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# MobileNet v3 MobileNetV3 is a convolutional neural network that is designed for mobile phone CPUs. The network design includes the use of a [hard swish activation](https://paperswithcode.com/method/hard-swish) and [squeeze-and-excitation](https://paperswithcode.com/method/squeeze-and-excitation-block) modules in...	pytorch-image-models/hfdocs/source/models/mobilenet-v3.mdx/0	{ "file_path": "pytorch-image-models/hfdocs/source/models/mobilenet-v3.mdx", "repo_id": "pytorch-image-models", "token_count": 2579 }	184
# SK-ResNet SK ResNet is a variant of a [ResNet](https://www.paperswithcode.com/method/resnet) that employs a [Selective Kernel](https://paperswithcode.com/method/selective-kernel) unit. In general, all the large kernel convolutions in the original bottleneck blocks in ResNet are replaced by the proposed [SK convo...	pytorch-image-models/hfdocs/source/models/skresnet.mdx/0	{ "file_path": "pytorch-image-models/hfdocs/source/models/skresnet.mdx", "repo_id": "pytorch-image-models", "token_count": 2082 }	185
# Data [[autodoc]] timm.data.create_dataset [[autodoc]] timm.data.create_loader [[autodoc]] timm.data.create_transform [[autodoc]] timm.data.resolve_data_config	pytorch-image-models/hfdocs/source/reference/data.mdx/0	{ "file_path": "pytorch-image-models/hfdocs/source/reference/data.mdx", "repo_id": "pytorch-image-models", "token_count": 67 }	186
# Validation and Benchmark Results This folder contains validation and benchmark results for the models in this collection. Validation scores are currently only run for models with pretrained weights and ImageNet-1k heads, benchmark numbers are run for all. ## Datasets There are currently results for the ImageNet va...	pytorch-image-models/results/README.md/0	{ "file_path": "pytorch-image-models/results/README.md", "repo_id": "pytorch-image-models", "token_count": 1173 }	187
from copy import deepcopy __all__ = ['get_img_extensions', 'is_img_extension', 'set_img_extensions', 'add_img_extensions', 'del_img_extensions'] IMG_EXTENSIONS = ('.png', '.jpg', '.jpeg') # singleton, kept public for bwd compat use _IMG_EXTENSIONS_SET = set(IMG_EXTENSIONS) # set version, private, kept in sync de...	pytorch-image-models/timm/data/readers/img_extensions.py/0	{ "file_path": "pytorch-image-models/timm/data/readers/img_extensions.py", "repo_id": "pytorch-image-models", "token_count": 582 }	188
""" Activations A collection of activations fn and modules with a common interface so that they can easily be swapped. All have an `inplace` arg even if not used. Hacked together by / Copyright 2020 Ross Wightman """ import torch from torch import nn as nn from torch.nn import functional as F def swish(x, inplace:...	pytorch-image-models/timm/layers/activations.py/0	{ "file_path": "pytorch-image-models/timm/layers/activations.py", "repo_id": "pytorch-image-models", "token_count": 2012 }	189
""" Create Conv2d Factory Method Hacked together by / Copyright 2020 Ross Wightman """ from .mixed_conv2d import MixedConv2d from .cond_conv2d import CondConv2d from .conv2d_same import create_conv2d_pad def create_conv2d(in_channels, out_channels, kernel_size, **kwargs): """ Select a 2d convolution implementat...	pytorch-image-models/timm/layers/create_conv2d.py/0	{ "file_path": "pytorch-image-models/timm/layers/create_conv2d.py", "repo_id": "pytorch-image-models", "token_count": 652 }	190
""" Interpolation helpers for timm layers RegularGridInterpolator from https://github.com/sbarratt/torch_interpolations Copyright Shane Barratt, Apache 2.0 license """ import torch from itertools import product class RegularGridInterpolator: """ Interpolate data defined on a rectilinear grid with even or uneven ...	pytorch-image-models/timm/layers/interpolate.py/0	{ "file_path": "pytorch-image-models/timm/layers/interpolate.py", "repo_id": "pytorch-image-models", "token_count": 1121 }	191
""" Sin-cos, fourier, rotary position embedding modules and functions Hacked together by / Copyright 2022 Ross Wightman """ import math from typing import List, Tuple, Optional, Union import torch from torch import nn as nn from .grid import ndgrid from .trace_utils import _assert def pixel_freq_bands( num...	pytorch-image-models/timm/layers/pos_embed_sincos.py/0	{ "file_path": "pytorch-image-models/timm/layers/pos_embed_sincos.py", "repo_id": "pytorch-image-models", "token_count": 7200 }	192
import torch import torch.nn as nn import torch.nn.functional as F from .cross_entropy import LabelSmoothingCrossEntropy class JsdCrossEntropy(nn.Module): """ Jensen-Shannon Divergence + Cross-Entropy Loss Based on impl here: https://github.com/google-research/augmix/blob/master/imagenet.py From paper: ...	pytorch-image-models/timm/loss/jsd.py/0	{ "file_path": "pytorch-image-models/timm/loss/jsd.py", "repo_id": "pytorch-image-models", "token_count": 639 }	193
""" Deep Layer Aggregation and DLA w/ Res2Net DLA original adapted from Official Pytorch impl at: https://github.com/ucbdrive/dla DLA Paper: `Deep Layer Aggregation` - https://arxiv.org/abs/1707.06484 Res2Net additions from: https://github.com/gasvn/Res2Net/ Res2Net Paper: `Res2Net: A New Multi-scale Backbone Architec...	pytorch-image-models/timm/models/dla.py/0	{ "file_path": "pytorch-image-models/timm/models/dla.py", "repo_id": "pytorch-image-models", "token_count": 9144 }	194
from functools import partial import torch.nn as nn from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD from ._builder import build_model_with_cfg from ._builder import pretrained_cfg_for_features from ._efficientnet_blocks import SqueezeExcite from ._efficientnet_builder import decode_arch_def, resolve...	pytorch-image-models/timm/models/hardcorenas.py/0	{ "file_path": "pytorch-image-models/timm/models/hardcorenas.py", "repo_id": "pytorch-image-models", "token_count": 4629 }	195
""" NasNet-A (Large) nasnetalarge implementation grabbed from Cadene's pretrained models https://github.com/Cadene/pretrained-models.pytorch """ from functools import partial import torch import torch.nn as nn import torch.nn.functional as F from timm.layers import ConvNormAct, create_conv2d, create_pool2d, create_...	pytorch-image-models/timm/models/nasnet.py/0	{ "file_path": "pytorch-image-models/timm/models/nasnet.py", "repo_id": "pytorch-image-models", "token_count": 13247 }	196
""" SEResNet implementation from Cadene's pretrained models https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/senet.py Additional credit to https://github.com/creafz Original model: https://github.com/hujie-frank/SENet ResNet code gently borrowed from https://github.com/pytorch/v...	pytorch-image-models/timm/models/senet.py/0	{ "file_path": "pytorch-image-models/timm/models/senet.py", "repo_id": "pytorch-image-models", "token_count": 8344 }	197
""" Vision OutLOoker (VOLO) implementation Paper: `VOLO: Vision Outlooker for Visual Recognition` - https://arxiv.org/abs/2106.13112 Code adapted from official impl at https://github.com/sail-sg/volo, original copyright in comment below Modifications and additions for timm by / Copyright 2022, Ross Wightman """ # Co...	pytorch-image-models/timm/models/volo.py/0	{ "file_path": "pytorch-image-models/timm/models/volo.py", "repo_id": "pytorch-image-models", "token_count": 15802 }	198
""" PyTorch MADGRAD optimizer MADGRAD: https://arxiv.org/abs/2101.11075 Code from: https://github.com/facebookresearch/madgrad """ # Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import ma...	pytorch-image-models/timm/optim/madgrad.py/0	{ "file_path": "pytorch-image-models/timm/optim/madgrad.py", "repo_id": "pytorch-image-models", "token_count": 3505 }	199
""" Step Scheduler Basic step LR schedule with warmup, noise. Hacked together by / Copyright 2020 Ross Wightman """ import math import torch from .scheduler import Scheduler class StepLRScheduler(Scheduler): """ """ def __init__( self, optimizer: torch.optim.Optimizer, ...	pytorch-image-models/timm/scheduler/step_lr.py/0	{ "file_path": "pytorch-image-models/timm/scheduler/step_lr.py", "repo_id": "pytorch-image-models", "token_count": 939 }	200
import random import numpy as np import torch def random_seed(seed=42, rank=0): torch.manual_seed(seed + rank) np.random.seed(seed + rank) random.seed(seed + rank)	pytorch-image-models/timm/utils/random.py/0	{ "file_path": "pytorch-image-models/timm/utils/random.py", "repo_id": "pytorch-image-models", "token_count": 68 }	201
# Rust builder FROM lukemathwalker/cargo-chef:latest-rust-1.71 AS chef WORKDIR /usr/src ARG CARGO_REGISTRIES_CRATES_IO_PROTOCOL=sparse FROM chef as planner COPY Cargo.toml Cargo.toml COPY rust-toolchain.toml rust-toolchain.toml COPY proto proto COPY benchmark benchmark COPY router router COPY launcher launcher RUN ca...	text-generation-inference/Dockerfile/0	{ "file_path": "text-generation-inference/Dockerfile", "repo_id": "text-generation-inference", "token_count": 3209 }	202
{ "openapi": "3.0.3", "info": { "title": "Text Generation Inference", "description": "Text Generation Webserver", "contact": { "name": "Olivier Dehaene" }, "license": { "name": "Apache 2.0", "url": "https://www.apache.org/licenses/LICENSE-2.0" }, "version": "1.4.0" },...	text-generation-inference/docs/openapi.json/0	{ "file_path": "text-generation-inference/docs/openapi.json", "repo_id": "text-generation-inference", "token_count": 20966 }	203
# Messages API Text Generation Inference (TGI) now supports the Messages API, which is fully compatible with the OpenAI Chat Completion API. This feature is available starting from version 1.4.0. You can use OpenAI's client libraries or third-party libraries expecting OpenAI schema to interact with TGI's Messages API....	text-generation-inference/docs/source/messages_api.md/0	{ "file_path": "text-generation-inference/docs/source/messages_api.md", "repo_id": "text-generation-inference", "token_count": 1733 }	204
[ { "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 50, "logprob": null, "text": "G" }, { "id": 330, "logprob": -5.96875, "text": "ir" ...	text-generation-inference/integration-tests/models/__snapshots__/test_flash_falcon/test_flash_falcon_load.json/0	{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_falcon/test_flash_falcon_load.json", "repo_id": "text-generation-inference", "token_count": 21427 }	205
[ { "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 50278, "logprob": null, "text": "<\|prompter\|>" }, { "id": 1276, "logprob": -8.03125, "text...	text-generation-inference/integration-tests/models/__snapshots__/test_flash_neox_sharded/test_flash_neox_load.json/0	{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_flash_neox_sharded/test_flash_neox_load.json", "repo_id": "text-generation-inference", "token_count": 9176 }	206
{ "details": { "best_of_sequences": null, "finish_reason": "eos_token", "generated_tokens": 5, "prefill": [ { "id": 0, "logprob": null, "text": "<pad>" } ], "seed": 0, "tokens": [ { "id": 926, "logprob": -4.3554688, "special...	text-generation-inference/integration-tests/models/__snapshots__/test_mt0_base/test_mt0_base.json/0	{ "file_path": "text-generation-inference/integration-tests/models/__snapshots__/test_mt0_base/test_mt0_base.json", "repo_id": "text-generation-inference", "token_count": 532 }	207
import pytest @pytest.fixture(scope="module") def flash_medusa_handle(launcher): with launcher("FasterDecoding/medusa-vicuna-7b-v1.3", num_shard=2) as handle: yield handle @pytest.fixture(scope="module") async def flash_medusa(flash_medusa_handle): await flash_medusa_handle.health(300) return fl...	text-generation-inference/integration-tests/models/test_flash_medusa.py/0	{ "file_path": "text-generation-inference/integration-tests/models/test_flash_medusa.py", "repo_id": "text-generation-inference", "token_count": 750 }	208
[pytest] addopts = --snapshot-warn-unused asyncio_mode = auto markers = private: marks tests as requiring an admin hf token (deselect with '-m "not private"')	text-generation-inference/integration-tests/pytest.ini/0	{ "file_path": "text-generation-inference/integration-tests/pytest.ini", "repo_id": "text-generation-inference", "token_count": 57 }	209
/// Single shard Client use crate::pb::generate::v2::text_generation_service_client::TextGenerationServiceClient; use crate::pb::generate::v2::*; use crate::Result; use grpc_metadata::InjectTelemetryContext; use std::cmp::min; use std::time::Duration; use tonic::transport::{Channel, Uri}; use tracing::instrument; /// ...	text-generation-inference/router/client/src/client.rs/0	{ "file_path": "text-generation-inference/router/client/src/client.rs", "repo_id": "text-generation-inference", "token_count": 3649 }	210
include Makefile-flash-att include Makefile-flash-att-v2 include Makefile-vllm include Makefile-awq include Makefile-eetq unit-tests: pytest -s -vv -m "not private" tests gen-server: # Compile protos pip install grpcio-tools==1.51.1 mypy-protobuf==3.4.0 'types-protobuf>=3.20.4' --no-cache-dir mkdir text_generatio...	text-generation-inference/server/Makefile/0	{ "file_path": "text-generation-inference/server/Makefile", "repo_id": "text-generation-inference", "token_count": 486 }	211
// Adapted from turboderp exllama: https://github.com/turboderp/exllama #ifndef _q4_matmul_cuh #define _q4_matmul_cuh #include <cuda_runtime.h> #include <cuda_fp16.h> #include <cstdint> #include <cstdio> #include <ATen/cuda/CUDAContext.h> #include "q4_matrix.cuh" #include "../tuning.h" void q4_matmul_cuda ( ExL...	text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/q4_matmul.cuh/0	{ "file_path": "text-generation-inference/server/exllama_kernels/exllama_kernels/cuda_func/q4_matmul.cuh", "repo_id": "text-generation-inference", "token_count": 328 }	212
#include "compat.cuh" __forceinline__ __device__ half2 dot22_8(half2(&dq)[4], const half* a_ptr, const half2 g_result) { half2 result = {}; const half2* a2_ptr = (const half2)a_ptr; #pragma unroll for (int i = 0; i < 4; i++) result = __hfma2(dq[i], a2_ptr++, result); return __hadd2(result, g_resu...	text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm_kernel_gptq.cuh/0	{ "file_path": "text-generation-inference/server/exllamav2_kernels/exllamav2_kernels/cuda/q_gemm_kernel_gptq.cuh", "repo_id": "text-generation-inference", "token_count": 4791 }	213
import torch import grpc from google.rpc import status_pb2, code_pb2 from grpc_status import rpc_status from grpc_interceptor.server import AsyncServerInterceptor from loguru import logger from typing import Callable, Any class ExceptionInterceptor(AsyncServerInterceptor): async def intercept( self, ...	text-generation-inference/server/text_generation_server/interceptor.py/0	{ "file_path": "text-generation-inference/server/text_generation_server/interceptor.py", "repo_id": "text-generation-inference", "token_count": 449 }	214
# coding=utf-8 # Copyright 2022 EleutherAI and the HuggingFace Inc. team. All rights reserved. # # This code is based on EleutherAI's GPT-NeoX library and the GPT-NeoX # and OPT implementations in this library. It has been modified from its # original forms to accommodate minor architectural differences compared # to G...	text-generation-inference/server/text_generation_server/models/custom_modeling/idefics_modeling.py/0	{ "file_path": "text-generation-inference/server/text_generation_server/models/custom_modeling/idefics_modeling.py", "repo_id": "text-generation-inference", "token_count": 28422 }	215
import torch import torch.distributed from opentelemetry import trace from transformers import AutoTokenizer, AutoConfig from typing import Optional, List import json import os from huggingface_hub import hf_hub_download from text_generation_server.models import FlashCausalLM from text_generation_server.models.custom...	text-generation-inference/server/text_generation_server/models/flash_santacoder.py/0	{ "file_path": "text-generation-inference/server/text_generation_server/models/flash_santacoder.py", "repo_id": "text-generation-inference", "token_count": 1285 }	216
import grpc from opentelemetry import trace from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter from opentelemetry.instrumentation.grpc._aio_server import ( OpenTelemetryAioServerInterceptor, ) from opentelemetry.semconv.trace import SpanAttributes from opentelemetry.sdk.resources im...	text-generation-inference/server/text_generation_server/tracing.py/0	{ "file_path": "text-generation-inference/server/text_generation_server/tracing.py", "repo_id": "text-generation-inference", "token_count": 985 }	217
import torch from dataclasses import dataclass from text_generation_server.utils.layers import TensorParallelHead, FastLinear @dataclass class Output: logits: torch.FloatTensor = None speculative_logits: torch.FloatTensor = None class ResBlock(torch.nn.Module): def __init__(self, config, prefix, weights...	text-generation-inference/server/text_generation_server/utils/medusa.py/0	{ "file_path": "text-generation-inference/server/text_generation_server/utils/medusa.py", "repo_id": "text-generation-inference", "token_count": 803 }	218
nodeLinker: node-modules npmAuditRegistry: 'https://registry.npmjs.org' yarnPath: .yarn/releases/yarn-3.5.1.cjs	tokenizers/bindings/node/.yarnrc.yml/0	{ "file_path": "tokenizers/bindings/node/.yarnrc.yml", "repo_id": "tokenizers", "token_count": 53 }	219
/* eslint-disable @typescript-eslint/no-empty-function / / eslint-disable @typescript-eslint/no-explicit-any */ import { BPE, Unigram, WordPiece } from '../../' const MOCKS_DIR = __dirname + '/__mocks__' describe('WordPiece', () => { describe('fromFile', () => { it('throws if called with only one argument', ...	tokenizers/bindings/node/lib/bindings/models.test.ts/0	{ "file_path": "tokenizers/bindings/node/lib/bindings/models.test.ts", "repo_id": "tokenizers", "token_count": 818 }	220
# `tokenizers-linux-arm-gnueabihf` This is the armv7-unknown-linux-gnueabihf binary for `tokenizers`	tokenizers/bindings/node/npm/linux-arm-gnueabihf/README.md/0	{ "file_path": "tokenizers/bindings/node/npm/linux-arm-gnueabihf/README.md", "repo_id": "tokenizers", "token_count": 42 }	221
{ "name": "tokenizers", "version": "0.14.0-dev0", "repository": { "type": "git", "url": "git+https://github.com/huggingface/tokenizers.git" }, "bugs": { "url": "https://github.com/huggingface/tokenizers/issues" }, "homepage": "https://github.com/huggingface/tokenizers/tree/master/bindings/node...	tokenizers/bindings/node/package.json/0	{ "file_path": "tokenizers/bindings/node/package.json", "repo_id": "tokenizers", "token_count": 1532 }	222
{ "compilerOptions": { "target": "ES2018", "strict": true, "moduleResolution": "node", "module": "CommonJS", "noUnusedLocals": true, "noUnusedParameters": true, "esModuleInterop": true, "allowSyntheticDefaultImports": true }, "include": ["."], "exclude": ["node_modules"] }	tokenizers/bindings/node/tsconfig.json/0	{ "file_path": "tokenizers/bindings/node/tsconfig.json", "repo_id": "tokenizers", "token_count": 129 }	223