relative_path stringclasses 812
values | section stringclasses 339
values | filename stringlengths 2 61 | text stringlengths 6 1.76M |
|---|---|---|---|
TensorFlow/Detection/SSD/models/research/object_detection/utils | utils | np_mask_ops_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/Segmentation/UNet_Industrial/scripts | scripts | UNet_FP32_8GPU_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/LanguageModeling/BERT | BERT | README | # BERT For TensorFlow
This repository provides a script and recipe to train the BERT model for TensorFlow to achieve state-of-the-art accuracy, and is tested and maintained by NVIDIA.
BERT model for TensorFlow1 is no longer maintained and will soon become unavailable, please consider PyTorch or TensorFlow2 models as a... |
Kaldi/SpeechRecognition/scripts | scripts | run_inference_all_t4 | #!/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... |
TensorFlow/Recommendation/NCF | NCF | input_pipeline | # -----------------------------------------------------------------------
#
# 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
#
# ... |
Tools/PyTorch/TimeSeriesPredictionPlatform/models/tft_pyt/scripts | scripts | run_volatility_DGX1-16G | # 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/Classification/GPUNet/configs | configs | gpunet_torchhub | # 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/Segmentation/MaskRCNN/pytorch/scripts | scripts | inference_benchmark | #!/bin/bash
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#Predictions will be stored in `FOLDER`/inference`
#1x8x4 DGX1V
GPU=1
CONFIG='configs/e2e_mask_rcnn_R_50_FPN_1x.yaml'
DTYPE=$1
#This folder should a file called 'last_checkpoint' which contains the path to the actual checkpoint
FOLDER='/resul... |
TensorFlow/Segmentation/UNet_Medical/examples | examples | unet_TRAIN_BENCHMARK_1GPU | # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
Tools/PyTorch/TimeSeriesPredictionPlatform/models/tft_pyt | tft_pyt | requirements | tensorboard
pandas==1.1.4 |
PyTorch/SpeechRecognition/Jasper/platform | platform | DGX2_Jasper_AMP_8GPU | #!/bin/bash
NUM_GPUS=8 AMP=true BATCH_SIZE=64 GRAD_ACCUMULATION_STEPS=1 bash scripts/train.sh "$@"
|
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... |
TensorFlow/Detection/SSD/models/research/object_detection | object_detection | README |
# Tensorflow Object Detection API
Creating accurate machine learning models capable of localizing and identifying
multiple objects in a single image remains a core challenge in computer vision.
The TensorFlow Object Detection API is an open source framework built on top of
TensorFlow that makes it easy to construct, t... |
PyTorch/Forecasting/TFT/triton/runner | runner | start_NVIDIA-A30 | # 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/layers | layers | padding | """ Padding Helpers
Hacked together by / Copyright 2020 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
#
# ... |
PyTorch/Classification/ConvNets/efficientnet | efficientnet | README | # EfficientNet For PyTorch
This repository provides a script and recipe to train the EfficientNet model to
achieve state-of-the-art accuracy, and is tested and maintained by NVIDIA.
## Table Of Contents
* [Model overview](#model-overview)
* [Default configuration](#default-configuration)
* [Feature support matri... |
TensorFlow2/Recommendation/DLRM_and_DCNv2/nn | nn | interaction | # Copyright 2020 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/HiFiGAN/common | common | tb_dllogger | # 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/Recommendation/DLRM/dlrm/cuda_src/dot_based_interact | dot_based_interact | dot_based_interact_tf32_bwd | #include <cuda.h>
#include <cuda_fp16.h>
#include <cuda_runtime_api.h>
#include <device_launch_parameters.h>
#include <mma.h>
#include <cuda_fp16.hpp>
#include <math.h>
#include <fstream>
#include <iomanip>
#include <iostream>
#include <vector>
#include <ATen/cuda/CUDAContext.h>
#include <torch/extension.h>
#include... |
PyTorch/Classification/GPUNet/triton/deployment_toolkit/triton_performance_runner/perf_analyzer | perf_analyzer | 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... |
TensorFlow/Segmentation/VNet/examples | examples | vnet_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... |
TensorFlow/Recommendation/WideAndDeep/scripts | scripts | DGXA100_benchmark_training_tf32_1gpu | #!/bin/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 requi... |
TensorFlow/Classification/ConvNets/triton/deployment_toolkit/library | library | tf2onnx_conv | # 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/BART/bart/tokenization | tokenization | tokenization_mbart | # coding=utf-8
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# Copyright 2020 The Facebook AI Research Team Authors and The 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 cop... |
CUDA-Optimized/FastSpeech/fastspeech/utils | utils | fp16 | # 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... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/generator/tabular/data_transformer | data_transformer | ctgan_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... |
Tools/PyTorch/TimeSeriesPredictionPlatform/models/tft_pyt/triton/deployment_toolkit | deployment_toolkit | report | # 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_3D_Medical/runtime | runtime | arguments | # 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/LanguageModeling/BERT/utils | utils | cuda_bind | # 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/LanguageModeling/BERT/triton/large/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/Classification/GPUNet/triton/08ms-D/runner | runner | config_NVIDIA-DGX-A100-(1x-A100-80GB) | batching: dynamic
checkpoints:
- name: 0.8ms-D
url: https://api.ngc.nvidia.com/v2/models/nvidia/dle/gpunet_p1_pyt_ckpt/versions/21.12.0_amp/zip
configurations:
- checkpoint: 0.8ms-D
parameters:
backend_accelerator: trt
checkpoint: 0.8ms-D
device_kind: gpu
export_format: onnx
export_precision: fp... |
TensorFlow2/Segmentation/MaskRCNN/mrcnn_tf2/utils | utils | coco_metric | # 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... |
TensorFlow2/Recommendation/DLRM_and_DCNv2/deployment/deployment_toolkit/triton_performance_runner | triton_performance_runner | runner | # 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/triton/deployment_toolkit/perf_analyzer | perf_analyzer | perf_config | # 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/Segmentation/MaskRCNN/pytorch/configs | configs | e2e_mask_rcnn_X_101_32x8d_FPN_1x | MODEL:
META_ARCHITECTURE: "GeneralizedRCNN"
WEIGHT: "catalog://ImageNetPretrained/FAIR/20171220/X-101-32x8d"
BACKBONE:
CONV_BODY: "R-101-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:... |
PyTorch/LanguageModeling/BERT/triton/dist6l/runner | runner | config_NVIDIA-T4 | checkpoints:
- name: dist-6l-qa
url: https://api.ngc.nvidia.com/v2/models/nvidia/dle/bert_pyt_ckpt_distilled_6l_768d_qa_squad11_amp/versions/20.12.0/zip
configurations:
- accelerator: none
accelerator_precision: fp16
batch_size:
- 1
batch_sizes: '1'
capture_cuda_graph: 0
checkpoint_variant: dist-6l-qa
e... |
TensorFlow/Detection/SSD/models/research/object_detection/models | models | ssd_mobilenet_v1_fpn_feature_extractor | # 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/HiFiGAN/scripts/docker | docker | build | #!/usr/bin/env bash
docker build . -t hifigan:latest
|
TensorFlow2/LanguageModeling/ELECTRA/data | data | Downloader | # 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/Forecasting/TFT/triton/runner | runner | runner_proxy | # 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 | configuration | # 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/QuartzNet/common/text | text | __init__ | # Copyright (c) 2017 Keith Ito
""" from https://github.com/keithito/tacotron """
import re
import string
from . import cleaners
def _clean_text(text, cleaner_names, *args):
for name in cleaner_names:
cleaner = getattr(cleaners, name)
if not cleaner:
raise Exception('Unknown cleaner: %s'... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/trt/tacotron2 | tacotron2 | tacotron2Instance | /*
* 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/SpeechRecognition/wav2vec2/scripts/docker | docker | run | #!/usr/bin/env bash
# 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
#
# Unle... |
TensorFlow2/Classification/ConvNets/dataloader | dataloader | dali_index | #!/bin/bash
SRC_DIR=${1}
DST_DIR=${2}
echo "Creating training file indexes"
mkdir -p ${DST_DIR}
for file in ${SRC_DIR}/train-*; do
BASENAME=$(basename $file)
DST_NAME=$DST_DIR/$BASENAME
echo "Creating index $DST_NAME for $file"
tfrecord2idx $file $DST_NAME
done
echo "Creating validation file indexe... |
PyTorch/Segmentation/MaskRCNN/pytorch/configs/quick_schedules | quick_schedules | e2e_mask_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
ROI_MASK_HEAD:
PREDICTOR: "MaskRCNNC4Predictor"
SHARE_BOX_FEATURE_EXTRACTOR: True
MASK_ON: True
DATASE... |
PyTorch/Translation/Transformer | Transformer | train | #!/usr/bin/env python3 -u
# 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.
#
#------... |
PyTorch/Classification/GPUNet/triton/08ms-D/runner | runner | __main__ | # 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/Detection/Efficientdet/efficientnet/blocks | blocks | __init__ | from efficientnet.blocks.conv2d_block import conv2d_block
from efficientnet.blocks.mb_conv_block import mb_conv_block
__all__ = ['conv2d_block', 'mb_conv_block'] |
TensorFlow/Detection/SSD/models/research/object_detection/samples/configs | configs | ssd_mobilenet_v1_0.75_depth_300x300_coco14_sync | # SSD with Mobilenet v1 0.75 depth multiplied feature extractor and focal loss.
# Trained on COCO14, initialized from Imagenet classification checkpoint
# Achieves 17.5 mAP on COCO14 minival dataset. Doubling the number of training
# steps gets to 18.4.
# This config is TPU compatible
model {
ssd {
inplace_bat... |
TensorFlow2/Detection/Efficientdet/scripts/D0 | D0 | inference-benchmark | #!/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/FastPitch/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/SpeechSynthesis/Tacotron2/waveglow | waveglow | model | # *****************************************************************************
# 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... |
TensorFlow/Segmentation/UNet_Industrial/model/blocks | blocks | __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... |
PyTorch/Forecasting/TFT/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/Classification/GPUNet/triton/085ms/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/HiFiGAN/platform | platform | DGXA100_HiFi-GAN_AMP_1GPU | #!/bin/bash
set -a
: ${NUM_GPUS:=1}
: ${BATCH_SIZE:=128}
: ${GRAD_ACCUMULATION:=1}
: ${AMP:=true}
bash scripts/train_lj22khz.sh "$@" --no_amp_grouped_conv
|
Tools/PyTorch/TimeSeriesPredictionPlatform/models | models | tspp_xgboost | # 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/tensorflow-dot-based-interact/tensorflow_dot_based_interact | tensorflow_dot_based_interact | __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/Segmentation/MaskRCNN/pytorch/configs | configs | e2e_mask_rcnn_R_50_C4_1x | MODEL:
META_ARCHITECTURE: "GeneralizedRCNN"
WEIGHT: "catalog://ImageNetPretrained/MSRA/R-50"
RPN:
PRE_NMS_TOP_N_TEST: 6000
POST_NMS_TOP_N_TEST: 1000
ROI_MASK_HEAD:
PREDICTOR: "MaskRCNNC4Predictor"
SHARE_BOX_FEATURE_EXTRACTOR: True
MASK_ON: True
DATASETS:
TRAIN: ("coco_2014_train", "coco_2014... |
PyTorch/Classification/ConvNets/resnext101-32x4d/training/AMP | AMP | DGXA100_resnext101-32x4d_AMP_90E | python ./multiproc.py --nproc_per_node 8 ./launch.py --model resnext101-32x4d --precision AMP --mode convergence --platform DGXA100 /imagenet --epochs 90 --mixup 0.0 --workspace ${1:-./} --raport-file raport.json
|
PyTorch/SpeechSynthesis/FastPitch/platform | platform | DGX1_FastPitch_AMP_4GPU | #!/bin/bash
set -a
: ${NUM_GPUS:=4}
: ${BATCH_SIZE:=16}
: ${GRAD_ACCUMULATION:=4}
: ${AMP:=true}
bash scripts/train.sh "$@"
|
TensorFlow/Detection/SSD/models/research/object_detection/box_coders | box_coders | mean_stddev_box_coder_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/Recommendation/WideAndDeep/tests | tests | test_with_opts | #!/bin/bash
set -e
set -x
NAMES=${1:-'*.yaml'}
TARGET=/wd/tests/feature_specs/${NAMES}
OPTIONS=${2-""}
for file in ${TARGET};
do
echo "${file}";
done
for fspec_file in ${TARGET};
do
CSV_DIR=/tmp/generated_data/csv_dir
TRANS_DIR=/tmp/generated_data/trans_dir
# generate data based on fspec
python gen_csv.py --f... |
PyTorch/SpeechSynthesis/FastPitch/triton | triton | run_inference_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/mobilenet | mobilenet | mobilenet_v2 | # 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/SpeechRecognition/Jasper/triton/model_repo_configs/fp32/jasper-onnx | jasper-onnx | config | # Copyright (c) 2019, 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 conditions a... |
PyTorch/Segmentation/nnUNet/data_loading | data_loading | data_module | # 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/Recommendation/DLRM/dlrm/cuda_src/dot_based_interact_volta | dot_based_interact_volta | dot_based_interact_pytorch_types | #include <torch/extension.h>
#include <torch/types.h>
#include <stdexcept>
#include "../dot_based_interact/dot_based_interact_fp16_fwd.cu"
#include "../dot_based_interact/dot_based_interact_fp16_bwd.cu"
#include "../dot_based_interact/dot_based_interact_fp32_fwd.cu"
#include "../dot_based_interact/dot_based_interact_fp... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/utils | utils | memory_manager | # 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/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/Detection/SSD/models/research/object_detection/samples/configs | configs | mask_rcnn_resnet50_atrous_coco | # Mask R-CNN with Resnet-50 (v1), Atrous version
# Configured 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 tha... |
TensorFlow/Detection/SSD/models/research/object_detection/utils | utils | vrd_evaluation_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/Classification/ConvNets/se-resnext101-32x4d/training/FP32 | FP32 | DGX1V_se-resnext101-32x4d_FP32_250E | python ./multiproc.py --nproc_per_node 8 ./launch.py --model se-resnext101-32x4d --precision FP32 --mode convergence --platform DGX1V /imagenet --workspace ${1:-./} --raport-file raport.json
|
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/trt/waveglow | waveglow | waveGlowBuilder | /*
* 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/FastPitch/common/text | text | acronyms | import re
from . import cmudict
_letter_to_arpabet = {
'A': 'EY1',
'B': 'B IY1',
'C': 'S IY1',
'D': 'D IY1',
'E': 'IY1',
'F': 'EH1 F',
'G': 'JH IY1',
'H': 'EY1 CH',
'I': 'AY1',
'J': 'JH EY1',
'K': 'K EY1',
'L': 'EH1 L',
'M': 'EH1 M',
'N': 'EH1 N',
'O': 'OW1',... |
PyTorch/SpeechRecognition/Jasper/triton/model_repo_configs/fp32/jasper-ts-trace-ensemble | jasper-ts-trace-ensemble | config | name: "jasper-ts-trace-ensemble"
platform: "ensemble"
max_batch_size: 8#MAX_BATCH
input {
name: "AUDIO_SIGNAL"
data_type: TYPE_FP32
dims: -1#AUDIO_LENGTH
}
input {
name: "NUM_SAMPLES"
data_type: TYPE_INT32
dims: [ 1 ]
}
output {
name: "TRANSCRIPT"
data_type: TYPE_INT32
dims: [-1]
}
e... |
PyTorch/SpeechSynthesis/Tacotron2/waveglow | waveglow | entrypoints | # *****************************************************************************
# 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/SpeechRecognition/Jasper/triton | triton | jasper-client | #!/usr/bin/python
# 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
#
# U... |
PyTorch/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/data/samplers | samplers | iteration_based_batch_sampler | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
from torch.utils.data.sampler import BatchSampler
class IterationBasedBatchSampler(BatchSampler):
"""
Wraps a BatchSampler, resampling from it until
a specified number of iterations have been sampled
"""
def __init__(self, ba... |
PyTorch/LanguageModeling/BERT/triton/dist6l/runner | runner | start_NVIDIA-DGX-1-(1x-V100-32GB) | # 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/plugins/taco2ModulationRemovalPlugin | taco2ModulationRemovalPlugin | taco2ModulationRemovalLayerPluginCreator | /*
* 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/Classification/ConvNets/resnext101-32x4d/training/TF32 | TF32 | DGXA100_resnext101-32x4d_TF32_250E | python ./multiproc.py --nproc_per_node 8 ./launch.py --model resnext101-32x4d --precision TF32 --mode convergence --platform DGXA100 /imagenet --workspace ${1:-./} --raport-file raport.json
|
PyTorch/SpeechRecognition/wav2vec2/common/fairseq/data | data | dictionary | # 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... |
PyTorch/SpeechRecognition/wav2vec2/common/fairseq/data | data | data_utils_fast | # 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/utils | utils | data_utils | #!/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 | FastPitch | models | # 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... |
TensorFlow/Detection/SSD/models/research/object_detection/anchor_generators | anchor_generators | grid_anchor_generator | # 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/DrugDiscovery/MoFlow/moflow/data | data | encoding | # 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/LanguageModeling/BART/bart/tokenization | tokenization | tokenization_bart | # coding=utf-8
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# Copyright 2020 The Facebook AI Research Team Authors and The 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 cop... |
TensorFlow2/Segmentation/MaskRCNN/mrcnn_tf2/ops | ops | training_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... |
PyTorch/Detection/Efficientdet/scripts/D0 | D0 | train_TF32_8xA100-80G | #!/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 8 /workspace/object_detection/dat... |
TensorFlow/Detection/SSD/models/research/object_detection/samples/configs | configs | ssd_mobilenet_v1_pets | # SSD with Mobilenet v1, configured for Oxford-IIIT Pets 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 co... |
TensorFlow/Segmentation/UNet_Medical | UNet_Medical | download_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 applic... |
PyTorch/Segmentation/MaskRCNN/pytorch/configs/pascal_voc | pascal_voc | e2e_faster_rcnn_R_50_C4_1x_4_gpu_voc | MODEL:
META_ARCHITECTURE: "GeneralizedRCNN"
WEIGHT: "catalog://ImageNetPretrained/MSRA/R-50"
RPN:
PRE_NMS_TOP_N_TEST: 6000
POST_NMS_TOP_N_TEST: 300
ANCHOR_SIZES: (128, 256, 512)
ROI_BOX_HEAD:
NUM_CLASSES: 21
DATASETS:
TRAIN: ("voc_2007_train", "voc_2007_val")
TEST: ("voc_2007_test",)
SOLVER:... |
TensorFlow/Detection/SSD/models/research/object_detection/utils | utils | np_box_list_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... |
MxNet/Classification/RN50v1.5 | RN50v1.5 | benchmarking | # 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... |
TensorFlow/Segmentation/UNet_Industrial/datasets | datasets | __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... |
PyTorch/SpeechSynthesis/Tacotron2/phrases | phrases | phrase | 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.
|
Tools/PyTorch/TimeSeriesPredictionPlatform/conf/hydra/job_logging | job_logging | primary | # @package _group_
# 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
#
# ... |
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