repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/engine/protocol.py | vllm/engine/protocol.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from abc import ABC, abstractmethod
from collections.abc import AsyncGenerator, Iterable, Mapping
from typing import Any
from vllm.config import ModelConfig, VllmConfig
from vllm.inputs.data import PromptType
fr... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/engine/async_llm_engine.py | vllm/engine/async_llm_engine.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm.v1.engine.async_llm import AsyncLLM
AsyncLLMEngine = AsyncLLM # type: ignore
| python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/logging_utils/lazy.py | vllm/logging_utils/lazy.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from collections.abc import Callable
from typing import Any
class lazy:
"""Wrap a zero-argument callable evaluated only during log formatting."""
__slots__ = ("_factory",)
def __init__(self, facto... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/logging_utils/formatter.py | vllm/logging_utils/formatter.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import logging
from pathlib import Path
from vllm import envs
class NewLineFormatter(logging.Formatter):
"""Adds logging prefix to newlines to align multi-line messages."""
def __init__(self, fmt, dat... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/logging_utils/__init__.py | vllm/logging_utils/__init__.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm.logging_utils.formatter import ColoredFormatter, NewLineFormatter
from vllm.logging_utils.lazy import lazy
from vllm.logging_utils.log_time import logtime
__all__ = [
"NewLineFormatter",
"Color... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/logging_utils/dump_input.py | vllm/logging_utils/dump_input.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import contextlib
import enum
import json
import torch
from vllm.config import VllmConfig
from vllm.logger import init_logger
from vllm.v1.core.sched.output import SchedulerOutput
from vllm.v1.metrics.stats imp... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/logging_utils/log_time.py | vllm/logging_utils/log_time.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Provides a timeslice logging decorator
"""
import functools
import time
def logtime(logger, msg=None):
"""
Logs the execution time of the decorated function.
Always place it beneath other decora... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/tokenizers/deepseek_v32_encoding.py | vllm/tokenizers/deepseek_v32_encoding.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
# copy from https://huggingface.co/deepseek-ai/DeepSeek-V3.2/blob/main/encoding/encoding_dsv32.py
import copy
import json
from typing import Any
import regex as re
# flake8: noqa: E501
TOOLS_SYSTEM_TEMPLATE = ... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/tokenizers/registry.py | vllm/tokenizers/registry.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import importlib.util
from dataclasses import dataclass, field
from functools import lru_cache
from pathlib import Path
from typing import TYPE_CHECKING
import huggingface_hub
from typing_extensions import TypeVa... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/tokenizers/detokenizer_utils.py | vllm/tokenizers/detokenizer_utils.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm.tokenizers import TokenizerLike
def _replace_none_with_empty(tokens: list[str | None]):
for i, token in enumerate(tokens):
if token is None:
tokens[i] = ""
def _convert_toke... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/tokenizers/hf.py | vllm/tokenizers/hf.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import contextlib
import copy
from pathlib import Path
from typing import TypeAlias
from transformers import AutoTokenizer, PreTrainedTokenizer, PreTrainedTokenizerFast
from vllm.transformers_utils.config import... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/tokenizers/__init__.py | vllm/tokenizers/__init__.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from .protocol import TokenizerLike
from .registry import (
TokenizerRegistry,
cached_get_tokenizer,
cached_tokenizer_from_config,
get_tokenizer,
)
__all__ = [
"TokenizerLike",
"Tokenizer... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/tokenizers/protocol.py | vllm/tokenizers/protocol.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from pathlib import Path
from typing import TYPE_CHECKING, Any, Protocol
if TYPE_CHECKING:
from transformers import BatchEncoding
from vllm.entrypoints.chat_utils import ChatCompletionMessageParam
clas... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/tokenizers/deepseek_v32.py | vllm/tokenizers/deepseek_v32.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from pathlib import Path
from typing import Any
from transformers import BatchEncoding
from vllm.entrypoints.chat_utils import ChatCompletionMessageParam
from .deepseek_v32_encoding import encode_messages
from... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/tokenizers/mistral.py | vllm/tokenizers/mistral.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from pathlib import Path
from typing import TYPE_CHECKING, Any, cast
from mistral_common.protocol.instruct.request import (
ChatCompletionRequest as MistralChatCompletionRequest,
)
from mistral_common.protoco... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/peft_helper.py | vllm/lora/peft_helper.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
# Adapted from: https://github.com/huggingface/peft/blob/main/src/peft/tuners/lora/config.py
import json
import math
import os
from dataclasses import MISSING, dataclass, field, fields
from typing import Literal... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/worker_manager.py | vllm/lora/worker_manager.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from contextlib import contextmanager
from typing import Any, Literal
import torch
from vllm.config import VllmConfig
from vllm.logger import init_logger
from vllm.lora.lora_model import LoRAModel
from vllm.lor... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/resolver.py | vllm/lora/resolver.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from abc import ABC, abstractmethod
from collections.abc import Set
from dataclasses import dataclass, field
from vllm.logger import init_logger
from vllm.lora.request import LoRARequest
logger = init_logger(__... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/lora_model.py | vllm/lora/lora_model.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import os
import safetensors
import torch
from vllm.logger import init_logger
from vllm.lora.lora_weights import LoRALayerWeights
from vllm.lora.peft_helper import PEFTHelper
from vllm.lora.utils import (
g... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/request.py | vllm/lora/request.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import msgspec
class LoRARequest(
msgspec.Struct,
omit_defaults=True, # type: ignore[call-arg]
array_like=True,
): # type: ignore[call-arg]
"""
Request for a LoRA adapter.
lora_int_i... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/utils.py | vllm/lora/utils.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import os
from typing import TYPE_CHECKING, Optional
import huggingface_hub
from huggingface_hub.utils import (
EntryNotFoundError,
HfHubHTTPError,
HFValidationError,
RepositoryNotFoundError,
)
f... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/model_manager.py | vllm/lora/model_manager.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import math
from collections.abc import Callable
from typing import TypeVar
import regex as re
import torch
from torch import nn
from vllm.config import VllmConfig
from vllm.config.lora import LoRAConfig, Model... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | true |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/__init__.py | vllm/lora/__init__.py | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false | |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/lora_weights.py | vllm/lora/lora_weights.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from collections.abc import Sequence as GenericSequence
from typing import Optional
import torch
import torch.types
from vllm.lora.peft_helper import PEFTHelper
from vllm.utils.platform_utils import is_pin_memo... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/punica_wrapper/punica_base.py | vllm/lora/punica_wrapper/punica_base.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Based on:
Chen, L., Ye, Z., Wu, Y., Zhuo, D., Ceze, L., & Krishnamurthy, A. (2023).
Punica: Multi-Tenant LoRA Serving.
https://arxiv.org/abs/2310.18547
"""
from abc import ABC, abstractmethod
from typing impo... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/punica_wrapper/punica_xpu.py | vllm/lora/punica_wrapper/punica_xpu.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Based on:
Chen, L., Ye, Z., Wu, Y., Zhuo, D., Ceze, L., & Krishnamurthy, A. (2023).
Punica: Multi-Tenant LoRA Serving.
https://arxiv.org/abs/2310.18547
"""
from typing import final
import torch
from vllm.lo... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/punica_wrapper/punica_tpu.py | vllm/lora/punica_wrapper/punica_tpu.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import math
from typing import TYPE_CHECKING
import torch
import torch.nn.functional as F
import torch_xla
from vllm.lora.ops.xla_ops import bgmv_expand, bgmv_expand_slice, bgmv_shrink
from vllm.lora.punica_wra... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/punica_wrapper/punica_cpu.py | vllm/lora/punica_wrapper/punica_cpu.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from collections.abc import Callable
import torch
from vllm.lora.ops.torch_ops import (
bgmv_expand,
bgmv_expand_slice,
bgmv_shrink,
sgmv_expand,
sgmv_expand_slice,
sgmv_shrink,
)
from ... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/punica_wrapper/utils.py | vllm/lora/punica_wrapper/utils.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from typing import TYPE_CHECKING
import torch
if TYPE_CHECKING:
# avoid circuit import
from vllm.lora.layers import LoRAMapping
def compute_meta(
token_lora_tensor: torch.Tensor,
) -> tuple[torch.... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/punica_wrapper/__init__.py | vllm/lora/punica_wrapper/__init__.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm.lora.punica_wrapper.punica_base import PunicaWrapperBase
from vllm.lora.punica_wrapper.punica_selector import get_punica_wrapper
__all__ = [
"PunicaWrapperBase",
"get_punica_wrapper",
]
| python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/punica_wrapper/punica_gpu.py | vllm/lora/punica_wrapper/punica_gpu.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Based on:
Chen, L., Ye, Z., Wu, Y., Zhuo, D., Ceze, L., & Krishnamurthy, A. (2023).
Punica: Multi-Tenant LoRA Serving.
https://arxiv.org/abs/2310.18547
"""
from typing import final
import torch
from vllm.lo... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/punica_wrapper/punica_selector.py | vllm/lora/punica_wrapper/punica_selector.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm.logger import init_logger
from vllm.platforms import current_platform
from vllm.utils.import_utils import resolve_obj_by_qualname
from .punica_base import PunicaWrapperBase
logger = init_logger(__name... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/layers/row_parallel_linear.py | vllm/lora/layers/row_parallel_linear.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import torch
import torch.nn as nn
from transformers import PretrainedConfig
from vllm.config.lora import LoRAConfig
from vllm.distributed import (
split_tensor_along_last_dim,
tensor_model_parallel_all... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/layers/logits_processor.py | vllm/lora/layers/logits_processor.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import torch
import torch.nn as nn
from transformers import PretrainedConfig
from vllm.config.lora import LoRAConfig
from vllm.distributed import (
get_tensor_model_parallel_rank,
get_tensor_model_paral... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/layers/base_linear.py | vllm/lora/layers/base_linear.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import torch
from transformers import PretrainedConfig
from vllm.config.lora import LoRAConfig
from vllm.distributed.utils import divide
from vllm.model_executor.layers.linear import (
ColumnParallelLinear,... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/layers/utils.py | vllm/lora/layers/utils.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from dataclasses import dataclass
from enum import Enum
import torch
import torch.nn as nn
class LoRAMappingType(Enum):
LANGUAGE = 1
TOWER = 2
CONNECTOR = 3
@dataclass
class LoRAMapping:
inde... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/layers/column_parallel_linear.py | vllm/lora/layers/column_parallel_linear.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import torch
import torch.nn as nn
from transformers import PretrainedConfig
from vllm.config.lora import LoRAConfig
from vllm.distributed import tensor_model_parallel_all_gather
from vllm.distributed.utils imp... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/layers/vocal_parallel_embedding.py | vllm/lora/layers/vocal_parallel_embedding.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers import PretrainedConfig
from vllm.config.lora import LoRAConfig
from vllm.model_executor.layers.vocab_parallel_embedding impo... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/layers/__init__.py | vllm/lora/layers/__init__.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm.lora.layers.base import BaseLayerWithLoRA
from vllm.lora.layers.column_parallel_linear import (
ColumnParallelLinearWithLoRA,
ColumnParallelLinearWithShardedLoRA,
MergedColumnParallelLinearWi... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/layers/base.py | vllm/lora/layers/base.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from typing import TYPE_CHECKING
import torch
import torch.nn as nn
from transformers import PretrainedConfig
from vllm.config.lora import LoRAConfig
if TYPE_CHECKING:
from vllm.lora.punica_wrapper import ... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/layers/replicated_linear.py | vllm/lora/layers/replicated_linear.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import torch
import torch.nn as nn
from transformers import PretrainedConfig
from vllm.config.lora import LoRAConfig
from vllm.model_executor.layers.linear import ReplicatedLinear
from .base_linear import Base... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/layers/fused_moe.py | vllm/lora/layers/fused_moe.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import functools
import torch
import torch.nn as nn
from transformers import PretrainedConfig
from vllm import envs
from vllm.config.lora import LoRAConfig
from vllm.distributed.parallel_state import (
get_t... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/__init__.py | vllm/lora/ops/__init__.py | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false | |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/torch_ops/lora_ops.py | vllm/lora/ops/torch_ops/lora_ops.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import torch
def sgmv_expand(
inputs: torch.Tensor,
lora_b_weights: torch.Tensor,
output_tensor: torch.Tensor,
b_seq_start_loc: torch.Tensor,
seq_len_tensor: torch.Tensor,
lora_indices_t... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/torch_ops/__init__.py | vllm/lora/ops/torch_ops/__init__.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm.lora.ops.torch_ops.lora_ops import (
bgmv_expand, # noqa: F401
bgmv_expand_slice,
bgmv_shrink,
sgmv_expand,
sgmv_expand_slice,
sgmv_shrink,
)
__all__ = [
"bgmv_expand",
... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/ipex_ops/lora_ops.py | vllm/lora/ops/ipex_ops/lora_ops.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import torch
from vllm.logger import init_logger
logger = init_logger(__name__)
try:
import intel_extension_for_pytorch as ipex
except ImportError as e:
raise e
def bgmv_shrink(
inputs: torch.Ten... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/ipex_ops/__init__.py | vllm/lora/ops/ipex_ops/__init__.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm.lora.ops.ipex_ops.lora_ops import bgmv_expand, bgmv_expand_slice, bgmv_shrink
__all__ = ["bgmv_expand", "bgmv_expand_slice", "bgmv_shrink"]
| python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/triton_ops/lora_kernel_metadata.py | vllm/lora/ops/triton_ops/lora_kernel_metadata.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
LoRA kernels metadata preparation utilities.
"""
from dataclasses import dataclass
import torch
@dataclass
class LoRAKernelMeta:
token_lora_mapping: torch.Tensor
token_indices_sorted_by_lora_ids: t... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/triton_ops/kernel_utils.py | vllm/lora/ops/triton_ops/kernel_utils.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Utilities for Punica kernel construction.
"""
from vllm.triton_utils import tl, triton
@triton.jit
def mm_k(
a_ptr,
b_ptr,
ak_stride,
bk_stride,
offset_k,
K: tl.constexpr,
BLOCK_... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/triton_ops/lora_expand_op.py | vllm/lora/ops/triton_ops/lora_expand_op.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Based on:
Chen, L., Ye, Z., Wu, Y., Zhuo, D., Ceze, L., & Krishnamurthy, A. (2023).
Punica: Multi-Tenant LoRA Serving.
https://arxiv.org/abs/2310.18547
"""
import torch
from vllm.lora.ops.triton_ops.kernel_u... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/triton_ops/fused_moe_lora_op.py | vllm/lora/ops/triton_ops/fused_moe_lora_op.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import torch
from vllm.distributed import (
tensor_model_parallel_all_gather,
tensor_model_parallel_all_reduce,
)
from vllm.triton_utils import tl, triton
from vllm.utils.torch_utils import direct_regist... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/triton_ops/utils.py | vllm/lora/ops/triton_ops/utils.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import functools
import json
from functools import lru_cache
from pathlib import Path
from typing import Any
import torch
from vllm import envs
from vllm.logger import init_logger
from vllm.model_executor.layer... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/triton_ops/__init__.py | vllm/lora/ops/triton_ops/__init__.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm.lora.ops.triton_ops.fused_moe_lora_op import (
fused_moe_lora,
fused_moe_lora_expand,
fused_moe_lora_shrink,
)
from vllm.lora.ops.triton_ops.lora_expand_op import lora_expand
from vllm.lora... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/triton_ops/lora_shrink_op.py | vllm/lora/ops/triton_ops/lora_shrink_op.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
Based on:
Chen, L., Ye, Z., Wu, Y., Zhuo, D., Ceze, L., & Krishnamurthy, A. (2023).
Punica: Multi-Tenant LoRA Serving.
https://arxiv.org/abs/2310.18547
"""
import torch
from vllm.lora.ops.triton_ops.kernel_u... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/xla_ops/lora_ops.py | vllm/lora/ops/xla_ops/lora_ops.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import jax
import jax.numpy as jnp
import torch
import torch.nn.functional as F
import torch_xla.core.xla_builder as xb
from torch.library import impl
from torch_xla.experimental.custom_kernel import XLA_LIB, jax... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/vllm/lora/ops/xla_ops/__init__.py | vllm/lora/ops/xla_ops/__init__.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from vllm.lora.ops.xla_ops.lora_ops import bgmv_expand, bgmv_expand_slice, bgmv_shrink
__all__ = ["bgmv_expand", "bgmv_expand_slice", "bgmv_shrink"]
| python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/csrc/cutlass_extensions/vllm_cutlass_library_extension.py | csrc/cutlass_extensions/vllm_cutlass_library_extension.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import enum
from cutlass_library import *
#
# Extend cutlass library with custom types, and missing values
#
class VLLMDataType(enum.Enum):
u4b8 = enum_auto()
u8b128 = enum_auto()
class MixedInput... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/csrc/quantization/gptq_marlin/generate_kernels.py | csrc/quantization/gptq_marlin/generate_kernels.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import glob
import itertools
import os
import subprocess
import sys
import jinja2
ARCHS = []
SUPPORT_FP8 = False
SUPPORT_SM75 = False
SUPPORT_SM80 = False
for arch in sys.argv[1].split(","):
arch = arch[: ar... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/csrc/quantization/machete/generate.py | csrc/quantization/machete/generate.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import itertools
import math
import os
import shutil
from collections.abc import Iterable
from copy import deepcopy
from dataclasses import dataclass, fields
from functools import reduce
import jinja2
from vllm_... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
vllm-project/vllm | https://github.com/vllm-project/vllm/blob/0d4044edd85de30d7d4558aeea4d1e95c7c556d6/csrc/moe/marlin_moe_wna16/generate_kernels.py | csrc/moe/marlin_moe_wna16/generate_kernels.py | # SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import glob
import itertools
import os
import subprocess
import sys
import jinja2
ARCHS = []
SUPPORT_FP8 = False
SUPPORT_SM75 = False
SUPPORT_SM80 = False
for arch in sys.argv[1].split(","):
arch = arch[: ar... | python | Apache-2.0 | 0d4044edd85de30d7d4558aeea4d1e95c7c556d6 | 2026-01-04T14:38:19.902011Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/setup.py | setup.py | import setuptools
with open("readme.md", "r", encoding="utf-8") as f:
long_description = f.read()
setuptools.setup(
name='labml_nn',
version='0.5.1',
author="Varuna Jayasiri, Nipun Wijerathne",
author_email="[email protected], [email protected]",
description="🧑🏫 Implementations/tutorials ... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/utils/papers_list.py | utils/papers_list.py | import json
import re
from pathlib import Path
from labml import logger
from labml.logger import Text
HOME = Path('./labml_nn').absolute()
print(HOME)
REGEX = re.compile(r"""
\(
https://arxiv\.org/abs/ # Start of a numeric entity reference
(?P<id>[0-9\.]+) # Paper ID
\)
""", re.VERBOSE)
IGNORE = {
'neox/m... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/utils/sitemap.py | utils/sitemap.py | from pathlib import Path
import git
HOME = Path('./labml_nn')
REPO = git.Repo('.')
def collect(path: Path):
if path.is_file():
try:
commit = next(iter(REPO.iter_commits(paths=path)))
except StopIteration:
return []
html = path.relative_to(HOME)
if html.su... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/utils/diagrams.py | utils/diagrams.py | import shutil
from pathlib import Path
from typing import List
from xml.dom import minidom
import os
from labml import monit
HOME = Path('.').absolute()
STYLES = """
.black-stroke {
stroke: #aaa;
}
rect.black-stroke {
stroke: #444;
}
.black-fill {
fill: #ddd;
}
.white-fill {
fill: #333;
}
.blue-s... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/utils/__init__.py | utils/__init__.py | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false | |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/__init__.py | labml_nn/__init__.py | """
# [Annotated Research Paper Implementations: Transformers, StyleGAN, Stable Diffusion, DDPM/DDIM, LayerNorm, Nucleus Sampling and more](index.html)
This is a collection of simple PyTorch implementations of
neural networks and related algorithms.
[These implementations](https://github.com/labmlai/annotated_deep_lea... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/rl/__init__.py | labml_nn/rl/__init__.py | """
---
title: Reinforcement Learning Algorithms
summary: >
This is a collection of PyTorch implementations/tutorials of reinforcement learning algorithms.
It currently includes Proximal Policy Optimization, Generalized Advantage Estimation, and
Deep Q Networks.
---
# Reinforcement Learning Algorithms
* [Proxim... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/rl/game.py | labml_nn/rl/game.py | """
---
title: Atari wrapper with multi-processing
summary: This implements the Atari games with multi-processing.
---
# Atari wrapper with multi-processing
"""
import multiprocessing
import multiprocessing.connection
import cv2
import gym
import numpy as np
class Game:
"""
<a id="GameEnvironment"></a>
... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/rl/ppo/gae.py | labml_nn/rl/ppo/gae.py | """
---
title: Generalized Advantage Estimation (GAE)
summary: A PyTorch implementation/tutorial of Generalized Advantage Estimation (GAE).
---
# Generalized Advantage Estimation (GAE)
This is a [PyTorch](https://pytorch.org) implementation of paper
[Generalized Advantage Estimation](https://arxiv.org/abs/1506.02438)... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/rl/ppo/experiment.py | labml_nn/rl/ppo/experiment.py | """
---
title: PPO Experiment with Atari Breakout
summary: Annotated implementation to train a PPO agent on Atari Breakout game.
---
# PPO Experiment with Atari Breakout
This experiment trains Proximal Policy Optimization (PPO) agent Atari Breakout game on OpenAI Gym.
It runs the [game environments on multiple proce... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/rl/ppo/__init__.py | labml_nn/rl/ppo/__init__.py | """
---
title: Proximal Policy Optimization - PPO
summary: >
An annotated implementation of Proximal Policy Optimization - PPO algorithm in PyTorch.
---
# Proximal Policy Optimization - PPO
This is a [PyTorch](https://pytorch.org) implementation of
[Proximal Policy Optimization - PPO](https://arxiv.org/abs/1707.0634... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/rl/dqn/experiment.py | labml_nn/rl/dqn/experiment.py | """
---
title: DQN Experiment with Atari Breakout
summary: Implementation of DQN experiment with Atari Breakout
---
# DQN Experiment with Atari Breakout
This experiment trains a Deep Q Network (DQN) to play Atari Breakout game on OpenAI Gym.
It runs the [game environments on multiple processes](../game.html) to sampl... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/rl/dqn/model.py | labml_nn/rl/dqn/model.py | """
---
title: Deep Q Network (DQN) Model
summary: Implementation of neural network model for Deep Q Network (DQN).
---
# Deep Q Network (DQN) Model
[](https://colab.research.google.com/github/labmlai/annotated_deep_learning_paper_implementatio... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/rl/dqn/__init__.py | labml_nn/rl/dqn/__init__.py | """
---
title: Deep Q Networks (DQN)
summary: >
This is a PyTorch implementation/tutorial of Deep Q Networks (DQN) from paper
Playing Atari with Deep Reinforcement Learning.
This includes dueling network architecture, a prioritized replay buffer and
double-Q-network training.
---
# Deep Q Networks (DQN)
This... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/rl/dqn/replay_buffer.py | labml_nn/rl/dqn/replay_buffer.py | """
---
title: Prioritized Experience Replay Buffer
summary: Annotated implementation of prioritized experience replay using a binary segment tree.
---
# Prioritized Experience Replay Buffer
This implements paper [Prioritized experience replay](https://arxiv.org/abs/1511.05952),
using a binary segment tree.
[ benefits.
"""
import torch.nn as nn
from labml import experimen... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/distillation/large.py | labml_nn/distillation/large.py | """
---
title: Train a large model on CIFAR 10
summary: >
Train a large model on CIFAR 10 for distillation.
---
# Train a large model on CIFAR 10
This trains a large model on CIFAR 10 for [distillation](index.html).
"""
import torch.nn as nn
from labml import experiment, logger
from labml.configs import option
f... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/distillation/__init__.py | labml_nn/distillation/__init__.py | """
---
title: Distilling the Knowledge in a Neural Network
summary: >
PyTorch implementation and tutorial of the paper
Distilling the Knowledge in a Neural Network.
---
# Distilling the Knowledge in a Neural Network
This is a [PyTorch](https://pytorch.org) implementation/tutorial of the paper
[Distilling the Kno... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/experiments/nlp_classification.py | labml_nn/experiments/nlp_classification.py | """
---
title: NLP classification trainer
summary: >
This is a reusable trainer for classification tasks
---
# NLP model trainer for classification
"""
from collections import Counter
from typing import Callable
import torchtext
import torchtext.vocab
from torchtext.vocab import Vocab
import torch
from labml impo... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/experiments/arithmetic_dataset.py | labml_nn/experiments/arithmetic_dataset.py | """
---
title: Arithmetic Dataset
summary: >
This creates arithmetic problems.
---
*This is based on code by [Georges Harik (@gharik)](https://twitter.com/gharik).*
"""
import random
import string
from typing import List
import torch
from labml.logger import Text
from torch.utils.data import DataLoader, Dataset
f... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/experiments/mnist.py | labml_nn/experiments/mnist.py | """
---
title: MNIST Experiment
summary: >
This is a reusable trainer for MNIST dataset
---
# MNIST Experiment
"""
import torch.nn as nn
import torch.utils.data
from labml import tracker
from labml.configs import option
from labml_nn.helpers.datasets import MNISTConfigs as MNISTDatasetConfigs
from labml_nn.helpers... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/experiments/__init__.py | labml_nn/experiments/__init__.py | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false | |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/experiments/cifar10.py | labml_nn/experiments/cifar10.py | """
---
title: CIFAR10 Experiment
summary: >
This is a reusable trainer for CIFAR10 dataset
---
# CIFAR10 Experiment
"""
from typing import List
import torch.nn as nn
from labml import lab
from labml.configs import option
from labml_nn.helpers.datasets import CIFAR10Configs as CIFAR10DatasetConfigs
from labml_nn.e... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/experiments/nlp_autoregression.py | labml_nn/experiments/nlp_autoregression.py | """
---
title: NLP auto-regression trainer
summary: >
This is a reusable trainer for auto-regressive tasks
---
# Auto-regressive NLP model trainer
"""
from typing import Callable
import torch
import torch.nn as nn
from labml import lab, monit, logger, tracker
from labml.configs import option
from labml.logger impo... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/unet/experiment.py | labml_nn/unet/experiment.py | """
---
title: Training a U-Net on Carvana dataset
summary: >
Code for training a U-Net model on Carvana dataset.
---
# Training [U-Net](index.html)
This trains a [U-Net](index.html) model on [Carvana dataset](carvana.html).
You can find the download instructions
[on Kaggle](https://www.kaggle.com/competitions/carv... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/unet/carvana.py | labml_nn/unet/carvana.py | """
---
title: Carvana dataset for the U-Net experiment
summary: >
Carvana dataset for the U-Net experiment.
---
# Carvana Dataset for the [U-Net](index.html) [experiment](experiment.html)
You can find the download instructions
[on Kaggle](https://www.kaggle.com/competitions/carvana-image-masking-challenge/data).
... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/unet/__init__.py | labml_nn/unet/__init__.py | """
---
title: U-Net
summary: >
PyTorch implementation and tutorial of U-Net model.
---
# U-Net
This is an implementation of the U-Net model from the paper,
[U-Net: Convolutional Networks for Biomedical Image Segmentation](https://arxiv.org/abs/1505.04597).
U-Net consists of a contracting path and an expansive p... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/adaptive_computation/__init__.py | labml_nn/adaptive_computation/__init__.py | """
---
title: Neural Networks with Adaptive Computation
summary: >
A set of PyTorch implementations/tutorials related to adaptive computation
---
# Neural Networks with Adaptive Computation
These are neural network architectures that change the computation complexity based on the
complexity of the input sample.
* ... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/adaptive_computation/parity.py | labml_nn/adaptive_computation/parity.py | """
---
title: "Parity Task"
summary: >
This creates data for Parity Task from the paper Adaptive Computation Time
for Recurrent Neural Networks
---
# Parity Task
This creates data for Parity Task from the paper
[Adaptive Computation Time for Recurrent Neural Networks](https://arxiv.org/abs/1603.08983).
The inpu... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/adaptive_computation/ponder_net/experiment.py | labml_nn/adaptive_computation/ponder_net/experiment.py | """
---
title: "PonderNet Parity Task Experiment"
summary: >
This trains is a PonderNet on Parity Task
---
# [PonderNet](index.html) [Parity Task](../parity.html) Experiment
This trains a [PonderNet](index.html) on [Parity Task](../parity.html).
"""
from typing import Any
import torch
from torch import nn
from to... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/adaptive_computation/ponder_net/__init__.py | labml_nn/adaptive_computation/ponder_net/__init__.py | """
---
title: "PonderNet: Learning to Ponder"
summary: >
A PyTorch implementation/tutorial of PonderNet: Learning to Ponder.
---
# PonderNet: Learning to Ponder
This is a [PyTorch](https://pytorch.org) implementation of the paper
[PonderNet: Learning to Ponder](https://arxiv.org/abs/2107.05407).
PonderNet adapts t... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/optimizers/adam_warmup_cosine_decay.py | labml_nn/optimizers/adam_warmup_cosine_decay.py | """
---
title: Adam optimizer with warm-up and cosine decay
summary: A PyTorch implementation/tutorial of Adam optimizer with warm-up and cosine decay for GPT.
---
# Adam Optimizer with Warmup and Cosine Decay
This extends [AMSGrad optimizer](adam.html) and adds a warmup stage.
"""
import math
from typing import Dict... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/optimizers/ada_belief.py | labml_nn/optimizers/ada_belief.py | """
---
title: AdaBelief optimizer
summary: A simple PyTorch implementation/tutorial of AdaBelief optimizer.
---
# AdaBelief Optimizer
This is based from AdaBelief
[official implementation](https://github.com/juntang-zhuang/Adabelief-Optimizer)
of the paper
[AdaBelief Optimizer: Adapting Stepsizes by the Belief in Ob... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/optimizers/radam.py | labml_nn/optimizers/radam.py | """
---
title: Rectified Adam (RAdam) optimizer
summary: A simple PyTorch implementation/tutorial of RAdam optimizer.
---
# Rectified Adam (RAdam) optimizer
This implementation is based on
[the official implementation](https://github.com/LiyuanLucasLiu/RAdam)
of the paper
[On the Variance of the Adaptive Learning Rat... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/optimizers/adam.py | labml_nn/optimizers/adam.py | """
---
title: Adam Optimizer
summary: A simple PyTorch implementation/tutorial of Adam optimizer
---
# Adam Optimizer
This is a [PyTorch](https://pytorch.org) implementation of popular optimizer *Adam* from paper
[Adam: A Method for Stochastic Optimization](https://arxiv.org/abs/1412.6980).
*Adam* update is,
\beg... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/optimizers/configs.py | labml_nn/optimizers/configs.py | """
---
title: Configurable optimizer module
summary: This implements a configurable module for optimizers.
---
# Configurable Optimizer
"""
from typing import Tuple
import torch
from labml.configs import BaseConfigs, option, meta_config
from labml_nn.optimizers import WeightDecay
class OptimizerConfigs(BaseConfi... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/optimizers/adam_fp16.py | labml_nn/optimizers/adam_fp16.py | """
---
title: Adam Optimizer for Half Precision Training
summary: A simple PyTorch implementation/tutorial of Adam optimizer
---
# Adam Optimizer for Half Precision Training
"""
from typing import Dict, Tuple, Optional, Any
import torch
from torch import nn
from torch.optim import Optimizer
from torch.cuda.amp impo... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/optimizers/__init__.py | labml_nn/optimizers/__init__.py | """
---
title: Optimizers
summary: >
A set of PyTorch implementations/tutorials of popular gradient descent based optimizers.
Currently includes Adam, AMSGrad and RAdam optimizers.
---
# Optimizers
## Optimizer Implementations
* [Adam Optimizer](adam.html)
* [AMSGrad Optimizer](amsgrad.html)
* [Adam Optimizer with ... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/optimizers/sophia.py | labml_nn/optimizers/sophia.py | """
---
title: Sophia Optimizer
summary: A simple PyTorch implementation/tutorial of Sophia optimizer
---
# Sophia Optimizer
This is a [PyTorch](https://pytorch.org) implementation of *Sophia-G* from paper
[Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training](https://arxiv.org/abs/23... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
labmlai/annotated_deep_learning_paper_implementations | https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/25e169843e93980faa1d0468ea4df42ca7463382/labml_nn/optimizers/adam_warmup.py | labml_nn/optimizers/adam_warmup.py | """
---
title: Adam optimizer with warm-up
summary: A simple PyTorch implementation/tutorial of Adam optimizer with warm-up.
---
# Adam Optimizer with Warmup
This extends [AMSGrad optimizer](amsgrad.html) and adds a warmup stage.
"""
from typing import Dict
from labml_nn.optimizers import WeightDecay
from labml_nn.... | python | MIT | 25e169843e93980faa1d0468ea4df42ca7463382 | 2026-01-04T14:38:23.238891Z | false |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.