relative_path stringclasses 812
values | section stringclasses 339
values | filename stringlengths 2 61 | text stringlengths 6 1.76M |
|---|---|---|---|
TensorFlow2/Recommendation/WideAndDeep/triton/deployment_toolkit/library | library | __init__ | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... |
PyTorch/LanguageModeling/BERT/triton/dist4l/runner | runner | config_NVIDIA-A30 | checkpoints:
- name: dist-4l-qa
url: https://api.ngc.nvidia.com/v2/models/nvidia/dle/bert_pyt_ckpt_distilled_4l_288d_qa_squad11_amp/versions/21.11.0/zip
configurations:
- accelerator: none
accelerator_precision: fp16
batch_size:
- 1
batch_sizes: '1'
capture_cuda_graph: 0
checkpoint_variant: dist-4l-qa
e... |
TensorFlow2/Detection/Efficientdet/scripts/docker | docker | build | #!/bin/bash
docker build --rm -t effdet_tf2 . -f Dockerfile |
CUDA-Optimized/FastSpeech/fastspeech/model | model | __init__ | # Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditio... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/trt/util | util | engineDriver | /*
* Copyright (c) 2019-2020, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright
* notice, this l... |
PyTorch/Detection/Efficientdet/scripts/D0 | D0 | train-benchmark_AMP_A100-80G | #!/bin/bash
function get_dataloader_workers {
gpus=$(nvidia-smi -i 0 --query-gpu=count --format=csv,noheader)
core=$(nproc --all)
workers=$((core/gpus-2))
workers=$((workers>16?16:workers))
echo ${workers}
}
WORKERS=$(get_dataloader_workers)
./distributed_train.sh ${NUM_PROC:-8} /workspace/object_... |
PyTorch/LanguageModeling/BERT/distillation/utils | utils | utils | # coding=utf-8
# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... |
TensorFlow/Classification/ConvNets/triton/deployment_toolkit | deployment_toolkit | core | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow/Detection | Detection | README | # Object Detection
A natural progression from image classification would be classification and localization of the subject of the image. We can take this idea one step further and localize objects in a given image. Simply put, object detection refers to identifying which object(s) are there in an image.
 2021, NVIDIA CORPORATION. All rights reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required ... |
TensorFlow/Segmentation/UNet_Industrial/scripts | scripts | UNet_EVAL_XLA | #!/usr/bin/env bash
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unle... |
TensorFlow/Detection/SSD/examples | examples | SSD320_FP32_8GPU_BENCHMARK | # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
Tools/DGLPyTorch/SyntheticGraphGeneration/demos/performance | performance | tabular_generator | #!/usr/bin/env python
# coding: utf-8
# Copyright 2023 NVIDIA Corporation. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... |
TensorFlow2/Segmentation/Contrib/UNet3P | UNet3P | requirements | hydra-core
opencv-python
jupyter
matplotlib
tqdm
nibabel
numba |
PyTorch/Classification/ConvNets/triton/deployment_toolkit/library | library | pyt | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... |
CUDA-Optimized/FastSpeech/fastspeech/utils | utils | __init__ | # Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditio... |
TensorFlow/Detection/SSD/models/research/object_detection/core | core | preprocessor_test | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
PyTorch/Detection/Efficientdet/data | data | dataset | """ COCO dataset (quick and dirty)
Hacked together by Ross Wightman
"""
# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ... |
Tools/PyTorch/TimeSeriesPredictionPlatform/models/tft_pyt | tft_pyt | utils | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... |
PyTorch/SpeechSynthesis/FastPitch/phrases | phrases | phrase_4_256 | The forms of printed letters should be beautiful, and that their arrangement on the page should be reasonable and a help to the shapeliness of the letters themselves and the form of printed letters should be beautiful, and that their arrangement on pages.
The forms of printed letters should be beautiful, and that their... |
TensorFlow/LanguageModeling/BERT/triton/scripts | scripts | run_perf_client | #!/bin/bash
# Copyright (c) 2019 NVIDIA CORPORATION. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required... |
PyTorch/SpeechSynthesis/Tacotron2/phrases | phrases | phrase_8_64 | She sells seashells by the seashore, shells she sells are great
She sells seashells by the seashore, shells she sells are great
She sells seashells by the seashore, shells she sells are great
She sells seashells by the seashore, shells she sells are great
She sells seashells by the seashore, shells she sells are great
... |
TensorFlow2/Recommendation/WideAndDeep/tests/feature_specs | feature_specs | less_onehot | channel_spec:
label:
- clicked
map: []
multihot_categorical:
- topic_id_list
- entity_id_list
- category_id_list
numerical:
- document_id_document_id_promo_sim_categories
- document_id_document_id_promo_sim_topics
- document_id_document_id_promo_sim_entities
- document_id_promo_ctr
- publisher... |
PyTorch/LanguageModeling/BERT/triton/dist4l/runner | runner | prepare_datasets | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow/Detection/SSD/models/research/slim/nets | nets | mobilenet_v1_eval | # Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
TensorFlow/Recommendation/WideAndDeep/preproc | preproc | preproc4 | #!/usr/bin/env python
# coding: utf-8
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... |
PyTorch/SpeechRecognition/Jasper/triton/scripts/docker | docker | build_triton_client | #!/bin/bash
# ensure the TRTIS submodule is added and build the clients
SCRIPT_DIR=$(cd $(dirname $0); pwd)
PROJECT_DIR=${SCRIPT_DIR}/../../../
docker pull nvcr.io/nvidia/tritonserver:20.10-py3-clientsdk
git submodule update --init --recursive
docker build . --rm -f ${PROJECT_DIR}/triton/Dockerfile -t jasper:triton
|
TensorFlow/Segmentation/VNet/model | model | layers | # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow2/Recommendation/WideAndDeep/triton | triton | requirements | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... |
TensorFlow2/Detection/Efficientdet/scripts/docker | docker | interactive | #!/bin/bash
docker run --runtime=nvidia \
-v $BACKBONE_CKPT:/workspace/checkpoints/efficientnet-b0-joc \
-v $CKPT:/workspace/checkpoints/efficientdet-tf2 \
-v ${DATA:-/mnt/nvdl/datasets/coco_master/coco2017_tfrecords}:/workspace/coco \
--rm --name=${name:-interactive} \
--shm-size=30g --ulimit memlock=-1 --ulimit stac... |
TensorFlow/LanguageModeling/BERT/utils | utils | dllogger_class | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/lic... |
TensorFlow/Classification/ConvNets/triton | triton | dataloader | import logging
from pathlib import Path
import numpy as np
from PIL import Image
from rn50_model import HEIGHT, WIDTH
LOGGER = logging.getLogger(__name__)
def get_dataloader_fn(
*, data_dir: str, batch_size: int = 1, width: int = WIDTH, height: int = HEIGHT, images_num: int = None
):
image_extensions = [".... |
PyTorch/LanguageModeling/BART/scripts/docker | docker | launch | #!/bin/bash
# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requi... |
TensorFlow/Detection/SSD/models/research/object_detection/utils | utils | np_box_ops | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
PaddlePaddle/LanguageModeling/BERT | BERT | squad_dataset | # Copyright (c) 2022 NVIDIA Corporation. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow2/Recommendation/WideAndDeep/triton/runner/maintainer/docker/containers | containers | __init__ | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... |
TensorFlow2/Classification/ConvNets/model/blocks | blocks | mb_conv_block | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/Classification/ConvNets/resnext101-32x4d/training/AMP | AMP | DGXA100_resnext101-32x4d_AMP_250E | python ./multiproc.py --nproc_per_node 8 ./launch.py --model resnext101-32x4d --precision AMP --mode convergence --platform DGXA100 /imagenet --workspace ${1:-./} --raport-file raport.json
|
PyTorch/Classification/GPUNet/triton/deployment_toolkit/triton_performance_runner | triton_performance_runner | runner | # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow2/Recommendation/WideAndDeep/triton/runner | runner | triton | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... |
TensorFlow/Classification/ConvNets/triton/scripts/docker | docker | triton_inference_server | #!/usr/bin/env bash
# Copyright (c) 2021 NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unle... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/model-config/tacotron2waveglow | tacotron2waveglow | mapping | # sequence-number symbol
0 _
1 -
2 !
3 '
4 (
5 )
6 ,
7 .
8 :
9 ;
10 ?
11
38 A
39 B
40 C
41 D
42 E
43 F
44 G
45 H
46 I
47 J
48 K
49 L
50 M
51 N
52 O
53 P
54 Q
55 R
56 S
57 T
58 U
59 V
60 W
61 X
62 Y
63 Z
38 a
39 b
40 c
41 d
42 e
43 f
44 g
45 h
46 i
47 j
48 k
49 l
50 m
51 n
52 o
53 p
54 q
55 r
56 s
57 t
58 u
59 v
60 w
... |
TensorFlow/Segmentation/UNet_Industrial/datasets | datasets | core | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# ==============================================================================
#
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the L... |
TensorFlow2/LanguageModeling/ELECTRA/scripts | scripts | benchmark_squad | #!/usr/bin/env bash
# Copyright (c) 2020 NVIDIA CORPORATION. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless ... |
TensorFlow/Detection/SSD/models/research/object_detection/dataset_tools | dataset_tools | create_pascal_tf_record_test | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
TensorFlow/Detection/SSD/models/research/slim/nets | nets | inception_v4_test | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
TensorFlow/Detection/SSD/models/research/object_detection/models | models | embedded_ssd_mobilenet_v1_feature_extractor | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
JAX/LanguageModeling/T5X | T5X | README | T5X is a framework for training, evaluation, and inference of sequence models (starting with language). It is based on [JAX](https://github.com/google/jax) and [Flax](https://github.com/google/flax). To learn more, see the [T5X Paper](https://arxiv.org/abs/2203.17189).
# T5X on GPUs
Please refer to [Rosetta T5X](http... |
PyTorch/Classification/ConvNets/triton | triton | run_offline_performance_test_on_triton | #!/usr/bin/env python3
# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... |
Tools/DGLPyTorch/SyntheticGraphGeneration/scripts | scripts | get_datasets | #Note: Each user is responsible for checking the content of datasets and the applicable licenses and determining if suitable for the intended use
if [ ! "$(ls | grep -c ^scripts$)" -eq 1 ]; then
echo "Run this script from root directory. Usage: bash ./scripts/get_datasets.sh"
exit 1
fi
mkdir -p data
cd data || ex... |
TensorFlow2/Segmentation/nnUNet/models | models | layers | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/Classification/GPUNet/triton/runner/maintainer/docker | docker | maintainer | # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/synthesizer | synthesizer | configuration_graph_synthesizer | # Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/LanguageModeling/BERT/lamb_amp_opt/csrc | csrc | multi_tensor_lamb_out | #include <ATen/ATen.h>
#include <ATen/AccumulateType.h>
#include <ATen/cuda/CUDAContext.h>
#include <ATen/cuda/Exceptions.h>
// Another possibility:
// #include <torch/all.h>
#include <assert.h>
#include "type_shim.h"
#include "multi_tensor_apply.cuh"
#define BLOCK_SIZE 512
#define ILP 4
std::tuple<at::Tensor, at::... |
TensorFlow/Classification/ConvNets/dataprep | dataprep | build_imagewoof_data | #!/usr/bin/python
# Copyright 2016 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... |
PyTorch/Detection/Efficientdet | Efficientdet | README | # EfficientDet For PyTorch
This repository provides a script and recipe to train and infer on EfficientDet to achieve state-of-the-art accuracy and is tested and maintained by NVIDIA.
## Table Of Contents
* [Model overview](#model-overview)
* [Model Architecture](#model-architecture)
* [Default configuration](#... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/trt/plugins/taco2DenoiseTransformPlugin | taco2DenoiseTransformPlugin | taco2DenoiseTransformKernel | /*
* Copyright (c) 2019-2020, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright
* notice, this l... |
TensorFlow/Detection/SSD/models/research/object_detection/core | core | prefetcher_test | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
PaddlePaddle/LanguageModeling/BERT/vocab | vocab | bert-base-cased-vocab | [PAD]
[unused1]
[unused2]
[unused3]
[unused4]
[unused5]
[unused6]
[unused7]
[unused8]
[unused9]
[unused10]
[unused11]
[unused12]
[unused13]
[unused14]
[unused15]
[unused16]
[unused17]
[unused18]
[unused19]
[unused20]
[unused21]
[unused22]
[unused23]
[unused24]
[unused25]
[unused26]
[unused27]
[unused28]
[unused29]
[unu... |
PyTorch/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/modeling/roi_heads/mask_head | mask_head | mask_head | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
from torch import nn
from maskrcnn_benchmark.structures.bounding_box import BoxList
from .roi_mask_feature_extractors import make_roi_mask_feature_extractor
from .roi_mask_predictors import make_roi_mask_predictor
from .inference imp... |
PyTorch/SpeechSynthesis/FastPitch/platform | platform | DGX1_FastPitch_AMP_8GPU | #!/bin/bash
set -a
: ${NUM_GPUS:=8}
: ${BATCH_SIZE:=16}
: ${GRAD_ACCUMULATION:=2}
: ${AMP:=true}
bash scripts/train.sh "$@"
|
TensorFlow/Recommendation/WideAndDeep/utils | utils | metrics | # Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
CUDA-Optimized/FastSpeech | FastSpeech | README | # FastSpeech For PyTorch and TensorRT
This repository provides a script and recipe to train the FastSpeech model to achieve state-of-the-art accuracy and is tested and maintained by NVIDIA.
It also provides an optimization in TensorRT to accelerate inference performance without loss of accuracy.
For more details, see... |
PyTorch/Forecasting/TFT | TFT | inference | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... |
Tools/PyTorch/TimeSeriesPredictionPlatform | TimeSeriesPredictionPlatform | launch_triton_configure | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... |
TensorFlow2/Recommendation/DLRM_and_DCNv2/tests | tests | test_fspecs | # Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/Segmentation/nnUNet/triton/deployment_toolkit/bermuda | bermuda | utils | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/Forecasting/TFT/scripts | scripts | run_electricity | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... |
PyTorch/Detection/SSD | SSD | README | # SSD300 v1.1 For PyTorch
This repository provides a script and recipe to train the SSD300 v1.1 model to achieve state of the art accuracy, and is tested and maintained by NVIDIA.
## Table Of Contents
- [Model overview](#model-overview)
* [Model architecture](#model-architecture)
* [Default configuration](#de... |
TensorFlow/Detection/SSD | SSD | requirements | cython==0.29.24
pycocotools==2.0.2
contextlib2==21.6.0
|
PyTorch/SpeechRecognition/QuartzNet/scripts/docker | docker | launch | #!/bin/bash
SCRIPT_DIR=$(cd $(dirname $0); pwd)
QN_REPO=${QN_REPO:-"${SCRIPT_DIR}/../.."}
DATA_DIR=${1:-${DATA_DIR-${QN_REPO}"/datasets"}}
RESULT_DIR=${2:-${RESULT_DIR:-${QN_REPO}"/results"}}
SCRIPT=${3:-${SCRIPT:-""}}
MOUNTS=""
MOUNTS+=" -v $DATA_DIR:/datasets"
MOUNTS+=" -v $RESULT_DIR:/results"
MOUNTS+=" -v ${QN_R... |
TensorFlow2/Classification/ConvNets/efficientnet_v1/B4/training/AMP | AMP | convergence_8xV100-32G | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/Forecasting/TFT | TFT | requirements | git+https://github.com/NVIDIA/dllogger@v1.0.0#egg=dllogger
pandas==1.3.4
pynvml==11.0.0
|
PyTorch/SpeechSynthesis/Tacotron2/scripts | scripts | train_tacotron2 | mkdir -p output
python -m multiproc train.py -m Tacotron2 -o ./output/ -lr 1e-3 --epochs 1501 -bs 48 --weight-decay 1e-6 --grad-clip-thresh 1.0 --cudnn-enabled --log-file nvlog.json --anneal-steps 500 1000 1500 --anneal-factor 0.1
|
TensorFlow2/Recommendation/DLRM_and_DCNv2/deployment/hps | hps | triton_ensemble_wrapper | # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow/Detection/SSD/models/research/slim/nets | nets | vgg | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
PyTorch/Detection/Efficientdet/effdet | effdet | efficientnet_test | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow/Segmentation/UNet_Industrial/utils | utils | cmdline_helper | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# ==============================================================================
#
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the L... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/generator/tabular | tabular | gaussian_generator | # Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/SpeechSynthesis/FastPitch/hifigan | hifigan | metrics | import timer
from collections import defaultdict
class Metrics(defaultdict):
# TODO Where to measure - gpu:0 or all gpus?
def __init__(self, tb_keys=[], benchmark_epochs=10):
super().__init__(float)
# dll_tb_keys=['loss_gen', 'loss_discrim', 'loss_mel', 'took']:
self.tb_keys = tb_k... |
PyTorch/LanguageModeling/BART/configs | configs | config_xsum | {
"_num_labels": 3,
"activation_dropout": 0.0,
"activation_function": "gelu",
"add_bias_logits": false,
"add_final_layer_norm": false,
"architectures": [
"BartForConditionalGeneration"
],
"attention_dropout": 0.0,
"bos_token_id": 0,
"classif_dropout": 0.0,
"d_model": 1024,
"decoder_attention... |
TensorFlow/Detection/SSD/models/research/slim/nets/mobilenet | mobilenet | mobilenet_example | #!/usr/bin/env python
# coding: utf-8
# >[Prerequisites (downloading tensorflow_models and checkpoints)](#scrollTo=T_cETKXHDTXu)
#
# >[Checkpoint based inference](#scrollTo=fxMe7_pkk_Vo)
#
# >[Frozen inference](#scrollTo=PlwvpK3ElBk6)
#
#
# # Prerequisites (downloading tensorflow_models and checkpoints)
# In[ ]:... |
CUDA-Optimized/FastSpeech/fastspeech | fastspeech | train | # Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditio... |
PyTorch/Segmentation/nnUNet/triton/scripts/docker | docker | interactive | #Copyright (c) 2021 NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/scripts/import_utils | import_utils | waveglow | #!/usr/bin/env python3
##
# Copyright (c) 2019-2020, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# # Redistributions of source code must retain the above copyright
# ... |
TensorFlow2/Recommendation/WideAndDeep/triton/deployment_toolkit/triton_performance_runner/model_analyzer | model_analyzer | model_analyzer | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... |
PyTorch/LanguageModeling/BERT/triton/runner | runner | summary | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/Classification/GPUNet/triton/scripts/docker | docker | triton_inference_server | #!/usr/bin/env bash
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... |
TensorFlow2/Recommendation/WideAndDeep/triton/runner/maintainer/docker | docker | __init__ | # Copyright (c) 2021-2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/benchmark/models | models | __init__ | # Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/SpeechRecognition/Jasper/triton/scripts | scripts | prepare_model_repository | #!/bin/bash
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless ... |
PyTorch/Translation/Transformer/scripts | scripts | build_sym_alignment | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
#
"""
Use this script in order to ... |
CUDA-Optimized/FastSpeech/tacotron2 | tacotron2 | audio_processing | # BSD 3-Clause License
# Copyright (c) 2018-2020, NVIDIA Corporation
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, thi... |
DGLPyTorch/DrugDiscovery/SE3Transformer | SE3Transformer | .gitignore | data/
.DS_Store
*wandb/
*.pt
*.swp
# added by FAFU
.idea/
cache/
downloaded/
*.lprof
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
*.egg-info/
... |
TensorFlow2/Classification/ConvNets/efficientnet_v1/B0/training/AMP | AMP | convergence_8xA100-80G | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/SpeechSynthesis/Tacotron2 | Tacotron2 | config | {
"audio": {
"max-wav-value": 32768.0,
"sampling-rate": 22050,
"filter-length": 1024,
"hop-length": 256,
"win-length": 1024,
"mel-fmin": 0.0,
"mel-fmax": 7000.0
}
}
|
TensorFlow/Detection/SSD/models/research/slim/datasets | datasets | preprocess_imagenet_validation_data | #!/usr/bin/python
# Copyright 2016 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... |
TensorFlow/Segmentation/UNet_Industrial/utils | utils | __init__ | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# ==============================================================================
#
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the L... |
Tools/PyTorch/TimeSeriesPredictionPlatform/conf/trainer/callbacks/callbacks | callbacks | throughput_benchmark | # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... |
PyTorch/LanguageModeling/BERT/data | data | Downloader | # Copyright (c) 2019-2020 NVIDIA CORPORATION. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
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