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{ "docstring": "\n Roll an array of matrices along *axis* (0: rows, 1: columns) according to\n an array of indices *roll_indices*.\n ", "language": "en", "n_whitespaces": 28, "n_words": 18, "vocab_size": 15 }

{ "docstring": "Ensure pdf and png figures can be saved via visualization API call.\n\n :param experiment_to_use: Object containing trained model and results to\n test visualization\n :return: None\n ", "language": "en", "n_whitespaces": 41, "n_words": 25, "vocab_size": 23 }

{ "docstring": "\n Tests that the user get server notice in a new room\n after the first server notice room was deleted.\n ", "language": "en", "n_whitespaces": 41, "n_words": 19, "vocab_size": 15 }

{ "docstring": "\n Whether the requests to Metaseq worker have failed.\n\n It checks this based on the existences of the failure reasons as they get\n accumulated in `_make_request` functionn calls.\n ", "language": "en", "n_whitespaces": 56, "n_words": 27, "vocab_size": 25 }

{ "docstring": "\n Draw the arc to the given *renderer*.\n\n Notes\n -----\n Ellipses are normally drawn using an approximation that uses\n eight cubic Bezier splines. The error of this approximation\n is 1.89818e-6, according to this unverified source:\n\n Lancaster, Don. *Approximating a Circle or an Ellipse Using\n Four Bezier Cubic Splines.*\n\n https://www.tinaja.com/glib/ellipse4.pdf\n\n There is a use case where very large ellipses must be drawn\n with very high accuracy, and it is too expensive to render the\n entire ellipse with enough segments (either splines or line\n segments). Therefore, in the case where either radius of the\n ellipse is large enough that the error of the spline\n approximation will be visible (greater than one pixel offset\n from the ideal), a different technique is used.\n\n In that case, only the visible parts of the ellipse are drawn,\n with each visible arc using a fixed number of spline segments\n (8). The algorithm proceeds as follows:\n\n 1. The points where the ellipse intersects the axes (or figure)\n bounding box are located. (This is done by performing an inverse\n transformation on the bbox such that it is relative to the unit\n circle -- this makes the intersection calculation much easier than\n doing rotated ellipse intersection directly.)\n\n This uses the \"line intersecting a circle\" algorithm from:\n\n Vince, John. *Geometry for Computer Graphics: Formulae,\n Examples & Proofs.* London: Springer-Verlag, 2005.\n\n 2. The angles of each of the intersection points are calculated.\n\n 3. Proceeding counterclockwise starting in the positive\n x-direction, each of the visible arc-segments between the\n pairs of vertices are drawn using the Bezier arc\n approximation technique implemented in `.Path.arc`.\n ", "language": "en", "n_whitespaces": 541, "n_words": 258, "vocab_size": 160 }

{ "docstring": "Validate types and values of given parameters.\n\n Parameters\n ----------\n parameter_constraints : dict or {\"no_validation\"}\n If \"no_validation\", validation is skipped for this parameter.\n\n If a dict, it must be a dictionary `param_name: list of constraints`.\n A parameter is valid if it satisfies one of the constraints from the list.\n Constraints can be:\n - an Interval object, representing a continuous or discrete range of numbers\n - the string \"array-like\"\n - the string \"sparse matrix\"\n - the string \"random_state\"\n - callable\n - None, meaning that None is a valid value for the parameter\n - any type, meaning that any instance of this type is valid\n - an Options object, representing a set of elements of a given type\n - a StrOptions object, representing a set of strings\n - the string \"boolean\"\n - the string \"verbose\"\n - the string \"cv_object\"\n - the string \"missing_values\"\n - a HasMethods object, representing method(s) an object must have\n - a Hidden object, representing a constraint not meant to be exposed to the user\n\n params : dict\n A dictionary `param_name: param_value`. The parameters to validate against the\n constraints.\n\n caller_name : str\n The name of the estimator or function or method that called this function.\n ", "language": "en", "n_whitespaces": 367, "n_words": 195, "vocab_size": 103 }

{ "docstring": "\n Determine the module/package collection mode for the given module name , based on the provided collection\n mode settings dictionary.\n ", "language": "en", "n_whitespaces": 29, "n_words": 19, "vocab_size": 15 }

{ "docstring": "Computes exact Gaussian kernel value(s) for tensors x and y and stddev.\n\n The Gaussian kernel for vectors u, v is defined as follows:\n K(u, v) = exp(-||u-v||^2 / (2* stddev^2))\n where the norm is the l2-norm. x, y can be either vectors or matrices. If they\n are vectors, they must have the same dimension. If they are matrices, they\n must have the same number of columns. In the latter case, the method returns\n (as a matrix) K(u, v) values for all pairs (u, v) where u is a row from x and\n v is a row from y.\n\n Args:\n x: a tensor of rank 1 or 2. It's shape should be either [dim] or [m, dim].\n y: a tensor of rank 1 or 2. It's shape should be either [dim] or [n, dim].\n stddev: The width of the Gaussian kernel.\n\n Returns:\n A single value (scalar) with shape (1, 1) (if x, y are vectors) or a matrix\n of shape (m, n) with entries K(u, v) (where K is the Gaussian kernel) for\n all (u,v) pairs where u, v are rows from x and y respectively.\n\n Raises:\n ValueError: if the shapes of x, y are not compatible.\n ", "language": "en", "n_whitespaces": 273, "n_words": 196, "vocab_size": 107 }

{ "docstring": "\n Create a JobResult instance and enqueue a job using the given callable\n\n func: The callable object to be enqueued for execution\n name: Name for the JobResult instance\n obj_type: ContentType to link to the JobResult instance obj_type\n user: User object to link to the JobResult instance\n schedule_at: Schedule the job to be executed at the passed date and time\n args: additional args passed to the callable\n kwargs: additional kargs passed to the callable\n ", "language": "en", "n_whitespaces": 136, "n_words": 72, "vocab_size": 39 }

{ "docstring": "Get the text style object.\n\n A widget's style is influenced by its parent. For instance if a widgets background has an alpha,\n then its parent's background color will show through. Additionally, widgets will inherit their\n parent's text style (i.e. bold, italic etc).\n\n Returns:\n Style: Rich Style object.\n ", "language": "en", "n_whitespaces": 93, "n_words": 47, "vocab_size": 38 }

{ "docstring": "\n Return a sorted list of all the installed apps that have been\n registered in this site.\n ", "language": "en", "n_whitespaces": 38, "n_words": 16, "vocab_size": 16 }

{ "docstring": "Search the specified list of directories for a static or shared\n library file 'lib' and return the full path to that file. If\n 'debug' true, look for a debugging version (if that makes sense on\n the current platform). Return None if 'lib' wasn't found in any of\n the specified directories.\n ", "language": "en", "n_whitespaces": 87, "n_words": 50, "vocab_size": 41 }

{ "docstring": "Test that we can take out a lock and that while we hold it nobody\n else can take it out.\n ", "language": "en", "n_whitespaces": 34, "n_words": 20, "vocab_size": 15 }

{ "docstring": "\n Change the font family. May be either an alias (generic name\n is CSS parlance), such as: 'serif', 'sans-serif', 'cursive',\n 'fantasy', or 'monospace', a real font name or a list of real\n font names. Real font names are not supported when\n :rc:`text.usetex` is `True`. Default: :rc:`font.family`\n ", "language": "en", "n_whitespaces": 90, "n_words": 45, "vocab_size": 37 }

{ "docstring": "\n calculate biased stat and unbiased stat in each step using exponential moving average method\n\n Parameters\n ----------\n biased_ema : float\n previous stat value\n value : float\n current stat value\n decay : float\n the weight of previous stat value, larger means smoother curve\n\n Returns\n -------\n float, float\n ", "language": "en", "n_whitespaces": 97, "n_words": 45, "vocab_size": 33 }

{ "docstring": "\n Calculate the partition function P(n), i.e. the number of ways that\n n can be written as a sum of positive integers.\n\n P(n) is computed using the Hardy-Ramanujan-Rademacher formula [1]_.\n\n\n The correctness of this implementation has been tested through $10^10$.\n\n Examples\n ========\n\n >>> from sympy.ntheory import npartitions\n >>> npartitions(25)\n 1958\n\n References\n ==========\n\n .. [1] http://mathworld.wolfram.com/PartitionFunctionP.html\n\n ", "language": "en", "n_whitespaces": 94, "n_words": 54, "vocab_size": 49 }

{ "docstring": "\n Build and return the command to put the container to sleep.\n\n The sleep duration below was selected to:\n\n - Allow enough time to perform necessary operations in the container before waking it.\n - Make the delay obvious if the wake command doesn't run or succeed.\n - Avoid hanging indefinitely or for an unreasonably long time.\n\n NOTE: The container must have a POSIX-compliant default shell \"sh\" with a non-builtin \"sleep\" command.\n ", "language": "en", "n_whitespaces": 126, "n_words": 70, "vocab_size": 56 }

{ "docstring": "Expect some sub-envs to fail (and not recover), but ignore.", "language": "en", "n_whitespaces": 9, "n_words": 10, "vocab_size": 10 }

{ "docstring": "Test three levels and dropping the infrequent category.", "language": "en", "n_whitespaces": 7, "n_words": 8, "vocab_size": 8 }

{ "docstring": "Returns True if the model should not be in the main init.", "language": "en", "n_whitespaces": 11, "n_words": 12, "vocab_size": 11 }

{ "docstring": "Test midnight turnover setting before midnight outside period.", "language": "en", "n_whitespaces": 7, "n_words": 8, "vocab_size": 7 }

{ "docstring": "Raise an error if this BlockList has been previously cleared.", "language": "en", "n_whitespaces": 9, "n_words": 10, "vocab_size": 10 }

{ "docstring": "Tests that rooms are correctly excluded from the 'join' and 'leave' sections of\n sync responses.\n ", "language": "en", "n_whitespaces": 29, "n_words": 15, "vocab_size": 15 }

{ "docstring": "\n A custom field has been added to the inspect view's `inspect_view_fields` and since\n this field has a `short_description` we expect it to be used as the field's label,\n and not use the name of the function.\n ", "language": "en", "n_whitespaces": 65, "n_words": 36, "vocab_size": 29 }

{ "docstring": "\n\t\t\tselect * from tabBin where item_code = %s\n\t\t\t\tand (reserved_qty > 0 or ordered_qty > 0 or indented_qty > 0 or planned_qty > 0)\n\t\t\t\tand stock_uom != %s\n\t\t\tupdate tabBin set stock_uom=%s where item_code=%s", "language": "en", "n_whitespaces": 30, "n_words": 34, "vocab_size": 23 }

{ "docstring": "\n UPDATE sentry_groupedmessage SET num_comments = (\n SELECT COUNT(*) from sentry_activity\n WHERE type = %s and group_id = sentry_groupedmessage.id\n )\n ", "language": "en", "n_whitespaces": 59, "n_words": 19, "vocab_size": 17 }

{ "docstring": "\n Returns an eventstore filter given the search text provided by the user and\n URL params\n ", "language": "en", "n_whitespaces": 25, "n_words": 15, "vocab_size": 14 }

{ "docstring": "\n Reset the UniversalDetector and all of its probers back to their\n initial states. This is called by ``__init__``, so you only need to\n call this directly in between analyses of different documents.\n ", "language": "en", "n_whitespaces": 62, "n_words": 32, "vocab_size": 30 }

{ "docstring": "\n GIVEN:\n - Various Redis connection URI formats\n WHEN:\n - The URI is parsed\n THEN:\n - Socket based URIs are translated\n - Non-socket URIs are unchanged\n - None provided uses default\n ", "language": "en", "n_whitespaces": 114, "n_words": 30, "vocab_size": 23 }

{ "docstring": "\n The URL's path components as a tuple of strings.\n Components are unquoted.\n ", "language": "en", "n_whitespaces": 34, "n_words": 12, "vocab_size": 12 }

{ "docstring": "Generator to create slices containing `batch_size` elements from 0 to `n`.\n\n The last slice may contain less than `batch_size` elements, when\n `batch_size` does not divide `n`.\n\n Parameters\n ----------\n n : int\n Size of the sequence.\n batch_size : int\n Number of elements in each batch.\n min_batch_size : int, default=0\n Minimum number of elements in each batch.\n\n Yields\n ------\n slice of `batch_size` elements\n\n See Also\n --------\n gen_even_slices: Generator to create n_packs slices going up to n.\n\n Examples\n --------\n >>> from sklearn.utils import gen_batches\n >>> list(gen_batches(7, 3))\n [slice(0, 3, None), slice(3, 6, None), slice(6, 7, None)]\n >>> list(gen_batches(6, 3))\n [slice(0, 3, None), slice(3, 6, None)]\n >>> list(gen_batches(2, 3))\n [slice(0, 2, None)]\n >>> list(gen_batches(7, 3, min_batch_size=0))\n [slice(0, 3, None), slice(3, 6, None), slice(6, 7, None)]\n >>> list(gen_batches(7, 3, min_batch_size=2))\n [slice(0, 3, None), slice(3, 7, None)]\n ", "language": "en", "n_whitespaces": 233, "n_words": 131, "vocab_size": 71 }

{ "docstring": "Tests condinst maskhead loss when truth is empty and non-empty.", "language": "en", "n_whitespaces": 9, "n_words": 10, "vocab_size": 10 }

{ "docstring": "Assert that ContinuousSelector works as expected with threshold=5.", "language": "en", "n_whitespaces": 7, "n_words": 8, "vocab_size": 8 }

{ "docstring": "Test add view restricts access and actually adds items.", "language": "en", "n_whitespaces": 8, "n_words": 9, "vocab_size": 9 }

{ "docstring": "Install a collection under a given path.\n\n :param collection: Collection to be installed.\n :param path: Collection dirs layout path.\n :param artifacts_manager: Artifacts manager.\n ", "language": "en", "n_whitespaces": 35, "n_words": 23, "vocab_size": 18 }

{ "docstring": "Bring up an editor and execute the resulting code.\n\n Usage:\n %edit [options] [args]\n\n %edit runs IPython's editor hook. The default version of this hook is\n set to call the editor specified by your $EDITOR environment variable.\n If this isn't found, it will default to vi under Linux/Unix and to\n notepad under Windows. See the end of this docstring for how to change\n the editor hook.\n\n You can also set the value of this editor via the\n ``TerminalInteractiveShell.editor`` option in your configuration file.\n This is useful if you wish to use a different editor from your typical\n default with IPython (and for Windows users who typically don't set\n environment variables).\n\n This command allows you to conveniently edit multi-line code right in\n your IPython session.\n\n If called without arguments, %edit opens up an empty editor with a\n temporary file and will execute the contents of this file when you\n close it (don't forget to save it!).\n\n\n Options:\n\n -n <number>: open the editor at a specified line number. By default,\n the IPython editor hook uses the unix syntax 'editor +N filename', but\n you can configure this by providing your own modified hook if your\n favorite editor supports line-number specifications with a different\n syntax.\n\n -p: this will call the editor with the same data as the previous time\n it was used, regardless of how long ago (in your current session) it\n was.\n\n -r: use 'raw' input. This option only applies to input taken from the\n user's history. By default, the 'processed' history is used, so that\n magics are loaded in their transformed version to valid Python. If\n this option is given, the raw input as typed as the command line is\n used instead. When you exit the editor, it will be executed by\n IPython's own processor.\n\n -x: do not execute the edited code immediately upon exit. This is\n mainly useful if you are editing programs which need to be called with\n command line arguments, which you can then do using %run.\n\n\n Arguments:\n\n If arguments are given, the following possibilities exist:\n\n - If the argument is a filename, IPython will load that into the\n editor. It will execute its contents with execfile() when you exit,\n loading any code in the file into your interactive namespace.\n\n - The arguments are ranges of input history, e.g. \"7 ~1/4-6\".\n The syntax is the same as in the %history magic.\n\n - If the argument is a string variable, its contents are loaded\n into the editor. You can thus edit any string which contains\n python code (including the result of previous edits).\n\n - If the argument is the name of an object (other than a string),\n IPython will try to locate the file where it was defined and open the\n editor at the point where it is defined. You can use `%edit function`\n to load an editor exactly at the point where 'function' is defined,\n edit it and have the file be executed automatically.\n\n - If the object is a macro (see %macro for details), this opens up your\n specified editor with a temporary file containing the macro's data.\n Upon exit, the macro is reloaded with the contents of the file.\n\n Note: opening at an exact line is only supported under Unix, and some\n editors (like kedit and gedit up to Gnome 2.8) do not understand the\n '+NUMBER' parameter necessary for this feature. Good editors like\n (X)Emacs, vi, jed, pico and joe all do.\n\n After executing your code, %edit will return as output the code you\n typed in the editor (except when it was an existing file). This way\n you can reload the code in further invocations of %edit as a variable,\n via _<NUMBER> or Out[<NUMBER>], where <NUMBER> is the prompt number of\n the output.\n\n Note that %edit is also available through the alias %ed.\n\n This is an example of creating a simple function inside the editor and\n then modifying it. First, start up the editor::\n\n In [1]: edit\n Editing... done. Executing edited code...\n Out[1]: 'def foo():\\\\n print \"foo() was defined in an editing\n session\"\\\\n'\n\n We can then call the function foo()::\n\n In [2]: foo()\n foo() was defined in an editing session\n\n Now we edit foo. IPython automatically loads the editor with the\n (temporary) file where foo() was previously defined::\n\n In [3]: edit foo\n Editing... done. Executing edited code...\n\n And if we call foo() again we get the modified version::\n\n In [4]: foo()\n foo() has now been changed!\n\n Here is an example of how to edit a code snippet successive\n times. First we call the editor::\n\n In [5]: edit\n Editing... done. Executing edited code...\n hello\n Out[5]: \"print 'hello'\\\\n\"\n\n Now we call it again with the previous output (stored in _)::\n\n In [6]: edit _\n Editing... done. Executing edited code...\n hello world\n Out[6]: \"print 'hello world'\\\\n\"\n\n Now we call it with the output #8 (stored in _8, also as Out[8])::\n\n In [7]: edit _8\n Editing... done. Executing edited code...\n hello again\n Out[7]: \"print 'hello again'\\\\n\"\n\n\n Changing the default editor hook:\n\n If you wish to write your own editor hook, you can put it in a\n configuration file which you load at startup time. The default hook\n is defined in the IPython.core.hooks module, and you can use that as a\n starting example for further modifications. That file also has\n general instructions on how to set a new hook for use once you've\n defined it.", "language": "en", "n_whitespaces": 1675, "n_words": 882, "vocab_size": 385 }

{ "docstring": "Get the number of cells required to render this object.", "language": "en", "n_whitespaces": 9, "n_words": 10, "vocab_size": 10 }

{ "docstring": "Show the same message twice -> only one should be shown.", "language": "en", "n_whitespaces": 10, "n_words": 11, "vocab_size": 11 }

{ "docstring": "\n Create all default plugins for the given ``placeholders`` if they have\n a \"default_plugins\" configuration value in settings.\n return all plugins, children, grandchildren (etc.) created\n ", "language": "en", "n_whitespaces": 37, "n_words": 24, "vocab_size": 23 }

{ "docstring": "Parse the JP2 header box to extract size, component count,\n color space information, and optionally DPI information,\n returning a (size, mode, mimetype, dpi) tuple.", "language": "en", "n_whitespaces": 29, "n_words": 24, "vocab_size": 23 }

{ "docstring": "Ensure that there are test events in the database.\n\n When testing with the in-memory SQLite database, all the events are lost during\n the simulated outage.\n\n To ensure consistency between `room_id`s and `event_id`s before and after the\n outage, rows are built and inserted manually.\n\n Upserts are used to handle the non-SQLite case where events are not lost.\n ", "language": "en", "n_whitespaces": 98, "n_words": 56, "vocab_size": 43 }

{ "docstring": "\n Check if the context is empty. If it is, we don't want to send an email.\n ", "language": "en", "n_whitespaces": 23, "n_words": 16, "vocab_size": 16 }

{ "docstring": "Delete all occurrences of a header, if present.\n\n Does not raise an exception if the header is missing.\n ", "language": "en", "n_whitespaces": 32, "n_words": 18, "vocab_size": 17 }

{ "docstring": "Update placement group status.\n\n Moves ready placement groups from `self._staging` to\n `self._ready`.\n ", "language": "en", "n_whitespaces": 33, "n_words": 12, "vocab_size": 11 }

{ "docstring": "\n\t\t\tselect name, serial_no\n\t\t\tfrom `tabStock Ledger Entry`\n\t\t\twhere\n\t\t\t\tis_cancelled = 0\n\t\t\t\tand (serial_no like %s or serial_no like %s or serial_no like %s or serial_no like %s)\n\t\t\t\n\t\t\t\t\t\t\tselect name\n\t\t\t\t\t\t\tfrom `tabSerial No`\n\t\t\t\t\t\t\twhere status='Active'\n\t\t\t\t\t\t\t\tand coalesce(purchase_document_type, '') = ''\n\t\t\t\t\t\t\t\tand name in %s ", "language": "en", "n_whitespaces": 34, "n_words": 43, "vocab_size": 25 }

{ "docstring": "\n Individual cache factors will be loaded from the environment.\n ", "language": "en", "n_whitespaces": 24, "n_words": 9, "vocab_size": 9 }

{ "docstring": "\n When ``is_delete_operator_pod=False``, pod should have 'already_checked'\n label, whether pod is successful or not.\n ", "language": "en", "n_whitespaces": 35, "n_words": 13, "vocab_size": 12 }

{ "docstring": "select parent, cost_center, warehouse\n\t\tfrom `tabSales Invoice Item` where parent in (%s)\n\t\tand (ifnull(cost_center, '') != '' or ifnull(warehouse, '') != '')", "language": "en", "n_whitespaces": 19, "n_words": 22, "vocab_size": 19 }

{ "docstring": "\n Parses table column names and types from specified SQLite table schema\n\n >>> kb.data.cachedColumns = {}\n >>> parseSqliteTableSchema(\"CREATE TABLE users(\\\\n\\\\t\\\\tid INTEGER,\\\\n\\\\t\\\\tname TEXT\\\\n);\")\n True\n >>> tuple(kb.data.cachedColumns[conf.db][conf.tbl].items()) == (('id', 'INTEGER'), ('name', 'TEXT'))\n True\n >>> parseSqliteTableSchema(\"CREATE TABLE dummy(`foo bar` BIGINT, \\\\\"foo\\\\\" VARCHAR, 'bar' TEXT)\");\n True\n >>> tuple(kb.data.cachedColumns[conf.db][conf.tbl].items()) == (('foo bar', 'BIGINT'), ('foo', 'VARCHAR'), ('bar', 'TEXT'))\n True\n >>> parseSqliteTableSchema(\"CREATE TABLE suppliers(\\\\n\\\\tsupplier_id INTEGER PRIMARY KEY DESC,\\\\n\\\\tname TEXT NOT NULL\\\\n);\");\n True\n >>> tuple(kb.data.cachedColumns[conf.db][conf.tbl].items()) == (('supplier_id', 'INTEGER'), ('name', 'TEXT'))\n True\n >>> parseSqliteTableSchema(\"CREATE TABLE country_languages (\\\\n\\\\tcountry_id INTEGER NOT NULL,\\\\n\\\\tlanguage_id INTEGER NOT NULL,\\\\n\\\\tPRIMARY KEY (country_id, language_id),\\\\n\\\\tFOREIGN KEY (country_id) REFERENCES countries (country_id) ON DELETE CASCADE ON UPDATE NO ACTION,\\\\tFOREIGN KEY (language_id) REFERENCES languages (language_id) ON DELETE CASCADE ON UPDATE NO ACTION);\");\n True\n >>> tuple(kb.data.cachedColumns[conf.db][conf.tbl].items()) == (('country_id', 'INTEGER'), ('language_id', 'INTEGER'))\n True\n ", "language": "en", "n_whitespaces": 177, "n_words": 119, "vocab_size": 69 }

{ "docstring": " phrase = 1*word / obs-phrase\n obs-phrase = word *(word / \".\" / CFWS)\n\n This means a phrase can be a sequence of words, periods, and CFWS in any\n order as long as it starts with at least one word. If anything other than\n words is detected, an ObsoleteHeaderDefect is added to the token's defect\n list. We also accept a phrase that starts with CFWS followed by a dot;\n this is registered as an InvalidHeaderDefect, since it is not supported by\n even the obsolete grammar.\n\n ", "language": "en", "n_whitespaces": 115, "n_words": 84, "vocab_size": 63 }

{ "docstring": "Test media states are read from group if entity has no state.", "language": "en", "n_whitespaces": 11, "n_words": 12, "vocab_size": 12 }

{ "docstring": "The serialized value of a PageChooserBlock (an ID) should deserialize to a Page object", "language": "en", "n_whitespaces": 13, "n_words": 14, "vocab_size": 13 }

{ "docstring": "Check if the current device is explicitly set on the device type specified.\n\n Args:\n device_type: A string containing `GPU` or `CPU` (case-insensitive).\n\n Returns:\n A boolean indicating if the current device scope is explicitly set on the\n device type.\n\n Raises:\n ValueError: If the `device_type` string indicates an unsupported device.\n ", "language": "en", "n_whitespaces": 88, "n_words": 48, "vocab_size": 33 }

{ "docstring": " Return native stringified values from datastructures.\n\n For use with removing sensitive values pre-jsonification.", "language": "en", "n_whitespaces": 16, "n_words": 13, "vocab_size": 12 }

{ "docstring": "\n Iterate over the messages in the message stream\n ", "language": "en", "n_whitespaces": 23, "n_words": 8, "vocab_size": 7 }

{ "docstring": "Return the `.GridSpec` associated with the subplot, or None.", "language": "en", "n_whitespaces": 8, "n_words": 9, "vocab_size": 8 }

{ "docstring": "\n ESNet_x0_5\n Args:\n pretrained: bool=False or str. If `True` load pretrained parameters, `False` otherwise.\n If str, means the path of the pretrained model.\n use_ssld: bool=False. Whether using distillation pretrained model when pretrained=True.\n Returns:\n model: nn.Layer. Specific `ESNet_x0_5` model depends on args.\n ", "language": "en", "n_whitespaces": 93, "n_words": 40, "vocab_size": 35 }

{ "docstring": "\n Decorator marking a test that requires rjieba. These tests are skipped when rjieba isn't installed.\n ", "language": "en", "n_whitespaces": 22, "n_words": 15, "vocab_size": 15 }

{ "docstring": "\n [*Discouraged*] Return the YAxis instance.\n\n .. admonition:: Discouraged\n\n The use of this function is discouraged. You should instead\n directly access the attribute ``ax.yaxis``.\n ", "language": "en", "n_whitespaces": 67, "n_words": 23, "vocab_size": 22 }

{ "docstring": "Disable the `tf.random.Generator` as the RNG for Keras.\n\n See `tf.keras.backend.experimental.is_tf_random_generator_enabled` for more\n details.\n ", "language": "en", "n_whitespaces": 22, "n_words": 13, "vocab_size": 11 }

{ "docstring": "dt,val\n 2018-01-04 09:01:00+09:00,23350\n 2018-01-04 09:02:00+09:00,23400\n 2018-01-04 09:03:00+09:00,23400\n 2018-01-04 09:04:00+09:00,23400\n 2018-01-04 09:05:00+09:00,23400", "language": "en", "n_whitespaces": 75, "n_words": 11, "vocab_size": 7 }

{ "docstring": "*Deprecated:* An outdated alias for Connection.alpn.", "language": "en", "n_whitespaces": 5, "n_words": 6, "vocab_size": 6 }

{ "docstring": "Define this cover as either awning, blind, garage, gate, shutter or window.", "language": "en", "n_whitespaces": 11, "n_words": 12, "vocab_size": 12 }

{ "docstring": "Get country yield curve [Source: Investing.com]\n\n Returns\n -------\n pd.DataFrame\n Country yield curve\n ", "language": "en", "n_whitespaces": 31, "n_words": 12, "vocab_size": 10 }

{ "docstring": "Test PercentageController, PowerLevelController reports humidifier humidity correctly.", "language": "en", "n_whitespaces": 6, "n_words": 7, "vocab_size": 7 }

{ "docstring": "\n Prepare a value for storage as JSON data.\n ", "language": "en", "n_whitespaces": 23, "n_words": 8, "vocab_size": 8 }

{ "docstring": " Revert the frame's alignments to their saved version for the given frame index.\n\n Parameters\n ----------\n frame_index: int\n The frame that should have their faces reverted to their saved version\n ", "language": "en", "n_whitespaces": 69, "n_words": 29, "vocab_size": 22 }

{ "docstring": "Parse command line arguments.\n\n :param args: command line arguments with the program name removed. This is\n usually taken from sys.argv[1:].\n :type args: `list` of `str`\n\n :returns: parsed arguments\n :rtype: argparse.Namespace\n\n ", "language": "en", "n_whitespaces": 52, "n_words": 30, "vocab_size": 26 }

{ "docstring": "\n Checks if a field is conservative.\n\n Parameters\n ==========\n\n field : Vector\n The field to check for conservative property\n\n Examples\n ========\n\n >>> from sympy.physics.vector import ReferenceFrame\n >>> from sympy.physics.vector import is_conservative\n >>> R = ReferenceFrame('R')\n >>> is_conservative(R[1]*R[2]*R.x + R[0]*R[2]*R.y + R[0]*R[1]*R.z)\n True\n >>> is_conservative(R[2] * R.y)\n False\n\n ", "language": "en", "n_whitespaces": 96, "n_words": 46, "vocab_size": 36 }

{ "docstring": "Function needed to make build_ext tests pass.\n\n When Python was built with --enable-shared on Unix, -L. is not enough to\n find libpython<blah>.so, because regrtest runs in a tempdir, not in the\n source directory where the .so lives.\n\n When Python was built with in debug mode on Windows, build_ext commands\n need their debug attribute set, and it is not done automatically for\n some reason.\n\n This function handles both of these things. Example use:\n\n cmd = build_ext(dist)\n support.fixup_build_ext(cmd)\n cmd.ensure_finalized()\n\n Unlike most other Unix platforms, Mac OS X embeds absolute paths\n to shared libraries into executables, so the fixup is not needed there.\n ", "language": "en", "n_whitespaces": 152, "n_words": 100, "vocab_size": 80 }

{ "docstring": "\n\tVerify if the Batch is to be named using a naming series\n\t:return: bool\n\t", "language": "en", "n_whitespaces": 12, "n_words": 14, "vocab_size": 14 }

{ "docstring": "Add the options to rest server\n\n :param parser: the parser\n \n If set, a CORS middleware is added to FastAPI frontend to allow cross-origin access.\n \n If set, `/index`, `/search`, `/update`, `/delete` endpoints are removed from HTTP interface.\n\n Any executor that has `@requests(on=...)` bind with those values will receive data requests.\n \n A JSON string that represents a map from executor endpoints (`@requests(on=...)`) to HTTP endpoints.\n \nDictionary of kwargs arguments that will be passed to Uvicorn server when starting the server\n\nMore details can be found in Uvicorn docs: https://www.uvicorn.org/settings/\n\n\n Dictionary of kwargs arguments that will be passed to the grpc server when starting the server # todo update\n \n the path to the certificate file\n \n the path to the key file\n ", "language": "en", "n_whitespaces": 211, "n_words": 118, "vocab_size": 75 }

{ "docstring": "In this test, we input one ``DocumentArray`` with one ``Document``,\n and the `craft` method in the ``ImageCrafter`` returns chunks.\n In the ``ImageCrafter``, we filtered out all the modalities and only kept `image/jpeg`.\n So the 2 chunks should left only 1 chunk.\n And the tensor value of the ``Document`` is not empty once we finished crafting since\n we converted image uri/datauri to tensor.\n ", "language": "en", "n_whitespaces": 80, "n_words": 62, "vocab_size": 49 }

{ "docstring": "\n Search the environment for the relative path.\n ", "language": "en", "n_whitespaces": 14, "n_words": 7, "vocab_size": 6 }

{ "docstring": "\n Returns the list of supported prompt templates.\n :return: List of supported prompt templates.\n ", "language": "en", "n_whitespaces": 35, "n_words": 13, "vocab_size": 9 }

{ "docstring": "\n CREATE VIEW mindsdb.{}\n FROM test_integration_{} (\n select * from rentals limit 50\n )\n ", "language": "en", "n_whitespaces": 69, "n_words": 13, "vocab_size": 13 }

{ "docstring": "\n Convert the named file to png; return the name of the created file.\n\n If *cache* is True, the result of the conversion is cached in\n `matplotlib.get_cachedir() + '/test_cache/'`. The caching is based on a\n hash of the exact contents of the input file. Old cache entries are\n automatically deleted as needed to keep the size of the cache capped to\n twice the size of all baseline images.\n ", "language": "en", "n_whitespaces": 91, "n_words": 67, "vocab_size": 46 }

{ "docstring": "\n Returns a resized copy of this image.\n\n :param size: The requested size in pixels, as a 2-tuple:\n (width, height).\n :param resample: An optional resampling filter. This can be\n one of :py:data:`PIL.Image.Resampling.NEAREST`,\n :py:data:`PIL.Image.Resampling.BOX`,\n :py:data:`PIL.Image.Resampling.BILINEAR`,\n :py:data:`PIL.Image.Resampling.HAMMING`,\n :py:data:`PIL.Image.Resampling.BICUBIC` or\n :py:data:`PIL.Image.Resampling.LANCZOS`.\n If the image has mode \"1\" or \"P\", it is always set to\n :py:data:`PIL.Image.Resampling.NEAREST`.\n If the image mode specifies a number of bits, such as \"I;16\", then the\n default filter is :py:data:`PIL.Image.Resampling.NEAREST`.\n Otherwise, the default filter is\n :py:data:`PIL.Image.Resampling.BICUBIC`. See: :ref:`concept-filters`.\n :param box: An optional 4-tuple of floats providing\n the source image region to be scaled.\n The values must be within (0, 0, width, height) rectangle.\n If omitted or None, the entire source is used.\n :param reducing_gap: Apply optimization by resizing the image\n in two steps. First, reducing the image by integer times\n using :py:meth:`~PIL.Image.Image.reduce`.\n Second, resizing using regular resampling. The last step\n changes size no less than by ``reducing_gap`` times.\n ``reducing_gap`` may be None (no first step is performed)\n or should be greater than 1.0. The bigger ``reducing_gap``,\n the closer the result to the fair resampling.\n The smaller ``reducing_gap``, the faster resizing.\n With ``reducing_gap`` greater or equal to 3.0, the result is\n indistinguishable from fair resampling in most cases.\n The default value is None (no optimization).\n :returns: An :py:class:`~PIL.Image.Image` object.\n ", "language": "en", "n_whitespaces": 528, "n_words": 207, "vocab_size": 130 }

{ "docstring": "\\\nbackend: XLA\ncpp_namespace: torch_xla\nsupported:\n- abs\ninvalid_key: invalid_val contains unexpected keys: invalid_key. Only the following keys are supported: backend, cpp_namespace, extra_headers, supported, autograd, full_codegen", "language": "en", "n_whitespaces": 20, "n_words": 26, "vocab_size": 25 }

{ "docstring": "Rewrite Fortran expression as f2py supported C expression.\n\n Due to the lack of a proper expression parser in f2py, this\n function uses a heuristic approach that assumes that Fortran\n arithmetic expressions are valid C arithmetic expressions when\n mapping Fortran function calls to the corresponding C function/CPP\n macros calls.\n\n ", "language": "en", "n_whitespaces": 66, "n_words": 48, "vocab_size": 36 }

{ "docstring": " Build the faceswap command and arguments list.\n\n If training, pass the model folder and name to the training\n :class:`lib.gui.analysis.Session` for the GUI.\n ", "language": "en", "n_whitespaces": 44, "n_words": 22, "vocab_size": 18 }

{ "docstring": "Queries one or more VSwitches.\n\n :param vpc_id: The ID of the VPC to which the VSwitch belongs.\n :return: VSwitch list.\n ", "language": "en", "n_whitespaces": 41, "n_words": 20, "vocab_size": 18 }

{ "docstring": "\n This function draws a line plot. It takes in an `N` or `NxM` tensor\n `Y` that specifies the values of the `M` lines (that connect `N` points)\n to plot. It also takes an optional `X` tensor that specifies the\n corresponding x-axis values; `X` can be an `N` tensor (in which case all\n lines will share the same x-axis values) or have the same size as `Y`.\n\n `update` can be used to efficiently update the data of an existing line.\n Use 'append' to append data, 'replace' to use new data, and 'remove' to\n delete the trace that is specified in `name`. If updating a\n single trace, use `name` to specify the name of the trace to be updated.\n Update data that is all NaN is ignored (can be used for masking update).\n Using `update='append'` will create a plot if it doesn't exist\n and append to the existing plot otherwise.\n\n The following `opts` are supported:\n\n - `opts.fillarea` : fill area below line (`boolean`)\n - `opts.markers` : show markers (`boolean`; default = `false`)\n - `opts.markersymbol`: marker symbol (`string`; default = `'dot'`)\n - `opts.markersize` : marker size (`number`; default = `'10'`)\n - `opts.linecolor` : line colors (`np.array`; default = None)\n - `opts.dash` : line dash type (`np.array`; default = None)\n - `opts.legend` : `list` or `tuple` containing legend names\n\n If `update` is specified, the figure will be updated without\n creating a new plot -- this can be used for efficient updating.\n ", "language": "en", "n_whitespaces": 421, "n_words": 237, "vocab_size": 140 }

{ "docstring": "\n Test the execute function using Repo ID.\n ", "language": "en", "n_whitespaces": 22, "n_words": 7, "vocab_size": 7 }

{ "docstring": "Test that ignoring an error issue until it's hit by 10 users in an hour works.", "language": "en", "n_whitespaces": 15, "n_words": 16, "vocab_size": 15 }

{ "docstring": "Create a zip file from all the files under 'base_dir'.\n\n The output zip file will be named 'base_name' + \".zip\". Uses either the\n \"zipfile\" Python module (if available) or the InfoZIP \"zip\" utility\n (if installed and found on the default search path). If neither tool is\n available, raises DistutilsExecError. Returns the name of the output zip\n file.\n ", "language": "en", "n_whitespaces": 78, "n_words": 57, "vocab_size": 47 }

{ "docstring": "\n Another user can upgrade the room if the default power level for users is increased.\n ", "language": "en", "n_whitespaces": 30, "n_words": 15, "vocab_size": 14 }

{ "docstring": "Returns the sum of each Sales Invoice Item Amount which is Vat Exempt.\n\t\t\tselect\n\t\t\t\tsum(i.base_amount) as total\n\t\t\tfrom\n\t\t\t\t`tabSales Invoice Item` i inner join `tabSales Invoice` s\n\t\t\ton\n\t\t\t\ti.parent = s.name\n\t\t\twhere\n\t\t\t\ts.docstatus = 1 and i.is_exempt = 1\n\t\t\t\t{where_conditions} ;\n\t\t\t", "language": "en", "n_whitespaces": 32, "n_words": 41, "vocab_size": 36 }

{ "docstring": "\n Encrypt text and set it into cipher.\n\n :param key: the key to use for encryption\n :param text: the bytes value to encode\n :param confounder: (optional) specify the confounder bytes. Random otherwise\n :param key_usage_number: (optional) specify the key usage number.\n Guessed otherwise\n ", "language": "en", "n_whitespaces": 116, "n_words": 41, "vocab_size": 30 }

{ "docstring": "Create vSwitches to divide the VPC into one or more subnets\n\n :param vpc_id: The ID of the VPC to which the VSwitch belongs.\n :param zone_id: The ID of the zone to which\n the target VSwitch belongs.\n :param cidr_block: The CIDR block of the VSwitch.\n :return:\n ", "language": "en", "n_whitespaces": 103, "n_words": 45, "vocab_size": 27 }

{ "docstring": "Check if the style specified a transparent background.", "language": "en", "n_whitespaces": 7, "n_words": 8, "vocab_size": 8 }

{ "docstring": "\n input: positive integer 'number' > 1\n returns true if 'number' is a perfect number otherwise false.\n ", "language": "en", "n_whitespaces": 26, "n_words": 16, "vocab_size": 15 }

{ "docstring": "\n Get a colormap instance, defaulting to rc values if *name* is None.\n\n Colormaps added with :func:`register_cmap` take precedence over\n built-in colormaps.\n\n Parameters\n ----------\n name : `matplotlib.colors.Colormap` or str or None, default: None\n If a `.Colormap` instance, it will be returned. Otherwise, the name of\n a colormap known to Matplotlib, which will be resampled by *lut*. The\n default, None, means :rc:`image.cmap`.\n lut : int or None, default: None\n If *name* is not already a Colormap instance and *lut* is not None, the\n colormap will be resampled to have *lut* entries in the lookup table.\n\n Returns\n -------\n Colormap\n ", "language": "en", "n_whitespaces": 165, "n_words": 96, "vocab_size": 65 }

{ "docstring": "Cancel the future if possible.\n\n Returns True if the future was cancelled, False otherwise. A future\n cannot be cancelled if it is running or has already completed.\n ", "language": "en", "n_whitespaces": 48, "n_words": 27, "vocab_size": 22 }