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def is_response_paginated(response_data): """Checks if the response data dict has expected paginated results keys Returns True if it finds all the paginated keys, False otherwise """ try: keys = list(response_data.keys()) except AttributeError: # If we can't get keys, wer'e certainl...
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def compute_power(rawvolts, rawamps): """ Compute the power. Looks trivial, but I'm gonna implement smoothing later. """ power = rawvolts * 1.58 power_low = rawvolts * 1.51 power_high = rawvolts * 1.648 return power, power_low, power_high
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import csv def read_aa_losses(filename): """ Read AA losses from data file. (assume fixed structure...) """ aa_losses = {} with open(filename, 'r') as f: reader = csv.reader(f, delimiter=',') next(reader) # skip headers for line in reader: if len(line) == 0: ...
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def add(M1, M2): """ Returns a matrix Q, where Q[i][j] = M1[i][j] + M2[i][j]. M2 is replaced by Q. """ m = len(M1) n = len(M1[0]) for p in range(m): for q in range(n): M2[p][q] = M2[p][q] + M1[p][q] return M2
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def get_config_by_url(cfg, url): """ :param cfg: dictionary :param url: path to value separated by dot, e.g, key1.key2.key3 :return: value from dictionary """ keys = url.split('.') for key in keys: cfg = cfg[key] return cfg
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def imq_kernel(x, y, score_x, score_y, g=1, beta=0.5, return_kernel=False): """Compute the IMQ Stein kernel between x and y Parameters ---------- x : torch.tensor, shape (n, p) Input particles y : torch.tensor, shape (n, p) Input particles score_x : torch.tensor, shape (n, p) ...
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def build_rgb_and_opacity(s): """ Given a KML color string, return an equivalent RGB hex color string and an opacity float rounded to 2 decimal places. EXAMPLE:: >>> build_rgb_and_opacity('ee001122') ('#221100', 0.93) """ # Set defaults color = '000000' opacity = 1 ...
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def url_add_api_key(url_dict: dict, api_key: str) -> str: """Attaches the api key to a given url Args: url_dict: Dict with the request url and it's relevant metadata. api_key: User's API key provided by US Census. Returns: URL with attached API key infor...
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def _compute_fans(shape): """Computes the fan-in and fan-out for a depthwise convolution's kernel.""" if len(shape) != 4: raise ValueError( 'DepthwiseVarianceScaling() is only supported for the rank-4 kernels ' 'of 2D depthwise convolutions. Bad kernel shape: {}' .format(str(shape))) ...
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def merge_shards(shard_data, existing): """ Compares ``shard_data`` with ``existing`` and updates ``shard_data`` with any items of ``existing`` that take precedence over the corresponding item in ``shard_data``. :param shard_data: a dict representation of shard range that may be modified by...
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def usage_percent(used, total, round_=None): """Calculate percentage usage of 'used' against 'total'.""" try: ret = (float(used) / total) * 100 except ZeroDivisionError: return 0.0 else: if round_ is not None: ret = round(ret, round_) return ret
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import re def is_valid_regex(string): """ Checks whether the re module can compile the given regular expression. :param string: str :return: boolean """ try: re.compile(string) is_valid = True except re.error: is_valid = False return is_valid
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import calendar def year_add(date, years): """Add number of years to date. >>> import datetime >>> year_add(datetime.datetime(2016, 2, 29), 1) datetime.date(2017, 2, 28) >>> year_add(datetime.date(2016, 2, 29), 1) datetime.date(2017, 2, 28) >>> year_add(datetime.date(2015, 2, 28), 1) ...
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def _get_command_powershell_script(command): """Return a valid CMD command that runs a powershell script.""" return "powershell -NonInteractive -NoLogo -File {}".format(command)
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from pathlib import Path import json def latest_checkpoint(model_dir, model_name): """return path of latest checkpoint in a model_dir Args: model_dir: string, indicate your model dir(save ckpts, summarys, logs, etc). model_name: name of your model. we find ckpts by name Returns...
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def get_token_list(text): """Returns a list of tokens. This function expects that the tokens in the text are separated by space character(s). Example: "ca n't , touch". This is the case at least for the public DiscoFuse and WikiSplit datasets. Args: text: String to be split into tokens. """ return t...
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def cut_string(string, limit=30): """Shorten the length of longer strings.""" if len(string) <= limit: return string else: return string[:limit-3] + '...'
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def heading(heading_string, underline='='): """ Takes a raw string and underlines it with the given underline char """ return '%s\n%s' % (heading_string, underline * len(heading_string))
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def profile_to_node(src_profile): """convert source profile to graph node.""" return (src_profile['uid'], src_profile)
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def matchnocase(word, vocab): """ Match a word to a vocabulary while ignoring case :param word: Word to try to match :param vocab: Valid vocabulary :return: >>> matchnocase('mary', {'Alice', 'Bob', 'Mary'}) 'Mary' """ lword = word.lower() listvocab = list(vocab) # this trick catc...
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from datetime import datetime def get_first_timestamp(log_file, search_text): """Get the first timestamp of `search_text' in the log_file Args: log_file search_text (str) Returns: timestamp: datetime object """ timestamp = None with open(log_file, "r") as f: c...
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def get_fetaure_names(df, feature_name_substring) : """ Returns the list of features with name matching 'feature_name_substring' """ return [col_name for col_name in df.columns if col_name.find(feature_name_substring) != -1]
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import numbers def ISNUMBER(value): """ Checks whether a value is a number. >>> ISNUMBER(17) True >>> ISNUMBER(-123.123423) True >>> ISNUMBER(False) True >>> ISNUMBER(float('nan')) True >>> ISNUMBER(float('inf')) True >>> ISNUMBER('17') False >>> ISNUMBER(None) False >>> ISNUMBER(da...
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def eval_multiple(exprs,**kwargs): """Given a list of expressions, and keyword arguments that set variable values, returns a list of the evaluations of the expressions. This can leverage common subexpressions in exprs to speed up running times compared to multiple eval() calls. """ for e in exp...
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import requests def get(url, params, proxies, headers): """Send a request with the GET method.""" response = requests.get(url, params=params, proxies=proxies, headers=headers) return response
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def action_from_trinary_to_env(action) -> int: """ Maps trinary model output to int action understandable by env """ assert action in (0, 1, 2), f'Wrong action: {action}' return { 0: 0, 1: 2, 2: 5 }[action]
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import hashlib def file_md5(file_path: str) -> str: """Compute the md5 hex digest of a binary file with reasonable memory usage.""" md5_hash = hashlib.md5() with open(file_path, 'rb') as f: while True: data = f.read(65536) if not data: break md5_...
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def pl_to_eng(unit: str) -> str: """Converts Polish terminology to English""" switcher = { "pikinier": "spear", "miecznik": "sword", "topornik": "axe", "lucznik": "archer", "zwiadowca": "spy", "lekki kawalerzysta": "light", "lucznik na koniu": "marcher", ...
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from typing import Dict from typing import List from pathlib import Path import yaml def write_commands_instructions( commands_instructions: Dict[str, List[str]], scene_path: Path, index: int ) -> Path: """*Deprecated, use `write_yaml_instructions` instead.* Writes a command instruction `yaml` file. ...
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import re def replace_simultaneous(s: str, r0: str, r1: str) -> str: """ Replace all instances of `r0` in `s` with `r1` and vice versa. This method does the replacements simultaneously so that, e.g., if you call `replace_simultaneous("apple banana", "apple", "banana")` the result will be `"banana...
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def retry_http(response): """Retry on specific HTTP errors: * 429: Rate limited to 50 reqs/minute. Args: response (dict): Dynatrace API response. Returns: bool: True to retry, False otherwise. """ retry_codes = [429] code = int(response.get('error', {}).get('code', 200)) ...
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def circular_wetted_perimeter(angle, diameter): """Returns circle wetted perimeter. :param angle: angle in radians from angle_in_partial_filled_pipe function :param diameter: diameter of pipe [m] """ return angle * diameter
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def is_dunder(attr_name: str) -> bool: """ Retuns whether the given attr is a magic/dunder method. :param attr_name: """ return attr_name.startswith("__") and attr_name.endswith("__")
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def regularize_layer_weighted(layers, penalty, tags={'regularizable': True}, **kwargs): """ Computes a regularization cost by applying a penalty to a group of layers, weighted by a coefficient for each layer. Parameters ---------- layers : dict A mapping from : tuple of class:`Layer` instances to coefficients. ...
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def convert_df_2_string(df): """ Convert data frame rows to string output where each new line is defined as \n """ # ititialise string output = 'agent,wkt\n' for i, row in df.iterrows(): if i == len(df) - 1: output += str(row['label']) + ',' + str(row['geometry']) els...
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from typing import List from typing import Any import random def shuffle_list(elements: List[Any]) -> List[Any]: """ Shuffle the input list in random order :param elements: List to be reshuffled :return: reshuffled list """ random.shuffle(elements) return elements
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def merge_sort(array): """ ### Merge sort Implementation of one of the most powerful sorting algorithms algorithms.\n Return a sorted array, """ def merge(L, R): res = [] left_ind = right_ind = 0 while left_ind < len(L) and right_ind < len(R): if...
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def split_col_row(ref): """Split the letter and number components of a cell reference. Examples: >>> split_col_row('A1') ('A', 1) >>> split_col_row('B100') ('B', 100) >>> split_col_row('CC12') ('CC', 12) """ head = ref.rstrip("0123456789") tail = ref[...
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import gzip def get_file_handle(file_path, compression): """ Returns a file handle to the given path. :param file_path: path to the file to open :param compression: indicates whether or not the input file is compressed :return: a file handle to file_path """ if compression: return...
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def save_params(net, best_metric, current_metric, epoch, save_interval, prefix): """Logic for if/when to save/checkpoint model parameters""" if current_metric < best_metric: best_metric = current_metric net.save_parameters('{:s}_best.params'.format(prefix, epoch, current_metric)) with op...
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import operator def vector_add(a, b): """Component-wise addition of two vectors. >>> vector_add((0, 1), (8, 9)) (8, 10) """ return tuple(map(operator.add, a, b))
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import json def get_aws_key_and_secret(aws_creds_file_path): """ Given a filename containing AWS credentials (see README.md), return a 2-tuple (access key, secret key). """ with open(aws_creds_file_path, 'r') as f: creds_dict = json.load(f) return creds_dict['accessKeyId'], creds_dict[...
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def freq_id_to_stream_id(f_id): """ Convert a frequency ID to a stream ID. """ pre_encode = (0, (f_id % 16), (f_id // 16), (f_id // 256)) stream_id = ( (pre_encode[0] & 0xF) + ((pre_encode[1] & 0xF) << 4) + ((pre_encode[2] & 0xF) << 8) + ((pre_encode[3] & 0xF) << 12) ) ...
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import dateutil.parser def get_entry_end_date(e): """Returns end date for entry""" return dateutil.parser.parse(e['time_end'])
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from pathlib import Path def get_launch_agents_dir() -> Path: """Returns user LaunchAgents directory.""" launch_agents_dir = Path.home() / "Library" / "LaunchAgents" assert launch_agents_dir.is_dir() return launch_agents_dir
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def yddot_d_z(mu, state, r_15_inv, r_25_inv): """ Partial of x acceleration with respect to z Args: mu (float): three body constant state (np.array): 6 dimensional state vector of (x, y, z, dx, dy, dz) r_15_inv (float): 1 / norm(r_1)^(5) where r_1 is the vector from the ...
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def decypher(text): """ Decypher file name into descriptive label for legend """ # name shortcuts help_dict = {"h": "Target/Hunt AI", "p": "Probabilistic AI", "r": "Random AI"} final = "" t_split = text.split("-") final += help_dict[t_split[0]] # hunt/target AI branch if t_spli...
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import re def compute_rq_type(oslevel, empty_list): """Compute rq_type. return: Latest when oslevel is blank or latest (not case sensitive) Latest when oslevel is a TL (6 digits) and target list is empty TL when oslevel is xxxx-xx(-00-0000) SP when oslevel is xxxx-xx-x...
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import re def convert_input_paths(argo_json): """ argo aggregation is not valid json as properties are not enclosed in quotes: flow/step/[{task-id:flow-step-3119439657},{task-id:flow-step-195521861},{task-id:flow-step-3020891073}] Parameters ---------- argo_json Returns ------- l...
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from pathlib import Path def get_solar_charge_state() -> str: """ Gets the current state of the charging system Returns: The charge state object as a json string """ current_state = Path('current_state.json').read_text() return current_state
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def get_fixture_value(request, fixture_name): """ Returns the value associated with fixture named `fixture_name`, in provided `request` context. This is just an easy way to use `getfixturevalue` or `getfuncargvalue` according to whichever is available in current `pytest` version. :param request: ...
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def printSchoolYear(year1): """Return a print version of the given school year. """ if year1: return "%d–%d" % (year1 - 1, year1)
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def dahua_brightness_to_hass_brightness(bri_str: str) -> int: """ Converts a dahua brightness (which is 0 to 100 inclusive) and converts it to what HASS expects, which is 0 to 255 inclusive """ bri = 100 if not bri_str: bri = int(bri_str) current = bri / 100 return int(current *...
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def fit_parabola(x1,x2,x3,y1,y2,y3): """Returns the parabola coefficients a,b,c given 3 data points [y(x)=a*x**2+b*x+c]""" denom = (x1-x2)*(x1-x3)*(x2-x3) a = (x3*(y2-y1)+x2*(y1-y3)+x1*(y3-y2))/denom b = (x1**2*(y2-y3)+x3**2*(y1-y2)+x2**2*(y3-y1))/denom c = (x2**2*(x3*y1-x1*y3)+x2*(x1**2*y3-x3**2*y1...
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def generate_list(usb_dict: dict) -> list: """ wrapper for list conversion :param usb_dict: usb dictionary :return: list of usb devices for tui print """ devices = [] for usb in usb_dict.values(): devices.append(usb) return devices
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def reset_line_breaks(curr_boundary={}): """ Builds a fresh line breaks dictionary while keeping any information provided concerning line boundaries. Parameters ---------- curr_boundary: dict Line boundaries to be preserved Returns ------- dict The newly initialize...
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def stop(M, i): """ Check if the algorithm converged. :param M: input matrix :param i: iteration steo :return: boolean: True if converged """ # this saves time, so we dont have to do multiplication in the first 7 iterations if i > 6: M_temp = M ** 2 - M m = M_temp.max() -...
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def split_text(text, sep='\n'): """Split text.""" if isinstance(text, bytes): text = text.decode("utf8") return [elm.strip() for elm in text.split(sep) if elm.strip()]
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import re def replace_image_link(target_str): """ Replace the shorthand of an image link { image.jpg } with the full link {{ img_tag("image.jpg") | safe }} :param target_str: String with images in it to be edited :return: string with images formatted as {{ img_tag("image.jpg") | safe }} """ # ...
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def create_option(option, display, window, active=True): """ Returns an option `dict` to be used by lottus :param option `str`: the value of the option :param option `str`: the value that will be displayed :param window `str`: the name of the window that this option points to ...
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import re def remove_proximity_around_booleans(query_str): """ Clients like PEP-Web (Gavant) send fulltext1 as a proximity string. This removes the proximity if there's a boolean inside. We could have the client "not do that", but it's actually easier to remove than to parse and add. >>> ...
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def api_client(application, request): """ Fixture that returns api_client Parameters: app (Application): Application for which create the client. Returns: api_client (HttpClient): Api client for application """ def _api_client(app=application, **kwargs): client = app.api_...
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from functools import reduce def _is_num_tuple(t,size): """Returns: True if t is a sequence of numbers; False otherwise. If the sequence is not of the given size, it also returns False. Parameter t: The value to test Precondition: NONE Parameter size: The size of the sequence Pr...
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def jsonify_dict(d): """Turns python booleans into strings so hps dict can be written in json. Creates a shallow-copied dictionary first, then accomplishes string conversion. Args: d: hyperparameter dictionary Returns: hyperparameter dictionary with bool's as strings """ d2 = d.copy() # shallow c...
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from pathlib import Path def _load_requirements(requirements_file, folder="requirements"): """Load requirements from a file.""" requirements = [] with open(Path(folder) / Path(requirements_file), "r") as f: for line in f: line = line.strip() if line and not line.startswith(...
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def get_emails(notification_rec): """ Get list of emails for users listed in the specified notification """ # Use a set instead of list as there could be duplicates. ret = [] for recipient in notification_rec.recipients.all(): ret.append(recipient.email) return ret
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import six def text_type(string, encoding='utf-8'): """ Given text, or bytes as input, return text in both python 2/3 This is needed because the arguments to six.binary_type and six.text_type change based on if you are passing it text or bytes, and if you simply pass bytes to six.text_type w...
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def quote_value(value: str) -> str: """ Ensures values with ";" are quoted. >>> quote_value("foo") 'foo' >>> quote_value("foo;bar") '"foo;bar"' """ if value.find(";") != -1: return f'"{value}"' return value
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def idx2token(idx, reverse_vocab): """ index换取词 :param idx: index :param reverse_vocab: 反查表 @see chatbot.build_vocab :return: 词 """ return reverse_vocab[idx]
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def message_from_lax(data): """ format a message from a Lax response data """ return data.get("message") if data.get("message") else "(empty message)"
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import itertools def get_n_bits_combinations(num_bits: int) -> list: """ Function returning list containing all combinations of n bits. Given num_bits binary bits, each bit has value 0 or 1, there are in total 2**n_bits combinations. :param num_bits: int, number of combinations to evaluate :r...
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def get_centers(bins): """Return the center of the provided bins. Example: >>> get_centers(bins=np.array([0.0, 1.0, 2.0])) array([0.5, 1.5]) """ bins = bins.astype(float) return (bins[:-1] + bins[1:]) / 2
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def hex_16bit(value): """Converts 16bit value into bytearray. args: 16bit value returns: bytearray of size 2 """ if value > 0xffff or value < 0: raise Exception('Sar file 16bit value %s out of range' % value) return value.to_bytes(2, 'little')
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def transpose(matrix): """Transpose a list of lists. >>> transpose([['a', 'b', 'c'], ['d', 'e', 'f'], ['g', 'h', 'i']]) [['a', 'd', 'g'], ['b', 'e', 'h'], ['c', 'f', 'i']] >>> transpose([['a', 'b', 'c'], ['d', 'e', 'f']]) [['a', 'd'], ['b', 'e'], ['c', 'f']] >>> transpose([['a', 'b'], ['d', '...
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import torch def reduce(tensor: torch.Tensor, reduction: str) -> torch.Tensor: """Reduces the given tensor using a specific criterion. Args: tensor (torch.Tensor): input tensor reduction (str): string with fixed values [elementwise_mean, none, sum] Raises: ValueError: when the re...
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def load_cows(filename): """ Read the contents of the given file. Assumes the file contents contain data in the form of comma-separated cow name, weight pairs, and return a dictionary containing cow names as keys and corresponding weights as values. Parameters: filename - the name of the data ...
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def wrap_hashlib(hasher, length=None): """ Wraps hashlib's functions, returning a function that returns the hex-digest of its input. >>> from hashlib import sha1 >>> wrap_hashlib(sha1)(b'heyo') 'f8bb1031d6d82b30817a872b8a2ec31d5380cee5' :param hasher: A function from :mod:`hashlib` :return...
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import re def isBlank(s): """ Returns True if string contains only space characters.""" return bool(re.compile("^\s*$").match(s))
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def __extract_tzd(m): """Return the Time Zone Designator as an offset in seconds from UTC.""" if not m: return 0 tzd = m.group("tzd") if not tzd: return 0 if tzd == "Z": return 0 hours = int(m.group("tzdhours"), 10) minutes = m.group("tzdminutes") if minutes: ...
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def compute_heuristic_conn_4(init_pos, coord): """Returns Manhattan heuristic for distance from coord to init_pos init_pos - coordinate of position of goal configuration coord - coordinate of configuration for which heursitic is being computed Returns the heuristic distance to goal t...
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def frequency(text, char): """ Counts frequency of a character in a string. """ count = 0 for c in text: if c == char: count += 1 return count
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import time def measure_command(func, kwargs): """ Measures the execution time of a function :param func: function :param kwargs: dict keyword arguments :return: float, result (time, result of fucntion) """ time_start = time.time() r = func(**kwargs) dt = time.time() -...
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def largest_number(seq_seq): """ Returns the largest number in the subsequences of the given sequence of sequences. Returns None if there are NO numbers in the subsequences. For example, if the given argument is: [(3, 1, 4), (13, 10, 11, 7, 10), [1, 2, 3, 4]] then thi...
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def __unwrap_nonsense_request(request): """ Unwrap the given "estimate nonsense" request into a string. Args: request: A JSON-like dict describing an "estimate nonsense" request (as described on https://clusterdocs.azurewebsites.net/) Returns: A string that represents the sentence of w...
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def _clean(target_str: str, is_cellref: bool = False) -> str: """Rids a string of its most common problems: spacing, capitalisation,etc.""" try: output_str = target_str.lstrip().rstrip() except AttributeError: raise AttributeError("Cannot clean value other than a string here.") if is_cel...
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def get_values(record, tag): """Gets values that matches |tag| from |record|.""" keys = [key for key in record.keys() if key[0] == tag] return [record[k] for k in sorted(keys)]
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from typing import List def expected_value(values: List[float]) -> float: """Return the expected value of the input list >>> expected_value([1, 2, 3]) 2.0 """ return sum(values) / len(values)
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def is_valid_gadget(gadget, bad_chars): """Determine if a gadget is valid (i.e., contains no bad characters). Args: gadget (Gadget): A namedtuple-like object with `shellcode` and `asm` fields. bad_chars (bytearray): The bad characters not allowed to be present. Returns: ...
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def month(dt): """ For a given datetime, return the matching first-day-of-month date. """ return dt.date().replace(day=1)
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def count_frequency(df, col): """Count the number of occurence value in a column.""" df['Freq'] = df.groupby(col)[col].transform('count') return df
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def extract_tty_phone(service_center): """ Extract a TTY phone number if one exists from the service_center entry in the YAML. """ tty_phones = [p for p in service_center['phone'] if 'TTY' in p] if len(tty_phones) > 0: return tty_phones[0]
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from pathlib import Path def get_data_dir() -> str: """Get a filepath to the drem data directory. Returns: str: Filepath to the drem data directory """ cwd = Path(__file__) base_dir = cwd.resolve().parents[3] data_dir = base_dir / "data" return str(data_dir)
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def sentinel(name): """Create a unique, one-off object with a useful repr""" def __repr__(_): return f'<{name}>' return type(name, (), {'__repr__': __repr__})()
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import math import torch def wrap_phi_to_2pi_torch(x): """Shift input angle x to the range of [-pi, pi] """ pi = math.pi x = torch.fmod(2 * pi + torch.fmod(x + pi, 2 * pi), 2 * pi) - pi return x
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def FixAbsolutePathInLine(line, relative_paths): """Fix absolute paths present in |line| to relative paths.""" absolute_path = line.split(':')[0] relative_path = relative_paths.get(absolute_path, absolute_path) if absolute_path == relative_path: return line return relative_path + line[len(absolute_path):]
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def lazyprop(func): """Wraps a property so it is lazily evaluated. Args: func: The property to wrap. Returns: A property that only does computation the first time it is called. """ attr_name = '_lazy_' + func.__name__ @property def _lazyprop(self): """A lazily evalu...
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def simpleCollision(spriteOne, spriteTwo): """ Simple bounding box collision detection. """ widthSpriteOne, heightSpriteOne = spriteOne.image.get_size() rectSpriteOne = spriteOne.image.get_rect().move( spriteOne.pos.x - widthSpriteOne / 2, spriteOne.pos.y - heightSpriteOne / 2) ...
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import numbers import json import base64 def encode(d): """Encode an object in a way that can be transported via Mesos attributes: first to JSON, then to base64url. The JSON string is padded with spaces so that the base64 string has no = pad characters, which are outside the legal set for Mesos. """ ...
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def __read_dataset_item(path): """Reads data set from path returns a movie dict. Parameters ---------- path : str Absolute path of the MovieLens data set(u.data). Returns ------- rating_dict : dict Returns a dict of users, movies and ratings....
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import torch def query_ball_point(radius, nsample, xyz, new_xyz): """ Input: radius: local region radius nsample: max sample number in local region xyz: all points, [B, N, 3] new_xyz: query points, [B, S, 3] Return: group_idx: grouped points index, [B, S, nsample] ...
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