JorgeVB/code_unlearning_dataset · Datasets at Hugging Face

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If `text` is an SArray of strings or an SArray of lists of strings, the occurances of word are counted for each row in the SArray. If `text` is an SArray of dictionaries, the keys are tokenized and the values are the counts. Counts for the same word, in the same row, are added together. This outpu...
Return an SArray of ``dict`` type where each element contains the count for each of the n-grams that appear in the corresponding input element. The n-grams can be specified to be either character n-grams or word n-grams. The input SArray could contain strings, dicts with string keys and numeric values,...
Compute the TF-IDF scores for each word in each document. The collection of documents must be in bag-of-words format. .. math:: \mbox{TF-IDF}(w, d) = tf(w, d) * log(N / f(w)) where :math:`tf(w, d)` is the number of times word :math:`w` appeared in document :math:`d`, :math:`f(w)` is the number...
Remove words that occur below a certain number of times in an SArray. This is a common method of cleaning text before it is used, and can increase the quality and explainability of the models learned on the transformed data. RareWordTrimmer can be applied to all the string-, dictionary-, and list-typed ...
Tokenize the input SArray of text strings and return the list of tokens. Parameters ---------- text : SArray[str] Input data of strings representing English text. This tokenizer is not intended to process XML, HTML, or other structured text formats. to_lower : bool, optional If...
For a given query and set of documents, compute the BM25 score for each document. If we have a query with words q_1, ..., q_n the BM25 score for a document is: .. math:: \sum_{i=1}^N IDF(q_i)\\frac{f(q_i) * (k_1+1)}{f(q_i) + k_1 * (1-b+b\|D\|/d_avg))} where :math:`\mbox{IDF}(q_i) = log((N - ...
Parse a file that's in libSVM format. In libSVM format each line of the text file represents a document in bag of words format: num_unique_words_in_doc word_id:count another_id:count The word_ids have 0-based indexing, i.e. 0 corresponds to the first word in the vocab filename. Parameters ---...
Parse a file that's in "docword" format. This consists of a 3-line header comprised of the document count, the vocabulary count, and the number of tokens, i.e. unique (doc_id, word_id) pairs. After the header, each line contains a space-separated triple of (doc_id, word_id, frequency), where frequency i...
Utility for performing a random split for text data that is already in bag-of-words format. For each (word, count) pair in a particular element, the counts are uniformly partitioned in either a training set or a test set. Parameters ---------- dataset : SArray of type dict, SFrame with columns ...
Train a booster with given parameters. Parameters ---------- params : dict Booster params. dtrain : DMatrix Data to be trained. num_boost_round: int Number of boosting iterations. watchlist (evals): list of pairs (DMatrix, string) List of items to be evaluated du...
Make an n-fold list of CVPack from random indices. def mknfold(dall, nfold, param, seed, evals=(), fpreproc=None): """ Make an n-fold list of CVPack from random indices. """ evals = list(evals) np.random.seed(seed) randidx = np.random.permutation(dall.num_row()) kstep = len(randidx) / nfold...
Aggregate cross-validation results. def aggcv(rlist, show_stdv=True, show_progress=None, as_pandas=True): # pylint: disable=invalid-name """ Aggregate cross-validation results. """ cvmap = {} idx = rlist[0].split()[0] for line in rlist: arr = line.split() assert idx == arr[0...
Cross-validation with given paramaters. Parameters ---------- params : dict Booster params. dtrain : DMatrix Data to be trained. num_boost_round : int Number of boosting iterations. nfold : int Number of folds in CV. metrics : list of strings Evaluati...
Create a :class:`ImageClassifier` model. Parameters ---------- dataset : SFrame Input data. The column named by the 'feature' parameter will be extracted for modeling. target : string, or int Name of the column containing the target variable. The values in this column m...
Save the model as a dictionary, which can be loaded with the :py:func:`~turicreate.load_model` method. def _get_native_state(self): """ Save the model as a dictionary, which can be loaded with the :py:func:`~turicreate.load_model` method. """ state = self.__proxy__.get_s...
A function to load a previously saved ImageClassifier instance. def _load_version(cls, state, version): """ A function to load a previously saved ImageClassifier instance. """ _tkutl._model_version_check(version, cls._PYTHON_IMAGE_CLASSIFIER_VERSION) from turicre...
Return predictions for ``dataset``, using the trained logistic regression model. Predictions can be generated as class labels, probabilities that the target value is True, or margins (i.e. the distance of the observations from the hyperplane separating the classes). `probability_vector` ...
Return top-k predictions for the ``dataset``, using the trained model. Predictions are returned as an SFrame with three columns: `id`, `class`, and `probability`, `margin`, or `rank`, depending on the ``output_type`` parameter. Input dataset size must be the same as for training of the model. ...
Evaluate the model by making predictions of target values and comparing these to actual values. Parameters ---------- dataset : SFrame Dataset of new observations. Must include columns with the same names as the target and features used for model training. Additi...
Save the model in Core ML format. See Also -------- save Examples -------- >>> model.export_coreml('myModel.mlmodel') def export_coreml(self, filename): """ Save the model in Core ML format. See Also -------- save Examp...
Extract the ordering of the input layers. def make_input_layers(self): """ Extract the ordering of the input layers. """ self.input_layers = [] in_nodes = self.model._inbound_nodes if hasattr( self.model,'_inbound_nodes') else self.model.inbound_nodes if ...
Extract the ordering of output layers. def make_output_layers(self): """ Extract the ordering of output layers. """ self.output_layers = [] # import pytest; pytest.set_trace() if hasattr(self.model, 'output_layers'): # find corresponding output layers in Core...
Remove the layer, and reconnect each of its predecessor to each of its successor def _remove_layer_and_reconnect(self, layer): """ Remove the layer, and reconnect each of its predecessor to each of its successor """ successors = self.get_successors(layer) predecessors = ...
Defuse the fused activation layers in the network. def defuse_activation(self): """ Defuse the fused activation layers in the network. """ idx, nb_layers = 0, len(self.layer_list) while idx < nb_layers: layer = self.layer_list[idx] k_layer = self.keras_layer_map[...
Returns a new SArray that represents a fixed frequency datetime index. Parameters ---------- start_time : datetime.datetime Left bound for generating dates. end_time : datetime.datetime Right bound for generating dates. freq : datetime.timedelta F...
Constructs an SArray of size with a const value. Parameters ---------- value : [int \| float \| str \| array.array \| list \| dict \| datetime] The value to fill the SArray size : int The size of the SArray dtype : type The type of the SArray. If not spec...
from_sequence(start=0, stop) Create an SArray from sequence .. sourcecode:: python Construct an SArray of integer values from 0 to 999 >>> tc.SArray.from_sequence(1000) This is equivalent, but more efficient than: >>> tc.SArray(range(1000)) ...
Construct an SArray from a json file or glob of json files. The json file must contain a list of dictionaries. The returned SArray type will be of dict type Parameters ---------- filename : str The filename or glob to load into an SArray. Examples ----...
Selects elements from either istrue or isfalse depending on the value of the condition SArray. Parameters ---------- condition : SArray An SArray of values such that for each value, if non-zero, yields a value from istrue, otherwise from isfalse. istrue : SArray...
Saves the SArray to file. The saved SArray will be in a directory named with the `targetfile` parameter. Parameters ---------- filename : string A local path or a remote URL. If format is 'text', it will be saved as a text file. If format is 'binary', a...
If this SArray contains vectors or lists, this returns a new SArray containing each individual element sliced, between start and end (exclusive). Parameters ---------- start : int The start position of the slice. end : int, optional. The end posi...
This returns an SArray with each element sliced accordingly to the slice specified. This is conceptually equivalent to: >>> g.apply(lambda x: x[start:step:stop]) The SArray must be of type list, vector, or string. For instance: >>> g = SArray(["abcdef","qwerty"]) >>> ...
This returns an SArray with, for each input string, a dict from the unique, delimited substrings to their number of occurrences within the original string. The SArray must be of type string. ..WARNING:: This function is deprecated, and will be removed in future versions of Turi...
For documentation, see turicreate.text_analytics.count_ngrams(). ..WARNING:: This function is deprecated, and will be removed in future versions of Turi Create. Please use the `text_analytics.count_words` function instead. def _count_ngrams(self, n=2, method="word", to_lower=True, ignore_space...
Filter an SArray of dictionary type by the given keys. By default, all keys that are in the provided list in ``keys`` are excluded from the returned SArray. Parameters ---------- keys : list A collection of keys to trim down the elements in the SArray. exc...
Filter dictionary values to a given range (inclusive). Trimming is only performed on values which can be compared to the bound values. Fails on SArrays whose data type is not ``dict``. Parameters ---------- lower : int or long or float, optional The lowest dictionary...
Create a boolean SArray by checking the keys of an SArray of dictionaries. An element of the output SArray is True if the corresponding input element's dictionary has any of the given keys. Fails on SArrays whose data type is not ``dict``. Parameters ---------- keys : li...
Create a boolean SArray by checking the keys of an SArray of dictionaries. An element of the output SArray is True if the corresponding input element's dictionary has all of the given keys. Fails on SArrays whose data type is not ``dict``. Parameters ---------- keys : li...
apply(fn, dtype=None, skip_na=True, seed=None) Transform each element of the SArray by a given function. The result SArray is of type ``dtype``. ``fn`` should be a function that returns exactly one value which can be cast into the type specified by ``dtype``. If ``dtype`` is not specifi...
Filter this SArray by a function. Returns a new SArray filtered by this SArray. If `fn` evaluates an element to true, this element is copied to the new SArray. If not, it isn't. Throws an exception if the return type of `fn` is not castable to a boolean value. Parameters ...
Create an SArray which contains a subsample of the current SArray. Parameters ---------- fraction : float Fraction of the rows to fetch. Must be between 0 and 1. if exact is False (default), the number of rows returned is approximately the fraction times the ...
Returns an SArray with a hash of each element. seed can be used to change the hash function to allow this method to be used for random number generation. Parameters ---------- seed : int Defaults to 0. Can be changed to different values to get different h...
Returns an SArray with random integer values. def random_integers(cls, size, seed=None): """ Returns an SArray with random integer values. """ if seed is None: seed = abs(hash("%0.20f" % time.time())) % (2 ** 31) return cls.from_sequence(size).hash(seed)
Get the index of the minimum numeric value in SArray. Returns None on an empty SArray. Raises an exception if called on an SArray with non-numeric type. Returns ------- out : int index of the minimum value of SArray See Also -------- argmax ...
Mean of all the values in the SArray, or mean image. Returns None on an empty SArray. Raises an exception if called on an SArray with non-numeric type or non-Image type. Returns ------- out : float \| turicreate.Image Mean of all values in SArray, or image holding pe...
Create a new SArray with all the values cast to str. The string format is specified by the 'format' parameter. Parameters ---------- format : str The format to output the string. Default format is "%Y-%m-%dT%H:%M:%S%ZP". Returns ------- out : SArray[...
Create a new SArray with all the values cast to datetime. The string format is specified by the 'format' parameter. Parameters ---------- format : str The string format of the input SArray. Default format is "%Y-%m-%dT%H:%M:%S%ZP". If format is "ISO", the the for...
Create a new SArray with all the values cast to :py:class:`turicreate.image.Image` of uniform size. Parameters ---------- width: int The width of the new images. height: int The height of the new images. channels: int. Number of chan...
Create a new SArray with all values cast to the given type. Throws an exception if the types are not castable to the given type. Parameters ---------- dtype : {int, float, str, list, array.array, dict, datetime.datetime} The type to cast the elements to in SArray un...
Create a new SArray with each value clipped to be within the given bounds. In this case, "clipped" means that values below the lower bound will be set to the lower bound value. Values above the upper bound will be set to the upper bound value. This function can operate on SArrays of ...
Create new SArray with all values clipped to the given lower bound. This function can operate on numeric arrays, as well as vector arrays, in which case each individual element in each vector is clipped. Throws an exception if the SArray is empty or the types are non-numeric. Parameters...
Get an SArray that contains the last n elements in the SArray. Parameters ---------- n : int The number of elements to fetch Returns ------- out : SArray A new SArray which contains the last n rows of the current SArray. def tail(self, n=10): ...
Create new SArray with all missing values (None or NaN) filled in with the given value. The size of the new SArray will be the same as the original SArray. If the given value is not the same type as the values in the SArray, `fillna` will attempt to convert the value to the original SAr...
Create an SArray indicating which elements are in the top k. Entries are '1' if the corresponding element in the current SArray is a part of the top k elements, and '0' if that corresponding element is not. Order is descending by default. Parameters ---------- topk : in...
Summary statistics that can be calculated with one pass over the SArray. Returns a turicreate.Sketch object which can be further queried for many descriptive statistics over this SArray. Many of the statistics are approximate. See the :class:`~turicreate.Sketch` documentation for more d...
Return an SFrame containing counts of unique values. The resulting SFrame will be sorted in descending frequency. Returns ------- out : SFrame An SFrame containing 2 columns : 'value', and 'count'. The SFrame will be sorted in descending order by the column 'coun...
Append an SArray to the current SArray. Creates a new SArray with the rows from both SArrays. Both SArrays must be of the same type. Parameters ---------- other : SArray Another SArray whose rows are appended to current SArray. Returns ------- out : ...
Get all unique values in the current SArray. Raises a TypeError if the SArray is of dictionary type. Will not necessarily preserve the order of the given SArray in the new SArray. Returns ------- out : SArray A new SArray that contains the unique values of the curr...
Visualize the SArray. Notes ----- - The plot will render either inline in a Jupyter Notebook, or in a native GUI window, depending on the value provided in `turicreate.visualization.set_target` (defaults to 'auto'). Parameters ---------- title : str ...
Create a Plot object representing the SArray. Notes ----- - The plot will render either inline in a Jupyter Notebook, or in a native GUI window, depending on the value provided in `turicreate.visualization.set_target` (defaults to 'auto'). Parameters -------...
Length of each element in the current SArray. Only works on SArrays of dict, array, or list type. If a given element is a missing value, then the output elements is also a missing value. This function is equivalent to the following but more performant: sa_item_len = sa.apply(lambd...
Randomly split the rows of an SArray into two SArrays. The first SArray contains M rows, sampled uniformly (without replacement) from the original SArray. M is approximately the fraction times the original number of rows. The second SArray contains the remaining rows of the original ...
Splits an SArray of datetime type to multiple columns, return a new SFrame that contains expanded columns. A SArray of datetime will be split by default into an SFrame of 6 columns, one for each year/month/day/hour/minute/second element. Column Naming When splitting a SArra...
Convert a "wide" SArray to one or two "tall" columns in an SFrame by stacking all values. The stack works only for columns of dict, list, or array type. If the column is dict type, two new columns are created as a result of stacking: one column holds the key and another column holds th...
Convert an SArray of list, array, or dict type to an SFrame with multiple columns. `unpack` expands an SArray using the values of each list/array/dict as elements in a new SFrame of multiple columns. For example, an SArray of lists each of length 4 will be expanded into an SFrame of 4 c...
Sort all values in this SArray. Sort only works for sarray of type str, int and float, otherwise TypeError will be raised. Creates a new, sorted SArray. Parameters ---------- ascending: boolean, optional If true, the sarray values are sorted in ascending order, other...
Calculate a new SArray of the sum of different subsets over this SArray. Also known as a "moving sum" or "running sum". The subset that the sum is calculated over is defined as an inclusive range relative to the position to each value in the SArray, using `window_start` and `win...
Calculate a new SArray of the maximum value of different subsets over this SArray. The subset that the maximum is calculated over is defined as an inclusive range relative to the position to each value in the SArray, using `window_start` and `window_end`. For a better understanding of ...
Count the number of non-NULL values of different subsets over this SArray. The subset that the count is executed on is defined as an inclusive range relative to the position to each value in the SArray, using `window_start` and `window_end`. For a better understanding of this, s...
Return the cumulative sum of the elements in the SArray. Returns an SArray where each element in the output corresponds to the sum of all the elements preceding and including it. The SArray is expected to be of numeric type (int, float), or a numeric vector type. Returns ------...
Return the cumulative mean of the elements in the SArray. Returns an SArray where each element in the output corresponds to the mean value of all the elements preceding and including it. The SArray is expected to be of numeric type (int, float), or a numeric vector type. Return...
Return the cumulative minimum value of the elements in the SArray. Returns an SArray where each element in the output corresponds to the minimum value of all the elements preceding and including it. The SArray is expected to be of numeric type (int, float). Returns ------- ...
Return the cumulative maximum value of the elements in the SArray. Returns an SArray where each element in the output corresponds to the maximum value of all the elements preceding and including it. The SArray is expected to be of numeric type (int, float). Returns ------- ...
Return the cumulative standard deviation of the elements in the SArray. Returns an SArray where each element in the output corresponds to the standard deviation of all the elements preceding and including it. The SArray is expected to be of numeric type, or a numeric vector type. Retur...
Return the cumulative variance of the elements in the SArray. Returns an SArray where each element in the output corresponds to the variance of all the elements preceding and including it. The SArray is expected to be of numeric type, or a numeric vector type. Returns ------- ...
Filter an SArray by values inside an iterable object. The result is an SArray that only includes (or excludes) the values in the given ``values`` :class:`~turicreate.SArray`. If ``values`` is not an SArray, we attempt to convert it to one before filtering. Parameters ---------- ...
Run the doxygen make command in the designated folder. def run_build_lib(folder): """Run the doxygen make command in the designated folder.""" try: retcode = subprocess.call("cd %s; make" % folder, shell=True) retcode = subprocess.call("rm -rf _build/html/doxygen", shell=True) retcode =...
Run the doxygen make commands if we're on the ReadTheDocs server def generate_doxygen_xml(app): """Run the doxygen make commands if we're on the ReadTheDocs server""" read_the_docs_build = os.environ.get('READTHEDOCS', None) == 'True' if read_the_docs_build: run_doxygen('..') sys.stderr.wri...
Converts protobuf message to JSON format. Args: message: The protocol buffers message instance to serialize. including_default_value_fields: If True, singular primitive fields, repeated fields, and map fields will always be serialized. If False, only serialize non-empty fields. Singular mes...
Converts protobuf message to a JSON dictionary. Args: message: The protocol buffers message instance to serialize. including_default_value_fields: If True, singular primitive fields, repeated fields, and map fields will always be serialized. If False, only serialize non-empty fields. Singul...
Parses a JSON dictionary representation into a message. Args: js_dict: Dict representation of a JSON message. message: A protocol buffer message to merge into. ignore_unknown_fields: If True, do not raise errors for unknown fields. Returns: The same message passed as argument. def ParseDict(js_di...
Convert a single scalar field value. Args: value: A scalar value to convert the scalar field value. field: The descriptor of the field to convert. require_str: If True, the field value must be a str. Returns: The converted scalar field value Raises: ParseError: In case of convert problems. ...
Convert an integer. Args: value: A scalar value to convert. Returns: The integer value. Raises: ParseError: If an integer couldn't be consumed. def _ConvertInteger(value): """Convert an integer. Args: value: A scalar value to convert. Returns: The integer value. Raises: Pars...
Convert an floating point number. def _ConvertFloat(value): """Convert an floating point number.""" if value == 'nan': raise ParseError('Couldn\'t parse float "nan", use "NaN" instead.') try: # Assume Python compatible syntax. return float(value) except ValueError: # Check alternative spellings...
Convert a boolean value. Args: value: A scalar value to convert. require_str: If True, value must be a str. Returns: The bool parsed. Raises: ParseError: If a boolean value couldn't be consumed. def _ConvertBool(value, require_str): """Convert a boolean value. Args: value: A scalar va...
Converts message to an object according to Proto3 JSON Specification. def _MessageToJsonObject(self, message): """Converts message to an object according to Proto3 JSON Specification.""" message_descriptor = message.DESCRIPTOR full_name = message_descriptor.full_name if _IsWrapperMessage(message_descri...
Converts normal message according to Proto3 JSON Specification. def _RegularMessageToJsonObject(self, message, js): """Converts normal message according to Proto3 JSON Specification.""" fields = message.ListFields() try: for field, value in fields: if self.preserving_proto_field_name: ...
Converts field value according to Proto3 JSON Specification. def _FieldToJsonObject(self, field, value): """Converts field value according to Proto3 JSON Specification.""" if field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE: return self._MessageToJsonObject(value) elif field.cpp_type == d...
Converts Any message according to Proto3 JSON Specification. def _AnyMessageToJsonObject(self, message): """Converts Any message according to Proto3 JSON Specification.""" if not message.ListFields(): return {} # Must print @type first, use OrderedDict instead of {} js = OrderedDict() type_ur...
Converts Value message according to Proto3 JSON Specification. def _ValueMessageToJsonObject(self, message): """Converts Value message according to Proto3 JSON Specification.""" which = message.WhichOneof('kind') # If the Value message is not set treat as null_value when serialize # to JSON. The parse ...
Converts Struct message according to Proto3 JSON Specification. def _StructMessageToJsonObject(self, message): """Converts Struct message according to Proto3 JSON Specification.""" fields = message.fields ret = {} for key in fields: ret[key] = self._ValueMessageToJsonObject(fields[key]) retur...
Convert a JSON object into a message. Args: value: A JSON object. message: A WKT or regular protocol message to record the data. Raises: ParseError: In case of convert problems. def ConvertMessage(self, value, message): """Convert a JSON object into a message. Args: value: A ...
Convert field value pairs into regular message. Args: js: A JSON object to convert the field value pairs. message: A regular protocol message to record the data. Raises: ParseError: In case of problems converting. def _ConvertFieldValuePair(self, js, message): """Convert field value pai...
Convert a JSON representation into Any message. def _ConvertAnyMessage(self, value, message): """Convert a JSON representation into Any message.""" if isinstance(value, dict) and not value: return try: type_url = value['@type'] except KeyError: raise ParseError('@type is missing when ...
Convert a JSON representation into Wrapper message. def _ConvertWrapperMessage(self, value, message): """Convert a JSON representation into Wrapper message.""" field = message.DESCRIPTOR.fields_by_name['value'] setattr(message, 'value', _ConvertScalarFieldValue(value, field))
Convert map field value for a message map field. Args: value: A JSON object to convert the map field value. message: A protocol message to record the converted data. field: The descriptor of the map field to be converted. Raises: ParseError: In case of convert problems. def _ConvertMa...
Plots the data in `x` on the X axis and the data in `y` on the Y axis in a 2d visualization, and shows the resulting visualization. Uses the following heuristic to choose the visualization: * If `x` and `y` are both numeric (SArray of int or float), and they contain fewer than or equal to 5,000 value...
Plots the data in `x` on the X axis and the data in `y` on the Y axis in a 2d visualization, and shows the resulting visualization. Uses the following heuristic to choose the visualization: * If `x` and `y` are both numeric (SArray of int or float), and they contain fewer than or equal to 5,000 value...
Plots the data in `x` on the X axis and the data in `y` on the Y axis in a 2d scatter plot, and returns the resulting Plot object. The function supports SArrays of dtypes: int, float. Parameters ---------- x : SArray The data to plot on the X axis of the scatter plot. Must be nume...
Plots the data in `x` on the X axis and the data in `y` on the Y axis in a 2d categorical heatmap, and returns the resulting Plot object. The function supports SArrays of dtypes str. Parameters ---------- x : SArray The data to plot on the X axis of the categorical heatmap. Must b...

If `text` is an SArray of strings or an SArray of lists of strings, the occurances of word are counted for each row in the SArray. If `text` is an SArray of dictionaries, the keys are tokenized and the values are the counts. Counts for the same word, in the same row, are added together. This outpu...

Return an SArray of ``dict`` type where each element contains the count for each of the n-grams that appear in the corresponding input element. The n-grams can be specified to be either character n-grams or word n-grams. The input SArray could contain strings, dicts with string keys and numeric values,...

Compute the TF-IDF scores for each word in each document. The collection of documents must be in bag-of-words format. .. math:: \mbox{TF-IDF}(w, d) = tf(w, d) * log(N / f(w)) where :math:`tf(w, d)` is the number of times word :math:`w` appeared in document :math:`d`, :math:`f(w)` is the number...

Remove words that occur below a certain number of times in an SArray. This is a common method of cleaning text before it is used, and can increase the quality and explainability of the models learned on the transformed data. RareWordTrimmer can be applied to all the string-, dictionary-, and list-typed ...

Tokenize the input SArray of text strings and return the list of tokens. Parameters ---------- text : SArray[str] Input data of strings representing English text. This tokenizer is not intended to process XML, HTML, or other structured text formats. to_lower : bool, optional If...

For a given query and set of documents, compute the BM25 score for each document. If we have a query with words q_1, ..., q_n the BM25 score for a document is: .. math:: \sum_{i=1}^N IDF(q_i)\\frac{f(q_i) * (k_1+1)}{f(q_i) + k_1 * (1-b+b*|D|/d_avg))} where * :math:`\mbox{IDF}(q_i) = log((N - ...

Parse a file that's in libSVM format. In libSVM format each line of the text file represents a document in bag of words format: num_unique_words_in_doc word_id:count another_id:count The word_ids have 0-based indexing, i.e. 0 corresponds to the first word in the vocab filename. Parameters ---...

Parse a file that's in "docword" format. This consists of a 3-line header comprised of the document count, the vocabulary count, and the number of tokens, i.e. unique (doc_id, word_id) pairs. After the header, each line contains a space-separated triple of (doc_id, word_id, frequency), where frequency i...

Utility for performing a random split for text data that is already in bag-of-words format. For each (word, count) pair in a particular element, the counts are uniformly partitioned in either a training set or a test set. Parameters ---------- dataset : SArray of type dict, SFrame with columns ...

Train a booster with given parameters. Parameters ---------- params : dict Booster params. dtrain : DMatrix Data to be trained. num_boost_round: int Number of boosting iterations. watchlist (evals): list of pairs (DMatrix, string) List of items to be evaluated du...

Make an n-fold list of CVPack from random indices. def mknfold(dall, nfold, param, seed, evals=(), fpreproc=None): """ Make an n-fold list of CVPack from random indices. """ evals = list(evals) np.random.seed(seed) randidx = np.random.permutation(dall.num_row()) kstep = len(randidx) / nfold...

Aggregate cross-validation results. def aggcv(rlist, show_stdv=True, show_progress=None, as_pandas=True): # pylint: disable=invalid-name """ Aggregate cross-validation results. """ cvmap = {} idx = rlist[0].split()[0] for line in rlist: arr = line.split() assert idx == arr[0...

Cross-validation with given paramaters. Parameters ---------- params : dict Booster params. dtrain : DMatrix Data to be trained. num_boost_round : int Number of boosting iterations. nfold : int Number of folds in CV. metrics : list of strings Evaluati...

Create a :class:`ImageClassifier` model. Parameters ---------- dataset : SFrame Input data. The column named by the 'feature' parameter will be extracted for modeling. target : string, or int Name of the column containing the target variable. The values in this column m...

Save the model as a dictionary, which can be loaded with the :py:func:`~turicreate.load_model` method. def _get_native_state(self): """ Save the model as a dictionary, which can be loaded with the :py:func:`~turicreate.load_model` method. """ state = self.__proxy__.get_s...

A function to load a previously saved ImageClassifier instance. def _load_version(cls, state, version): """ A function to load a previously saved ImageClassifier instance. """ _tkutl._model_version_check(version, cls._PYTHON_IMAGE_CLASSIFIER_VERSION) from turicre...

Return predictions for ``dataset``, using the trained logistic regression model. Predictions can be generated as class labels, probabilities that the target value is True, or margins (i.e. the distance of the observations from the hyperplane separating the classes). `probability_vector` ...

Return top-k predictions for the ``dataset``, using the trained model. Predictions are returned as an SFrame with three columns: `id`, `class`, and `probability`, `margin`, or `rank`, depending on the ``output_type`` parameter. Input dataset size must be the same as for training of the model. ...

Evaluate the model by making predictions of target values and comparing these to actual values. Parameters ---------- dataset : SFrame Dataset of new observations. Must include columns with the same names as the target and features used for model training. Additi...

Save the model in Core ML format. See Also -------- save Examples -------- >>> model.export_coreml('myModel.mlmodel') def export_coreml(self, filename): """ Save the model in Core ML format. See Also -------- save Examp...

Extract the ordering of the input layers. def make_input_layers(self): """ Extract the ordering of the input layers. """ self.input_layers = [] in_nodes = self.model._inbound_nodes if hasattr( self.model,'_inbound_nodes') else self.model.inbound_nodes if ...

Extract the ordering of output layers. def make_output_layers(self): """ Extract the ordering of output layers. """ self.output_layers = [] # import pytest; pytest.set_trace() if hasattr(self.model, 'output_layers'): # find corresponding output layers in Core...

Remove the layer, and reconnect each of its predecessor to each of its successor def _remove_layer_and_reconnect(self, layer): """ Remove the layer, and reconnect each of its predecessor to each of its successor """ successors = self.get_successors(layer) predecessors = ...

Defuse the fused activation layers in the network. def defuse_activation(self): """ Defuse the fused activation layers in the network. """ idx, nb_layers = 0, len(self.layer_list) while idx < nb_layers: layer = self.layer_list[idx] k_layer = self.keras_layer_map[...

Returns a new SArray that represents a fixed frequency datetime index. Parameters ---------- start_time : datetime.datetime Left bound for generating dates. end_time : datetime.datetime Right bound for generating dates. freq : datetime.timedelta F...

from_sequence(start=0, stop) Create an SArray from sequence .. sourcecode:: python Construct an SArray of integer values from 0 to 999 >>> tc.SArray.from_sequence(1000) This is equivalent, but more efficient than: >>> tc.SArray(range(1000)) ...

Construct an SArray from a json file or glob of json files. The json file must contain a list of dictionaries. The returned SArray type will be of dict type Parameters ---------- filename : str The filename or glob to load into an SArray. Examples ----...

Selects elements from either istrue or isfalse depending on the value of the condition SArray. Parameters ---------- condition : SArray An SArray of values such that for each value, if non-zero, yields a value from istrue, otherwise from isfalse. istrue : SArray...

Saves the SArray to file. The saved SArray will be in a directory named with the `targetfile` parameter. Parameters ---------- filename : string A local path or a remote URL. If format is 'text', it will be saved as a text file. If format is 'binary', a...

If this SArray contains vectors or lists, this returns a new SArray containing each individual element sliced, between start and end (exclusive). Parameters ---------- start : int The start position of the slice. end : int, optional. The end posi...

This returns an SArray with each element sliced accordingly to the slice specified. This is conceptually equivalent to: >>> g.apply(lambda x: x[start:step:stop]) The SArray must be of type list, vector, or string. For instance: >>> g = SArray(["abcdef","qwerty"]) >>> ...

This returns an SArray with, for each input string, a dict from the unique, delimited substrings to their number of occurrences within the original string. The SArray must be of type string. ..WARNING:: This function is deprecated, and will be removed in future versions of Turi...

For documentation, see turicreate.text_analytics.count_ngrams(). ..WARNING:: This function is deprecated, and will be removed in future versions of Turi Create. Please use the `text_analytics.count_words` function instead. def _count_ngrams(self, n=2, method="word", to_lower=True, ignore_space...

Filter an SArray of dictionary type by the given keys. By default, all keys that are in the provided list in ``keys`` are *excluded* from the returned SArray. Parameters ---------- keys : list A collection of keys to trim down the elements in the SArray. exc...

Filter dictionary values to a given range (inclusive). Trimming is only performed on values which can be compared to the bound values. Fails on SArrays whose data type is not ``dict``. Parameters ---------- lower : int or long or float, optional The lowest dictionary...

Create a boolean SArray by checking the keys of an SArray of dictionaries. An element of the output SArray is True if the corresponding input element's dictionary has any of the given keys. Fails on SArrays whose data type is not ``dict``. Parameters ---------- keys : li...

Create a boolean SArray by checking the keys of an SArray of dictionaries. An element of the output SArray is True if the corresponding input element's dictionary has all of the given keys. Fails on SArrays whose data type is not ``dict``. Parameters ---------- keys : li...

apply(fn, dtype=None, skip_na=True, seed=None) Transform each element of the SArray by a given function. The result SArray is of type ``dtype``. ``fn`` should be a function that returns exactly one value which can be cast into the type specified by ``dtype``. If ``dtype`` is not specifi...

Filter this SArray by a function. Returns a new SArray filtered by this SArray. If `fn` evaluates an element to true, this element is copied to the new SArray. If not, it isn't. Throws an exception if the return type of `fn` is not castable to a boolean value. Parameters ...

Create an SArray which contains a subsample of the current SArray. Parameters ---------- fraction : float Fraction of the rows to fetch. Must be between 0 and 1. if exact is False (default), the number of rows returned is approximately the fraction times the ...

Returns an SArray with a hash of each element. seed can be used to change the hash function to allow this method to be used for random number generation. Parameters ---------- seed : int Defaults to 0. Can be changed to different values to get different h...

Returns an SArray with random integer values. def random_integers(cls, size, seed=None): """ Returns an SArray with random integer values. """ if seed is None: seed = abs(hash("%0.20f" % time.time())) % (2 ** 31) return cls.from_sequence(size).hash(seed)

Get the index of the minimum numeric value in SArray. Returns None on an empty SArray. Raises an exception if called on an SArray with non-numeric type. Returns ------- out : int index of the minimum value of SArray See Also -------- argmax ...

Mean of all the values in the SArray, or mean image. Returns None on an empty SArray. Raises an exception if called on an SArray with non-numeric type or non-Image type. Returns ------- out : float | turicreate.Image Mean of all values in SArray, or image holding pe...

Create a new SArray with all the values cast to str. The string format is specified by the 'format' parameter. Parameters ---------- format : str The format to output the string. Default format is "%Y-%m-%dT%H:%M:%S%ZP". Returns ------- out : SArray[...

Create a new SArray with all the values cast to datetime. The string format is specified by the 'format' parameter. Parameters ---------- format : str The string format of the input SArray. Default format is "%Y-%m-%dT%H:%M:%S%ZP". If format is "ISO", the the for...

Create a new SArray with all the values cast to :py:class:`turicreate.image.Image` of uniform size. Parameters ---------- width: int The width of the new images. height: int The height of the new images. channels: int. Number of chan...

Create a new SArray with all values cast to the given type. Throws an exception if the types are not castable to the given type. Parameters ---------- dtype : {int, float, str, list, array.array, dict, datetime.datetime} The type to cast the elements to in SArray un...

Create a new SArray with each value clipped to be within the given bounds. In this case, "clipped" means that values below the lower bound will be set to the lower bound value. Values above the upper bound will be set to the upper bound value. This function can operate on SArrays of ...

Create new SArray with all values clipped to the given lower bound. This function can operate on numeric arrays, as well as vector arrays, in which case each individual element in each vector is clipped. Throws an exception if the SArray is empty or the types are non-numeric. Parameters...

Get an SArray that contains the last n elements in the SArray. Parameters ---------- n : int The number of elements to fetch Returns ------- out : SArray A new SArray which contains the last n rows of the current SArray. def tail(self, n=10): ...

Create new SArray with all missing values (None or NaN) filled in with the given value. The size of the new SArray will be the same as the original SArray. If the given value is not the same type as the values in the SArray, `fillna` will attempt to convert the value to the original SAr...

Create an SArray indicating which elements are in the top k. Entries are '1' if the corresponding element in the current SArray is a part of the top k elements, and '0' if that corresponding element is not. Order is descending by default. Parameters ---------- topk : in...

Summary statistics that can be calculated with one pass over the SArray. Returns a turicreate.Sketch object which can be further queried for many descriptive statistics over this SArray. Many of the statistics are approximate. See the :class:`~turicreate.Sketch` documentation for more d...

Return an SFrame containing counts of unique values. The resulting SFrame will be sorted in descending frequency. Returns ------- out : SFrame An SFrame containing 2 columns : 'value', and 'count'. The SFrame will be sorted in descending order by the column 'coun...

Append an SArray to the current SArray. Creates a new SArray with the rows from both SArrays. Both SArrays must be of the same type. Parameters ---------- other : SArray Another SArray whose rows are appended to current SArray. Returns ------- out : ...

Get all unique values in the current SArray. Raises a TypeError if the SArray is of dictionary type. Will not necessarily preserve the order of the given SArray in the new SArray. Returns ------- out : SArray A new SArray that contains the unique values of the curr...

Visualize the SArray. Notes ----- - The plot will render either inline in a Jupyter Notebook, or in a native GUI window, depending on the value provided in `turicreate.visualization.set_target` (defaults to 'auto'). Parameters ---------- title : str ...

Create a Plot object representing the SArray. Notes ----- - The plot will render either inline in a Jupyter Notebook, or in a native GUI window, depending on the value provided in `turicreate.visualization.set_target` (defaults to 'auto'). Parameters -------...

Length of each element in the current SArray. Only works on SArrays of dict, array, or list type. If a given element is a missing value, then the output elements is also a missing value. This function is equivalent to the following but more performant: sa_item_len = sa.apply(lambd...

Randomly split the rows of an SArray into two SArrays. The first SArray contains *M* rows, sampled uniformly (without replacement) from the original SArray. *M* is approximately the fraction times the original number of rows. The second SArray contains the remaining rows of the original ...

Splits an SArray of datetime type to multiple columns, return a new SFrame that contains expanded columns. A SArray of datetime will be split by default into an SFrame of 6 columns, one for each year/month/day/hour/minute/second element. **Column Naming** When splitting a SArra...

Convert a "wide" SArray to one or two "tall" columns in an SFrame by stacking all values. The stack works only for columns of dict, list, or array type. If the column is dict type, two new columns are created as a result of stacking: one column holds the key and another column holds th...

Convert an SArray of list, array, or dict type to an SFrame with multiple columns. `unpack` expands an SArray using the values of each list/array/dict as elements in a new SFrame of multiple columns. For example, an SArray of lists each of length 4 will be expanded into an SFrame of 4 c...

Sort all values in this SArray. Sort only works for sarray of type str, int and float, otherwise TypeError will be raised. Creates a new, sorted SArray. Parameters ---------- ascending: boolean, optional If true, the sarray values are sorted in ascending order, other...

Calculate a new SArray of the sum of different subsets over this SArray. Also known as a "moving sum" or "running sum". The subset that the sum is calculated over is defined as an inclusive range relative to the position to each value in the SArray, using `window_start` and `win...

Calculate a new SArray of the maximum value of different subsets over this SArray. The subset that the maximum is calculated over is defined as an inclusive range relative to the position to each value in the SArray, using `window_start` and `window_end`. For a better understanding of ...

Count the number of non-NULL values of different subsets over this SArray. The subset that the count is executed on is defined as an inclusive range relative to the position to each value in the SArray, using `window_start` and `window_end`. For a better understanding of this, s...

Return the cumulative sum of the elements in the SArray. Returns an SArray where each element in the output corresponds to the sum of all the elements preceding and including it. The SArray is expected to be of numeric type (int, float), or a numeric vector type. Returns ------...

Return the cumulative mean of the elements in the SArray. Returns an SArray where each element in the output corresponds to the mean value of all the elements preceding and including it. The SArray is expected to be of numeric type (int, float), or a numeric vector type. Return...

Return the cumulative minimum value of the elements in the SArray. Returns an SArray where each element in the output corresponds to the minimum value of all the elements preceding and including it. The SArray is expected to be of numeric type (int, float). Returns ------- ...

Return the cumulative maximum value of the elements in the SArray. Returns an SArray where each element in the output corresponds to the maximum value of all the elements preceding and including it. The SArray is expected to be of numeric type (int, float). Returns ------- ...

Return the cumulative standard deviation of the elements in the SArray. Returns an SArray where each element in the output corresponds to the standard deviation of all the elements preceding and including it. The SArray is expected to be of numeric type, or a numeric vector type. Retur...

Return the cumulative variance of the elements in the SArray. Returns an SArray where each element in the output corresponds to the variance of all the elements preceding and including it. The SArray is expected to be of numeric type, or a numeric vector type. Returns ------- ...

Filter an SArray by values inside an iterable object. The result is an SArray that only includes (or excludes) the values in the given ``values`` :class:`~turicreate.SArray`. If ``values`` is not an SArray, we attempt to convert it to one before filtering. Parameters ---------- ...

Run the doxygen make command in the designated folder. def run_build_lib(folder): """Run the doxygen make command in the designated folder.""" try: retcode = subprocess.call("cd %s; make" % folder, shell=True) retcode = subprocess.call("rm -rf _build/html/doxygen", shell=True) retcode =...

Run the doxygen make commands if we're on the ReadTheDocs server def generate_doxygen_xml(app): """Run the doxygen make commands if we're on the ReadTheDocs server""" read_the_docs_build = os.environ.get('READTHEDOCS', None) == 'True' if read_the_docs_build: run_doxygen('..') sys.stderr.wri...

Converts protobuf message to JSON format. Args: message: The protocol buffers message instance to serialize. including_default_value_fields: If True, singular primitive fields, repeated fields, and map fields will always be serialized. If False, only serialize non-empty fields. Singular mes...

Converts protobuf message to a JSON dictionary. Args: message: The protocol buffers message instance to serialize. including_default_value_fields: If True, singular primitive fields, repeated fields, and map fields will always be serialized. If False, only serialize non-empty fields. Singul...

Parses a JSON dictionary representation into a message. Args: js_dict: Dict representation of a JSON message. message: A protocol buffer message to merge into. ignore_unknown_fields: If True, do not raise errors for unknown fields. Returns: The same message passed as argument. def ParseDict(js_di...

Convert a single scalar field value. Args: value: A scalar value to convert the scalar field value. field: The descriptor of the field to convert. require_str: If True, the field value must be a str. Returns: The converted scalar field value Raises: ParseError: In case of convert problems. ...

Convert an integer. Args: value: A scalar value to convert. Returns: The integer value. Raises: ParseError: If an integer couldn't be consumed. def _ConvertInteger(value): """Convert an integer. Args: value: A scalar value to convert. Returns: The integer value. Raises: Pars...

Convert an floating point number. def _ConvertFloat(value): """Convert an floating point number.""" if value == 'nan': raise ParseError('Couldn\'t parse float "nan", use "NaN" instead.') try: # Assume Python compatible syntax. return float(value) except ValueError: # Check alternative spellings...

Convert a boolean value. Args: value: A scalar value to convert. require_str: If True, value must be a str. Returns: The bool parsed. Raises: ParseError: If a boolean value couldn't be consumed. def _ConvertBool(value, require_str): """Convert a boolean value. Args: value: A scalar va...

Converts message to an object according to Proto3 JSON Specification. def _MessageToJsonObject(self, message): """Converts message to an object according to Proto3 JSON Specification.""" message_descriptor = message.DESCRIPTOR full_name = message_descriptor.full_name if _IsWrapperMessage(message_descri...

Converts normal message according to Proto3 JSON Specification. def _RegularMessageToJsonObject(self, message, js): """Converts normal message according to Proto3 JSON Specification.""" fields = message.ListFields() try: for field, value in fields: if self.preserving_proto_field_name: ...

Converts field value according to Proto3 JSON Specification. def _FieldToJsonObject(self, field, value): """Converts field value according to Proto3 JSON Specification.""" if field.cpp_type == descriptor.FieldDescriptor.CPPTYPE_MESSAGE: return self._MessageToJsonObject(value) elif field.cpp_type == d...

Converts Any message according to Proto3 JSON Specification. def _AnyMessageToJsonObject(self, message): """Converts Any message according to Proto3 JSON Specification.""" if not message.ListFields(): return {} # Must print @type first, use OrderedDict instead of {} js = OrderedDict() type_ur...

Converts Value message according to Proto3 JSON Specification. def _ValueMessageToJsonObject(self, message): """Converts Value message according to Proto3 JSON Specification.""" which = message.WhichOneof('kind') # If the Value message is not set treat as null_value when serialize # to JSON. The parse ...

Converts Struct message according to Proto3 JSON Specification. def _StructMessageToJsonObject(self, message): """Converts Struct message according to Proto3 JSON Specification.""" fields = message.fields ret = {} for key in fields: ret[key] = self._ValueMessageToJsonObject(fields[key]) retur...

Convert a JSON object into a message. Args: value: A JSON object. message: A WKT or regular protocol message to record the data. Raises: ParseError: In case of convert problems. def ConvertMessage(self, value, message): """Convert a JSON object into a message. Args: value: A ...

Convert field value pairs into regular message. Args: js: A JSON object to convert the field value pairs. message: A regular protocol message to record the data. Raises: ParseError: In case of problems converting. def _ConvertFieldValuePair(self, js, message): """Convert field value pai...

Convert a JSON representation into Any message. def _ConvertAnyMessage(self, value, message): """Convert a JSON representation into Any message.""" if isinstance(value, dict) and not value: return try: type_url = value['@type'] except KeyError: raise ParseError('@type is missing when ...

Convert a JSON representation into Wrapper message. def _ConvertWrapperMessage(self, value, message): """Convert a JSON representation into Wrapper message.""" field = message.DESCRIPTOR.fields_by_name['value'] setattr(message, 'value', _ConvertScalarFieldValue(value, field))

Convert map field value for a message map field. Args: value: A JSON object to convert the map field value. message: A protocol message to record the converted data. field: The descriptor of the map field to be converted. Raises: ParseError: In case of convert problems. def _ConvertMa...

Plots the data in `x` on the X axis and the data in `y` on the Y axis in a 2d visualization, and shows the resulting visualization. Uses the following heuristic to choose the visualization: * If `x` and `y` are both numeric (SArray of int or float), and they contain fewer than or equal to 5,000 value...

Plots the data in `x` on the X axis and the data in `y` on the Y axis in a 2d scatter plot, and returns the resulting Plot object. The function supports SArrays of dtypes: int, float. Parameters ---------- x : SArray The data to plot on the X axis of the scatter plot. Must be nume...

Plots the data in `x` on the X axis and the data in `y` on the Y axis in a 2d categorical heatmap, and returns the resulting Plot object. The function supports SArrays of dtypes str. Parameters ---------- x : SArray The data to plot on the X axis of the categorical heatmap. Must b...