textflint.generation_layer.generator.absa_generator

Generator for ABSA Task

class textflint.generation_layer.generator.absa_generator.ABSAGenerator(task='ABSA', fields='sentence', max_trans=1, trans_methods=None, trans_config=None, return_unk=True, sub_methods=None, sub_config=None, attack_methods=None, validate_methods=None, dataset_config='restaurant', **kwargs)

Bases: textflint.generation_layer.generator.generator.Generator

Generate extra text for AbsaAddDiff, and dataset type is assigned in configure.

static get_extra_sentence(term_list, term_id, phrases)

Get the extra sentence from phrases text.

Parameters

• term_list (dict) – term list

• term_id (str) – term id

• phrases (list) – phrase list

Return list

extra sentences

get_extra_text()

Get extra text from training dataset.

Returns

dict of extra text

generate_by_transformations(dataset, **kwargs)

Generate samples by a list of transformation methods.

Parameters

dataset – the input dataset

Returns

(original samples, new samples, generated function string)

class textflint.generation_layer.generator.absa_generator.ABSASample(data, trans_id=None, origin=None, sample_id=None)

Bases: textflint.input_layer.component.sample.sample.Sample

ABSASample Class

check_data(data)

Check the format of input data.

Parameters

data (dict) – data name

load(data)

Load the legal data and convert it into SASample.

Parameters

data (dict) – data name

dump()

Dump the legal data.

Return dict

output of transformed data

is_legal()

Check whether aspect words and opinion words are

in the correct position.

Return bool

whether format of data is legal.

tokenize_term_list()

Tokenize the term list of ABSASample.

Return list

terms in ABSASample

update_sentence(trans_sentence)

Update the sentence of ABSASample.

Parameters

trans_sentence (str|list) – updated sentence

update_terms(trans_terms)

Update the terms of ABSASample.

Parameters

trans_terms (dict) – updated terms

update_term_list(sample)

Update the term_list of ABSASample.

Parameters

sample (ABSAsample) – updated sample

insert_field_before_indices(field, indices, items)

Insert items of multi given scopes before indices of field value at the same time.

Parameters

• field (str) – transformed field

• indices (list) – indices of insert positions

• items (list) – insert items

Return ~textflint.ABSAsample

modified sample

insert_field_before_index(field, ins_index, new_item)

Insert items of multi given scope before index of field value.

Parameters

• field (str) – transformed field

• ins_index (int|list) – index of insert position

• new_item (str|list) – insert item

Return ~textflint.ABSAsample

modified sample

insert_field_after_indices(field, indices, items)

Insert items of multi given scopes after indices of field value at the same time.

Parameters

• field (str) – transformed field

• indices (list) – indices of insert positions

• items (list) – insert items

Return ABSAsample

modified sample

insert_field_after_index(field, ins_index, new_item)

Insert items of multi given scope after index of field value.

Parameters

• field (str) – transformed field

• ins_index (int|list) – index of insert position

• new_item (str|list) – insert item

Return ~textflint.ABSAsample

modified sample

delete_field_at_indices(field, indices)

Delete items of given scopes of field value.

Parameters

• field (str) – transformed field

• indices (list) – indices of delete positions

Return ABSAsample

modified sample

delete_field_at_index(field, del_index)

Delete items of given scopes of field value.

Parameters

• field (str) – transformed field

• del_index (list) – index of delete position

Return ~textflint.ABSAsample

modified sample

class textflint.generation_layer.generator.absa_generator.Generator(task='UT', max_trans=1, random_seed=1, fields='x', trans_methods=None, trans_config=None, return_unk=True, sub_methods=None, sub_config=None, attack_methods=None, validate_methods=None, **kwargs)

Bases: abc.ABC

Transformation controller which applies multi transformations to each data sample.

__init__(task='UT', max_trans=1, random_seed=1, fields='x', trans_methods=None, trans_config=None, return_unk=True, sub_methods=None, sub_config=None, attack_methods=None, validate_methods=None, **kwargs)

Parameters

• task (str) – Indicate which task of your transformation data.

• max_trans (int) – Maximum transformed samples generate by one original sample pre Transformation.

• random_seed (int) – random number seed to reproduce generation.

• fields (str|list) – Indicate which fields to apply transformations. Multi fields transform just for some special task, like: SM、NLI.

• trans_methods (list) – list of transformations’ name.

• trans_config (dict) – transformation class configs, useful to control the behavior of transformations.

• return_unk (bool) – Some transformation may generate unk labels, s.t. insert a word to a sequence in NER task. If set False, would skip these transformations.

• sub_methods (list) – list of subpopulations’ name.

• sub_config (dict) – subpopulation class configs, useful to control the behavior of subpopulation.

• attack_methods (str) – path to the python file containing the Attack instances.

• validate_methods (list) – confidence calculate functions.

prepare(dataset)

Check dataset

Parameters

dataset (textflint.Dataset) – the input dataset

generate(dataset, model=None)

Returns a list of possible generated samples for dataset.

Parameters

• dataset (textflint.Dataset) – the input dataset

• model (textflint.FlintModel) – the model to attack if given.

Returns

yield (original samples, new samples, generated function string).

generate_by_transformations(dataset, **kwargs)

Generate samples by a list of transformation methods.

Parameters

dataset – the input dataset

Returns

(original samples, new samples, generated function string)

generate_by_subpopulations(dataset, **kwargs)

Generate samples by a list of subpopulation methods.

Parameters

dataset – the input dataset

Returns

the transformed dataset

generate_by_attacks(dataset, model=None, **kwargs)

Generate samples by a list of attack methods.

Parameters

• dataset – the input dataset

• model – the model to attack if given.

Returns

the transformed dataset

class textflint.generation_layer.generator.absa_generator.Transformation(**kwargs)

Bases: abc.ABC

An abstract class for transforming a sequence of text to produce a list of potential adversarial example.

processor = <textflint.common.preprocess.en_processor.EnProcessor object>

transform(sample, n=1, field='x', **kwargs)

Transform data sample to a list of Sample.

Parameters

• sample (Sample) – Data sample for augmentation.

• n (int) – Max number of unique augmented output, default is 5.

• field (str|list) – Indicate which fields to apply transformations.

• **kwargs (dict) –

  other auxiliary params.

Returns

list of Sample

classmethod sample_num(x, num)

Get ‘num’ samples from x.

Parameters

• x (list) – list to sample

• num (int) – sample number

Returns

max ‘num’ unique samples.

textflint.generation_layer.generator.absa_generator.download_if_needed(folder_name)

Folder name will be saved as .cache/textflint/[folder_name]. If it doesn’t exist on disk, the zip file will be downloaded and extracted.

Parameters

folder_name (str) – path to folder or file in cache

Returns

path to the downloaded folder or file on disk

class textflint.generation_layer.generator.absa_generator.tqdm(*args, **kwargs)

Bases: tqdm.utils.Comparable

Decorate an iterable object, returning an iterator which acts exactly like the original iterable, but prints a dynamically updating progressbar every time a value is requested.

monitor_interval = 10

static format_sizeof(num, suffix='', divisor=1000)

Formats a number (greater than unity) with SI Order of Magnitude prefixes.

numfloat

Number ( >= 1) to format.

suffixstr, optional

Post-postfix [default: ‘’].

divisorfloat, optional

Divisor between prefixes [default: 1000].

outstr

Number with Order of Magnitude SI unit postfix.

static format_interval(t)

Formats a number of seconds as a clock time, [H:]MM:SS

tint

Number of seconds.

outstr

[H:]MM:SS

static format_num(n)

Intelligent scientific notation (.3g).

nint or float or Numeric

A Number.

outstr

Formatted number.

static ema(x, mu=None, alpha=0.3)

Exponential moving average: smoothing to give progressively lower weights to older values.

xfloat

New value to include in EMA.

mufloat, optional

Previous EMA value.

alphafloat, optional

Smoothing factor in range [0, 1], [default: 0.3]. Increase to give more weight to recent values. Ranges from 0 (yields mu) to 1 (yields x).

static status_printer(file)

Manage the printing and in-place updating of a line of characters. Note that if the string is longer than a line, then in-place updating may not work (it will print a new line at each refresh).

static format_meter(n, total, elapsed, ncols=None, prefix='', ascii=False, unit='it', unit_scale=False, rate=None, bar_format=None, postfix=None, unit_divisor=1000, initial=0, **extra_kwargs)

Return a string-based progress bar given some parameters

nint or float

Number of finished iterations.

totalint or float

The expected total number of iterations. If meaningless (None), only basic progress statistics are displayed (no ETA).

elapsedfloat

Number of seconds passed since start.

ncolsint, optional

The width of the entire output message. If specified, dynamically resizes {bar} to stay within this bound [default: None]. If 0, will not print any bar (only stats). The fallback is {bar:10}.

prefixstr, optional

Prefix message (included in total width) [default: ‘’]. Use as {desc} in bar_format string.

asciibool, optional or str, optional

If not set, use unicode (smooth blocks) to fill the meter [default: False]. The fallback is to use ASCII characters ” 123456789#”.

unitstr, optional

The iteration unit [default: ‘it’].

unit_scalebool or int or float, optional

If 1 or True, the number of iterations will be printed with an appropriate SI metric prefix (k = 10^3, M = 10^6, etc.) [default: False]. If any other non-zero number, will scale total and n.

ratefloat, optional

Manual override for iteration rate. If [default: None], uses n/elapsed.

bar_formatstr, optional

Specify a custom bar string formatting. May impact performance. [default: ‘{l_bar}{bar}{r_bar}’], where l_bar=’{desc}: {percentage:3.0f}%|’ and r_bar=’| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, ‘

‘{rate_fmt}{postfix}]’

Possible vars: l_bar, bar, r_bar, n, n_fmt, total, total_fmt,

percentage, elapsed, elapsed_s, ncols, nrows, desc, unit, rate, rate_fmt, rate_noinv, rate_noinv_fmt, rate_inv, rate_inv_fmt, postfix, unit_divisor, remaining, remaining_s.

Note that a trailing “: ” is automatically removed after {desc} if the latter is empty.

postfix*, optional

Similar to prefix, but placed at the end (e.g. for additional stats). Note: postfix is usually a string (not a dict) for this method, and will if possible be set to postfix = ‘, ‘ + postfix. However other types are supported (#382).

unit_divisorfloat, optional

[default: 1000], ignored unless unit_scale is True.

initialint or float, optional

The initial counter value [default: 0].

out : Formatted meter and stats, ready to display.

classmethod write(s, file=None, end='\n', nolock=False)

Print a message via tqdm (without overlap with bars).

classmethod external_write_mode(file=None, nolock=False)

Disable tqdm within context and refresh tqdm when exits. Useful when writing to standard output stream

classmethod set_lock(lock)

Set the global lock.

classmethod get_lock()

Get the global lock. Construct it if it does not exist.

classmethod pandas(**tqdm_kwargs)

Registers the current tqdm class with

pandas.core. ( frame.DataFrame | series.Series | groupby.(generic.)DataFrameGroupBy | groupby.(generic.)SeriesGroupBy ).progress_apply

A new instance will be create every time progress_apply is called, and each instance will automatically close() upon completion.

tqdm_kwargs : arguments for the tqdm instance

>>> import pandas as pd
>>> import numpy as np
>>> from tqdm import tqdm
>>> from tqdm.gui import tqdm as tqdm_gui
>>>
>>> df = pd.DataFrame(np.random.randint(0, 100, (100000, 6)))
>>> tqdm.pandas(ncols=50)  # can use tqdm_gui, optional kwargs, etc
>>> # Now you can use `progress_apply` instead of `apply`
>>> df.groupby(0).progress_apply(lambda x: x**2)

<https://stackoverflow.com/questions/18603270/ progress-indicator-during-pandas-operations-python>

__init__(iterable=None, desc=None, total=None, leave=True, file=None, ncols=None, mininterval=0.1, maxinterval=10.0, miniters=None, ascii=None, disable=False, unit='it', unit_scale=False, dynamic_ncols=False, smoothing=0.3, bar_format=None, initial=0, position=None, postfix=None, unit_divisor=1000, write_bytes=None, lock_args=None, nrows=None, gui=False, **kwargs)

iterableiterable, optional

Iterable to decorate with a progressbar. Leave blank to manually manage the updates.

descstr, optional

Prefix for the progressbar.

totalint or float, optional

The number of expected iterations. If unspecified, len(iterable) is used if possible. If float(“inf”) or as a last resort, only basic progress statistics are displayed (no ETA, no progressbar). If gui is True and this parameter needs subsequent updating, specify an initial arbitrary large positive number, e.g. 9e9.

leavebool, optional

If [default: True], keeps all traces of the progressbar upon termination of iteration. If None, will leave only if position is 0.

fileio.TextIOWrapper or io.StringIO, optional

Specifies where to output the progress messages (default: sys.stderr). Uses file.write(str) and file.flush() methods. For encoding, see write_bytes.

ncolsint, optional

The width of the entire output message. If specified, dynamically resizes the progressbar to stay within this bound. If unspecified, attempts to use environment width. The fallback is a meter width of 10 and no limit for the counter and statistics. If 0, will not print any meter (only stats).

minintervalfloat, optional

Minimum progress display update interval [default: 0.1] seconds.

maxintervalfloat, optional

Maximum progress display update interval [default: 10] seconds. Automatically adjusts miniters to correspond to mininterval after long display update lag. Only works if dynamic_miniters or monitor thread is enabled.

minitersint or float, optional

Minimum progress display update interval, in iterations. If 0 and dynamic_miniters, will automatically adjust to equal mininterval (more CPU efficient, good for tight loops). If > 0, will skip display of specified number of iterations. Tweak this and mininterval to get very efficient loops. If your progress is erratic with both fast and slow iterations (network, skipping items, etc) you should set miniters=1.

asciibool or str, optional

If unspecified or False, use unicode (smooth blocks) to fill the meter. The fallback is to use ASCII characters ” 123456789#”.

disablebool, optional

Whether to disable the entire progressbar wrapper [default: False]. If set to None, disable on non-TTY.

unitstr, optional

String that will be used to define the unit of each iteration [default: it].

unit_scalebool or int or float, optional

If 1 or True, the number of iterations will be reduced/scaled automatically and a metric prefix following the International System of Units standard will be added (kilo, mega, etc.) [default: False]. If any other non-zero number, will scale total and n.

dynamic_ncolsbool, optional

If set, constantly alters ncols and nrows to the environment (allowing for window resizes) [default: False].

smoothingfloat, optional

Exponential moving average smoothing factor for speed estimates (ignored in GUI mode). Ranges from 0 (average speed) to 1 (current/instantaneous speed) [default: 0.3].

bar_formatstr, optional

Specify a custom bar string formatting. May impact performance. [default: ‘{l_bar}{bar}{r_bar}’], where l_bar=’{desc}: {percentage:3.0f}%|’ and r_bar=’| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, ‘

‘{rate_fmt}{postfix}]’

Possible vars: l_bar, bar, r_bar, n, n_fmt, total, total_fmt,

percentage, elapsed, elapsed_s, ncols, nrows, desc, unit, rate, rate_fmt, rate_noinv, rate_noinv_fmt, rate_inv, rate_inv_fmt, postfix, unit_divisor, remaining, remaining_s.

Note that a trailing “: ” is automatically removed after {desc} if the latter is empty.

initialint or float, optional

The initial counter value. Useful when restarting a progress bar [default: 0]. If using float, consider specifying {n:.3f} or similar in bar_format, or specifying unit_scale.

positionint, optional

Specify the line offset to print this bar (starting from 0) Automatic if unspecified. Useful to manage multiple bars at once (eg, from threads).

postfixdict or *, optional

Specify additional stats to display at the end of the bar. Calls set_postfix(**postfix) if possible (dict).

unit_divisorfloat, optional

[default: 1000], ignored unless unit_scale is True.

write_bytesbool, optional

If (default: None) and file is unspecified, bytes will be written in Python 2. If True will also write bytes. In all other cases will default to unicode.

lock_argstuple, optional

Passed to refresh for intermediate output (initialisation, iterating, and updating).

nrowsint, optional

The screen height. If specified, hides nested bars outside this bound. If unspecified, attempts to use environment height. The fallback is 20.

guibool, optional

WARNING: internal parameter - do not use. Use tqdm.gui.tqdm(…) instead. If set, will attempt to use matplotlib animations for a graphical output [default: False].

out : decorated iterator.

update(n=1)

Manually update the progress bar, useful for streams such as reading files. E.g.: >>> t = tqdm(total=filesize) # Initialise >>> for current_buffer in stream: … … … t.update(len(current_buffer)) >>> t.close() The last line is highly recommended, but possibly not necessary if t.update() will be called in such a way that filesize will be exactly reached and printed.

nint or float, optional

Increment to add to the internal counter of iterations [default: 1]. If using float, consider specifying {n:.3f} or similar in bar_format, or specifying unit_scale.

outbool or None

True if a display() was triggered.

close()

Cleanup and (if leave=False) close the progressbar.

clear(nolock=False)

Clear current bar display.

refresh(nolock=False, lock_args=None)

Force refresh the display of this bar.

nolockbool, optional

If True, does not lock. If [default: False]: calls acquire() on internal lock.

lock_argstuple, optional

Passed to internal lock’s acquire(). If specified, will only display() if acquire() returns True.

unpause()

Restart tqdm timer from last print time.

reset(total=None)

Resets to 0 iterations for repeated use.

Consider combining with leave=True.

total : int or float, optional. Total to use for the new bar.

set_description(desc=None, refresh=True)

Set/modify description of the progress bar.

desc : str, optional refresh : bool, optional

Forces refresh [default: True].

set_description_str(desc=None, refresh=True)

Set/modify description without ‘: ‘ appended.

set_postfix(ordered_dict=None, refresh=True, **kwargs)

Set/modify postfix (additional stats) with automatic formatting based on datatype.

ordered_dict : dict or OrderedDict, optional refresh : bool, optional

Forces refresh [default: True].

kwargs : dict, optional

set_postfix_str(s='', refresh=True)

Postfix without dictionary expansion, similar to prefix handling.

property format_dict

Public API for read-only member access.

display(msg=None, pos=None)

Use self.sp to display msg in the specified pos.

Consider overloading this function when inheriting to use e.g.: self.some_frontend(**self.format_dict) instead of self.sp.

msg : str, optional. What to display (default: repr(self)). pos : int, optional. Position to moveto

(default: abs(self.pos)).

classmethod wrapattr(stream, method, total=None, bytes=True, **tqdm_kwargs)

stream : file-like object. method : str, “read” or “write”. The result of read() and

the first argument of write() should have a len().

>>> with tqdm.wrapattr(file_obj, "read", total=file_obj.size) as fobj:
...     while True:
...         chunk = fobj.read(chunk_size)
...         if not chunk:
...             break