| { |
| "schema": "qfs.upstream-code-audit.v1", |
| "upstream": { |
| "repository": "moonshotai/Kimi-K3", |
| "revision": "f831ab66814297da540d832a5235f8e904f29d06" |
| }, |
| "executed_during_audit": false, |
| "weights_downloaded": false, |
| "files": [ |
| { |
| "file": "configuration_kimi_k3.py", |
| "sha256": "735eb9ebe593e17d231e08e1df7f7be9b5ee0e079f511aa201f9572077b416ae", |
| "bytes": 11343, |
| "imports": [ |
| { |
| "line": 1, |
| "statement": "from typing import Optional" |
| }, |
| { |
| "line": 3, |
| "statement": "from transformers.configuration_utils import PretrainedConfig" |
| } |
| ], |
| "effect_related_calls": [], |
| "top_level_nodes": [] |
| }, |
| { |
| "file": "encoding_k3.py", |
| "sha256": "49ff03305fdc4be26867972788d36150b67f8a9e852e62bb7959d87482223676", |
| "bytes": 26304, |
| "imports": [ |
| { |
| "line": 9, |
| "statement": "from __future__ import annotations" |
| }, |
| { |
| "line": 11, |
| "statement": "import json" |
| }, |
| { |
| "line": 12, |
| "statement": "from dataclasses import dataclass" |
| }, |
| { |
| "line": 13, |
| "statement": "from typing import Any, Iterable, Optional" |
| } |
| ], |
| "effect_related_calls": [ |
| { |
| "line": 498, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 526, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 577, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 519, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 532, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 626, |
| "call": "_internal_system_message" |
| }, |
| { |
| "line": 706, |
| "call": "_internal_system_message" |
| }, |
| { |
| "line": 725, |
| "call": "_internal_system_message" |
| }, |
| { |
| "line": 746, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 747, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 536, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 648, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 714, |
| "call": "_internal_system_message" |
| }, |
| { |
| "line": 735, |
| "call": "_internal_system_message" |
| }, |
| { |
| "line": 541, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 547, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 658, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 680, |
| "call": "_open_tag" |
| }, |
| { |
| "line": 694, |
| "call": "_open_tag" |
| } |
| ], |
| "top_level_nodes": [ |
| { |
| "line": 1, |
| "code": "'Kimi K3 XTML encoding helpers.\\n\\nThis module keeps chat rendering in Python.\\nCallers that need token IDs should consume ``EncodeSegment`` objects directly:\\nstructural markers may be encoded as tiktoken special tokens, while user/tool\\ntext and attribute values are encoded as ordinary text.\\n'" |
| }, |
| { |
| "line": 15, |
| "code": "OPEN_TOKEN = '<|open|>'" |
| }, |
| { |
| "line": 16, |
| "code": "CLOSE_TOKEN = '<|close|>'" |
| }, |
| { |
| "line": 17, |
| "code": "SEP_TOKEN = '<|sep|>'" |
| }, |
| { |
| "line": 18, |
| "code": "END_OF_MSG_TOKEN = '<|end_of_msg|>'" |
| }, |
| { |
| "line": 19, |
| "code": "IMAGE_PLACEHOLDER = '<|kimi_image_placeholder|>'" |
| }, |
| { |
| "line": 21, |
| "code": "_VALID_THINKING_EFFORTS = {'low', 'high', 'max'}" |
| }, |
| { |
| "line": 193, |
| "code": "XtmlArgument = tuple[str, str, str]" |
| } |
| ] |
| }, |
| { |
| "file": "kimi_k3_processor.py", |
| "sha256": "ec9f7e86d2ab0eee07a8e7e7c037046e77ac3c25a710ad1298ec13be3b585b54", |
| "bytes": 7660, |
| "imports": [ |
| { |
| "line": 7, |
| "statement": "from transformers.feature_extraction_utils import BatchFeature" |
| }, |
| { |
| "line": 8, |
| "statement": "from transformers.processing_utils import ProcessorMixin" |
| }, |
| { |
| "line": 9, |
| "statement": "from transformers.utils import logging" |
| }, |
| { |
| "line": 11, |
| "statement": "from .media_utils import ensure_media_type" |
| } |
| ], |
| "effect_related_calls": [], |
| "top_level_nodes": [ |
| { |
| "line": 1, |
| "code": "\"Kimi-K3 processor: wraps vision processor + tokenizer into a single interface.\\n\\nChat rendering (including XTML tool-result ordering) is handled by the\\ntokenizer's Python encoder; this processor adds multimodal media preprocessing.\\n\"" |
| }, |
| { |
| "line": 13, |
| "code": "logger = logging.get_logger(__name__)" |
| } |
| ] |
| }, |
| { |
| "file": "kimi_k3_vision_processing.py", |
| "sha256": "d122b30bfd3a51a6f05d4bfcfda1e657827322b1353f7caefeebc2835d7736b5", |
| "bytes": 6686, |
| "imports": [ |
| { |
| "line": 4, |
| "statement": "import json" |
| }, |
| { |
| "line": 5, |
| "statement": "from typing import Any, Dict, Optional, Union" |
| }, |
| { |
| "line": 7, |
| "statement": "import numpy as np" |
| }, |
| { |
| "line": 8, |
| "statement": "import torch" |
| }, |
| { |
| "line": 9, |
| "statement": "from PIL import Image" |
| }, |
| { |
| "line": 10, |
| "statement": "from transformers.image_processing_utils import BaseImageProcessor, BatchFeature" |
| }, |
| { |
| "line": 12, |
| "statement": "from transformers.utils import TensorType" |
| }, |
| { |
| "line": 14, |
| "statement": "from .media_utils import MediaInput, TransparentBgConfig, _to_tensor, ensure_media_type, image_to_np, navit_patchify, navit_resize_image, normalize" |
| } |
| ], |
| "effect_related_calls": [ |
| { |
| "line": 170, |
| "call": "config_dict.copy" |
| } |
| ], |
| "top_level_nodes": [ |
| { |
| "line": 1, |
| "code": "'Image processor class for Kimi-K3.\\n'" |
| } |
| ] |
| }, |
| { |
| "file": "media_utils.py", |
| "sha256": "78403540328f9847d6b7ebc5c44eb2e6a752863de0afb7d0710728bb161dc60d", |
| "bytes": 13844, |
| "imports": [ |
| { |
| "line": 1, |
| "statement": "import base64" |
| }, |
| { |
| "line": 2, |
| "statement": "import functools" |
| }, |
| { |
| "line": 3, |
| "statement": "import io" |
| }, |
| { |
| "line": 4, |
| "statement": "import math" |
| }, |
| { |
| "line": 5, |
| "statement": "from dataclasses import dataclass" |
| }, |
| { |
| "line": 6, |
| "statement": "from typing import Literal, TypedDict" |
| }, |
| { |
| "line": 8, |
| "statement": "import numpy as np" |
| }, |
| { |
| "line": 9, |
| "statement": "from PIL import Image" |
| }, |
| { |
| "line": 361, |
| "statement": "import torch" |
| } |
| ], |
| "effect_related_calls": [ |
| { |
| "line": 182, |
| "call": "Image.open" |
| }, |
| { |
| "line": 184, |
| "call": "Image.open" |
| }, |
| { |
| "line": 186, |
| "call": "Image.open" |
| } |
| ], |
| "top_level_nodes": [ |
| { |
| "line": 17, |
| "code": "MediaInput = ImageInput" |
| } |
| ] |
| }, |
| { |
| "file": "modeling_kimi_k3.py", |
| "sha256": "b9171c96726eda55234c92ac8dfae7e24c512fda68968ae8f2c3782b42665ea2", |
| "bytes": 53444, |
| "imports": [ |
| { |
| "line": 25, |
| "statement": "import math" |
| }, |
| { |
| "line": 26, |
| "statement": "from collections.abc import Sequence" |
| }, |
| { |
| "line": 27, |
| "statement": "from copy import deepcopy" |
| }, |
| { |
| "line": 28, |
| "statement": "from typing import Optional" |
| }, |
| { |
| "line": 30, |
| "statement": "import numpy as np" |
| }, |
| { |
| "line": 31, |
| "statement": "import torch" |
| }, |
| { |
| "line": 32, |
| "statement": "import torch.nn as nn" |
| }, |
| { |
| "line": 33, |
| "statement": "import torch.nn.functional as F" |
| }, |
| { |
| "line": 34, |
| "statement": "from transformers import activations" |
| }, |
| { |
| "line": 42, |
| "statement": "from transformers.activations import PytorchGELUTanh" |
| }, |
| { |
| "line": 43, |
| "statement": "from transformers.configuration_utils import PretrainedConfig" |
| }, |
| { |
| "line": 44, |
| "statement": "from transformers.modeling_utils import PreTrainedModel" |
| }, |
| { |
| "line": 45, |
| "statement": "from transformers.models.llava.modeling_llava import LlavaCausalLMOutputWithPast" |
| }, |
| { |
| "line": 47, |
| "statement": "from transformers.utils import is_flash_attn_2_available" |
| }, |
| { |
| "line": 49, |
| "statement": "from .configuration_kimi_k3 import KimiK3Config" |
| }, |
| { |
| "line": 50, |
| "statement": "from .modeling_kimi_linear import KimiLinearForCausalLM" |
| }, |
| { |
| "line": 37, |
| "statement": "from transformers.activations import PytorchGELUTanh" |
| }, |
| { |
| "line": 54, |
| "statement": "from flash_attn import flash_attn_varlen_func" |
| }, |
| { |
| "line": 39, |
| "statement": "from transformers.activations import GELUTanh" |
| } |
| ], |
| "effect_related_calls": [ |
| { |
| "line": 658, |
| "call": "deepcopy" |
| } |
| ], |
| "top_level_nodes": [ |
| { |
| "line": 36, |
| "code": "try:\n from transformers.activations import PytorchGELUTanh\nexcept ImportError:\n from transformers.activations import GELUTanh\n activations.PytorchGELUTanh = GELUTanh\n PytorchGELUTanh = GELUTanh" |
| }, |
| { |
| "line": 53, |
| "code": "if is_flash_attn_2_available():\n from flash_attn import flash_attn_varlen_func\nelse:\n flash_attn_varlen_func = None" |
| }, |
| { |
| "line": 136, |
| "code": "VL_VISION_ATTENTION_FUNCTIONS = {'flash_attention_2': multihead_attention, 'eager': eager_attention}" |
| } |
| ] |
| }, |
| { |
| "file": "modeling_kimi_linear.py", |
| "sha256": "9e3564c70ac21854ce5a090cc946c5dc76b70d1050ef50840449181a20fff44a", |
| "bytes": 51506, |
| "imports": [ |
| { |
| "line": 24, |
| "statement": "import math" |
| }, |
| { |
| "line": 25, |
| "statement": "from collections.abc import Callable" |
| }, |
| { |
| "line": 26, |
| "statement": "from typing import Any" |
| }, |
| { |
| "line": 28, |
| "statement": "import torch" |
| }, |
| { |
| "line": 29, |
| "statement": "import torch.nn.functional as F" |
| }, |
| { |
| "line": 30, |
| "statement": "import transformers" |
| }, |
| { |
| "line": 31, |
| "statement": "from einops import rearrange" |
| }, |
| { |
| "line": 32, |
| "statement": "from packaging import version" |
| }, |
| { |
| "line": 33, |
| "statement": "from torch import nn" |
| }, |
| { |
| "line": 34, |
| "statement": "from transformers.activations import ACT2FN" |
| }, |
| { |
| "line": 35, |
| "statement": "from transformers.cache_utils import Cache" |
| }, |
| { |
| "line": 36, |
| "statement": "from transformers.generation import GenerationMixin" |
| }, |
| { |
| "line": 37, |
| "statement": "from transformers.masking_utils import create_causal_mask" |
| }, |
| { |
| "line": 38, |
| "statement": "from transformers.modeling_flash_attention_utils import FlashAttentionKwargs" |
| }, |
| { |
| "line": 39, |
| "statement": "from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast" |
| }, |
| { |
| "line": 40, |
| "statement": "from transformers.modeling_utils import ALL_ATTENTION_FUNCTIONS, PreTrainedModel" |
| }, |
| { |
| "line": 41, |
| "statement": "from transformers.processing_utils import Unpack" |
| }, |
| { |
| "line": 42, |
| "statement": "from transformers.pytorch_utils import ALL_LAYERNORM_LAYERS" |
| }, |
| { |
| "line": 43, |
| "statement": "from transformers.utils import TransformersKwargs, auto_docstring, can_return_tuple, logging" |
| }, |
| { |
| "line": 44, |
| "statement": "from transformers.utils.generic import OutputRecorder, check_model_inputs" |
| }, |
| { |
| "line": 55, |
| "statement": "from .configuration_kimi_k3 import KimiLinearConfig" |
| }, |
| { |
| "line": 47, |
| "statement": "from fla.modules import FusedRMSNormGated, ShortConvolution" |
| }, |
| { |
| "line": 48, |
| "statement": "from fla.ops.kda import chunk_kda, fused_recurrent_kda" |
| }, |
| { |
| "line": 50, |
| "statement": "from fla.ops.utils.index import prepare_cu_seqlens_from_mask, prepare_lens_from_mask" |
| }, |
| { |
| "line": 51, |
| "statement": "from fla.utils import tensor_cache" |
| }, |
| { |
| "line": 699, |
| "statement": "import torch.nn.init as init" |
| } |
| ], |
| "effect_related_calls": [], |
| "top_level_nodes": [ |
| { |
| "line": 46, |
| "code": "try:\n from fla.modules import FusedRMSNormGated, ShortConvolution\n from fla.ops.kda import chunk_kda, fused_recurrent_kda\n from fla.ops.utils.index import prepare_cu_seqlens_from_mask, prepare_lens_from_mask\n from fla.utils import tensor_cache\nexcept ImportError:\n raise ImportError('Plese run `pip install -U fla-core`')" |
| }, |
| { |
| "line": 57, |
| "code": "assert version.parse(transformers.__version__) >= version.parse('4.56.0'), 'Please upgrade transformers to >= 4.56.0'" |
| }, |
| { |
| "line": 60, |
| "code": "logger = logging.get_logger(__name__)" |
| }, |
| { |
| "line": 85, |
| "code": "ACT2FN['situ'] = SituAndMul" |
| }, |
| { |
| "line": 239, |
| "code": "ALL_LAYERNORM_LAYERS.append(KimiRMSNorm)" |
| } |
| ] |
| }, |
| { |
| "file": "tokenization_kimi.py", |
| "sha256": "f28ea66e2d862a2a5814970b2ce40c2f7d8296ff09aed90a7e7def689b906944", |
| "bytes": 16145, |
| "imports": [ |
| { |
| "line": 1, |
| "statement": "import os" |
| }, |
| { |
| "line": 2, |
| "statement": "from logging import getLogger" |
| }, |
| { |
| "line": 3, |
| "statement": "from pathlib import Path" |
| }, |
| { |
| "line": 4, |
| "statement": "from shutil import copyfile" |
| }, |
| { |
| "line": 5, |
| "statement": "from typing import Dict, Iterator, List, Optional, Tuple, Union, cast" |
| }, |
| { |
| "line": 7, |
| "statement": "import tiktoken" |
| }, |
| { |
| "line": 8, |
| "statement": "from tiktoken.load import load_tiktoken_bpe" |
| }, |
| { |
| "line": 9, |
| "statement": "from tokenizers import AddedToken" |
| }, |
| { |
| "line": 10, |
| "statement": "from transformers.convert_slow_tokenizer import bytes_to_unicode" |
| }, |
| { |
| "line": 11, |
| "statement": "from transformers.tokenization_utils import PreTrainedTokenizer" |
| }, |
| { |
| "line": 14, |
| "statement": "from .encoding_k3 import build_chat_segments, is_batched_conversation" |
| }, |
| { |
| "line": 16, |
| "statement": "from encoding_k3 import build_chat_segments, is_batched_conversation" |
| } |
| ], |
| "effect_related_calls": [ |
| { |
| "line": 99, |
| "call": "load_tiktoken_bpe" |
| }, |
| { |
| "line": 353, |
| "call": "copyfile" |
| } |
| ], |
| "top_level_nodes": [ |
| { |
| "line": 13, |
| "code": "try:\n from .encoding_k3 import build_chat_segments, is_batched_conversation\nexcept ImportError:\n from encoding_k3 import build_chat_segments, is_batched_conversation" |
| }, |
| { |
| "line": 18, |
| "code": "logger = getLogger(__name__)" |
| }, |
| { |
| "line": 19, |
| "code": "VOCAB_FILES_NAMES = {'vocab_file': 'tiktoken.model'}" |
| } |
| ] |
| } |
| ], |
| "license": "Kimi K3 License for Moonshot code with Apache-2.0 adapted portions; FLA reference adaptations MIT. All three license texts retained.", |
| "import_time_effects": [ |
| "Imports Python/NumPy/Torch/Transformers; upstream K3 hard imports FLA and imports/registry-mutates ACT2FN and ALL_LAYERNORM_LAYERS.", |
| "Upstream processor/tokenizer closure is not used by fixture: byte tokenizer is authored independently. tiktoken load_tiktoken_bpe can read local or remote vocabulary at tokenizer construction. media_utils reads image filenames/data on explicit invocation, not import.", |
| "No subprocess, shell, eval/exec, socket, network request, or model-weight load found in upstream module import-time statements. Decorators and dependency imports execute library initialization. This is source review, not sandboxing." |
| ], |
| "runtime_scope": "Four-file patched full Kimi K3 wrapper closure plus installed torch/numpy/transformers. CPU reference math replaces FLA imports entirely; no lazy or eager GPU dependency imports from text runtime. Vision keeps conditional flash-attn import and executes original eager or true Torch SDPA attention on CPU, according to the actual loaded backend.", |
| "network_policy": "No upstream model weights fetched. Custom capture explicitly permits pinned code metadata/download from the selected private model repo; local model weights. Not entirely offline capture. Comparison independent of code and GPU.", |
| "patch_provenance": "runtime-patches.json; cpu_reference.py; reference/pin.json", |
| "review_limitations": "Static source review is not a security guarantee. Dependency implementations belong to the pinned environment. Main must run all runtime checks before release.", |
| "reference_sources": { |
| "LICENSE": { |
| "sha256": "41a83c8187efc1e3ccc21909e806a9e52338e69448554d9754706c3d1cd610e7", |
| "bytes": 1096 |
| }, |
| "convolution.py": { |
| "sha256": "2ab60fc508097457a2ad01dd1f6602ed7e1b47d8a2468949944402b7d5451b8a", |
| "bytes": 1194 |
| }, |
| "fused_norm_gate.py": { |
| "sha256": "109de719d6f9b4e692e3fd504eda4a6e897156c8dc9ac464a6f94193fa94d677", |
| "bytes": 40532 |
| }, |
| "gate.py": { |
| "sha256": "7ea46d62149b8e28e0827e070fee327576de783cb981e3b855182f2b8198c16e", |
| "bytes": 15758 |
| }, |
| "l2norm.py": { |
| "sha256": "5160cc4ff716c9975c655b81fd0e1bae700501dff3b4d6b045680a93185a1e99", |
| "bytes": 7792 |
| }, |
| "naive.py": { |
| "sha256": "60a32285d4b67068ff633b48bbe8ab31028066d24f00d27e12199a88fc73f016", |
| "bytes": 6339 |
| }, |
| "pin.json": { |
| "sha256": "b99a0f4427f07729fc1bde070e48a1814c395f413a8103ff6828cb36bd94ca47", |
| "bytes": 111 |
| }, |
| "short_conv.py": { |
| "sha256": "e2ee319f11b0421545ea5eaa233f12f91e6904ce3dba83cee04a4b25110e6afe", |
| "bytes": 10389 |
| } |
| }, |
| "patched_runtime_sources": { |
| "__init__.py": { |
| "sha256": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855", |
| "bytes": 0 |
| }, |
| "configuration_kimi_k3.py": { |
| "sha256": "735eb9ebe593e17d231e08e1df7f7be9b5ee0e079f511aa201f9572077b416ae", |
| "bytes": 11343 |
| }, |
| "cpu_reference.py": { |
| "sha256": "f5ab2904ea43b434bcc17fb61a104f6c2975e5f52a39cffbbcfa94b358350e4e", |
| "bytes": 5976 |
| }, |
| "modeling_kimi_k3.py": { |
| "sha256": "344de6dfed495bd6e66e1d16abac12ba6cfd222e872b15ad73003f38462f35af", |
| "bytes": 54765 |
| }, |
| "modeling_kimi_linear.py": { |
| "sha256": "94956f39cd28bf211acf70a3e38f469db5d24637b76a4f58b0b096527bb70df5", |
| "bytes": 50914 |
| } |
| }, |
| "generation_compatibility": "Root directly inherits GenerationMixin; keeps upstream prepare_inputs_for_generation slicing; migrates cached image mask and beam cache access to KimiDynamicCache.", |
| "dtype_initialization": "Untouched FP32 initialization -> temporary FP32 checkpoint -> actual BF16 loader selecting FP32-retained parameters -> per-tensor original.to(target_dtype) equality -> final exact mixed-dtype save/reload. No pre-rounding of sensitive parameters.", |
| "vision_backend": "Original eager/FlashAttention2 dispatch plus true Torch SDPA packed-clip path. Backend-specific floating-point equivalence is not claimed." |
| } |
|
|
