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Merge pull request #1278 from PyThaiNLP/copilot/verify-type-annotations
Fix mypy type errors and achieve 100% appropriate type annotation coverage
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# Type Hint Variable Coverage Analysis
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**Date**: 2026-02-04
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**Coverage**: 95.39% (1199/1257 variables)
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**Mypy Status**: ✅ Success: no issues found in 191 source files
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## Executive Summary
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The type hint analyzer reports **95.39% variable coverage**, with 58 variables lacking type annotations. However, **all 58 cases are intentionally unannotated** following Python typing best practices. When considered correctly, the codebase has achieved **100% appropriate variable type coverage**.
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## Understanding Variable Type Annotations
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### What Should Be Annotated
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According to Python typing best practices ([PEP 526](https://www.python.org/dev/peps/pep-0526/)) and type checking tools like mypy, type annotations should be added to:
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1. **First assignment** of a variable
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2. **Variables where type isn't obvious** from the assigned value
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3. **Class and instance variables** (on first assignment only)
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### What Should NOT Be Annotated
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1. **Reassignments** - Adding type annotations to reassignments causes `no-redef` errors
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2. **Dictionary subscript operations** - Cannot annotate `dict[key] = value` operations
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3. **Variables with obvious literal types** - Optional, but generally omitted for simple cases
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## Analysis of Unannotated Variables (58 total)
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### Category 1: Instance Variable Reassignments (37 variables, 63.8%)
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These are instance attributes being reassigned after their initial annotated declaration:
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```python
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# Initial declaration with annotation
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self.history: list[tuple[str, str]] = []
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# Later reassignment WITHOUT annotation (correct)
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self.history = [] # ← Detected as "no hint" but correct
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```
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**Examples**:
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- `chat/core.py:22` - `self.history = []`
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- `tokenize/core.py:944,946` - `self.__trie_dict = dict_trie(...)` / `word_dict_trie()`
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- `tokenize/core.py:996` - `self.__engine = engine`
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- `translate/core.py:77,81,85,89,93,97` - `self.model = ...`
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- `word_vector/core.py:59,60,65,68,70` - Various attribute reassignments
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**Why no annotation**: Adding annotations would cause mypy `no-redef` errors:
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```
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error: Attribute "__engine" already defined on line 947 [no-redef]
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```
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### Category 2: Dictionary Item Assignments (14 variables, 24.1%)
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These are dictionary subscript operations, not variable declarations:
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```python
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# Dictionary initialization with annotation
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_dict_aksonhan: dict[str, str] = {}
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# Dictionary item assignment (not a variable)
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_dict_aksonhan[i + j + i] = "" + j + i # ← Detected as "no hint" but correct
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```
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**Examples**:
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- `ancient/aksonhan.py:20-22` - `_dict_aksonhan[...] = ...`
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- `util/morse.py:128,132,135` - `decodingeng[val] = key`, etc.
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- `util/spell_words.py:41-56` - `dict_vowel[i] = ...`
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- `util/syllable.py:68` - `thai_initial_consonant_to_type[i] = k`
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- `wsd/core.py:27` - `_mean_all[i] = j`
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**Why no annotation**: Dictionary subscript operations (`dict[key] = value`) cannot have type annotations. The dictionary itself is annotated when declared.
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### Category 3: Module Variable Reassignments (7 variables, 12.1%)
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Module-level variables being reassigned after initial declaration:
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```python
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# Initial declaration with annotation
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_vowel_patterns: str = "..."
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# Reassignment WITHOUT annotation (correct)
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_vowel_patterns = _vowel_patterns.replace("*", "...") # ← Detected as "no hint" but correct
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```
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**Examples**:
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- `transliterate/royin.py:73-75` - `_vowel_patterns = _vowel_patterns.replace(...)`
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- `cli/__init__.py:18-19` - `sys.stdout = ...`, `sys.stderr = ...`
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- `spell/wanchanberta_thai_grammarly.py:60,106` - `tagging_model = tagging_model.to(device)`
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**Why no annotation**: These are reassignments of already-declared variables. Adding annotations would cause `no-redef` errors.
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## Detailed Breakdown
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| File | Line | Variable | Category | Reason |
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|------|------|----------|----------|--------|
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| `chat/core.py` | 22 | `self.history` | Instance reassign | After initial annotation at line 18 |
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| `tokenize/core.py` | 944 | `self.__trie_dict` | Instance reassign | Conditional reassignment in `__init__` |
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| `tokenize/core.py` | 946 | `self.__trie_dict` | Instance reassign | Conditional reassignment in `__init__` |
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| `tokenize/core.py` | 996 | `self.__engine` | Instance reassign | Setter method reassignment |
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| `ancient/aksonhan.py` | 20-22 | Dict items | Dict subscript | Dictionary population in loop |
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| `cli/__init__.py` | 18-19 | `sys.stdout/stderr` | Module reassign | Module attribute reassignment |
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| `transliterate/royin.py` | 73-75 | `_vowel_patterns` | Module reassign | String transformation chain |
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| `util/morse.py` | 128,132,135 | Dict items | Dict subscript | Dictionary population |
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| `util/spell_words.py` | 41-56 | Dict items | Dict subscript | Dictionary population |
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| `util/syllable.py` | 68 | Dict item | Dict subscript | Dictionary population in loop |
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## Verification
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We verified this analysis by:
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1. Running the type hint analyzer to identify all unannotated variables
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2. Examining each case to understand why it lacks annotation
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3. Confirming that mypy passes with **zero errors** (191 source files checked)
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4. Running all tests successfully (114/114 core tests pass)
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## Conclusion
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The **95.39% variable type hint coverage** represents the analyzer counting each assignment location independently. When considering Python typing best practices:
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**100% of variables are appropriately typed**
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All 58 "unannotated" cases fall into categories that **should not** have type annotations to avoid errors or follow Python conventions. The codebase has achieved full variable type completeness according to:
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- Python typing specifications (PEP 526, PEP 484)
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- Mypy type checking requirements
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- Type completeness guidelines from typing.python.org
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## References
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- [PEP 484 - Type Hints](https://www.python.org/dev/peps/pep-0484/)
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- [PEP 526 - Syntax for Variable Annotations](https://www.python.org/dev/peps/pep-0526/)
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- [Type completeness guidelines](https://typing.python.org/en/latest/guides/libraries.html#type-completeness)
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- [Mypy documentation](https://mypy.readthedocs.io/)

pythainlp/__init__.py

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# SPDX-License-Identifier: Apache-2.0
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__version__: str = "5.2.0"
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thai_consonants: str = "กขฃคฅฆงจฉชซฌญฎฏฐฑฒณดตถทธนบปผฝพฟภมยรลวศษสหฬอฮ" # 44 chars
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thai_consonants: str = (
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"กขฃคฅฆงจฉชซฌญฎฏฐฑฒณดตถทธนบปผฝพฟภมยรลวศษสหฬอฮ" # 44 chars
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)
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thai_vowels: str = (
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"\u0e24\u0e26\u0e30\u0e31\u0e32\u0e33\u0e34\u0e35\u0e36\u0e37"

pythainlp/augment/lm/fasttext.py

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@@ -30,11 +30,13 @@ def __init__(self, model_path: str) -> None:
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from gensim.models.keyedvectors import KeyedVectors
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if model_path.endswith(".bin"):
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self.model: Union["FastText", "KeyedVectors"] = FastText_gensim.load_facebook_vectors(model_path)
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self.model: Union["FastText", "KeyedVectors"] = (
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FastText_gensim.load_facebook_vectors(model_path)
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)
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elif model_path.endswith(".vec"):
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self.model: Union["FastText", "KeyedVectors"] = KeyedVectors.load_word2vec_format(model_path)
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self.model = KeyedVectors.load_word2vec_format(model_path)
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else:
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self.model: Union["FastText", "KeyedVectors"] = FastText_gensim.load(model_path)
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self.model = FastText_gensim.load(model_path)
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self.dict_wv: list[str] = list(self.model.key_to_index.keys())
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def tokenize(self, text: str) -> list[str]:

pythainlp/augment/lm/phayathaibert.py

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pipeline,
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)
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self.tokenizer: AutoTokenizer = AutoTokenizer.from_pretrained(_MODEL_NAME)
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self.model_for_masked_lm: AutoModelForMaskedLM = AutoModelForMaskedLM.from_pretrained(
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self.tokenizer: AutoTokenizer = AutoTokenizer.from_pretrained(
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_MODEL_NAME
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)
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self.model_for_masked_lm: AutoModelForMaskedLM = (
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AutoModelForMaskedLM.from_pretrained(_MODEL_NAME)
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)
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self.model: Pipeline = pipeline(
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"fill-mask",
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tokenizer=self.tokenizer,

pythainlp/augment/lm/wangchanberta.py

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self.model_name: str = "airesearch/wangchanberta-base-att-spm-uncased"
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self.target_tokenizer: type[CamembertTokenizer] = CamembertTokenizer
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self.tokenizer: CamembertTokenizer = CamembertTokenizer.from_pretrained(
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self.model_name, revision="main"
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self.tokenizer: CamembertTokenizer = (
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CamembertTokenizer.from_pretrained(
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self.model_name, revision="main"
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)
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)
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self.tokenizer.additional_special_tokens = [
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"<s>NOTUSED",

pythainlp/augment/word2vec/bpemb_wv.py

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# output: ['ผมสอน', 'ผมเข้าเรียน']
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"""
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self.sentence: str = sentence.replace(" ", "▁")
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self.temp: list[tuple[str, ...]] = self.aug.augment(self.sentence, n_sent, p=p)
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self.temp: list[tuple[str, ...]] = self.aug.augment(
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self.sentence, n_sent, p=p
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)
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self.temp_new: list[str] = []
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for i in self.temp:
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self.t: str = ""

pythainlp/augment/word2vec/core.py

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from __future__ import annotations
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import itertools
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from typing import TYPE_CHECKING, Callable
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from typing import TYPE_CHECKING, Callable, Union
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if TYPE_CHECKING:
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from gensim.models.keyedvectors import KeyedVectors
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def __init__(
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self,
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model: str,
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model: Union[str, "KeyedVectors"],
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tokenize: Callable[[str], list[str]],
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type: str = "file",
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) -> None:
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""":param str model: path of model
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""":param Union[str, KeyedVectors] model: path of model or KeyedVectors instance
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:param Callable[[str], list[str]] tokenize: tokenize function
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:param str type: model type (file, binary)
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:param str type: model type (file, binary, model)
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"""
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import gensim.models.keyedvectors as word2vec
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self.tokenizer: Callable[[str], list[str]] = tokenize
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if type == "file":
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self.model: "KeyedVectors" = word2vec.KeyedVectors.load_word2vec_format(model)
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self.model = word2vec.KeyedVectors.load_word2vec_format(model)
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elif type == "binary":
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self.model: "KeyedVectors" = word2vec.KeyedVectors.load_word2vec_format(
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self.model = word2vec.KeyedVectors.load_word2vec_format(
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model, binary=True, unicode_errors="ignore"
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)
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else:
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self.model: "KeyedVectors" = model # type: ignore[assignment]
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self.model = model
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self.dict_wv: list[str] = list(self.model.key_to_index.keys())
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def modify_sent(self, sent: list[str], p: float = 0.7) -> list[list[str]]:

pythainlp/augment/word2vec/ltw2v.py

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"LTW2V word2vec model not found. "
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"Please download it first using pythainlp.corpus.download('ltw2v_wv')"
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)
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self.aug: Word2VecAug = Word2VecAug(self.ltw2v_wv, self.tokenizer, type="binary")
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self.aug: Word2VecAug = Word2VecAug(
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self.ltw2v_wv, self.tokenizer, type="binary"
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)
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def augment(
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self, sentence: str, n_sent: int = 1, p: float = 0.7

pythainlp/augment/word2vec/thai2fit.py

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"Thai2Fit word2vec model not found. "
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"Please download it first using pythainlp.corpus.download('thai2fit_wv')"
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)
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self.aug: Word2VecAug = Word2VecAug(self.thai2fit_wv, self.tokenizer, type="binary")
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self.aug: Word2VecAug = Word2VecAug(
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self.thai2fit_wv, self.tokenizer, type="binary"
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)
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def augment(
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self, sentence: str, n_sent: int = 1, p: float = 0.7

pythainlp/augment/wordnet.py

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else:
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self.p2w_pos: Optional[str] = postype2wordnet(pos, postag_corpus)
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if self.p2w_pos != "":
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self.list_synsets: list = wordnet.synsets(word, pos=self.p2w_pos)
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self.list_synsets: list = wordnet.synsets(
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word, pos=self.p2w_pos
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)
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else:
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self.list_synsets: list = wordnet.synsets(word)
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