relative_path stringclasses 812
values | section stringclasses 339
values | filename stringlengths 2 61 | text stringlengths 6 1.76M |
|---|---|---|---|
PyTorch/Classification/GPUNet | GPUNet | train | #!/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... |
TensorFlow2/Segmentation/MaskRCNN/mrcnn_tf2/ops | ops | roi_ops | # 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... |
TensorFlow2/Classification/ConvNets/utils | utils | optimizer_factory | # 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/LanguageModeling/BERT/data | data | bertPrep | # 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... |
Tools/PyTorch/TimeSeriesPredictionPlatform/models/tft_pyt/triton/runner/maintainer | maintainer | exceptions | # 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 | triton | model | # 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/Classification/ConvNets/triton/scripts/docker | docker | interactive | #!/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... |
TensorFlow/Classification/ConvNets | ConvNets | inference | import argparse
import os
import pathlib
import time
import tempfile
import tensorflow as tf
import numpy as np
from tensorflow.python.compiler.tensorrt import trt_convert as trt
import dllogger
from runtime import runner_utils
from runtime import runner
from model.resnet import model_architectures
from utils impor... |
TensorFlow2/LanguageModeling/ELECTRA/data | data | __init__ | # 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/Classification/ConvNets/model/layers | layers | math_ops | # 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
#
# Unless required by applic... |
Tools/DGLPyTorch/SyntheticGraphGeneration/configurations | configurations | ogbn_mag | {
"nodes": [
{
"name": "paper",
"count": 736389,
"features": [
{
"name": "feat_0",
"dtype": "float32",
"feature_type": "continuous"
},
{
"name":... |
PyTorch/Classification/GPUNet/triton | triton | requirements | # 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... |
CUDA-Optimized/FastSpeech/fastspeech/utils | utils | optimizer | # 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/Forecasting/TFT | TFT | configuration | # 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/SpeechSynthesis/FastPitch/platform | platform | DGX1_FastPitch_FP32_1GPU | #!/bin/bash
set -a
: ${NUM_GPUS:=1}
: ${BATCH_SIZE:=16}
: ${GRAD_ACCUMULATION:=16}
: ${AMP:=false}
bash scripts/train.sh "$@"
|
PyTorch/Translation/Transformer/fairseq/modules | modules | sinusoidal_positional_embedding | # 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 math
from typing import Opt... |
TensorFlow/Detection/SSD/examples | examples | SSD320_FP32_1GPU | # 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/PyTorch/TimeSeriesPredictionPlatform/evaluators | evaluators | evaluator | # 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/Classification/ConvNets | ConvNets | multiproc | # From PyTorch:
#
# Copyright (c) 2018-2019, NVIDIA CORPORATION. All rights reserved.
# Copyright (c) 2016- Facebook, Inc (Adam Paszke)
# Copyright (c) 2014- Facebook, Inc (Soumith Chintala)
# Copyright (c) 2011-2014 Idiap Research Institute (Ronan Collobert)
# Copyright (c) 2012-2014 Deep... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/trt/tacotron2 | tacotron2 | tacotron2Loader | /*
* 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/Recommendation/VAE-CF | VAE-CF | prepare_dataset | # 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 appli... |
Tools/PyTorch/TimeSeriesPredictionPlatform/conf/trainer/optimizer | optimizer | SparseAdam | # 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/Recommendation/DLRM_and_DCNv2/deployment | deployment | __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/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.
![](img/2_obj... |
PyTorch/SpeechRecognition/QuartzNet/platform | platform | DGX2_QuartzNet_AMP_16GPU | #!/bin/bash
set -a
: ${NUM_GPUS:=16}
: ${GPU_BATCH_SIZE:=36}
: ${GRAD_ACCUMULATION:=2}
: ${AMP=:true}
bash scripts/train.sh "$@"
|
TensorFlow/Detection/SSD/models/research/object_detection/metrics | metrics | oid_vrd_challenge_evaluation | # 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... |
PyTorch/SpeechSynthesis/Tacotron2/platform | platform | DGX1_waveglow_FP32_4NGPU_train | mkdir -p output
python -m multiproc train.py -m WaveGlow -o output/ -lr 1e-4 --epochs 1001 -bs 4 --segment-length 8000 --weight-decay 0 --grad-clip-thresh 3.4028234663852886e+38 --cudnn-benchmark --cudnn-enabled --log-file nvlog.json
|
TensorFlow/Detection/SSD/models/research/object_detection/models | models | ssd_mobilenet_v2_fpn_feature_extractor_test | # 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/Detection/SSD/models/research/object_detection/samples/configs | configs | ssd_mobilenet_v1_0.75_depth_quantized_300x300_coco14_sync | # SSD with Mobilenet v1 with quantized training.
# Trained on COCO, initialized from Imagenet classification checkpoint
# Achieves 18.2 mAP on coco14 minival dataset.
# This config is TPU compatible
model {
ssd {
inplace_batchnorm_update: true
freeze_batchnorm: false
num_classes: 90
box_coder {
... |
PyTorch/Detection/Efficientdet/effdet/csrc/focal_loss | focal_loss | focal_loss_cuda_kernel | // 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 ... |
PyTorch/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/structures | structures | bounding_box | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
# transpose
FLIP_LEFT_RIGHT = 0
FLIP_TOP_BOTTOM = 1
class BoxList(object):
"""
This class represents a set of bounding boxes.
The bounding boxes are represen... |
PyTorch/Forecasting/TFT/triton/deployment_toolkit | deployment_toolkit | report | # 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/PyTorch/TimeSeriesPredictionPlatform/models/tft_pyt/triton/runner | runner | __main__ | # 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/image_classification | image_classification | logger | # Copyright (c) 2018-2019, NVIDIA CORPORATION
# Copyright (c) 2017- Facebook, Inc
#
# 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 ... |
TensorFlow2/Detection/Efficientdet/scripts/D0 | D0 | convergence-FP32-8xV100-32G | #!/bin/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
#
# Unless requir... |
TensorFlow/Detection/SSD/models/research/object_detection/samples/configs | configs | ssd_inception_v2_coco | # SSD with Inception v2 configuration for MSCOCO Dataset.
# Users should configure the fine_tune_checkpoint field in the train config as
# well as the label_map_path and input_path fields in the train_input_reader and
# eval_input_reader. Search for "PATH_TO_BE_CONFIGURED" to find the fields that
# should be configured... |
TensorFlow2/Segmentation/MaskRCNN/scripts | scripts | inference | # 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... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/graph_aligner | graph_aligner | __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/Segmentation/nnUNet/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... |
TensorFlow2/Recommendation/DLRM_and_DCNv2/doc | doc | DCNv2 | # DCNv2 for TensorFlow 2
## Table Of Contents
* [Model overview](#model-overview)
* [Model architecture](#model-architecture)
* [Quick Start Guide](#quick-start-guide)
* [Performance](#performance)
* [Benchmarking](#benchmarking)
* [Training performance benchmark](#training-performance-benchmar... |
PyTorch/Classification/ConvNets/efficientnet/inference/TF32 | TF32 | DGXA100_efficientnet-b4_TF32 |
python ./multiproc.py --nproc_per_node 8 ./launch.py --model efficientnet-b4 --precision TF32 --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-b4 --precision TF32 --mode benchmark_infe... |
TensorFlow/Detection/SSD/models/research/slim/datasets | datasets | download_and_convert_imagenet | #!/bin/bash
# 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 applica... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/bin | bin | CMakeLists | ##
# 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 list of... |
TensorFlow2/Detection/Efficientdet/scripts/D0 | D0 | evaluate-AMP-8xA100-80G | #!/bin/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
#
# Unless requir... |
PyTorch/Classification/GPUNet/triton/runner | runner | utils | # 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/Classification/ConvNets/utils | utils | cmdline_helper | #!/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... |
Kaldi/SpeechRecognition/notebooks | notebooks | README | ```
# 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 or agreed to in writing, software distributed under the Licen... |
TensorFlow/Detection/SSD/models/research/slim/nets | nets | resnet_v1 | # 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/examples | examples | SSD320_FP16_1GPU | # 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... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/test | test | CharacterMapping_test | /*
* 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/Forecasting/TFT/triton | triton | run_performance_on_triton | #!/usr/bin/env python3
# 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
... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/bin | bin | build_waveglow | /*
* 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/Recommendation/DLRM/dlrm/scripts | scripts | prepare_synthetic_dataset | # 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 appli... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/trt/tacotron2 | tacotron2 | decoderBuilderPlugins | /*
* 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/Translation/Transformer/fairseq | fairseq | multiprocessing_pdb | # 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 multiprocessing
import os
i... |
TensorFlow2/LanguageModeling/ELECTRA | ELECTRA | configuration_utils | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# 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 cop... |
PyTorch/LanguageModeling/BERT | BERT | create_pretraining_data | # coding=utf-8
# Copyright (c) 2019 NVIDIA CORPORATION. All rights reserved.
# Copyright 2018 The Google AI Language Team Authors and The HugginFace 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 ... |
PyTorch/Segmentation/nnUNet/notebooks | notebooks | custom_dataset | #!/usr/bin/env python
# coding: utf-8
# # nnUNet for custom dataset
# # Table of contents
# - [Introduction](#introduction)
# - [Model](#model)
# - [Model creation](#model-creation)
# - [Metric](#metric)
# - [Dataset](#dataset)
# - [Visualization](#visualization)
# - [Data loading](#dataloader)
# - [... |
TensorFlow2/Recommendation/WideAndDeep/triton/deployment_toolkit/triton_performance_runner/perf_analyzer | perf_analyzer | __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/Segmentation/MaskRCNN/mrcnn_tf2/object_detection | object_detection | region_similarity_calculator | # 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/Recommendation/DLRM/tests/transcoding | transcoding | small_csv | channel_spec:
categorical:
- cat_0.bin
- cat_1.bin
- cat_2.bin
- cat_3.bin
- cat_4.bin
- cat_5.bin
label:
- label
numerical: &id001
- num_0
- num_1
- num_2
feature_spec:
cat_0.bin:
cardinality: 10
cat_1.bin:
cardinality: 23412
cat_2.bin:
cardinality: 45000
cat_3.bin:
ca... |
PyTorch/Recommendation/DLRM/dlrm/cuda_src/sparse_gather | sparse_gather | gather_gpu | #include <cuda.h>
#include <cuda_fp16.h>
#include <cuda_runtime.h>
#include <math.h>
#include <cassert>
#include <iostream>
#include <ATen/cuda/CUDAContext.h>
#include <torch/extension.h>
// For simplicity reason, boundry checks are removed
// All the kernels MUST be launched with grid size = batch size and block s... |
Tools/PyTorch/TimeSeriesPredictionPlatform/conf/model_dataset | model_dataset | tft_electricity | # 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/Segmentation/MaskRCNN/pytorch/configs/quick_schedules | quick_schedules | e2e_faster_rcnn_R_50_C4_quick | MODEL:
META_ARCHITECTURE: "GeneralizedRCNN"
WEIGHT: "catalog://ImageNetPretrained/MSRA/R-50"
RPN:
PRE_NMS_TOP_N_TEST: 6000
POST_NMS_TOP_N_TEST: 1000
ROI_HEADS:
BATCH_SIZE_PER_IMAGE: 256
DATASETS:
TRAIN: ("coco_2014_minival",)
TEST: ("coco_2014_minival",)
INPUT:
MIN_SIZE_TRAIN: 600
MAX_SIZE_T... |
PyTorch/LanguageModeling/BERT | BERT | tokenization | # coding=utf-8
# Copyright (c) 2019-2021 NVIDIA CORPORATION. All rights reserved.
# Copyright 2018 The Google AI Language Team Authors and The HugginFace 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 cop... |
PyTorch/SpeechSynthesis/Tacotron2/tensorrt | tensorrt | test_infer_trt | # *****************************************************************************
# Copyright (c) 2018, 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... |
PyTorch/SpeechSynthesis/Tacotron2/notebooks/conversationalai/client/speech_ai_demo/utils/bert | bert | vocab | [PAD]
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[unused2]
[unused3]
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[unused5]
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[unused12]
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[unus... |
TensorFlow/Detection/SSD/models/research/object_detection/models | models | faster_rcnn_pnas_feature_extractor_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/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/layers | layers | __init__ | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
from .batch_norm import FrozenBatchNorm2d
from .misc import Conv2d
from .misc import ConvTranspose2d
from .misc import interpolate
from .misc import nhwc_to_nchw_transform... |
TensorFlow2/Classification/ConvNets/efficientnet_v1/B4/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... |
TensorFlow2/LanguageModeling/BERT/scripts | scripts | run_pretraining_lamb | #!/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/Detection/Efficientdet | Efficientdet | distributed_train | #!/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 requir... |
TensorFlow/Detection/SSD/models/research/slim/nets | nets | s3dg | # 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 applicable ... |
Tools/PyTorch/TimeSeriesPredictionPlatform/inference | inference | 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... |
TensorFlow2/Segmentation/nnUNet/models | models | nn_unet | # 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... |
PaddlePaddle/Classification/RN50v1.5/scripts/inference | inference | infer_resnet50_TF32 | # 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 app... |
PyTorch/SpeechSynthesis/Tacotron2 | Tacotron2 | multiproc | # *****************************************************************************
# Copyright (c) 2018, 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... |
TensorFlow2/Classification/ConvNets/efficientnet_v2/S/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... |
TensorFlow/Detection/SSD/configs | configs | ssd320_full_4gpus | # 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/Detection/Efficientdet/scripts/D0 | D0 | evaluate-AMP-8xV100-32G | #!/bin/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
#
# Unless requir... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/bin | bin | build_denoiser | /*
* 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/Recommendation/DLRM/dlrm/cuda_src | cuda_src | pytorch_embedding_ops | #include <torch/extension.h>
torch::Tensor gatherGPUFusedFwdTorch(torch::Tensor embedding,
torch::Tensor indices,
torch::Tensor offsets,
bool amp_train);
torch::Tensor gatherGPUFusedBwdTorch(torch::Ten... |
PyTorch/Detection/SSD/examples | examples | inference | #!/usr/bin/env python
# coding: utf-8
# # Inference on pretrained SSD model using Tensor Cores
# In this tutorial we will show, how to run an inference with our SSD implementation.
#
# We will start with defining input pipeline, then we will see how to load the model and then we will run an inference.
# ## Loading ... |
TensorFlow2/Recommendation/WideAndDeep/triton/scripts/docker | docker | interactive | #!/usr/bin/env bash
# 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
#
#... |
PyTorch/SpeechSynthesis/FastPitch/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... |
TensorFlow/Detection/SSD/models/research/object_detection/predictors/heads | heads | head | # 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/object_detection/builders | builders | post_processing_builder_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... |
TensorFlow2/Segmentation/MaskRCNN/mrcnn_tf2/ops | ops | postprocess_ops | # 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... |
PaddlePaddle/LanguageModeling/BERT | BERT | run_squad | # 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/Detection/SSD/examples | examples | SSD300_FP32_4GPU | # This script launches SSD300 training in FP32 on 4 GPUs using 128 batch size (32 per GPU)
# Usage ./SSD300_FP32_4GPU.sh <path to this repository> <path to dataset> <additional flags>
torchrun --nproc_per_node=4 $1/main.py --backbone resnet50 --warmup 300 --bs 32 --no-amp --data-layout channels_first --data $2 ${@:3}
|
TensorFlow/Classification/ConvNets/triton/deployment_toolkit/library | library | 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/Classification/ConvNets | ConvNets | launch | import os
from pathlib import Path
from dataclasses import dataclass
from typing import Dict, Any
import yaml
from main import main, add_parser_arguments, available_models
import torch.backends.cudnn as cudnn
import argparse
def get_config_path():
return Path(os.path.dirname(os.path.abspath(__file__))) / "confi... |
PyTorch/Classification/GPUNet/triton/065ms/runner | runner | start_NVIDIA-DGX-A100-(1x-A100-80GB) | # 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/Tacotron2/trtis_cpp/src/trt/util | util | speechDataBuffer | /*
* 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/Classification/ConvNets/resnet50v1.5/training | training | DGX1_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/DrugDiscovery/MoFlow/scripts | scripts | prepare_datasets | #!/bin/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
#
# Unless requi... |
PyTorch/Detection/Efficientdet/effdet/config | config | model_config | # 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... |
Tools/PyTorch/TimeSeriesPredictionPlatform/models/tft_pyt/triton/runner/maintainer | maintainer | maintainer_factory | # 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/src/trt/tacotron2 | tacotron2 | encoderBuilder | /*
* 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/slim/nets | nets | resnet_v2 | # 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 ... |
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