:

63

64

154

17

46

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

client_call_type

51

64

51

503a20d392354d1083570b245a68d4277a8497b2

bigcode/the-stack

train

d0b55ebba710e1da694580ee

train

class

class CodeGenerator(abc.ABC): """Generates RPC code for services and clients.""" def __init__(self, output_filename: str) -> None: self.output = OutputFile(output_filename) def indent(self, amount: int = OutputFile.INDENT_WIDTH) -> Any: """Indents the output. Use in a with block.""" ...

class CodeGenerator(abc.ABC):

"""Generates RPC code for services and clients.""" def __init__(self, output_filename: str) -> None: self.output = OutputFile(output_filename) def indent(self, amount: int = OutputFile.INDENT_WIDTH) -> Any: """Indents the output. Use in a with block.""" return self.output.indent(amo...

/Writer/Recevier for the call.""" if method.type() is ProtoServiceMethod.Type.UNARY: call_class = 'UnaryReceiver' elif method.type() is ProtoServiceMethod.Type.SERVER_STREAMING: call_class = 'ClientReader' elif method.type() is ProtoServiceMethod.Type.CLIENT_STREAMING: call_class = '...

137

138

463

8

129

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

CodeGenerator

67

123

67

c219547511a0385b9e50cca50225f7e09bf6ea49

bigcode/the-stack

train

95e455d184301b1cc509b1e2

train

class

class StubGenerator(abc.ABC): """Generates stub method implementations that can be copied-and-pasted.""" @abc.abstractmethod def unary_signature(self, method: ProtoServiceMethod, prefix: str) -> str: """Returns the signature of this unary method.""" @abc.abstractmethod def unary_stub(self, ...

class StubGenerator(abc.ABC):

"""Generates stub method implementations that can be copied-and-pasted.""" @abc.abstractmethod def unary_signature(self, method: ProtoServiceMethod, prefix: str) -> str: """Returns the signature of this unary method.""" @abc.abstractmethod def unary_stub(self, method: ProtoServiceMethod, ...

# Generate the method lookup table _method_lookup_table(gen, service) gen.line('};') def _method_lookup_table(gen: CodeGenerator, service: ProtoService) -> None: """Generates array of method IDs for looking up methods at compile time.""" gen.line('static constexpr std::array<uint32_t, ' ...

134

448

8

126

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

StubGenerator

381

428

381

407281a13497ed41118c76df47c4f98e4c83b679

bigcode/the-stack

train

1c7804548df387f3d9cdb489

train

function

def _generate_deprecated_aliases(gen: CodeGenerator, services: Sequence[ProtoService]) -> None: """Generates aliases for the original, deprecated naming scheme.""" gen.line('// Aliases for the deprecated namespaces.') gen.line('namespace generated {') gen.line() for...

def _generate_deprecated_aliases(gen: CodeGenerator, services: Sequence[ProtoService]) -> None:

"""Generates aliases for the original, deprecated naming scheme.""" gen.line('// Aliases for the deprecated namespaces.') gen.line('namespace generated {') gen.line() for service in services: gen.line('template <typename Implementation>') gen.line(f'using {service.name()} = pw_rpc::...

') with gen.indent(): gen.line(f'return &ServiceImpl::{method.name()};') gen.line('}') gen.method_info_specialization(method) gen.line('};') gen.line() def _generate_deprecated_aliases(gen: CodeGenerator, services: ...

68

228

23

45

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

_generate_deprecated_aliases

288

315

288

289

1114b588fff5cd32804126171c016a6587946301

bigcode/the-stack

train

fa84e6c46d879363788fd47a

train

function

def package_stubs(proto_package: ProtoNode, output: OutputFile, stub_generator: StubGenerator) -> None: """Generates the RPC stubs for a package.""" if proto_package.cpp_namespace(): file_ns = proto_package.cpp_namespace() if file_ns.startswith('::'): file_ns = file...

def package_stubs(proto_package: ProtoNode, output: OutputFile, stub_generator: StubGenerator) -> None:

"""Generates the RPC stubs for a package.""" if proto_package.cpp_namespace(): file_ns = proto_package.cpp_namespace() if file_ns.startswith('::'): file_ns = file_ns[2:] start_ns = lambda: output.write_line(f'namespace {file_ns} {{\n') finish_ns = lambda: output.writ...

_/ / /_/ (__ )_/ /____/\__/\__,_/_.___/____(_) */ // This section provides stub implementations of the RPC services in this file. // The code below may be referenced or copied to serve as a starting point for // your RPC service implementations. ''' def package_stubs(proto_package: ProtoNode, output: OutputFile, ...

83

84

282

25

58

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

package_stubs

469

509

469

470

c08cb9d2a0ee5fc2c91edc224bbc9ed6d5da6d8b

bigcode/the-stack

train

aec5f1716b795d8429b1e3e0

train

function

def _generate_service(gen: CodeGenerator, service: ProtoService) -> None: """Generates a C++ class for an RPC service.""" base_class = f'{RPC_NAMESPACE}::Service' gen.line('// The RPC service base class.') gen.line( '// Inherit from this to implement an RPC service for a pw_rpc server.' ) ...

def _generate_service(gen: CodeGenerator, service: ProtoService) -> None:

"""Generates a C++ class for an RPC service.""" base_class = f'{RPC_NAMESPACE}::Service' gen.line('// The RPC service base class.') gen.line( '// Inherit from this to implement an RPC service for a pw_rpc server.' ) gen.line('template <typename Implementation>') gen.line(f'class Ser...

. if gen.name() == 'nanopb': gen.line(f'namespace {gen.name()} {{') gen.line() for service in services: gen.line(f'using {service.name()}Client = ' f'pw_rpc::{gen.name()}::{service.name()}::Client;') gen.line() gen.line(f'}} // namespace {g...

98

99

330

17

81

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

_generate_service

318

366

318

6c0132dc7c76e3a3129f7fb73a114199fa3a3cf6

bigcode/the-stack

train

5cec538f315e327197fe443d

train

function

def _generate_client(gen: CodeGenerator, service: ProtoService) -> None: gen.line('// The Client is used to invoke RPCs for this service.') gen.line(f'class Client final : public {RPC_NAMESPACE}::internal::' 'ServiceClient {') gen.line(' public:') with gen.indent(): gen.line(f'cons...

def _generate_client(gen: CodeGenerator, service: ProtoService) -> None:

gen.line('// The Client is used to invoke RPCs for this service.') gen.line(f'class Client final : public {RPC_NAMESPACE}::internal::' 'ServiceClient {') gen.line(' public:') with gen.indent(): gen.line(f'constexpr Client({RPC_NAMESPACE}::Client& client,' ' uint32_...

( f'"{method.service().proto_path()}.{method.name()}" is not a ' f'valid method name! The name "{method.name()}" is reserved ' 'for internal use by pw_rpc.') def _generate_client(gen: CodeGenerator, service: ProtoService) -> None:

63

64

207

17

46

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

_generate_client

227

252

227

fa83805e6464c6e4a9a5bc48433a927915a76914

bigcode/the-stack

train

2b033bc405ff237a7c270e97

train

function

def _check_method_name(method: ProtoServiceMethod) -> None: if method.name() in ('Service', 'Client'): raise ValueError( f'"{method.service().proto_path()}.{method.name()}" is not a ' f'valid method name! The name "{method.name()}" is reserved ' 'for internal use by pw_rp...

def _check_method_name(method: ProtoServiceMethod) -> None:

if method.name() in ('Service', 'Client'): raise ValueError( f'"{method.service().proto_path()}.{method.name()}" is not a ' f'valid method name! The name "{method.name()}" is reserved ' 'for internal use by pw_rpc.')

) with gen.indent(): gen.line(f'// Hash of "{service.proto_path()}".') gen.line(f'static constexpr uint32_t kServiceId = {get_id(service)};') gen.line('};') def _check_method_name(method: ProtoServiceMethod) -> None:

64

76

14

50

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

_check_method_name

219

224

219

6560b1752856c5e91e96410f5ab08bdbe5d7b862

bigcode/the-stack

train

cb5a346bb543cc04e4d7db8e

train

function

def _method_lookup_table(gen: CodeGenerator, service: ProtoService) -> None: """Generates array of method IDs for looking up methods at compile time.""" gen.line('static constexpr std::array<uint32_t, ' f'{len(service.methods())}> kPwRpcMethodIds = {{') with gen.indent(4): for method i...

def _method_lookup_table(gen: CodeGenerator, service: ProtoService) -> None:

"""Generates array of method IDs for looking up methods at compile time.""" gen.line('static constexpr std::array<uint32_t, ' f'{len(service.methods())}> kPwRpcMethodIds = {{') with gen.indent(4): for method in service.methods(): gen.line(f'{get_id(method)}, // Hash of "{m...

4): for method in service.methods(): gen.method_descriptor(method) gen.line('};\n') # Generate the method lookup table _method_lookup_table(gen, service) gen.line('};') def _method_lookup_table(gen: CodeGenerator, service: ProtoService) -> None:

64

104

18

46

curtin-space/pigweed

pw_rpc/py/pw_rpc/codegen.py

Python

_method_lookup_table

369

378

369

767d2bf39ce9ff4794a52a1e90eaf98318780050

bigcode/the-stack

train

7944761eb0595c7820acc122

train

class

class NetworkSecurityGroup(Resource): """NetworkSecurityGroup resource. Variables are only populated by the server, and will be ignored when sending a request. :param id: Resource ID. :type id: str :ivar name: Resource name. :vartype name: str :ivar type: Resource type. :vartype ty...

class NetworkSecurityGroup(Resource):

"""NetworkSecurityGroup resource. Variables are only populated by the server, and will be ignored when sending a request. :param id: Resource ID. :type id: str :ivar name: Resource name. :vartype name: str :ivar type: Resource type. :vartype type: str :param location: Resource ...

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes ...

90

237

792

6

83

JonathanGailliez/azure-sdk-for-python

azure-mgmt-network/azure/mgmt/network/v2018_07_01/models/network_security_group_py3.py

Python

NetworkSecurityGroup

15

86

15

2ffa2494429cb274a8ffa3c2442fe64e8872f170

bigcode/the-stack

train

72eb40f840333f42bbf8b60a

train

function

@pytest.fixture() def runner(app): return app.test_cli_runner()

@pytest.fixture() def runner(app):

return app.test_cli_runner()

oped_session(options=options) db.session = session def teardown(): session.close() transaction.rollback() connection.close() request.addfinalizer(teardown) return session @pytest.fixture(scope='function') def test_client(app): return app.test_client() @pytest.fixture() d...

64

14

7

57

candicecz/conp-portal

tests/conftest.py

Python

runner

79

81

79

80

64979dfdce2347cb9186b6bf3d4b19ccebd00c05

bigcode/the-stack

train

e493a17887d7983bbdf9ca21

train

function

@pytest.fixture(scope='function') def session(db, request): """ This creates a mock session """ connection = db.engine.connect() transaction = connection.begin() options = dict(bind=connection) session = db.create_scoped_session(options=options) db.session = session def teardown()...

@pytest.fixture(scope='function') def session(db, request):

""" This creates a mock session """ connection = db.engine.connect() transaction = connection.begin() options = dict(bind=connection) session = db.create_scoped_session(options=options) db.session = session def teardown(): session.close() transaction.rollback() ...

_file): os.unlink(test_db_file) def teardown(): _db.drop_all() os.unlink(test_db_file) _db.app = app _db.create_all() request.addfinalizer(teardown) return _db @pytest.fixture(scope='function') def session(db, request):

64

90

12

51

candicecz/conp-portal

tests/conftest.py

Python

session

52

71

52

53

56be29d242d10033a0f9c29be3bd39a1359b526d

bigcode/the-stack

train

bc52b9526610f0caa84b8ef5

train

function

@pytest.fixture(scope='session') def db(app, request): """ This is creates the test db """ test_db_file = app.config['SQLALCHEMY_DATABASE_URI'].split(":///")[1] if os.path.exists(test_db_file): os.unlink(test_db_file) def teardown(): _db.drop_all() os.unlink(test_db_fil...

@pytest.fixture(scope='session') def db(app, request):

""" This is creates the test db """ test_db_file = app.config['SQLALCHEMY_DATABASE_URI'].split(":///")[1] if os.path.exists(test_db_file): os.unlink(test_db_file) def teardown(): _db.drop_all() os.unlink(test_db_file) _db.app = app _db.create_all() request...

TestingConfig in Config.py """ app = create_app(config_settings=TestingConfig) ctx = app.test_request_context() ctx.push() def teardown(): ctx.pop() request.addfinalizer(teardown) return app @pytest.fixture(scope='session') def db(app, request):

64

104

12

51

candicecz/conp-portal

tests/conftest.py

Python

db

31

49

31

32

7a8e08d840cd4d8faf477b395d8583b3d3f868b0

bigcode/the-stack

train

88d39e45bed7639ad706250b

train

function

@pytest.fixture(scope='function') def test_client(app): return app.test_client()

@pytest.fixture(scope='function') def test_client(app):

return app.test_client()

options = dict(bind=connection) session = db.create_scoped_session(options=options) db.session = session def teardown(): session.close() transaction.rollback() connection.close() request.addfinalizer(teardown) return session @pytest.fixture(scope='function') def test_clie...

64

17

11

52

candicecz/conp-portal

tests/conftest.py

Python

test_client

74

76

74

75

3f87eec4e09a1c69dd5d9c46b3ad349ea823d320

bigcode/the-stack

train

c09c9e28a7f73b67c36d03ff

train

function

@pytest.fixture(scope='session') def app(request): """ This is creates the mock app for testing, it uses the TestingConfig in Config.py """ app = create_app(config_settings=TestingConfig) ctx = app.test_request_context() ctx.push() def teardown(): ctx.pop() request.addfinal...

@pytest.fixture(scope='session') def app(request):

""" This is creates the mock app for testing, it uses the TestingConfig in Config.py """ app = create_app(config_settings=TestingConfig) ctx = app.test_request_context() ctx.push() def teardown(): ctx.pop() request.addfinalizer(teardown) return app

8 -*- """ This is the initial module that contains the pytest configuration fixtures """ import pytest import os from app import create_app from app import db as _db from sqlalchemy import event from sqlalchemy.orm import sessionmaker from config import TestingConfig @pytest.fixture(scope='session') def app(request):

64

78

10

53

candicecz/conp-portal

tests/conftest.py

Python

app

14

28

14

15

11cab38869529afdb4492d02a6f7e1361acd8225

bigcode/the-stack

train

8e1e5f92a3ab20fd7c0a444d

train

function

def register_args(*args): ''' Set `mit_argc` and `mit_argv`. - args - an iterable of `str` and/or `bytes`. ''' bargs = [] for arg in args: if isinstance(arg, str): arg = bytes(arg, 'utf-8') assert isinstance(arg, bytes) bargs.append(arg) global argc, arg...

def register_args(*args):

''' Set `mit_argc` and `mit_argv`. - args - an iterable of `str` and/or `bytes`. ''' bargs = [] for arg in args: if isinstance(arg, str): arg = bytes(arg, 'utf-8') assert isinstance(arg, bytes) bargs.append(arg) global argc, argv argc.value = len(bar...

_extend(x): if x & sign_bit: x |= -1 & ~uword_max return x argc = c_int.in_dll(libmit, "mit_argc") argv = POINTER(c_char_p).in_dll(libmit, "mit_argv") def register_args(*args):

64

111

6

58

rrthomas/m

python/mit/binding.py

Python

register_args

140

154

140

312d14ec54c2af0d6635170b6de771ba9f5d73b6

bigcode/the-stack

train

2eafe87b8fc6a33a11a9c8fc

train

class

class Error(Exception): ''' An error from the Python bindings for Mit. ''' pass

class Error(Exception):

''' An error from the Python bindings for Mit. ''' pass

: # For Windows # TODO: Do this portably # TODO: Substitute version when library is versioned library_file = find_library("libmit-0") assert(library_file) libmit = CDLL(library_file) assert(libmit) # Errors class Error(Exception):

64

21

4

59

rrthomas/m

python/mit/binding.py

Python

Error

32

36

32

045ecb7a354d1fb5d6dfd6645031bb4cb7de73ca

bigcode/the-stack

train

475a1a6f29cc842e78b30fa4

train

function

def errcheck(error_enum): ''' Returns a callback suitable for use as `ctypes._FuncPtr.errcheck`. - code_to_message - a mapping from int to message. If the message is `None` the code is considered to be a success, and `None` is returned. If the code is not found in `code_to_message`: -...

def errcheck(error_enum):

''' Returns a callback suitable for use as `ctypes._FuncPtr.errcheck`. - code_to_message - a mapping from int to message. If the message is `None` the code is considered to be a success, and `None` is returned. If the code is not found in `code_to_message`: - if an "ok" code exists, a...

Mit. ''' pass class VMError(Error): ''' An error from Mit. Public fields: - error_code - int - message - str ''' def __init__(self, error_code, message): super().__init__(error_code, message) def errcheck(error_enum):

67

225

6

61

rrthomas/m

python/mit/binding.py

Python

errcheck

51

76

51

61b89e2698457ce9626f2653952c70a57c845c8c

bigcode/the-stack

train

3c1556eb51afcb27f9d6e9fe

train

function

def run(pc, ir, stack, stack_words, stack_depth_ptr): return mit_error(_run(pc, ir, stack, stack_words, stack_depth_ptr))

def run(pc, ir, stack, stack_words, stack_depth_ptr):

return mit_error(_run(pc, ir, stack, stack_words, stack_depth_ptr))

_mit_fn.in_dll(libmit, "mit_run_fast") # run_profile = c_mit_fn.in_dll(libmit, "mit_run_profile") # Cannot add errcheck to a CFUNCTYPE, so wrap it manually. def run(pc, ir, stack, stack_words, stack_depth_ptr):

64

34

15

49

rrthomas/m

python/mit/binding.py

Python

run

117

118

117

e6f75c4f84822d061c4388fee241aa2dbf5c5101

bigcode/the-stack

train

c84e455b7e2cf9ec10dce389

train

class

class VMError(Error): ''' An error from Mit. Public fields: - error_code - int - message - str ''' def __init__(self, error_code, message): super().__init__(error_code, message)

class VMError(Error):

''' An error from Mit. Public fields: - error_code - int - message - str ''' def __init__(self, error_code, message): super().__init__(error_code, message)

library is versioned library_file = find_library("libmit-0") assert(library_file) libmit = CDLL(library_file) assert(libmit) # Errors class Error(Exception): ''' An error from the Python bindings for Mit. ''' pass class VMError(Error):

64

54

5

58

rrthomas/m

python/mit/binding.py

Python

VMError

39

48

39

959502373a34353537af602f26aec59dd2fc0a2a

bigcode/the-stack

train

96a572f47e588d7b10b60333

train

function

def is_aligned(addr): return (addr & (word_bytes - 1)) == 0

def is_aligned(addr):

return (addr & (word_bytes - 1)) == 0

): return mit_error(_run(pc, ir, stack, stack_words, stack_depth_ptr)) # libmit.mit_profile_reset.restype = None # libmit.mit_profile_reset.argtypes = None # libmit.mit_profile_dump.argtypes = [c_int] def is_aligned(addr):

64

22

6

58

rrthomas/m

python/mit/binding.py

Python

is_aligned

126

127

126

8a24a46e0cbb479f02e5a3002cb68242c01e70c3

bigcode/the-stack

train

12cab8f7e223dc2a4d2687b6

train

function

def sign_extend(x): if x & sign_bit: x |= -1 & ~uword_max return x

def sign_extend(x):

if x & sign_bit: x |= -1 & ~uword_max return x

libmit.mit_profile_reset.restype = None # libmit.mit_profile_reset.argtypes = None # libmit.mit_profile_dump.argtypes = [c_int] def is_aligned(addr): return (addr & (word_bytes - 1)) == 0 def sign_extend(x):

64

27

5

58

rrthomas/m

python/mit/binding.py

Python

sign_extend

130

133

130

567d2c382258ce376dac94fcf6ebb4ff94088a1e

bigcode/the-stack

train

6138c505e0690477f3c9cfb2

train

function

@contextmanager def databases_engine(): driver = os.environ["MS_SQL_ODBC_DRIVER"] username = os.environ["MS_SQL_UHL_DWH_USER"] password = os.environ["MS_SQL_UHL_DWH_PASSWORD"] host = os.environ["MS_SQL_UHL_DWH_HOST"] database = os.environ["MS_SQL_UHL_DWH_DATABASE"] database_echo = os.environ["DATABASE_ECHO...

@contextmanager def databases_engine():

driver = os.environ["MS_SQL_ODBC_DRIVER"] username = os.environ["MS_SQL_UHL_DWH_USER"] password = os.environ["MS_SQL_UHL_DWH_PASSWORD"] host = os.environ["MS_SQL_UHL_DWH_HOST"] database = os.environ["MS_SQL_UHL_DWH_DATABASE"] database_echo = os.environ["DATABASE_ECHO"] == 'True' connectionstring = f'mssq...

orenames, PATINDEX('%[ -/]%', forenames + ' ') - 1) AS name FROM DWREPO.dbo.PATIENT ) x WHERE name IS NOT NULL AND LEN(name) > 2 ORDER BY LOWER(name) ; """ @contextmanager def databases_engine():

64

143

8

56

LCBRU/ppi_finder

get_names.py

Python

databases_engine

30

43

30

32

c354895e6e6f33f353cc496032f0aa31fa19296e

bigcode/the-stack

train

9fe235404b3339011f0df1d5

train

function

def main(): with databases_engine() as conn: names = {r for r, in conn.execute(NAMES_SQL)} with open("_names.txt", "w") as outfile: outfile.write("\n".join(names))

def main():

with databases_engine() as conn: names = {r for r, in conn.execute(NAMES_SQL)} with open("_names.txt", "w") as outfile: outfile.write("\n".join(names))

["DATABASE_ECHO"] == 'True' connectionstring = f'mssql+pyodbc://{username}:{password}@{host}/{database}?driver={driver.replace(" ", "+")}' engine = create_engine(connectionstring, echo=database_echo) yield engine engine.dispose() def main():

64

48

3

61

LCBRU/ppi_finder

get_names.py

Python

main

46

51

46

ad52a680425417741d1d614d55bc9ffbfee5586a

bigcode/the-stack

train

7f121a9693fc0c962832fa06

train

class

@skipIf(NO_MOCK, NO_MOCK_REASON) class SensehatBeaconTestCase(TestCase, LoaderModuleMockMixin): ''' Test case for salt.beacons.[s] ''' def setup_loader_modules(self): self.HUMIDITY_MOCK = MagicMock(return_value=80) self.TEMPERATURE_MOCK = MagicMock(return_value=30) self.PRESSUR...

@skipIf(NO_MOCK, NO_MOCK_REASON) class SensehatBeaconTestCase(TestCase, LoaderModuleMockMixin):

''' Test case for salt.beacons.[s] ''' def setup_loader_modules(self): self.HUMIDITY_MOCK = MagicMock(return_value=80) self.TEMPERATURE_MOCK = MagicMock(return_value=30) self.PRESSURE_MOCK = MagicMock(return_value=1500) self.addCleanup(delattr, self, 'HUMIDITY_MOCK') ...

# coding: utf-8 # Python libs from __future__ import absolute_import # Salt testing libs from tests.support.unit import skipIf, TestCase from tests.support.mock import NO_MOCK, NO_MOCK_REASON, MagicMock from tests.support.mixins import LoaderModuleMockMixin # Salt libs import salt.beacons.sensehat as sensehat @skipI...

104

204

680

26

77

byteskeptical/salt

tests/unit/beacons/test_sensehat.py

Python

SensehatBeaconTestCase

15

109

15

16

ada01321c822e4cd694800077c1023e96fc79fba

bigcode/the-stack

train

a6448e75631d75be60c2a8cf

train

class

class Migration(migrations.Migration): dependencies = [ ('base', '0026_auto_20201003_2209'), ] operations = [ migrations.AlterField( model_name='schedule', name='duration', field=models.IntegerField(choices=[(900, '15min'), (1800, '30min'), (2700, '45min...

class Migration(migrations.Migration):

dependencies = [ ('base', '0026_auto_20201003_2209'), ] operations = [ migrations.AlterField( model_name='schedule', name='duration', field=models.IntegerField(choices=[(900, '15min'), (1800, '30min'), (2700, '45min'), (3600, '60min'), (4500, '75min'), (5...

# Generated by Django 3.0.6 on 2020-10-04 01:13 from django.db import migrations, models class Migration(migrations.Migration):

38

104

348

7

30

arantesdv/LaeliaAppProject

Laelia/apps/base/migrations/0027_auto_20201003_2213.py

Python

Migration

6

23

6

7

357ed6d6ec9787fc081862afbcc4dcd7e17b3342

bigcode/the-stack

train

3477fa67d2d0f17de737bb58

train

class

class RMSE(MSE): def __init__(self): super().__init__() self.name = "Root Mean Squared Error" # calculates MSE and takes square root def get_error(self, cover_image, stego_image): mean_squared_error = self.calculate_image_error(cover_image, stego_image) root_mean_squared...

class RMSE(MSE):

def __init__(self): super().__init__() self.name = "Root Mean Squared Error" # calculates MSE and takes square root def get_error(self, cover_image, stego_image): mean_squared_error = self.calculate_image_error(cover_image, stego_image) root_mean_squared_error = math.sqrt...

""" Root Mean Squared Error (MSE) Calculates the RMSE between a cover and stego image """ import cv2 import math from MSE import MSE class RMSE(MSE):

44

64

88

6

37

FaiZaman/Steganograph-app-y

evaluation/imperceptibility/RMSE.py

Python

RMSE

10

23

10

11

933abd226afbbc4a0252c67396607decbc64548f

bigcode/the-stack

train

7e859a1390ebf98c06339fbe

train

class

class TestBuildOrderDeviation(unittest.TestCase): #region time_deviation def test_time_deviation_calculated_correctly_when_late_on_time(self): golden_bo = [] compare_bo = [] golden_bo.append(BuildOrderElement(1, 'Probe', 12, 0, 0)) golden_bo.append(BuildOrderElement(2, 'A...

class TestBuildOrderDeviation(unittest.TestCase): #region time_deviation

def test_time_deviation_calculated_correctly_when_late_on_time(self): golden_bo = [] compare_bo = [] golden_bo.append(BuildOrderElement(1, 'Probe', 12, 0, 0)) golden_bo.append(BuildOrderElement(2, 'Assimilator', 15, 50, 200)) compare_bo.append(BuildOrderElement(1, 'Pro...

import os import sys if __name__ == '__main__': sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, os.pardir))) if sys.version_info[:2] < (2, 7): import unittest2 as unittest else: import unittest import metrics from metrics.bod import BuildOrderDeviatio...

113

256

9,884

15

97

matthewj8489/Starcraft2Metrics

tests/unit/test_bod.py

Python

TestBuildOrderDeviation

17

879

17

20

524c36207fcdda820eef1014d4d879d5b2bc8f49

bigcode/the-stack

train

927023ac7e01a1195e6c6495

train

function

def deprecated(reason): """ This is a decorator which can be used to mark functions as deprecated. It will result in a warning being emitted when the function is used. """ if isinstance(reason, string_types): # The @deprecated is used with a 'reason'. # # .. code-block:...

def deprecated(reason):

""" This is a decorator which can be used to mark functions as deprecated. It will result in a warning being emitted when the function is used. """ if isinstance(reason, string_types): # The @deprecated is used with a 'reason'. # # .. code-block:: python # ...

import functools import inspect import warnings string_types = (type(b''), type(u'')) def deprecated(reason):

25

136

455

4

21

rudimeier/BrainStat

surfstat/python/deprecated.py

Python

deprecated

8

78

8

7c0cf21c7af6fe8b8be15c0446929356427b8901

bigcode/the-stack

train

f1e92d2d8938c94c5e0e4d33

train

class

class TreeNode(object): """A node in the MCTS tree. Each node keeps track of its own value Q, prior probability P, and its visit-count-adjusted prior score u. """ def __init__(self, parent, prior_p): self._parent = parent self._children = {} # a map from action to TreeNode self...

class TreeNode(object):

"""A node in the MCTS tree. Each node keeps track of its own value Q, prior probability P, and its visit-count-adjusted prior score u. """ def __init__(self, parent, prior_p): self._parent = parent self._children = {} # a map from action to TreeNode self._n_visits = 0 s...

"""Monte Carlo Tree Search, as described in Silver et al 2015. This is a "pure" implementation of the AlphaGo MCTS algorithm in that it is not specific to the game of Go; everything in this file is implemented generically with respect to some state, actions, policy function, and value function. """ import numpy as np ...

83

210

701

5

77

sjkim04/AlphaGOZero-python-tensorflow

support/RocAlphaGo-develop/AlphaGo/mcts.py

Python

TreeNode

11

91

11

01cb1e7f7f9f8de6fcf013b0ec45827e5606df61

bigcode/the-stack

train

c1b69bd8bfd5536e97cd2687

train

class

class ParallelMCTS(MCTS): pass

class ParallelMCTS(MCTS):

pass

be garbage-collected. """ if last_move in self._root._children: self._root = self._root._children[last_move] self._root._parent = None else: self._root = TreeNode(None, 1.0) class ParallelMCTS(MCTS):

64

10

7

57

sjkim04/AlphaGOZero-python-tensorflow

support/RocAlphaGo-develop/AlphaGo/mcts.py

Python

ParallelMCTS

219

220

219

a47ae282f6080380f061b3777a4b8ffecc5fccc2

bigcode/the-stack

train

b0e14fb3c9a950192ff73602

train

class

class MCTS(object): """A simple (and slow) single-threaded implementation of Monte Carlo Tree Search. Search works by exploring moves randomly according to the given policy up to a certain depth, which is relatively small given the search space. "Leaves" at this depth are assigned a value comprising a ...

class MCTS(object):

"""A simple (and slow) single-threaded implementation of Monte Carlo Tree Search. Search works by exploring moves randomly according to the given policy up to a certain depth, which is relatively small given the search space. "Leaves" at this depth are assigned a value comprising a weighted combination...

u is not normalized to be a distribution. if not self.is_root(): self._u = c_puct * self._P * np.sqrt(self._parent._n_visits) / (1 + self._n_visits) def update_recursive(self, leaf_value, c_puct): """Like a call to update(), but applied recursively for all ancestors. Note: it ...

256

1,354

5

250

sjkim04/AlphaGOZero-python-tensorflow

support/RocAlphaGo-develop/AlphaGo/mcts.py

Python

MCTS

94

216

94

2a2e9831ae9f84de8a0fbeb422c063f3ab235d35

bigcode/the-stack

train

565e89caa608175bf1cda569

train

function

def test_bench(): main(fast=True)

def test_bench():

main(fast=True)

from ..bench import main def test_bench():

11

64

11

5

lpsinger/astropy-healpix

astropy_healpix/tests/test_bench.py

Python

test_bench

4

5

4

5cd3a820ced62c05f36cf3d1259664d60ff0427d

bigcode/the-stack

train

3823e035c387dd6374ba40c9

train

class

class AuthFail(RbacError): def __init__(self,msg="Authentication fail",id=USER_PW_INVLD, **kw): super().__init__(msg=msg,id=id,**kw)

class AuthFail(RbacError):

def __init__(self,msg="Authentication fail",id=USER_PW_INVLD, **kw): super().__init__(msg=msg,id=id,**kw)

: 2022 - Symas Corporation ''' from ..util import RbacError from ..util.global_ids import USER_PW_INVLD,USER_PW_CHK_FAILED class NotFound(RbacError): pass class NotUnique(RbacError): pass class AuthFail(RbacError):

64

43

7

56

shawnmckinney/py-fortress

rbac/file/fileex.py

Python

AuthFail

14

16

14

58f90687782ab47a8fefd3a0bbcd19b70284e581

bigcode/the-stack

train

0eed375b0072983c2aaa1f55

train

class

class AuthError(RbacError): def __init__(self,msg="Authentication error",id=USER_PW_CHK_FAILED, **kw): super().__init__(msg=msg,id=id,**kw)

class AuthError(RbacError):

def __init__(self,msg="Authentication error",id=USER_PW_CHK_FAILED, **kw): super().__init__(msg=msg,id=id,**kw)

): pass class NotUnique(RbacError): pass class AuthFail(RbacError): def __init__(self,msg="Authentication fail",id=USER_PW_INVLD, **kw): super().__init__(msg=msg,id=id,**kw) class AuthError(RbacError):

64

44

7

57

shawnmckinney/py-fortress

rbac/file/fileex.py

Python

AuthError

18

20

18

648b2805f5da0ee49b2d9b530009eefd090a5ded

bigcode/the-stack

train

1edb11656f749cb955bd5302

train

class

class NotUnique(RbacError): pass

class NotUnique(RbacError):

pass

''' @copyright: 2022 - Symas Corporation ''' from ..util import RbacError from ..util.global_ids import USER_PW_INVLD,USER_PW_CHK_FAILED class NotFound(RbacError): pass class NotUnique(RbacError):

57

64

10

7

49

shawnmckinney/py-fortress

rbac/file/fileex.py

Python

NotUnique

11

12

11

487aebb927649b3605b30d883bf6250d5a1618b0

bigcode/the-stack

train

88aad34e782f2355da385041

train

class

class NotFound(RbacError): pass

class NotFound(RbacError):

pass

''' @copyright: 2022 - Symas Corporation ''' from ..util import RbacError from ..util.global_ids import USER_PW_INVLD,USER_PW_CHK_FAILED class NotFound(RbacError):

47

64

10

7

39

shawnmckinney/py-fortress

rbac/file/fileex.py

Python

NotFound

8

9

8

694385575ccf0e2589e84d6dd04dfce51af52148

bigcode/the-stack

train

59e94b575bf102e6d5e88e96

train

function

def conv3x3(in_planes, out_planes, stride=1): """3x3 convolution with padding""" return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False)

def conv3x3(in_planes, out_planes, stride=1):

"""3x3 convolution with padding""" return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False)

import torch import torch.nn as nn import time def conv3x3(in_planes, out_planes, stride=1):

27

64

53

15

11

luk-ai-420/ExcelFIT_project

cor_src/cor_LSTM_network.py

Python

conv3x3

6

9

6

c528404493d0c64a6a3efc3ebfd94c3192386a34

bigcode/the-stack

train

00c3ee360371113be5775e81

train

function

def cor_LSTM_resnet34(num_classes,frame_num,grayscale): """Constructs a ResNet-34 model.""" model = LSTM_ResNet(block=BasicBlock, layers=[3, 4, 6, 3], num_classes=num_classes, frame_num = frame_num, grayscale=grayscale) retur...

def cor_LSTM_resnet34(num_classes,frame_num,grayscale):

"""Constructs a ResNet-34 model.""" model = LSTM_ResNet(block=BasicBlock, layers=[3, 4, 6, 3], num_classes=num_classes, frame_num = frame_num, grayscale=grayscale) return model

STM_t + time.time() - start_t)/2 logits = self.fc(x) logits = logits + self.linear_1_bias probas = torch.sigmoid(logits) return logits, probas def cor_LSTM_resnet34(num_classes,frame_num,grayscale):

64

77

16

47

luk-ai-420/ExcelFIT_project

cor_src/cor_LSTM_network.py

Python

cor_LSTM_resnet34

129

136

129

23cbd3af1dc68d236aa8ee299012fc329fe29c5e

bigcode/the-stack

train

2008fb946183fe2b3d95b4a7

train

class

class BasicBlock(nn.Module): expansion = 1 def __init__(self, inplanes, planes, stride=1, downsample=None): super(BasicBlock, self).__init__() self.conv1 = conv3x3(inplanes, planes, stride) self.bn1 = nn.BatchNorm2d(planes) self.relu = nn.ReLU(inplace=True) self....

class BasicBlock(nn.Module):

expansion = 1 def __init__(self, inplanes, planes, stride=1, downsample=None): super(BasicBlock, self).__init__() self.conv1 = conv3x3(inplanes, planes, stride) self.bn1 = nn.BatchNorm2d(planes) self.relu = nn.ReLU(inplace=True) self.conv2 = conv3x3(planes, planes...

nn import time def conv3x3(in_planes, out_planes, stride=1): """3x3 convolution with padding""" return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False) class BasicBlock(nn.Module):

64

208

6

58

luk-ai-420/ExcelFIT_project

cor_src/cor_LSTM_network.py

Python

BasicBlock

11

40

11

08fb2c036fc2f6d7643062349b379b8d968291d7

bigcode/the-stack

train

daa59e9655278bbfad87a0cd

train

class

class LSTM_ResNet(nn.Module): def __init__(self, block, layers, num_classes,frame_num, grayscale): self.num_classes = num_classes self.inplanes = 64 self.LSTMlayer_num = 2 self.LSTMframe_num = frame_num self.LSTMinputsize = 2048 self.LSTMhiddensize = 2048 ...

class LSTM_ResNet(nn.Module):

def __init__(self, block, layers, num_classes,frame_num, grayscale): self.num_classes = num_classes self.inplanes = 64 self.LSTMlayer_num = 2 self.LSTMframe_num = frame_num self.LSTMinputsize = 2048 self.LSTMhiddensize = 2048 self.average_LSTM_t = 0 ...

.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False) class BasicBlock(nn.Module): expansion = 1 def __init__(self, inplanes, planes, stride=1, downsample=None): super(BasicBlock, self).__init__() self.conv1 = conv3x3(inplanes, planes,...

243

812

9

233

luk-ai-420/ExcelFIT_project

cor_src/cor_LSTM_network.py

Python

LSTM_ResNet

42

127

42

43

ebcbf9100ce1bc1f46f6942a1a1e84d06a22b79f

bigcode/the-stack

train

21aa986d7b3bb95fb3eb4642

train

function

def test_diet_check_option_prints_configuration(): expected = """\ commands: optipng: {0}/optipng pipelines: png: - optipng """.format(TOOLS_DIR) helpers.TOOLS = ('optipng',) runner = CliRunner() result = runner.invoke(diet.diet, ['--check']) assert result.output == expected assert resu...

def test_diet_check_option_prints_configuration():

expected = """\ commands: optipng: {0}/optipng pipelines: png: - optipng """.format(TOOLS_DIR) helpers.TOOLS = ('optipng',) runner = CliRunner() result = runner.invoke(diet.diet, ['--check']) assert result.output == expected assert result.exit_code == 0

OLS_DIR', '/usr/local/bin') TEST_DIR = abspath(dirname(__file__)) TEST_FILES_DIR = join(TEST_DIR, 'test_files') TEST_FILE = join(TEST_FILES_DIR, 'nature.png') TEST_CONFIG = join(TEST_FILES_DIR, 'config2.yaml') def test_diet_check_option_prints_configuration():

64

96

10

54

biopredictive/pyimagediet

tests/test_scripts.py

Python

test_diet_check_option_prints_configuration

18

33

18

c0a45834d7823d435826bd7ce1dd03960761742e

bigcode/the-stack

train

9dec0ad226129ac24eaf5e88

train

function

def test_diet_complains_if_no_file_is_provided(): err = 'Usage: diet [OPTIONS] FILE\n\nError: Missing argument "file".\n' runner = CliRunner() result = runner.invoke(diet.diet, ['--config', TEST_CONFIG]) assert result.output == err assert result.exit_code == 2

def test_diet_complains_if_no_file_is_provided():

err = 'Usage: diet [OPTIONS] FILE\n\nError: Missing argument "file".\n' runner = CliRunner() result = runner.invoke(diet.diet, ['--config', TEST_CONFIG]) assert result.output == err assert result.exit_code == 2

] FILE\n\nError: Missing option "--config".\n' runner = CliRunner() result = runner.invoke(diet.diet, [TEST_FILE]) assert result.output == err assert result.exit_code == 2 def test_diet_complains_if_no_file_is_provided():

64

76

14

49

biopredictive/pyimagediet

tests/test_scripts.py

Python

test_diet_complains_if_no_file_is_provided

44

50

44

0c17c12381156910421762a913399ff54ec68bee

bigcode/the-stack

train

4f9c6400379c12cd721ba0ff

train

function

def test_diet_squeezes_file(): backup = process.backup_file(TEST_FILE, 'back') assert filecmp.cmp(TEST_FILE, backup) try: runner = CliRunner() result = runner.invoke(diet.diet, ['--config', TEST_CONFIG, backup]) assert not filecmp.cmp(TEST_FILE, backup) assert result.exit_c...

def test_diet_squeezes_file():

backup = process.backup_file(TEST_FILE, 'back') assert filecmp.cmp(TEST_FILE, backup) try: runner = CliRunner() result = runner.invoke(diet.diet, ['--config', TEST_CONFIG, backup]) assert not filecmp.cmp(TEST_FILE, backup) assert result.exit_code == 0 finally: o...

OPTIONS] FILE\n\nError: Missing argument "file".\n' runner = CliRunner() result = runner.invoke(diet.diet, ['--config', TEST_CONFIG]) assert result.output == err assert result.exit_code == 2 def test_diet_squeezes_file():

64

92

10

53

biopredictive/pyimagediet

tests/test_scripts.py

Python

test_diet_squeezes_file

53

64

53

4bbeb4060f79b6f218fd5399b9567862ec102716

bigcode/the-stack

train

bb6d7fafe684566aaaeaa307

train

function

def test_diet_complains_if_no_configuration_provided(): err = 'Usage: diet [OPTIONS] FILE\n\nError: Missing option "--config".\n' runner = CliRunner() result = runner.invoke(diet.diet, [TEST_FILE]) assert result.output == err assert result.exit_code == 2

def test_diet_complains_if_no_configuration_provided():

err = 'Usage: diet [OPTIONS] FILE\n\nError: Missing option "--config".\n' runner = CliRunner() result = runner.invoke(diet.diet, [TEST_FILE]) assert result.output == err assert result.exit_code == 2

TOOLS_DIR) helpers.TOOLS = ('optipng',) runner = CliRunner() result = runner.invoke(diet.diet, ['--check']) assert result.output == expected assert result.exit_code == 0 def test_diet_complains_if_no_configuration_provided():

64

72

13

50

biopredictive/pyimagediet

tests/test_scripts.py

Python

test_diet_complains_if_no_configuration_provided

36

41

36

4dddc4a66bed9a8c0d0fbbdcc8b8e1f84e9f22ec

bigcode/the-stack

train

50828e9dcfc62fa9c85b3a97

train

class

class IlluminaToPCLTestCase(TestCase, testing_utils.ProcessorJobTestCaseMixin): @tag("illumina") def test_illumina_to_pcl(self): """Most basic Illumina to PCL test""" organism = Organism(name="HOMO_SAPIENS", taxonomy_id=9606, is_scientific_name=True) organism.save() job = prepa...

class IlluminaToPCLTestCase(TestCase, testing_utils.ProcessorJobTestCaseMixin): @tag("illumina")

def test_illumina_to_pcl(self): """Most basic Illumina to PCL test""" organism = Organism(name="HOMO_SAPIENS", taxonomy_id=9606, is_scientific_name=True) organism.save() job = prepare_illumina_job({**GSE22427, "organism": organism}) # Remove the title of one of the samples...

ID_REF", "LV-C&si-Control-1", "Detection Pval", "LV-C&si-Control-2", "Detection Pval", "LV-C&si-Control-3", "Detection Pval", "LV-C&si-EZH2-1", "Detection Pval", "LV-C&si-EZH2-2", "Detection Pval", "LV-C&si-EZH2-3", "Detection Pval", "LV-EZH2&si-EZH2-1", "Detectio...

256

4,261

28

228

AlexsLemonade/refinebio

workers/data_refinery_workers/processors/test_illumina.py

Python

IlluminaToPCLTestCase

152

552

152

153

537df3d3c346dd8220ef34926227215565520978

bigcode/the-stack

train

859d533bbda113f2d42880f1

train

function

def prepare_illumina_job(job_info: Dict) -> ProcessorJob: pj = ProcessorJob() pj.pipeline_applied = "ILLUMINA_TO_PCL" pj.save() og_file = OriginalFile() og_file.source_filename = job_info["source_filename"] og_file.filename = job_info["filename"] og_file.absolute_file_path = job_info["absol...

def prepare_illumina_job(job_info: Dict) -> ProcessorJob:

pj = ProcessorJob() pj.pipeline_applied = "ILLUMINA_TO_PCL" pj.save() og_file = OriginalFile() og_file.source_filename = job_info["source_filename"] og_file.filename = job_info["filename"] og_file.absolute_file_path = job_info["absolute_file_path"] og_file.is_downloaded = True og_fi...

import os import os.path import shutil import tempfile from typing import Dict from django.test import TestCase, tag from data_refinery_common.enums import PipelineEnum from data_refinery_common.models import ( Organism, OriginalFile, OriginalFileSampleAssociation, Pipeline, ProcessorJob, Proc...

112

375

15

96

AlexsLemonade/refinebio

workers/data_refinery_workers/processors/test_illumina.py

Python

prepare_illumina_job

24

72

24

49058f6fd3a8120ce7a9ef68aceaae4c7c407bf2

bigcode/the-stack

train

26b982cdfdf1c65138bd7e27

train

function

def _make_original_file_with_contents(contents: str) -> OriginalFile: _, path = tempfile.mkstemp(suffix=".txt") with open(path, "w") as f: f.write(contents) og_file = OriginalFile() og_file.source_filename = path og_file.filename = os.path.basename(path) og_file.absolute_file_path = os....

def _make_original_file_with_contents(contents: str) -> OriginalFile:

_, path = tempfile.mkstemp(suffix=".txt") with open(path, "w") as f: f.write(contents) og_file = OriginalFile() og_file.source_filename = path og_file.filename = os.path.basename(path) og_file.absolute_file_path = os.path.realpath(path) og_file.is_downloaded = True og_file.save(...

[title]} sa.is_ccdl = False sa.save() sample_assoc = OriginalFileSampleAssociation() sample_assoc.original_file = og_file sample_assoc.sample = sample sample_assoc.save() return pj def _make_original_file_with_contents(contents: str) -> OriginalFile:

64

101

15

48

AlexsLemonade/refinebio

workers/data_refinery_workers/processors/test_illumina.py

Python

_make_original_file_with_contents

75

87

75

74d4e128b05387b6f8be20edb0fdda726672231e

bigcode/the-stack

train

5ac9ef9988a31d1c5eecf6a3

train

function

def _try_sanitizing_file(file: str) -> str: pj = ProcessorJob() pj.pipeline_applied = "ILLUMINA_TO_PCL" pj.save() og_file = _make_original_file_with_contents(file) job_context = illumina._prepare_files({"job_id": pj.pk, "original_files": [og_file], "job": pj}) job_context = illumina._detect_en...

def _try_sanitizing_file(file: str) -> str:

pj = ProcessorJob() pj.pipeline_applied = "ILLUMINA_TO_PCL" pj.save() og_file = _make_original_file_with_contents(file) job_context = illumina._prepare_files({"job_id": pj.pk, "original_files": [og_file], "job": pj}) job_context = illumina._detect_encoding(job_context) return illumina._san...

og_file.source_filename = path og_file.filename = os.path.basename(path) og_file.absolute_file_path = os.path.realpath(path) og_file.is_downloaded = True og_file.save() return og_file def _try_sanitizing_file(file: str) -> str:

64

102

14

49

AlexsLemonade/refinebio

workers/data_refinery_workers/processors/test_illumina.py

Python

_try_sanitizing_file

90

99

90

414d8006f3071cf2578fa6e4848608ab43a9fb11

bigcode/the-stack

train

bbf2f38fbbc5b529caa20e8e

train

class

class LongitudinalController: """ Longitudinal Controller using PID. """ def __init__(self): self.error_history = [] def __call__(self, target_speed, speed, dist): a = longitudinal_pid_P_gain * (target_speed - speed) if dist < 10.0: if speed > 3.0: ...

class LongitudinalController:

""" Longitudinal Controller using PID. """ def __init__(self): self.error_history = [] def __call__(self, target_speed, speed, dist): a = longitudinal_pid_P_gain * (target_speed - speed) if dist < 10.0: if speed > 3.0: a = -2.5 elif ...

import numpy as np from fcutils.maths import derivative from control_fc.config import ( longitudinal_pid_P_gain, longitudinal_pid_D_gain, longitudinal_pid_I_gain, ) """ Trajectory analyzer and longitudinal PID controller for LQR based control scripts """ class LongitudinalController:

63

92

308

6

57

FedeClaudi/LocomotionControl

archive/control/_control.py

Python

LongitudinalController

19

62

19

6fd84c67ddd71fd3acc42286878be16f842f2911

bigcode/the-stack

train

076397b00e6081ccc2e30af6

train

function

@trace() def plot_timestep_accuracy(directory: str, accumulator: Accumulator, timestep_labels: list = None): """Plots the average accuracy for each timestep as a bar chart. Params: - directory (str): The directory in which to save the plot - timestep_accuracy (list): The average accuracy of predi...

@trace() def plot_timestep_accuracy(directory: str, accumulator: Accumulator, timestep_labels: list = None):

"""Plots the average accuracy for each timestep as a bar chart. Params: - directory (str): The directory in which to save the plot - timestep_accuracy (list): The average accuracy of predictions for each timestep - timestep_labels (list): The labels for the timesteps """ if not accum...

.plot(x_range, precisions, label="Precision (final=%.2f)" % precisions[-1]) axes.plot(x_range, recalls, label="Recall(final=%.2f)" % recalls[-1]) axes.legend(loc='lower right') figure.savefig(directory + constants.PLT_F1_SCORE) # End of plot_f1_score() @trace() def plot_timestep_accuracy(directory: str...

97

324

24

73

ffrankies/tf-rnn

tf_rnn/plotter.py

Python

plot_timestep_accuracy

126

156

126

127

6bdc1b719d5cb544705da354c0b4297f20da6bbc

bigcode/the-stack

train

ac408d67c12b5796a01c207a

train

function

@trace() def plot_training_accuracy(directory: str, training_accuracy: list, validation_accuracy: list): """Plots the training and validation prediction accuracy on a sublot. Params: - directory (str): The directory in which to save the plot - training_accuracy (list): The list of training accura...

@trace() def plot_training_accuracy(directory: str, training_accuracy: list, validation_accuracy: list):

"""Plots the training and validation prediction accuracy on a sublot. Params: - directory (str): The directory in which to save the plot - training_accuracy (list): The list of training accuracies - validation_accuracy (list): The list of validation accuracies """ figure, axes = setu...

Validation Loss (final=%.2f)" % validation_loss[-1]) axes.legend(loc='upper right') figure.savefig(directory + constants.PLT_TRAIN_LOSS) # End of plot_training_loss() @trace() def plot_training_accuracy(directory: str, training_accuracy: list, validation_accuracy: list):

64

188

21

43

ffrankies/tf-rnn

tf_rnn/plotter.py

Python

plot_training_accuracy

87

101

87

88

9ea319591367adb00dffea7ebffc103f96eed988

bigcode/the-stack

train

7b5a782f160881ea3a235723

train

function

@trace() def plot_f1_score(directory: str, valid_accumulator: Accumulator): """Plots the f1_score (together with precision and recall) for the validation partition. Params: - directory (str): The directory in which to save the plot - valid_accumulator (Accumulator): The accumulator that contains ...

@trace() def plot_f1_score(directory: str, valid_accumulator: Accumulator):

"""Plots the f1_score (together with precision and recall) for the validation partition. Params: - directory (str): The directory in which to save the plot - valid_accumulator (Accumulator): The accumulator that contains the f1_score metrics """ figure, axes = setup_plot('F1 Score During ...

(x_range, validation_accuracy, label="Validation Accuracy (final=%.2f)" % validation_accuracy[-1]) axes.legend(loc='lower right') figure.savefig(directory + constants.PLT_TRAIN_ACCURACY) # End of plot_training_accuracy() @trace() def plot_f1_score(directory: str, valid_accumulator: Accumulator):

71

239

19

52

ffrankies/tf-rnn

tf_rnn/plotter.py

Python

plot_f1_score

105

122

105

106

29e7f2661708622cba759778a03577545c76a725

bigcode/the-stack

train

9258a432dc87d402eff69a79

train

function

@trace() def setup_plot(title: str, x_label: str, y_label: str) -> tuple: """Sets up the plot with the given parameters. Params: - title (str): The title of the plot - x_label (str): The x-axis label - y_label (str): The y-axis label Returns: - figure (matplotlib.figure.Figure): ...

@trace() def setup_plot(title: str, x_label: str, y_label: str) -> tuple:

"""Sets up the plot with the given parameters. Params: - title (str): The title of the plot - x_label (str): The x-axis label - y_label (str): The y-axis label Returns: - figure (matplotlib.figure.Figure): The figure containing the plot - axes (matplotlib.axes.Axes): The plot ...

, valid_accumulator) plot_timestep_accuracy(directory, test_accumulator) plot_confusion_matrix(directory, test_accumulator.latest_confusion_matrix, model.dataset.indexer) # End of plot() @trace() def setup_plot(title: str, x_label: str, y_label: str) -> tuple:

64

148

23

41

ffrankies/tf-rnn

tf_rnn/plotter.py

Python

setup_plot

47

65

47

48

6196f5f581148694c50f1c67a9459fa7830dd683

bigcode/the-stack

train

fb339c3d0c354974a7c939e1

train

function

@trace() def plot_confusion_matrix(directory: str, confusion_matrix: ConfusionMatrix, indexer: Indexer = None): """Plots a confusion matrix a more accurate breakdown of the predictions made. Params: - directory (str): The directory in which to save the plot - confusion_matrix (layers.utils.Confus...

@trace() def plot_confusion_matrix(directory: str, confusion_matrix: ConfusionMatrix, indexer: Indexer = None):

"""Plots a confusion matrix a more accurate breakdown of the predictions made. Params: - directory (str): The directory in which to save the plot - confusion_matrix (layers.utils.ConfusionMatrix): The confusion matrix - indexer (indexer.Indexer): Converts the label indexes to tokens """ ...

+ 5 axes.text(x_pos, y_pos, "%.1f" % height, ha='center', va='bottom', rotation=90) # Replace default labels with timestep_labels if timestep_labels is not None: axes.xaxis.set(ticklabels=timestep_labels) figure.savefig(directory + constants.PLT_TIMESTEP_ACCURACY) # End of plot_ti...

110

368

27

83

ffrankies/tf-rnn

tf_rnn/plotter.py

Python

plot_confusion_matrix

160

195

160

161

1c7e207518de7a4916cc5230e507fc39e54a28d8

bigcode/the-stack

train

80a2ef2351c00e4182012431

train

function

@trace() def plot_training_loss(directory: str, training_loss: list, validation_loss: list): """Plots the training and validation losses on a sublot. Params: - directory (str): The directory in which to save the plot - training_loss (list): The list of training losses - validation_loss (list...

@trace() def plot_training_loss(directory: str, training_loss: list, validation_loss: list):

"""Plots the training and validation losses on a sublot. Params: - directory (str): The directory in which to save the plot - training_loss (list): The list of training losses - validation_loss (list): The list of validation losses """ figure, axes = setup_plot('Training Loss Over Ti...

('all') figure, axes = plt.subplots() axes.set_title(title) axes.set_xlabel(x_label) axes.set_ylabel(y_label) return figure, axes # End of setup_plot() @trace() def plot_training_loss(directory: str, training_loss: list, validation_loss: list):

64

184

21

43

ffrankies/tf-rnn

tf_rnn/plotter.py

Python

plot_training_loss

69

83

69

70

05d5e42abe6684605ca954d725aec7fc82903e19

bigcode/the-stack

train

1f15d3975d6abd1d767cf7c2

train

function

@debug('Plotting training results') def plot(model: RNNBase, train_accumulator: Accumulator, valid_accumulator: Accumulator, test_accumulator: Accumulator): """Plots a graphical representation of the model's training performance over time. Saves the plot to file in <model_path>/run_<run_number>/gra...

@debug('Plotting training results') def plot(model: RNNBase, train_accumulator: Accumulator, valid_accumulator: Accumulator, test_accumulator: Accumulator):

"""Plots a graphical representation of the model's training performance over time. Saves the plot to file in <model_path>/run_<run_number>/graph.png. Params: - model (model.RNNModel): The model containing the path where the figure will be saved - train_accumulator (layers.utils.Accumulator): T...

import Accumulator # noqa from .layers.utils import ConfusionMatrix # noqa from .indexer import Indexer # noqa plt.style.use('ggplot') @debug('Plotting training results') def plot(model: RNNBase, train_accumulator: Accumulator, valid_accumulator: Accumulator, test_accumulator: Accumulator):

75

76

254

38

37

ffrankies/tf-rnn

tf_rnn/plotter.py

Python

plot

25

43

25

27

b175a30ba6d0a45898bb81036ac7daab9ba7f459

bigcode/the-stack

train

7be39b3db6672d6aa6a69e63

train

function

def checkout(driver): checkout_xpath = "(//button[@data-automation-id='pac-pos-proceed-to-checkout'])[1]" smart_clicker(driver, checkout_xpath)

def checkout(driver):

checkout_xpath = "(//button[@data-automation-id='pac-pos-proceed-to-checkout'])[1]" smart_clicker(driver, checkout_xpath)

ated((By.XPATH, xpath))) find_element.click() break except: driver.refresh() continue def add_to_cart(driver): add_to_cart_xpath = "(//*[@class='spin-button-children'])" smart_clicker(driver,add_to_cart_xpath) def checkout(driver):

63

64

36

4

59

jameslivulpi/wallybot

checkout.py

Python

checkout

48

50

48

c8d471ab7ef160d6c6f228a90f6e262b202cf4c1

bigcode/the-stack

train

2e58a1bf98c059dc2b6053b1

train

function

def smart_clicker(driver, xpath): while True: try: find_element = WebDriverWait(driver, 2).until(EC.visibility_of_element_located((By.XPATH, xpath))) find_element.click() break except: driver.refresh() continue

def smart_clicker(driver, xpath):

while True: try: find_element = WebDriverWait(driver, 2).until(EC.visibility_of_element_located((By.XPATH, xpath))) find_element.click() break except: driver.refresh() continue

("permissions.default.stylesheet", 2) #firefox_profile.set_preference("permissions.default.image", 2) driver = webdriver.Firefox(firefox_profile=firefox_profile) driver.get(TEST_URL) driver.maximize_window() return driver def smart_clicker(driver, xpath):

64

59

8

55

jameslivulpi/wallybot

checkout.py

Python

smart_clicker

34

42

34

db57a475588f3fd4ac0fb1f4c34cd283f7dd06ac

bigcode/the-stack

train