relative_path stringclasses 812
values | section stringclasses 339
values | filename stringlengths 2 61 | text stringlengths 6 1.76M |
|---|---|---|---|
PyTorch/Translation/GNMT/scripts/tests | tests | inference | #!/bin/bash
# Copyright (c) 2018-2020, NVIDIA CORPORATION. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights... |
PyTorch/Classification/GPUNet/triton | triton | export_model | #!/usr/bin/env python3
# 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
#
# U... |
Tools/PyTorch/TimeSeriesPredictionPlatform/models/tft_pyt/triton/deployment_toolkit/bermuda | bermuda | pyt | # 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... |
TensorFlow2/Recommendation/DLRM_and_DCNv2/dataloading | dataloading | feature_spec | # 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/scripts | scripts | UNet_AMP_8GPU | #!/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... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/benchmark/tasks | tasks | __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... |
TensorFlow2/LanguageModeling/BERT/official/nlp/modeling/layers | layers | attention | # 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/LanguageModeling/BERT/triton/dist4l/scripts | scripts | setup_environment | #!/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/Translation/Transformer/fairseq/data | data | dictionary | # 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.
from collections import Counter
im... |
PyTorch/Forecasting/TFT/triton/runner | runner | exceptions | # 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/hparams | hparams | trt | parent_yaml: 'infer.yaml'
# Inference
batch_size: 1 # Batch size.
use_trt: True # Usage of TensorRT. Must be True to enable TensorRT.
use_fp16: True # Usage of FP16. Set to True to enable half precision for the engine.
# TRT
trt_file_path: "/workspace/fastspeech/fastspee... |
PyTorch/Recommendation/NCF | NCF | neumf | # Copyright (c) 2018, deepakn94, robieta. 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 | scripts | export_symbols | #!/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
# ... |
PyTorch/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/structures | structures | boxlist_ops | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
from .bounding_box import BoxList
from maskrcnn_benchmark.layers import nms as _box_nms
from maskrcnn_benchmark import _C
def boxlist_nms(boxlist, nms_thresh, max_proposals=-1, score_field="score"):
"""
Performs non-maximum... |
PyTorch/Translation/Transformer/fairseq/optim | optim | __init__ | # 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.
import importlib
import os
from .... |
TensorFlow2/Recommendation/DLRM_and_DCNv2/deployment/deployment_toolkit | deployment_toolkit | __init__ | # 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/triton | triton | model | # 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/Forecasting/TFT/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... |
PyTorch/Detection/Efficientdet/effdet/object_detection | object_detection | argmax_matcher | # Copyright 2020 Google Research. 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 law... |
PyTorch/Classification/GPUNet/triton/05ms-D | 05ms-D | README | # Deploying the GPUNet model on Triton Inference Server
This folder contains instructions for deployment to run inference
on Triton Inference Server as well as a detailed performance analysis.
The purpose of this document is to help you with achieving
the best inference performance.
## Table of contents
- [Solution... |
PyTorch/Classification/ConvNets/efficientnet/training/AMP | AMP | DGX1V-16G_efficientnet-widese-b0_AMP | python ./multiproc.py --nproc_per_node 8 ./launch.py --model efficientnet-widese-b0 --precision AMP --mode convergence --platform DGX1V-16G /imagenet --workspace ${1:-./} --raport-file raport.json
|
Tools/PyTorch/TimeSeriesPredictionPlatform/conf/trainer/optimizer | optimizer | RMSprop | # 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 ... |
TensorFlow2/Classification/ConvNets/efficientnet_v2/S/training/AMP | AMP | train_benchmark_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/Segmentation/nnUNet/triton | triton | convert_model | #!/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... |
TensorFlow2/Recommendation/DLRM_and_DCNv2/tensorflow-dot-based-interact | tensorflow-dot-based-interact | setup | # 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/175ms/runner | runner | pipeline_impl | # 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/scripts | scripts | ieee_fraud | # 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... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/generator/tabular/data_transformer | data_transformer | base_data_transformer | # 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... |
TensorFlow2/LanguageModeling/BERT/official/utils/misc | misc | tpu_lib | # Copyright 2019 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... |
TensorFlow2/Classification/ConvNets/efficientnet_v1/B4/inference | inference | inference_AMP | # 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/Recommendation/DLRM | DLRM | requirements_preprocessing | numpy
pandas
joblib==0.16
tqdm
|
TensorFlow/Segmentation/UNet_Medical/tf_exports | tf_exports | tf_export | import glob
import inspect
import os
import shutil
import subprocess
from typing import List, Callable
import tensorflow as tf
from google.protobuf import text_format
from tensorflow.core.framework import graph_pb2
from tensorflow.python.compiler.tensorrt import trt_convert as trt
from tensorflow.python.framework impo... |
PyTorch/DrugDiscovery/MoFlow/moflow/runtime | runtime | train | # 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... |
PyTorch/SpeechSynthesis/FastPitch/triton | triton | calculate_metrics | #!/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... |
PyTorch/LanguageModeling/BERT/data | data | GooglePretrainedWeightDownloader | # 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 applicabl... |
TensorFlow/LanguageModeling/BERT/data | data | NVIDIAPretrainedWeightDownloader | # 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 applicabl... |
PyTorch/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/engine | engine | inference | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import datetime
import logging
import time
import os
import torch
from tqdm import tqdm
from maskrcnn_benchmark.data.datasets.evaluation import evaluate
from ..utils.comm import is_m... |
TensorFlow/LanguageModeling/BERT/triton | triton | run_squad_triton_client | # 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 applicabl... |
PyTorch/Classification/GPUNet/models | models | gpunet_modules | # 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/generator/graph | graph | random | # 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... |
TensorFlow2/Detection/Efficientdet/utils | utils | model_utils | # Copyright 2020 Google Research. 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 law... |
PyTorch/Segmentation/MaskRCNN/pytorch/configs | configs | e2e_mask_rcnn_R_50_FPN_1x_bs64 | MODEL:
META_ARCHITECTURE: "GeneralizedRCNN"
WEIGHT: "catalog://ImageNetPretrained/MSRA/R-50"
BACKBONE:
CONV_BODY: "R-50-FPN"
OUT_CHANNELS: 256
RPN:
USE_FPN: True
ANCHOR_STRIDE: (4, 8, 16, 32, 64)
PRE_NMS_TOP_N_TRAIN: 2000
PRE_NMS_TOP_N_TEST: 1000
POST_NMS_TOP_N_TEST: 1000
FPN_POS... |
TensorFlow2/LanguageModeling/BERT/official/modeling/training | training | distributed_executor | # Copyright 2019 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... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/preprocessing/datasets | datasets | ieee | # 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/Classification/ConvNets/resnext101-32x4d/training/AMP | AMP | DGX1V_resnext101-32x4d_AMP_250E | python ./multiproc.py --nproc_per_node 8 ./launch.py --model resnext101-32x4d --precision AMP --mode convergence --platform DGX1V /imagenet --workspace ${1:-./} --raport-file raport.json
|
TensorFlow2/Recommendation/SIM | SIM | requirements | pynvml==11.0.0
git+https://github.com/NVIDIA/dllogger#egg=dllogger |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/preprocessing/datasets | datasets | epinions | # 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... |
TensorFlow2/Recommendation/DLRM_and_DCNv2/deployment | deployment | deploy | # 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/DLRM_and_DCNv2/doc | doc | merlin_hps_inference | # Deploying Large Recommender models with Merlin HPS and Triton Inference Server
This file contains instructions to run inference
on Triton Inference Server as well as detailed performance analysis for DLRM and DCNv2
with Merlin HPS and TensorRT. It is intended to provide the best possible performance for
inference wi... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/utils | utils | cugraph | # 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/Detection/Efficientdet/effdet/layers | layers | drop | """ DropBlock, DropPath
PyTorch implementations of DropBlock and DropPath (Stochastic Depth) regularization layers.
Papers:
DropBlock: A regularization method for convolutional networks (https://arxiv.org/abs/1810.12890)
Deep Networks with Stochastic Depth (https://arxiv.org/abs/1603.09382)
Code:
DropBlock impl inspire... |
TensorFlow/Segmentation/MaskRCNN | MaskRCNN | README | Both TensorFlow 1.x and TensorFlow 2.x versions of Mask-RCNN are located in [TensorFlow2/Segmentation/MaskRCNN folder](https://github.com/NVIDIA/DeepLearningExamples/tree/master/TensorFlow2/Segmentation/MaskRCNN).
Mask-RCNN model for TensorFlow1 is no longer maintained.
|
PyTorch/Forecasting/TFT/triton | triton | metrics | # 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/WideAndDeep/data/outbrain | outbrain | embedding_sizes | {"document_id": 128, "ad_id": 128, "document_id_promo": 128, "source_id_promo": 64, "source_id": 64, "geo_location": 64, "advertiser_id": 64, "geo_location_state": 64, "publisher_id_promo": 64, "publisher_id": 64, "geo_location_country": 64, "platform": 19, "campaign_id": 128, "topic_id_list": 64, "entity_id_list": 64,... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/trt/denoiser | denoiser | denoiserInstance | /*
* 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/LanguageModeling/BART/bart/modeling | modeling | modeling_t5 | # coding=utf-8
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# Copyright 2018 Mesh TensorFlow authors, T5 Authors and HuggingFace Inc. team.
#
# 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 t... |
PyTorch/SpeechRecognition/QuartzNet/common | common | sampler | import torch
import numpy as np
from torch.utils.data.sampler import Sampler
class DistributedSampler(Sampler):
def __init__(self, dataset, batch_size, world_size, rank):
"""
Constructor for the DistributedSampler.
:param dataset: dataset
:param batch_size: local batch size
... |
PyTorch/Classification/ConvNets/triton/deployment_toolkit/library | library | onnx | # 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... |
TensorFlow2/Segmentation/MaskRCNN/mrcnn_tf2/object_detection | object_detection | shape_utils | # 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... |
TensorFlow2/Recommendation/SIM | SIM | README | # SIM For TensorFlow 2
This repository provides a script and recipe to train the SIM model to achieve state-of-the-art accuracy. The content of this repository is tested and maintained by NVIDIA.
## Table Of Contents
- [Model overview](#model-overview)
* [Model architecture](#model-architecture)
* [Default c... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/trt/plugins/taco2AttentionPlugin | taco2AttentionPlugin | taco2AttentionLayerPlugin | /*
* 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/SpeechSynthesis/Tacotron2/trtis_cpp/scripts | scripts | build_benchmark_engines | #!/bin/bash
##
# 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, ... |
TensorFlow2/Recommendation/WideAndDeep/triton | triton | README | # Deploying the Wide & Deep model on Triton Inference Server
This folder contains instructions for deployment to run inference
on Triton Inference Server as well as a detailed performance analysis.
The purpose of this document is to help you with achieving
the best inference performance.
## Table of contents
- [Sol... |
TensorFlow/Detection/SSD/models/research/object_detection/utils | utils | shape_utils_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/Classification/ConvNets/se-resnext101-32x4d | se-resnext101-32x4d | README | # SE-ResNext101-32x4d for TensorFlow
This repository provides a script and recipe to train the SE-ResNext101-32x4d model to achieve state-of-the-art accuracy, and is tested and maintained by NVIDIA.
SE-ResNext101-32x4d model for TensorFlow1 is no longer maintained and will soon become unavailable, please consider PyTo... |
TensorFlow2/LanguageModeling/ELECTRA/data | data | WikicorpusTextFormatting | # 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 applicabl... |
TensorFlow/Detection/SSD/models/research/object_detection | object_detection | model_lib_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/SpeechSynthesis/Tacotron2/trtis_cpp | trtis_cpp | build_trtis | #!/bin/bash
##
# 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, ... |
TensorFlow2/Segmentation/MaskRCNN/mrcnn_tf2/utils | utils | box_utils | # Copyright 2019 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/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/structures | structures | image_list | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
from __future__ import division
import torch
class ImageList(object):
"""
Structure that holds a list of images (of possibly
varying sizes) as a single tensor.
This w... |
FasterTransformer | FasterTransformer | README | # FasterTransformer
## This repo can now be found here: https://github.com/NVIDIA/FasterTransformer.
|
Tools/PyTorch/TimeSeriesPredictionPlatform | TimeSeriesPredictionPlatform | README | # Time-Series Prediction Platform 1.1 for PyTorch
Time-series prediction is a common problem in multiple domains for various applications, including retail, industry, smart cities, and financial services. Research in the time-series field is growing exponentially, with hundreds of deep learning time-series forecasting... |
PyTorch/SpeechSynthesis/Tacotron2/filelists | filelists | ljs_audio_text_val_filelist | LJSpeech-1.1/wavs/LJ022-0023.wav|The overwhelming majority of people in this country know how to sift the wheat from the chaff in what they hear and what they read.
LJSpeech-1.1/wavs/LJ043-0030.wav|If somebody did that to me, a lousy trick like that, to take my wife away, and all the furniture, I would be mad as hell, ... |
PyTorch/Classification/GPUNet/triton | triton | calculate_metrics | #!/usr/bin/env python3
# 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
#
# U... |
PyTorch/SpeechSynthesis/FastPitch/triton/deployment_toolkit/bermuda | bermuda | onnx | # 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/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... |
TensorFlow/Classification/ConvNets/resnext101-32x4d | resnext101-32x4d | README | # ResNext101-32x4d for TensorFlow
This repository provides a script and recipe to train the ResNext101-32x4d model to achieve state-of-the-art accuracy, and is tested and maintained by NVIDIA.
ResNext101-32x4d model for TensorFlow1 is no longer maintained and will soon become unavailable, please consider PyTorch or Te... |
TensorFlow/Classification/ConvNets/model/blocks | blocks | __init__ | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# 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/lic... |
PyTorch/SpeechSynthesis/FastPitch/common/text | text | abbreviations | import re
_no_period_re = re.compile(r'(No[.])(?=[ ]?[0-9])')
_percent_re = re.compile(r'([ ]?[%])')
_half_re = re.compile('([0-9]½)|(½)')
_url_re = re.compile(r'([a-zA-Z])\.(com|gov|org)')
# List of (regular expression, replacement) pairs for abbreviations:
_abbreviations = [(re.compile('\\b%s\\.' % x[0], re.IGNORE... |
DGLPyTorch/DrugDiscovery/SE3Transformer/scripts | scripts | benchmark_train_multi_gpu | #!/usr/bin/env bash
# Script to benchmark multi-GPU training performance, with bases precomputation
# CLI args with defaults
BATCH_SIZE=${1:-240}
AMP=${2:-true}
python -m torch.distributed.run --nnodes=1 --nproc_per_node=gpu --max_restarts 0 --module \
se3_transformer.runtime.training \
--amp "$AMP" \
--batch_s... |
PyTorch/LanguageModeling/Transformer-XL/pytorch/scripts/tests | tests | train_full | #!/bin/bash
# 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
#
# Un... |
TensorFlow2/Classification/ConvNets | ConvNets | requirements | six
google-api-python-client>=1.6.7
google-cloud-bigquery>=0.31.0
kaggle>=1.3.9
numpy>=1.15.4
oauth2client>=4.1.2
pandas>=0.22.0
psutil>=5.4.3
py-cpuinfo>=3.3.0
scipy>=0.19.1
tensorflow-hub>=0.6.0
tensorflow-model-optimization>=0.2.1
tensorflow-datasets
tensorflow-addons
dataclasses
gin-config
tf_slim>=1.1.0
typing
sen... |
CUDA-Optimized/FastSpeech/tacotron2 | tacotron2 | __init__ | # 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... |
TensorFlow/Detection/SSD/models/research/object_detection/utils | utils | config_util_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/SpeechRecognition/wav2vec2/common/fairseq/modules | modules | multihead_attention | # 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.
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may n... |
TensorFlow2/LanguageModeling/BERT | BERT | run_squad | # 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... |
DGLPyTorch/DrugDiscovery/SE3Transformer/se3_transformer/runtime | runtime | arguments | # Copyright (c) 2021-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the righ... |
PyTorch/Classification/ConvNets/resnet50v1.5/training/AMP | AMP | DGX1V_resnet50_AMP_90E | python ./multiproc.py --nproc_per_node 8 ./launch.py --model resnet50 --precision AMP --mode convergence --platform DGX1V /imagenet --epochs 90 --mixup 0.0 --workspace ${1:-./} --raport-file raport.json
|
PyTorch/Detection/Efficientdet/effdet/layers | layers | activations_me | # 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/SpeechRecognition/wav2vec2/common/fairseq/modules | modules | quant_noise | # 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.
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may n... |
TensorFlow/Classification/ConvNets/resnet50v1.5/training | training | DGX2_RN50_AMP_90E | #!/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 r... |
PyTorch/Classification/ConvNets/efficientnet/inference/FP32 | FP32 | DGXA100_efficientnet-widese-b4_FP32 |
python ./multiproc.py --nproc_per_node 8 ./launch.py --model efficientnet-widese-b4 --precision FP32 --mode benchmark_inference --platform DGXA100 /imagenet -b 1 --workspace ${1:-./} --raport-file raport_1.json
python ./multiproc.py --nproc_per_node 8 ./launch.py --model efficientnet-widese-b4 --precision FP32 --mode ... |
TensorFlow/Classification/ConvNets/triton | triton | run_offline_performance_test_on_triton | #!/usr/bin/env python3
# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... |
TensorFlow/Detection/SSD/models/research/slim/nets | nets | inception_v3_test | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
PyTorch/Recommendation/DLRM/tests | tests | test_fspecs | #!/bin/bash
NAMES=${1:-'*.yaml'}
COMMON_OPTS="--embedding_type=joint_sparse --interaction_op=dot"
bash test_with_opts.sh "${NAMES}" "${COMMON_OPTS}"
#
# usage:
# docker build . -t nvidia_dlrm_pyt
# docker run --security-opt seccomp=unconfined --runtime=nvidia -it --rm --ipc=host -v ${PWD}/data:/... |
PyTorch/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/modeling/rpn | rpn | __init__ | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# from .rpn import build_rpn
|
PyTorch/SpeechSynthesis/Tacotron2 | Tacotron2 | requirements | matplotlib
numpy
inflect
librosa
scipy
resampy==0.3.1
git+https://github.com/NVIDIA/dllogger@v0.1.0#egg=dllogger
|
PyTorch/Recommendation/NCF | NCF | LICENSE | Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
... |
TensorFlow2/Detection/Efficientdet/dataset | dataset | __init__ | # Copyright 2020 Google Research. 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 law... |
DGLPyTorch/DrugDiscovery/SE3Transformer/se3_transformer/model/layers | layers | pooling | # Copyright (c) 2021-2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the righ... |
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