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def autoclean_cv(training_dataframe, testing_dataframe, drop_nans=False, copy=False, encoder=None, encoder_kwargs=None, ignore_update_check=False): """Performs a series of automated data cleaning transformations on the provided training and testing data sets Unlike `autoclean()`, this function...
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import asyncio def make_coroutine_from_tree(tree, filename="<aexec>", symbol="single", local={}): """Make a coroutine from a tree structure.""" dct = {} tree.body[0].args.args = list(map(make_arg, local)) exec(compile(tree, filename, symbol), dct) return asyncio.corout...
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def update_Sigmai(Yi, Es, Vars): """ Return new Sigma_i: shape k """ return np.mean((Yi - Es) ** 2, axis=1) + np.mean(Vars, axis=1)
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def gather_indexes(sequence_tensor, positions): """Gathers the vectors at the specific positions over a minibatch.""" sequence_shape = get_shape_list(sequence_tensor, expected_rank=3) batch_size = sequence_shape[0] seq_length = sequence_shape[1] width = sequence_shape[2] flat_offsets = tf.resha...
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import typing def check_sub_schema_dict(sub_schema: typing.Any) -> dict: """Check that a sub schema in an allOf is a dict.""" if not isinstance(sub_schema, dict): raise exceptions.MalformedSchemaError( "The elements of allOf must be dictionaries." ) return sub_schema
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def get_proto_root(workspace_root): """Gets the root protobuf directory. Args: workspace_root: context.label.workspace_root Returns: The directory relative to which generated include paths should be. """ if workspace_root: return "/{}".format(workspace_root) else: r...
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def bwimcp(J, K, x, tr=.2, alpha=.05): """ Multiple comparisons for interactions in a split-plot design. The analysis is done by taking difference scores among all pairs of dependent groups and determining which of these differences differ across levels of Factor A using trimmed means. ...
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def trigger_decoder(mode: str, trigger_path: str=None) -> tuple: """Trigger Decoder. Given a mode of operation (calibration, copy phrase, etc) and a path to the trigger location (*.txt file), this function will split into symbols (A, ..., Z), timing info (32.222), and targetness (target...
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def method_comparison(filename=None, extension="png", usetex=False, passed_ax=None, **kwargs): """ Create a plot comparing how estimated redshift changes as a function of dispersion measure for each DM-z relation. Parameters ---------- filename: string or None, optional ...
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def logCompression(pilImg): """Does log compression processing on a photo Args: pilImg (PIL Image format image): Image to be processed """ npImg = PILtoNumpy(pilImg) c = 255 / (np.log10(1 + np.amax(npImg))) for all_pixels in np.nditer(npImg, op_flags=['readwrite']): all_pixels[....
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def quantile_turnover(quantile_factor, quantile, period=1): """ Computes the proportion of names in a factor quantile that were not in that quantile in the previous period. Parameters ---------- quantile_factor : pd.Series DataFrame with date, asset and factor quantile. quantile : i...
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def dmp_div(f, g, u, K): """ Polynomial division with remainder in ``K[X]``. Examples ======== >>> from sympy.polys import ring, ZZ, QQ >>> R, x,y = ring("x,y", ZZ) >>> R.dmp_div(x**2 + x*y, 2*x + 2) (0, x**2 + x*y) >>> R, x,y = ring("x,y", QQ) >>> R.dmp_div(x**2 + x*y, 2*x +...
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def is_designated_holiday(timestamp): """ Returns True if the date is one of Piedmont’s "designated holidays": - New Years Day (January 1st) - Memorial Day (last Monday of May) - Independence Day (July 4th) - Labor Day (First Monday of September) - Thanksgiving Day (4th Thursday in November)...
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def check(val, desc=None, as_warn=False) -> SimpleAssertions: """ function based assertion call :param val: val to check :param desc: optional, description of val :param as_warn: if set, convert assertion error to warning message :return: assertionClass """ return SimpleAssertions(as_wa...
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def ChangeExtension(filename, newExtension): """ChangeExtension(filename, newExtension) -> str Replaces the extension of the filename with the given one. If the given filename has no extension, the new extension is simply appended. arguments: filename string correspondi...
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def file_based_input_fn_builder(input_file, seq_length, is_training, drop_remainder): """Creates an `input_fn` closure to be passed to TPUEstimator.""" name_to_features = { "input_ids": tf.FixedLenFeature([se...
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def synchrotron_thin_spectrum(freqs, ne, te, bfield): """Optically thin (unobsorbed) synchrotron spectrum. Units of erg/cm^3/s/Hz NY95b Eq 3.9 """ const = 4.43e-30 # erg/cm^3/s/Hz theta_e = K_BLTZ * te / (MELC * SPLC * SPLC) v0 = QELC * bfield / (2*np.pi*MELC*SPLC) xm = 2*freqs/(3*v0...
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import os from pathlib import Path from re import DEBUG def extract_val_setup(timestamp, lat, lon, dataPath = "Data/IceData/"): """ Extracts a timestamped value from a NSIDC GeoTIFF File Inputs: timestamp = datetime struct of sample lat = sample latitude lon = sample longitude ...
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import base64 def create_message(service, to, subject, message_text): """Create a message for an email. Args: sender: Email address of the sender. to: Email address of the receiver. subject: The subject of the email message. message_text: The text of the email message. Returns: ...
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def numpy_ndarray(nb_arr): """Return a copy of numba DeviceNDArray data as a numpy.ndarray. """ return nb_arr.copy_to_host()
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def convert_to_dict(my_keys, my_values): """Merge a given list of keys and a list of values into a dictionary. Args: my_keys (list): A list of keys my_values (list): A list corresponding values Returns: Dict: Dictionary of the list of keys mapped to the list of values """ ...
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def add_vit(request): """ Add a new vit with API, currently image and video are not supported """ user = KeyBackend().authenticate(request) if request.method == "POST": if request.user.is_authenticated: form = VitForm(request.POST) if form.is_valid(): ...
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def long_control_state_trans(active, long_control_state, v_ego, v_target, v_pid, output_gb, brake_pressed, cruise_standstill, min_speed_can): """Update longitudinal control state machine""" stopping_target_speed = min_speed_can + STOPPING_TARGET_SPEED_OFFSET stopping_condition = (v_eg...
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def load_group_to_namedtuple(group: h5py.Group): """Returns namedtuple with name of group and key: values of group attrs e.g. srs1 group which has gpib: 1... will be returned as an srs1 namedtuple with .gpib etc """ # Check it was stored as a namedTuple if group.attrs.get('description', None) != 'Na...
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import json def export_json(blocks=None, subsections=False): """ Returns JSON representation of parsed config structure :param blocks: List of blocks to export :param subsections: Export all subblocks :return: JSON-dumped string """ if blocks is not None: blocks = [_canonicalize_bl...
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def get_dummy_message(text): """Get a dummy message with a custom text""" return botogram.objects.messages.Message({ "message_id": 1, "from": {"id": 123, "first_name": "Nobody"}, "chat": {"id": -123, "type": "chat", "title": "Something"}, "date": 1, "text": text, })
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import time def list_ga4_entities(admin_api): """Get a dictionary of GA4 entity settings based on type. Args: admin_api: The Admin API object. Returns: A dictionary of GA4 entity setting lists. """ entities = { 'ga4_account_summaries': [], 'ga4_accounts': [], 'ga4_properties': []...
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import textwrap import os def text_detection_background(text, background=None, hsize=15, vsize=15): """ Given a string TEXT, generate a picture with text in it arguments: TEXT -- a string to be displayed HSIZE -- maximum number of characters in one line VSIZE -- maximum number of lines background -- a ...
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def print_sig(expr): """ Arguments: - `expr`: """ return "{0!s} × {1!s}".format(expr.dom, expr.body)
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def is_grounded_concept(c: Concept) -> bool: """ Check if a concept is grounded """ return ( "UN" in c.db_refs and c.db_refs["UN"][0][0].split("/")[1] != "properties" )
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def _get_form(app, parent_form, factory_method, force_disable_csrf=False): """Create and fill a form.""" class AForm(parent_form): pass with app.test_request_context(): extra = _update_with_csrf_disabled() if force_disable_csrf else {} RF = factory_method(AForm) rf = RF(**...
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def get_root_disk_size(): """ Get size of the root disk """ context = pyudev.Context() rootfs_node = get_rootfs_node() size_gib = 0 for device in context.list_devices(DEVTYPE='disk'): # /dev/nvmeXn1 259 are for NVME devices major = device['MAJOR'] if (major == '8' or major =...
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import numpy def convert_to_premultiplied_png(file): """ http://stackoverflow.com/questions/6591361/method-for-converting-pngs-to-premultiplied-alpha """ logger.info("converting to premultiplied alpha") im = Img.open(file).convert('RGBA') a = numpy.fromstring(im.tobytes(), dtype=numpy.uint8) ...
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def DSQuery(dstype, objectname, attribute=None): """DirectoryServices query. Args: dstype: The type of objects to query. user, group. objectname: the object to query. attribute: the optional attribute to query. Returns: If an attribute is specified, the value of the attribute. Otherwise, the ...
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def calculate_offset(lon, first_element_value): """ Calculate the number of elements to roll the dataset by in order to have longitude from within requested bounds. :param lon: longitude coordinate of xarray dataset. :param first_element_value: the value of the first element of the longitude array ...
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def min_mean_col(m: ma.MaskedArray) -> int: """Calculate the index of the column with the smallest mean. """ if ma.count_masked(m) == m.size: return -1 col_mean = np.nanmean(m, axis=0) return np.argmin(col_mean)
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import resnet import sys import os import torch def load_simclrv2(init_args): """ Load pretrained SimCLR-v2 model. """ ckpt_file = init_args["ckpt_file"] model_dir = init_args["model_dir"] # Load the resnet.py that comes with the SimCLR-v2's PyTorch converter sys.path.insert( 0, ...
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def minekey_read(request, mk_hmac, mk_fid, mk_fversion, mk_iid, mk_depth, mk_type, mk_ext, **kwargs): """ arguments: request, mk_hmac, mk_fid, mk_fversion, mk_iid, mk_depth, mk_type, mk_ext, **kwargs implements: GET /key/(MK_HMAC)/(MK_FID)/(MK_FVERSION)/(MK_IID)/(MK_DEPTH)/(MK_TYPE).(MK_EXT) returns: a ...
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import os def get_file_metadata(folder, video_relative_path): """ """ # SAMPLE FILENAME: XXCam_01_20180517203949574.mp4 # XXXXX_XX_YYYYMMDDHHMMSSmmm.mp4 # 2019/01/01/XXCam-20180502-1727-34996.mp4 # XXCam-01-20180502-1727-34996.mp4 video_filen...
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def test_data_alignment(role_value, should_pass, check_model): """Test a custom model which returns a good and alignments from data(). qtmodeltest should capture this problem and fail when that happens. """ class MyModel(qt_api.QAbstractListModel): def rowCount(self, parent=qt_api.QtCore.QModel...
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def cov(a, b): """Return the sample covariance of vectors a and b""" a = flex.double(a) b = flex.double(b) n = len(a) assert n == len(b) resid_a = a - flex.mean(a) resid_b = b - flex.mean(b) return flex.sum(resid_a*resid_b) / (n - 1)
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from bs4 import BeautifulSoup import re def beautify(soup: BeautifulSoup, rich_terminal: bool = True) -> str: """ Cleans up the raw HTML so it's more presentable. Parse BeautifulSoup HTML and return prettified string """ beautifiedText = str() for i in soup: if rich_terminal: ...
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def design_complexity(design: Design) -> int: """Returns an approximation of the design's complexity to create.""" diversity = 3 * len(design.required) abundance = 2 * sum(design.required.values()) return diversity + abundance + design.additional
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import torch def approx_q_y(q_z, mu_lookup, logvar_lookup, k=10): """ refer to eq.13 in the paper """ q_z_shape = list(q_z.size()) # (b, z_dim) mu_lookup_shape = [mu_lookup.num_embeddings, mu_lookup.embedding_dim] # (k, z_dim) logvar_lookup_shape = [logvar_lookup.num_embeddings, logvar_looku...
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def svn_repos_get_logs2(*args): """ svn_repos_get_logs2(svn_repos_t repos, apr_array_header_t paths, svn_revnum_t start, svn_revnum_t end, svn_boolean_t discover_changed_paths, svn_boolean_t strict_node_history, svn_repos_authz_func_t authz_read_func, svn_log_message_receiver_t...
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def error_function(theta, X, y): """Error function J definition""" diff = np.dot(X, theta) - y return (1. / 2 * m) * np.dot(np.transpose(diff), diff)
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def register(operation_name): """ Registers the decorated class as an Operation with the supplied operation name :param operation_name: The identifying name for the Operation """ def wrapper(clazz): if operation_name not in OPERATIONS: OPERATIONS[operation_name] = clazz ...
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def url_exists(video): """ check each source for a url for this video; return True as soon as one is found. If none are found, return False """ max_timeout = int(kodi.get_setting('source_timeout')) logger.log('Checking for Url Existence: |%s|' % (video), log_utils.LOGDEBUG) for cls in relevant_s...
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import os def test_actions_explicit_get_collector_action_for_unexisting_terminal(): """ Test for situation when `get_collector` has an action for un-existing terminal. """ action = get_collector() @action def INT(context, value): return int(value) @action def STRING(cont...
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def log2_grad(orig, grad): """Returns [grad * 1 / (log(2) * x)]""" x = orig.args[0] ones = ones_like(x) two = const(2.0, dtype=x.checked_type.dtype) return [grad * ones / (log(two) * x)]
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import posixpath import requests def _stream_annotation(file_name, pn_dir): """ Stream an entire remote annotation file from Physionet. Parameters ---------- file_name : str The name of the annotation file to be read. pn_dir : str The PhysioNet directory where the annotation f...
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def get_scenarios(): """ Return a list scenarios and values for parameters in each of them :return: """ # Recover InteractiveSession isess = deserialize_isession_and_prepare_db_session() if isess and isinstance(isess, Response): return isess scenarios = get_scenarios_in_state(i...
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def download() -> str: """ Returns a download of the active files. :return: the zip files needs to be downloaded. """ file_manager = utility.load_file_manager() response = make_response(file_manager.zip_active_files( "scrubbed_documents.zip")) # Disable download caching response.h...
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import subprocess def evaluate_test_arff(model_path, test_arff_path, out_path): """ Obtain predictions of test_file using the trained model in model_path :param output_folder: :param output_name: :param model_path: :param test_file: """ # PREDICTIONS FILE HEADERS: INSTANCE, ACTUAL, PRE...
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import pickle def load_from_pickle_file(filepath): """ Loads a pickle file into a python variable """ with open(filepath, "rb") as f: python_obj = pickle.load(f) return python_obj
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from aiida.orm import Dict from aiida_quantumespresso.utils.resources import get_default_options def generate_inputs_pw(fixture_code, generate_structure, generate_kpoints_mesh, generate_upf_data): """Generate default inputs for a `PwCalculation.""" def _generate_inputs_pw(): """Generate default input...
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def connected_components(edge_index, num_nodes=None): """Find the connected components of a given graph. Args: edge_index (LongTensor): Edge coordinate matrix. num_nodes (int, optional): Number of nodes. Defaults to None. Returns: LongTensor: Vector assigning each node to i...
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import tqdm def assembly2graph(path=DATA_PATH): """Convert assemblies (assembly.json) to graph format""" """Return a list of NetworkX graphs""" graphs = [] input_files = get_input_files(path) for input_file in tqdm(input_files, desc="Generating Graphs"): ag = AssemblyGraph(input_file) ...
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def _get_default_backing(backing): """ _get_default_backing(backing) Returns the prefered backing store - if user provides a valid Backing object, use it - if there is a default_backing object instantiated, use it - if the user provided a configuration dict, use it to create a new de...
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def slice(request, response, start, end=None): """Send a byte range of the response body :param start: The starting offset. Follows python semantics including negative numbers. :param end: The ending offset, again with python semantics and None (spelled "null" in a query ...
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import warnings def get_ps(sdfits, scan, ifnum=0, intnum=None, plnum=0, fdnum=0, method='vector', avgf_min=256): """ Parameters ---------- sdfits : scan : int Scan number. plnum : int Polarization number. method : {'vector', 'classic'}, optional Method...
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import click def choiceprompt(variable: Variable) -> Binding: """Prompt to choose from several values for the given name.""" if not variable.choices: raise ValueError("variable with empty choices") choices = {str(number): value for number, value in enumerate(variable.choices, 1)} lines = [ ...
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import urllib import certifi import urllib3 import http import logging def GetCLInfo(review_host, change_id, auth_cookie='', include_messages=False, include_detailed_accounts=False): """Get the info of the specified CL by querying the Gerrit API. Args: review_host: Base URL to the API endpoint....
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import base64 import hashlib def rehash(file_path): """Return (hash, size) for a file with path file_path. The hash and size are used by pip to verify the integrity of the contents of a wheel.""" with open(file_path, 'rb') as file: contents = file.read() hash = base64.urlsafe_b64encode(has...
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import requests def _magpie_update_services_conflict(conflict_services, services_dict, request_cookies): # type: (List[Str], ServicesSettings, AnyCookiesType) -> Dict[Str, int] """ Resolve conflicting services by name during registration by updating them only if pointing to different URL. """ magp...
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def rtc_runner(rtc): """Resolved tool contract runner.""" return run_main(polish_chunks_pickle_file=rtc.task.input_files[0], sentinel_file=rtc.task.input_files[1], subreads_file=rtc.task.input_files[2], output_json_file=rtc.task.output_files[0], ...
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from typing import Any import json def dict_to_json_str(o: Any) -> str: """ Converts a python object into json. """ json_str = json.dumps(o, cls=EnhancedJSONEncoder, sort_keys=True) return json_str
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def paramid_to_paramname(paramid): """Turn a parameter id number into a parameter name""" try: return param_info[paramid]['n'] except KeyError: return "UNKNOWN_%s" % str(hex(paramid))
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def max_dist_comp(G, cc0, cc1): """ Maximum distance between components Parameters ---------- G : nx.graph Graph cc0 : list Component 0 cc1 : list Compoennt 1 Returns ------- threshold : float Maximum distance """ # Ass...
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def convert_examples_to_features( examples, label_list, max_seq_length, tokenizer, cls_token_at_end=False, cls_token="[CLS]", cls_token_segment_id=1, sep_token="[SEP]", sep_token_extra=False, pad_on_left=False, pad_token=0, pad_token_segment_id=0, pad_token_label_id=-...
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def exp(var): """ Returns variable representing exp applied to the input variable var """ result = Var(np.exp(var.val)) result.parents[var] = var.children[result] = np.exp(var.val) return result
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from typing import List from typing import Any from typing import Callable def invalidate_cache( key: str = None, keys: List = [], obj: Any = None, obj_attr: str = None, namespace: str = None, ): """Invalidates a specific cache key""" if not namespace: namespace = HTTPCache.namespa...
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def read_dataset(filename): """Reads in the TD events contained in the N-MNIST/N-CALTECH101 dataset file specified by 'filename'""" # NMIST: 34×34 pixels big f = open(filename, 'rb') raw_data = np.fromfile(f, dtype=np.uint8) f.close() raw_data = np.uint32(raw_data) all_y = raw_data[1::5] ...
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def prge_annotation(): """Returns an annotation with protein/gene entities (PRGE) identified. """ annotation = {"ents": [{"text": "p53", "label": "PRGE", "start": 0, "end": 0}, {"text": "MK2", "label": "PRGE", "start": 0, "end": 0}], "text": "p53 and MK2", ...
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from scipy.spatial import Delaunay def inner_points_mask(points): """Mask array into `points` where ``points[msk]`` are all "inner" points, i.e. `points` with one level of edge points removed. For 1D, this is simply points[1:-1,:] (assuming ordered points). For ND, we calculate and remove the convex h...
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from typing import Union import torch from typing import Tuple from typing import List def array2list(X_train: Union[np.ndarray, torch.Tensor], y_train: Union[np.ndarray, torch.Tensor], X_test: Union[np.ndarray, torch.Tensor], y_test: Union[np.ndarray, torch.Tensor], ...
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def livecoding_redirect_view(request): """ livecoding oath2 fetch access token after permission dialog """ code = request.GET.get('code') if code is None: return HttpResponse("code param is empty/not found") try: url = "https://www.livecoding.tv/o/token/" data = dict(cod...
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from typing import OrderedDict def sort_dict(value): """Sort a dictionary.""" return OrderedDict((key, value[key]) for key in sorted(value))
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def hyb_stor_capacity_rule(mod, prj, prd): """ Power capacity of a hybrid project's storage component. """ return 0
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def gilr_layer_cpu(X, hidden_size, nonlin=tf.nn.elu, name='gilr'): """ g_t = sigmoid(Ux_t + b) h_t = g_t h_{t-1} + (1-g_t) f(Vx_t + c) """ with vscope(name): n_dims = X.get_shape()[-1].value act = fc_layer(X, 2 * hidden_size, nonlin=tf.identity) gate, impulse =...
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from typing import Callable from typing import Awaitable from re import A from typing import Tuple import asyncio async def retry(f: Callable[..., Awaitable[A]], schedule: Schedule[Exception, Tuple[OpinionT, float]]): """ Run an awaitable computation, retrying on failures according to a schedule. """...
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import torch import os def dual_solve_u(v, s, alpha, eps, verbose=False, n_iters=100, gtol=0): """ min_{u>=0} max_pi L(pi, u, v) = E_xy [ u(x)alpha(x) + v(y)beta(y) + Softplus(1/eps)(s-u-v) ], where u = min{u>=0 : E_y[pi(x,y)] <= alpha(x)} find exact u s.t. E_y[pi(x,y)] == alpha(x) ...
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import urllib import json def activation(formula=None, instrument=None, flux=None, cdratio=0, fastratio=0, mass=None, exposure=24, getdata=False): """Calculate sample activation using the FRM II activation web services. ``formula``: the chemical formula, see belo...
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def wrap_parfor_blocks(parfor, entry_label = None): """wrap parfor blocks for analysis/optimization like CFG""" blocks = parfor.loop_body.copy() # shallow copy is enough if entry_label == None: entry_label = min(blocks.keys()) assert entry_label > 0 # we are using 0 for init block here # ...
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from typing import Counter def frequency_of_occurrence(words, specific_words=None): """ Returns a list of (instance, count) sorted in total order and then from most to least common Along with the count/frequency of each of those words as a tuple If specific_words list is present then SUM of frequencie...
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from typing import Union def cache_remove_all( connection: 'Connection', cache: Union[str, int], binary=False, query_id=None, ) -> 'APIResult': """ Removes all entries from cache, notifying listeners and cache writers. :param connection: connection to Ignite server, :param cache: name or ID o...
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import json from typing import OrderedDict import os import re def transform_bundle(bundle_uuid, bundle_version, bundle_path, bundle_manifest_path, extractor=None): """ This function is used with the ETL interface in dcplib.etl.DSSExtractor.extract. Given a bundle ID and directory containing its medatata ...
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from typing import List def choices_function() -> List[str]: """Choices functions are useful when the choice list is dynamically generated (e.g. from data in a database)""" return ['a', 'dynamic', 'list', 'goes', 'here']
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def GetInfraPythonPath(hermetic=True, master_dir=None): """Returns (PythonPath): The full working Chrome Infra utility path. This path is consistent for master, slave, and tool usage. It includes (in this order): - Any environment PYTHONPATH overrides. - If 'master_dir' is supplied, the master's python p...
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import uuid def nodeid(): """nodeid() -> UUID Generate a new node id >>> nodeid() UUID('...') :returns: node id :rtype: :class:`uuid.UUID` """ return uuid.uuid4()
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def drop_redundant_cols(movies_df): """ Drop the following redundant columns: 1. `release_data_wiki` - after dropping the outlier 2. `revenue` - after using it to fill `box_office` missing values 3. `budget_kaggle` - after using it to fill `budget_wiki` missing values 4. `duration` - after usin...
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import pickle import gzip import collections import re import fnmatch def get_msids_for_add_msids(opt, logger): """ Parse MSIDs spec file (opt.add_msids) and return corresponding list of MSIDs. This implements support for a MSID spec file like:: # MSIDs that match the name or pattern are include...
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def gaussian_similarity(stimulus_representation, i, j, w, c, r): """ Function that calculates and returns the gaussian similarity of stimuli i and j (equation 4b in [Noso86]_) Parameters ---------- stimulus_representation : np.array The stimuli are given to this function in the form of a n ...
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def windShearVector(u, v, top, bottom, unit=None): """ calculate the u and v layer difference and return as vector """ udiff = layerDiff(u, top, bottom, unit) vdiff = layerDiff(v, top, bottom, unit) return makeVector(udiff, vdiff)
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def withdraw_entry(contest): """Withdraws a submitted entry from the contest. After this step the submitted entry will be seen as a draft. """ return _update_sketch(contest, code=None, action="withdraw")
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def _conditional_field(if_, condition, colon, comment, eol, indent, body, dedent): """Formats an `if` construct.""" del indent, dedent # Unused # The body of an 'if' should be columnized with the surrounding blocks, so # much like an inline 'bits', its body is treated as an inline list o...
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def check_sum_cases(nation='England'): """check total data""" ck=LocalLatest() fail=False data=ck.data.get('data') latest={} data=clean_cases(data) #repair glitches #check latest data matches stored data for nation for i in data: _code=i['areaCode'] latest[_code...
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def get_module_name() -> str: """Gets the name of the module that called a function Is meant to be used within a function. :returns: The name of the module that called your function """ return getmodulename(stack()[2][1])
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def hand_points(work_hand): """returns the point value of a given hand""" debug_level = 1 work_points = 0 for card in work_hand: work_points += card_point_value(card) return work_points
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def elements_counter(arr, count=0): """递归计算列表包含的元素数 Arguments: arr {[list]} -- [列表] Keyword Arguments: count {int} -- [列表包含的元素数] (default: {0}) Returns: [int] -- [列表包含的元素数] """ if len(arr): arr.pop(0) count += 1 return elements_counter(arr, coun...
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