vrr/koboldcpp
2
0
Fork 0
mirror of https://github.com/LostRuins/koboldcpp.git synced 2026-04-28 03:30:20 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions 3

ci : switch from pyright to ty (#20826)

Browse source 
* type fixes

* switch to ty

* tweak rules

* tweak more rules

* more tweaks

* final tweak

* use common import-not-found rule
This commit is contained in:
Sigbjørn Skjæret 2026-03-21 08:54:34 +01:00 • committed by GitHub
parent cea560f483
commit 29b28a9824
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
20 changed files with 181 additions and 124 deletions
Download patch file Download diff file Expand all files Collapse all files

9
examples/json_schema_to_grammar.py
View file

@ -28,9 +28,6 @@ def _build_repetition(item_rule, min_items, max_items, separator_rule=None):
return f'({result})?' if min_items == 0 else result
def _generate_min_max_int(min_value: Optional[int], max_value: Optional[int], out: list, decimals_left: int = 16, top_level: bool = True):
has_min = min_value != None
has_max = max_value != None
def digit_range(from_char: str, to_char: str):
out.append("[")
if from_char == to_char:
@ -106,7 +103,7 @@ def _generate_min_max_int(min_value: Optional[int], max_value: Optional[int], ou
out.append(to_str[i])
out.append("]")
if has_min and has_max:
if min_value is not None and max_value is not None:
if min_value < 0 and max_value < 0:
out.append("\"-\" (")
_generate_min_max_int(-max_value, -min_value, out, decimals_left, top_level=True)
@ -133,7 +130,7 @@ def _generate_min_max_int(min_value: Optional[int], max_value: Optional[int], ou
less_decimals = max(decimals_left - 1, 1)
if has_min:
if min_value is not None:
if min_value < 0:
out.append("\"-\" (")
_generate_min_max_int(None, -min_value, out, decimals_left, top_level=False)
@ -177,7 +174,7 @@ def _generate_min_max_int(min_value: Optional[int], max_value: Optional[int], ou
more_digits(length - 1, less_decimals)
return
if has_max:
if max_value is not None:
if max_value >= 0:
if top_level:
out.append("\"-\" [1-9] ")

16
examples/model-conversion/scripts/embedding/run-original-model.py
View file

@ -64,7 +64,7 @@ def load_model_and_tokenizer(model_path, use_sentence_transformers=False, device
print("Using SentenceTransformer to apply all numbered layers")
model = SentenceTransformer(model_path)
tokenizer = model.tokenizer
config = model[0].auto_model.config # type: ignore
config = model[0].auto_model.config
else:
tokenizer = AutoTokenizer.from_pretrained(model_path)
config = AutoConfig.from_pretrained(model_path, trust_remote_code=True)
@ -108,8 +108,8 @@ def load_model_and_tokenizer(model_path, use_sentence_transformers=False, device
print(f"Model file: {type(model).__module__}")
# Verify the model is using the correct sliding window
if hasattr(model.config, 'sliding_window'): # type: ignore
print(f"Model's sliding_window: {model.config.sliding_window}") # type: ignore
if hasattr(model.config, 'sliding_window'):
print(f"Model's sliding_window: {model.config.sliding_window}")
else:
print("Model config does not have sliding_window attribute")
@ -152,7 +152,7 @@ def main():
device = next(model.parameters()).device
else:
# For SentenceTransformer, get device from the underlying model
device = next(model[0].auto_model.parameters()).device # type: ignore
device = next(model[0].auto_model.parameters()).device
model_name = os.path.basename(model_path)
@ -177,7 +177,7 @@ def main():
print(f"{token_id:6d} -> '{token_str}'")
print(f"Embeddings shape (after all SentenceTransformer layers): {all_embeddings.shape}")
print(f"Embedding dimension: {all_embeddings.shape[1] if len(all_embeddings.shape) > 1 else all_embeddings.shape[0]}") # type: ignore
print(f"Embedding dimension: {all_embeddings.shape[1] if len(all_embeddings.shape) > 1 else all_embeddings.shape[0]}")
else:
# Standard approach: use base model output only
encoded = tokenizer(
@ -205,12 +205,12 @@ def main():
print(f"Embedding dimension: {all_embeddings.shape[1]}")
if len(all_embeddings.shape) == 1:
n_embd = all_embeddings.shape[0] # type: ignore
n_embd = all_embeddings.shape[0]
n_embd_count = 1
all_embeddings = all_embeddings.reshape(1, -1)
else:
n_embd = all_embeddings.shape[1] # type: ignore
n_embd_count = all_embeddings.shape[0] # type: ignore
n_embd = all_embeddings.shape[1]
n_embd_count = all_embeddings.shape[0]
print()

2
examples/model-conversion/scripts/utils/compare_tokens.py
View file

@ -2,7 +2,7 @@
import argparse
import sys
from common import compare_tokens # type: ignore
from common import compare_tokens # type: ignore[import-not-found]
def parse_arguments():

10
examples/pydantic_models_to_grammar.py
View file

@ -6,7 +6,7 @@ import re
from copy import copy
from enum import Enum
from inspect import getdoc, isclass
from typing import TYPE_CHECKING, Any, Callable, List, Optional, Union, get_args, get_origin, get_type_hints
from typing import TYPE_CHECKING, Any, Callable, Optional, Union, get_args, get_origin, get_type_hints
from docstring_parser import parse
from pydantic import BaseModel, create_model
@ -1158,7 +1158,7 @@ def create_dynamic_model_from_function(func: Callable[..., Any]):
# Assert that the parameter has a type annotation
if param.annotation == inspect.Parameter.empty:
raise TypeError(f"Parameter '{param.name}' in function '{func.__name__}' lacks a type annotation")
raise TypeError(f"""Parameter '{param.name}' in function '{getattr(func, "__name__", "")}' lacks a type annotation""")
# Find the parameter's description in the docstring
param_doc = next((d for d in docstring.params if d.arg_name == param.name), None)
@ -1166,7 +1166,7 @@ def create_dynamic_model_from_function(func: Callable[..., Any]):
# Assert that the parameter has a description
if not param_doc or not param_doc.description:
raise ValueError(
f"Parameter '{param.name}' in function '{func.__name__}' lacks a description in the docstring")
f"""Parameter '{param.name}' in function '{getattr(func, "__name__", "")}' lacks a description in the docstring""")
# Add parameter details to the schema
param_docs.append((param.name, param_doc))
@ -1177,7 +1177,7 @@ def create_dynamic_model_from_function(func: Callable[..., Any]):
dynamic_fields[param.name] = (
param.annotation if param.annotation != inspect.Parameter.empty else str, default_value)
# Creating the dynamic model
dynamic_model = create_model(f"{func.__name__}", **dynamic_fields)
dynamic_model = create_model(f"{getattr(func, '__name__')}", **dynamic_fields)
for name, param_doc in param_docs:
dynamic_model.model_fields[name].description = param_doc.description
@ -1285,7 +1285,7 @@ def convert_dictionary_to_pydantic_model(dictionary: dict[str, Any], model_name:
if items != {}:
array = {"properties": items}
array_type = convert_dictionary_to_pydantic_model(array, f"{model_name}_{field_name}_items")
fields[field_name] = (List[array_type], ...)
fields[field_name] = (list[array_type], ...) # ty: ignore[invalid-type-form]
else:
fields[field_name] = (list, ...)
elif field_type == "object":