relative_path stringclasses 812
values | section stringclasses 339
values | filename stringlengths 2 61 | text stringlengths 6 1.76M |
|---|---|---|---|
PyTorch/Classification/GPUNet/triton/runner/maintainer | maintainer | container | # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow/Detection/SSD/models/research/slim/nets | nets | resnet_v2_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/SpeechRecognition/Jasper/scripts | scripts | inference | #!/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 requi... |
PyTorch/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/modeling/roi_heads/box_head | box_head | roi_box_feature_extractors | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
from torch import nn
from torch.nn import functional as F
from maskrcnn_benchmark.modeling import registry
from maskrcnn_benchmark.modeling.backbone import resnet
from mas... |
PyTorch/Forecasting/TFT/triton/runner | runner | executor | # 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/Detection/SSD/models/research/object_detection/core | core | preprocessor_cache | # 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... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/preprocessing/datasets | datasets | ogbn_mag240m | # 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/scripts/D0 | D0 | inference_TF32_A100-80G | #!/bin/bash
rm -rf *.json
python -u -m bind_launch --nproc_per_node=${NUM_PROC:-1} validate.py '/workspace/object_detection/datasets/coco/' --model efficientdet_d0 -b ${BATCH_SIZE:-8} --torchscript --use-ema --checkpoint ${CKPT_PATH:-/checkpoints/Effdet_B0.pth} --inference |
Tools/DGLPyTorch/SyntheticGraphGeneration/docker_scripts | docker_scripts | run_docker_interactive | if [ ! "$(ls | grep -c docker_scripts)" -eq 1 ]; then
echo "Run this script from root directory. Usage: bash ./docker_scripts/run_docker_interactive.sh"
exit 1
fi
IMG="${IMAGE:=graph_gen}"
nvidia-docker run --rm -it \
--ipc=host \
--net=host \
-v "$(pwd)":/workspace \
${IMG} \
bash
|
TensorFlow2/Classification/ConvNets/utils | utils | cmdline_helper | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/lic... |
CUDA-Optimized/FastSpeech/fastspeech/hparams | hparams | trt_multi_engine | parent_yaml: 'trt.yaml'
# TRT
trt_multi_engine: True
trt_file_path_list: [
"/fastspeech/preprocessed/v0.2.0/fastspeech.i32.o256.trt",
"/fastspeech/preprocessed/v0.2.0/fastspeech.i64.o512.trt",
"/fastspeech/preprocessed/v0.2.0/fastspeech.i96.o768.trt",
"/fastspeech/preprocessed/v0.2.0/fastspeech.i128.o1024.trt"... |
PyTorch/Segmentation/nnUNet/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/Classification/GPUNet/models | models | gpunet_builder | # 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/LanguageModeling/BERT/scripts | scripts | run_squad_inference | #!/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/LanguageModeling/BART/scripts | scripts | run_training_benchmark | #!/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/Segmentation/nnUNet/triton/scripts/docker | docker | triton_inference_server | #!/usr/bin/env bash
# Copyright (c) 2021 NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unle... |
PyTorch/Segmentation/nnUNet | nnUNet | requirements | git+https://github.com/NVIDIA/dllogger
git+https://github.com/NVIDIA/mlperf-common.git
nibabel==3.2.1
joblib==1.0.1
pytorch-lightning==1.7.7
scikit-learn==1.0
scikit-image==0.18.3
scipy==1.8.1
rich==12.5.0 |
TensorFlow2/Recommendation/DLRM_and_DCNv2/doc | doc | multidataset | # BYO dataset functionality overview
This section describes how you can train the DeepLearningExamples RecSys models on your own datasets without changing
the model or data loader and with similar performance to the one published in each repository.
This can be achieved thanks to Dataset Feature Specification, which d... |
TensorFlow2/LanguageModeling/ELECTRA/data | data | SquadDownloader | # 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/triton/deployment_toolkit/triton_performance_runner/perf_analyzer | perf_analyzer | exceptions | # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow/Detection/SSD/models/research/object_detection/metrics | metrics | oid_od_challenge_evaluation_utils | # 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/examples | examples | SSD320_inference | #
# 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 appl... |
TensorFlow2/Classification/ConvNets/efficientnet_v2/S/evaluation | evaluation | evaluation_FP32_V100-32G | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
Tools/DGLPyTorch/SyntheticGraphGeneration/docker_scripts | docker_scripts | build_docker | if [ ! "$(ls | grep -c docker_scripts)" -eq 1 ]; then
echo "Run this script from root directory. Usage: bash ./docker_scripts/build_docker.sh"
exit 1
fi
IMG="${IMAGE:=graph_gen}"
docker build . -t ${IMG}
|
Kaldi/SpeechRecognition/kaldi-asr-backend | kaldi-asr-backend | CMakeLists | # Copyright (c) 2021, 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... |
TensorFlow2/Recommendation/DLRM_and_DCNv2/tests/feature_specs | feature_specs | 20_num | channel_spec:
categorical:
- cat_0.bin
- cat_1.bin
- cat_2.bin
- cat_3.bin
- cat_4.bin
- cat_5.bin
- cat_6.bin
- cat_7.bin
- cat_8.bin
- cat_9.bin
- cat_10.bin
- cat_11.bin
- cat_12.bin
- cat_13.bin
- cat_14.bin
- cat_15.bin
- cat_16.bin
- cat_17.bin
- cat_18.bin
- cat_19.bin
... |
PyTorch/Segmentation/MaskRCNN/pytorch/tests | tests | test_data_samplers | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import itertools
import random
import unittest
from torch.utils.data.sampler import BatchSampler
from torch.utils.data.sampler import Sampler
from torch.utils.data.sampler import SequentialSampler
from torch.utils.data.sampler import RandomSampler... |
PyTorch/Classification/ConvNets/se-resnext101-32x4d/training/TF32 | TF32 | DGXA100_se-resnext101-32x4d_TF32_90E | python ./multiproc.py --nproc_per_node 8 ./launch.py --model se-resnext101-32x4d --precision TF32 --mode convergence --platform DGXA100 /imagenet --epochs 90 --mixup 0.0 --workspace ${1:-./} --raport-file raport.json
|
Tools/PyTorch/TimeSeriesPredictionPlatform/conf | conf | deployment_config | # 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/Recommendation/DLRM/preproc | preproc | split_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/Forecasting/TFT/triton/scripts/docker | docker | triton_inference_server | #!/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/LanguageModeling/BART | BART | pretrain | # 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/Classification/ConvNets/runtime | runtime | __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... |
TensorFlow/Segmentation/VNet/utils | utils | tf_export | # 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/LanguageModeling/BERT/triton/runner | runner | 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... |
PyTorch/Translation/Transformer/fairseq/models | models | fairseq_incremental_decoder | # 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 torch.nn as nn
class Fair... |
TensorFlow2/Recommendation/WideAndDeep/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/Segmentation/MaskRCNN/pytorch/scripts/docker | docker | build | #!/bin/bash
docker build --rm -t nvidia_joc_maskrcnn_pt . -f Dockerfile |
PyTorch/Classification/ConvNets/se-resnext101-32x4d/training/FP32 | FP32 | DGX1V_se-resnext101-32x4d_FP32_90E | python ./multiproc.py --nproc_per_node 8 ./launch.py --model se-resnext101-32x4d --precision FP32 --mode convergence --platform DGX1V /imagenet --epochs 90 --mixup 0.0 --workspace ${1:-./} --raport-file raport.json
|
TensorFlow/Recommendation/WideAndDeep/utils/hooks | hooks | training_hooks | #! /usr/bin/python
# -*- coding: utf-8 -*-
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licens... |
Tools/PyTorch/TimeSeriesPredictionPlatform/triton/deployment_toolkit/model_analyzer | model_analyzer | model_analyzer | # 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/LanguageModeling/ELECTRA/scripts | scripts | finetune_ckpts_on_squad | #!/usr/bin/env bash
# Copyright (c) 2020 NVIDIA CORPORATION. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... |
PyTorch/Detection/Efficientdet/scripts/waymo | waymo | validation_AMP_8xA100-80G | #!/bin/bash
NUM_PROC=$1
rm -rf *.json
python -u -m bind_launch --nproc_per_node=${NUM_PROC} validate.py '/workspace/object_detection/datasets/waymo' --model efficientdet_d0 -b 10 --amp --waymo --use-ema --input_size 1536 --num_classes 3 --waymo-val /waymo/validation/images --waymo-val-annotation /waymo/validation/anno... |
PyTorch/Segmentation/MaskRCNN/pytorch/maskrcnn_benchmark/utils | utils | imports | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
import torch
import importlib
import importlib.util
import sys
# from https://stackoverflow.com/questions/67631/how-to-import-a-module-given-the-full-path?utm_medium=organic&utm_sour... |
TensorFlow2/Recommendation/DLRM_and_DCNv2/dataloading | dataloading | defaults | # 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... |
Tools/PyTorch/TimeSeriesPredictionPlatform/conf/trainer/criterion | criterion | L1 | # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... |
PyTorch/LanguageModeling/Transformer-XL/pytorch/utils | utils | vocabulary | # Copyright (c) 2019-2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... |
PyTorch/Recommendation/DLRM/dlrm/cuda_src/dot_based_interact | dot_based_interact | dot_based_interact_tf32_fwd | #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... |
Kaldi/SpeechRecognition/kaldi-asr-client | kaldi-asr-client | asr_client_imp | // Copyright (c) 2020-2021, 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 requ... |
PyTorch/Recommendation/DLRM/dlrm/cuda_src/dot_based_interact | dot_based_interact | dot_based_interact_fp16_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 <fstream>
#include <iomanip>
#include <iostream>
#include <vector>
#include <ATen/cuda/CUDAContext.h>
#include <torch/extension.h>
#include "shared_utils.cuh... |
PyTorch/Detection/Efficientdet/scripts/D0 | D0 | train-benchmark_AMP_V100-32G | #!/bin/bash
function get_dataloader_workers {
gpus=$(nvidia-smi -i 0 --query-gpu=count --format=csv,noheader)
core=$(nproc --all)
workers=$((core/gpus-2))
workers=$((workers>16?16:workers))
echo ${workers}
}
WORKERS=$(get_dataloader_workers)
./distributed_train.sh ${NUM_PROC:-8} /workspace/object_... |
PaddlePaddle/LanguageModeling/BERT/utils | utils | config | # 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/Transformer-XL/pytorch/utils | utils | __init__ | # Copyright (c) 2019-2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... |
TensorFlow/LanguageModeling/BERT/scripts | scripts | run_glue_inference | #!/usr/bin/env bash
# Copyright (c) 2019 NVIDIA CORPORATION. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless ... |
PyTorch/SpeechRecognition/wav2vec2/scripts | scripts | finetune_vox_100h | #!/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... |
PaddlePaddle/LanguageModeling/BERT/utils | utils | affinity | # Copyright (c) 2022 NVIDIA Corporation. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow/Detection/SSD/models/research/object_detection/core | core | post_processing_test | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
TensorFlow/Detection/SSD/models/research/object_detection/metrics | metrics | coco_evaluation | # 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/UNet_Medical/examples | examples | unet_TRAIN_SINGLE | # 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/quick_schedules | quick_schedules | e2e_faster_rcnn_R_50_FPN_quick | 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... |
PyTorch/SpeechSynthesis/HiFiGAN/scripts | scripts | train_lj22khz | #!/usr/bin/env bash
export OMP_NUM_THREADS=1
# Enables faster cuDNN kernels (available since the 21.12-py3 NGC container)
export CUDNN_V8_API_ENABLED=1 # Keep the flag for older containers
export TORCH_CUDNN_V8_API_ENABLED=1
: ${NUM_GPUS:=8}
: ${BATCH_SIZE:=16}
: ${AMP:=false}
: ${EPOCHS:=6500}
: ${OUTPUT_DIR:="res... |
TensorFlow/LanguageModeling/BERT/scripts | scripts | run_squad_inference | #!/usr/bin/env bash
# Copyright (c) 2019 NVIDIA CORPORATION. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless ... |
PyTorch/Recommendation/DLRM | DLRM | bind | # 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... |
TensorFlow2/Segmentation/MaskRCNN/mrcnn_tf2/runtime | runtime | learning_rate | import tensorflow as tf
class PiecewiseConstantWithWarmupSchedule(tf.keras.optimizers.schedules.LearningRateSchedule):
"""
Schedule that starts with learning rate at `init_value` and monotonically increases
it up to `values[0]` at step `boundaries[0]`. After that the learning rate changes
on each boun... |
TensorFlow2/LanguageModeling/BERT/official/utils/logs | logs | hooks_helper_test | # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
TensorFlow/Detection/SSD/models/research/object_detection/dataset_tools | dataset_tools | download_and_preprocess_mscoco | #!/bin/bash
# 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 require... |
TensorFlow/Detection/SSD/models/research/object_detection/models | models | ssd_inception_v2_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... |
TensorFlow2/Recommendation/SIM/preprocessing | preprocessing | io | # 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 appli... |
PyTorch/SpeechRecognition/Jasper/triton/model_repo_configs/fp32/jasper-tensorrt-ensemble | jasper-tensorrt-ensemble | config | name: "jasper-tensorrt-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/Segmentation/MaskRCNN/pytorch/configs/caffe2 | caffe2 | e2e_mask_rcnn_R_50_C4_1x_caffe2 | MODEL:
META_ARCHITECTURE: "GeneralizedRCNN"
WEIGHT: "catalog://Caffe2Detectron/COCO/35858791/e2e_mask_rcnn_R-50-C4_1x"
ROI_MASK_HEAD:
PREDICTOR: "MaskRCNNC4Predictor"
SHARE_BOX_FEATURE_EXTRACTOR: True
MASK_ON: True
DATASETS:
TEST: ("coco_2014_minival",)
|
TensorFlow/Segmentation/UNet_Medical/model | model | layers | # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
PyTorch/Recommendation/DLRM/tests/feature_specs | feature_specs | 13_num_10_cat | channel_spec:
categorical:
- cat_0.bin
- cat_1.bin
- cat_2.bin
- cat_3.bin
- cat_4.bin
- cat_5.bin
- cat_6.bin
- cat_7.bin
- cat_8.bin
- cat_9.bin
label:
- label
numerical: &id001
- num_0
- num_1
- num_2
- num_3
- num_4
- num_5
- num_6
- num_7
- num_8
- num_9
- num_10
... |
TensorFlow/Detection/SSD/models/research/slim/nets | nets | mobilenet_v1 | # 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 applicable ... |
PyTorch/SpeechSynthesis/Tacotron2/trtis_cpp/src/trt/util | util | dataShuffler | /*
* 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/anchor_generators | anchor_generators | multiple_grid_anchor_generator_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... |
CUDA-Optimized/FastSpeech/fastspeech/hparams | hparams | train_amp | # Inheritance
parent_yaml: "train.yaml"
# Path
log_path: ""
checkpoint_path: ""
# Train
final_steps: 25
log_step: 1
use_amp: True
nvprof_iter_start: 5
nvprof_iter_end: 25
pyprof_enabled: False |
TensorFlow/Detection/SSD/models/research/object_detection/dataset_tools | dataset_tools | create_pycocotools_package | #!/bin/bash
# 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 require... |
PyTorch/LanguageModeling/BERT/triton/runner/maintainer/docker | docker | __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... |
TensorFlow2/Classification/ConvNets/efficientnet_v1/B4/training/FP32 | FP32 | train_benchmark_8xV100-32G | # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... |
TensorFlow/Detection/SSD/models/research/object_detection | object_detection | inputs | # 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... |
Tools/PyTorch/TimeSeriesPredictionPlatform/models/tft_pyt/scripts/autobench | autobench | ngc_favorita_HP_search | NGC: &NGC
hostname: ngc
instance: dgx1v.32g.8.norm
job_name: "ml-model.tft favorita HP search"
docker_image: nvcr.io/nvidian/swdl/jbaczek:tft_pyt
datasets:
/data: 78291
workspaces:
/ws: VUMFFB3uSv25FDlkXg80Vw
download_dir: /home/jbaczek/Downloads
jobs:
- steps:
- EPOCHS=10 DATASET=favor... |
TensorFlow2/Recommendation/WideAndDeep/triton | triton | calculate_metrics | #!/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
... |
Tools/PyTorch/TimeSeriesPredictionPlatform/conf/model | model | dask_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/LanguageModeling/BERT/official/utils/logs | logs | cloud_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/src/trt/util | util | engineCache | /*
* 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 | TFT | modeling | # 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/LanguageModeling/Transformer-XL | Transformer-XL | README | # Transformer-XL For TensorFlow
This repository provides a script and recipe to train the Transformer-XL model
to achieve state-of-the-art accuracy and is tested and maintained by NVIDIA.
Transformer-XL model for TensorFlow1 is no longer maintained and will soon become unavailable, please consider other PyTorch or Ten... |
Tools/DGLPyTorch/SyntheticGraphGeneration/syngen/generator/tabular | tabular | ctab | # 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... |
TensorFlow/Detection/SSD/models/research/slim/datasets | datasets | download_and_convert_cifar10 | # 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 applica... |
TensorFlow/Recommendation/VAE-CF/scripts | scripts | 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 appli... |
TensorFlow/Detection/SSD/models/research/object_detection/builders | builders | anchor_generator_builder | # 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/LanguageModeling/BERT/scripts/docker | docker | build | #!/bin/bash
URL=${1:-"bert"}
PUSH=${2:-"none"} # 'push' or 'none'
set -e
docker build \
--network=host \
--rm \
--pull \
--no-cache \
-t ${URL} \
.
if [ "${PUSH}" == "push" ]; then
docker push ${URL}
elif [ "${PUSH}" == "none" ]; then
echo "Keep the built image locally."
else
echo "Invalid \${PUSH... |
TensorFlow2/Segmentation/MaskRCNN/mrcnn_tf2 | mrcnn_tf2 | arguments | # 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... |
PyTorch/LanguageModeling/BART/scripts | scripts | run_pretraining | #!/usr/bin/env bash
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unle... |
PyTorch/Detection/Efficientdet/effdet | effdet | __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/SpeechSynthesis/Tacotron2/filelists | filelists | ljs_mel_text_train_subset_2500_filelist | LJSpeech-1.1/mels/LJ026-0104.pt|so starch manufactured in the leaves must be digested (dissolved) before it can be transported.
LJSpeech-1.1/mels/LJ012-0101.pt|They had had serious work to get at the diamonds. It was necessary to force one heavy door from its hinges, and to cut through the thick panels of another.
LJSp... |
TensorFlow/LanguageModeling/BERT/triton | triton | README | # Deploying the BERT TensorFlow model using Triton Inference Server
This folder contains instructions for deployment and exemplary client application to run inference on
Triton Inference Server as well as detailed performance analysis.
## Table Of Contents
* [Solution Overview](#solution-overview)
* [Setup](#setup... |
PyTorch/Forecasting/TFT/triton | triton | README | # Deploying the TFT 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 ov... |
TensorFlow/LanguageModeling/BERT | BERT | __init__ | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# 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/Recommendation/DLRM/tests/feature_specs | feature_specs | default | channel_spec:
categorical:
- cat_0.bin
- cat_1.bin
- cat_2.bin
- cat_3.bin
- cat_4.bin
- cat_5.bin
- cat_6.bin
- cat_7.bin
- cat_8.bin
- cat_9.bin
- cat_10.bin
- cat_11.bin
- cat_12.bin
- cat_13.bin
- cat_14.bin
- cat_15.bin
- cat_16.bin
- cat_17.bin
- cat_18.bin
- cat_19.bin
... |
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