python_code stringlengths 0 679k | repo_name stringlengths 9 41 | file_path stringlengths 6 149 |
|---|---|---|
# ============================================================================ #
# Copyright (c) 2022 - 2023 NVIDIA Corporation & Affiliates. #
# All rights reserved. #
# ... | cuda-quantum-main | python/cudaq/domains/chemistry/__init__.py |
# ============================================================================ #
# Copyright (c) 2022 - 2023 NVIDIA Corporation & Affiliates. #
# All rights reserved. #
# ... | cuda-quantum-main | utils/mock_qpu/__init__.py |
# ============================================================================ #
# Copyright (c) 2022 - 2023 NVIDIA Corporation & Affiliates. #
# All rights reserved. #
# ... | cuda-quantum-main | utils/mock_qpu/ionq/__init__.py |
# ============================================================================ #
# Copyright (c) 2022 - 2023 NVIDIA Corporation & Affiliates. #
# All rights reserved. #
# ... | cuda-quantum-main | utils/mock_qpu/iqm/mock_iqm_server.py |
# ============================================================================ #
# Copyright (c) 2022 - 2023 NVIDIA Corporation & Affiliates. #
# All rights reserved. #
# ... | cuda-quantum-main | utils/mock_qpu/iqm/mock_iqm_cortex_cli.py |
# ============================================================================ #
# Copyright (c) 2022 - 2023 NVIDIA Corporation & Affiliates. #
# All rights reserved. #
# ... | cuda-quantum-main | utils/mock_qpu/quantinuum/__init__.py |
# ============================================================================ #
# Copyright (c) 2022 - 2023 NVIDIA Corporation & Affiliates. #
# All rights reserved. #
# ... | cuda-quantum-main | utils/mock_qpu/oqc/__init__.py |
# ============================================================================ #
# Copyright (c) 2022 - 2023 NVIDIA Corporation & Affiliates. #
# All rights reserved. #
# ... | cuda-quantum-main | docs/sphinx/conf.py |
import cudaq
import numpy as np
# Set the target to our density matrix simulator.
cudaq.set_target('density-matrix-cpu')
# CUDA Quantum supports custom noise models through the definition of
# `KrausChannel`'s. In this case, we will define a set of `KrausOperator`'s
# that affect the same noise as the `AmplitudeDamp... | cuda-quantum-main | docs/sphinx/examples/python/noise_kraus_operator.py |
import cudaq
import random
def random_bitstring(length: int):
bitstring = ""
for bit in range(length):
bitstring += str(random.randint(0, 1))
return bitstring
def oracle(kernel: cudaq.Kernel, register: cudaq.QuakeValue,
auxillary_qubit: cudaq.QuakeValue, hidden_bitstring: str):
""... | cuda-quantum-main | docs/sphinx/examples/python/bernstein_vazirani.py |
import cudaq
# Set the target to our density matrix simulator.
cudaq.set_target('density-matrix-cpu')
# CUDA Quantum supports several different models of noise. In this
# case, we will examine the modeling of decoherence of the qubit phase.
# This will occur from "phase flip" errors, wherein the qubit has a
# user-sp... | cuda-quantum-main | docs/sphinx/examples/python/noise_phase_flip.py |
import cudaq
# Set the target to our density matrix simulator.
cudaq.set_target('density-matrix-cpu')
# CUDA Quantum supports several different models of noise. In this case,
# we will examine the modeling of decoherence of the qubit state. This
# will occur from "bit flip" errors, wherein the qubit has a user-specif... | cuda-quantum-main | docs/sphinx/examples/python/noise_bit_flip.py |
import cudaq
# Set the target to our density matrix simulator.
cudaq.set_target('density-matrix-cpu')
# CUDA Quantum supports several different models of noise. In this
# case, we will examine the modeling of depolarization noise. This
# depolarization will result in the qubit state decaying into a mix
# of the basis... | cuda-quantum-main | docs/sphinx/examples/python/noise_depolarization.py |
import cudaq
from cudaq import spin
import numpy as np
# Here we build up a kernel for QAOA with `p` layers, with each layer
# containing the alternating set of unitaries corresponding to the problem
# and the mixer Hamiltonians. The algorithm leverages the VQE algorithm
# to compute the Max-Cut of a rectangular grap... | cuda-quantum-main | docs/sphinx/examples/python/qaoa_maxcut.py |
import cudaq
# Set the target to our density matrix simulator.
cudaq.set_target('density-matrix-cpu')
# CUDA Quantum supports several different models of noise. In this case,
# we will examine the modeling of energy dissipation within our system
# via environmental interactions. The result of this "amplitude damping"... | cuda-quantum-main | docs/sphinx/examples/python/noise_amplitude_damping.py |
import cudaq
from cudaq import spin
from typing import List, Tuple
# We will be optimizing over a custom objective function that takes a vector
# of parameters as input and returns either the cost as a single float,
# or in a tuple of (cost, gradient_vector) depending on the optimizer used.
# In this case, we will u... | cuda-quantum-main | docs/sphinx/examples/python/advanced_vqe.py |
import cudaq
from cudaq import spin
# We begin by defining the spin Hamiltonian for the system that we are working
# with. This is achieved through the use of `cudaq.SpinOperator`'s, which allow
# for the convenient creation of complex Hamiltonians out of Pauli spin operators.
hamiltonian = 5.907 - 2.1433 * spin.x(0) ... | cuda-quantum-main | docs/sphinx/examples/python/simple_vqe.py |
import cudaq
# We begin by defining the `Kernel` that we will construct our
# program with.
kernel = cudaq.make_kernel()
# Next, we can allocate qubits to the kernel via `qalloc(qubit_count)`.
# An empty call to `qalloc` will return a single qubit.
qubit = kernel.qalloc()
# Now we can begin adding instructions to ap... | cuda-quantum-main | docs/sphinx/examples/python/intro.py |
import cudaq
# You only have to set the target once! No need to redefine it
# for every execution call on your kernel.
# To use different targets in the same file, you must update
# it via another call to `cudaq.set_target()`
cudaq.set_target("iqm",
url="http://localhost/cocos",
**{"q... | cuda-quantum-main | docs/sphinx/examples/python/providers/iqm.py |
import cudaq
# You only have to set the target once! No need to redefine it
# for every execution call on your kernel.
# By default, we will submit to the Quantinuum syntax checker.
cudaq.set_target("quantinuum")
# Create the kernel we'd like to execute on Quantinuum.
kernel = cudaq.make_kernel()
qubits = kernel.qall... | cuda-quantum-main | docs/sphinx/examples/python/providers/quantinuum.py |
import cudaq
# You only have to set the target once! No need to redefine it
# for every execution call on your kernel.
# To use different targets in the same file, you must update
# it via another call to `cudaq.set_target()`
cudaq.set_target("ionq")
# Create the kernel we'd like to execute on IonQ.
kernel = cudaq.ma... | cuda-quantum-main | docs/sphinx/examples/python/providers/ionq.py |
#!/usr/bin/env python
#################################################################################################
# Copyright (c) 2010, Lawrence Livermore National Security, LLC.
# Produced at the Lawrence Livermore National Laboratory
# Written by Todd Gamblin, tgamblin@llnl.gov.
# LLNL-CODE-417602
# All rights ... | cuda-profiler-master | nvtx_pmpi_wrappers/wrap/wrap.py |
#!/usr/bin/python
import json
from collections import OrderedDict
from sys import argv
def return_json(payload):
return(json.dumps(payload,
sort_keys=True,
indent=4
)
)
if argv[1] == 'update_order':
fw_manifest = argv[2]
ver... | deepops-master | roles/nvidia-dgx-firmware/files/parse_manifest.py |
#!/usr/bin/env python3
import sys
import getopt
import math
def print_help():
print("")
print("calculate_N.py -- A script to calculate a range of N values near maximum Memory Use")
print("")
print("Example:")
print(" ./calculate.py --mem 32768 --nb 192 --ranks 8")
print("")
print("")
... | deepops-master | workloads/bit/hpl/calculate_N.py |
#!/usr/bin/python3
#
# format_results.py
#
# This script will format the results from an HPL
# experiment and write them into a comma separated file
# to be read into a spreadsheet for additional analysis.
import sys
import os
import subprocess
import getopt
import re
def print_help():
print("")
print("\tf... | deepops-master | workloads/bit/hpl/format_results.py |
#!/usr/bin/env python3
#
# verify_hpl_experiment.sh <DIRECTORY> (SYSTEM)
#
# This script will do two things.
# 1) It will verify the performance against a reference, if the reference is available
# 2) It will verify performance based on jitter of all of the results.
#
# In the event there are failed jobs, the no... | deepops-master | workloads/bit/hpl/verify_hpl_experiment.py |
# pylint: disable-all
import os, sys, argparse, time
import cupy
import dask
import dask.array as da
from dask_cuda import LocalCUDACluster
from dask.distributed import Client, LocalCluster, wait
from dask.delayed import delayed
from dask.diagnostics import ProgressBar
from multiprocessing.pool import ThreadPool
import... | deepops-master | workloads/examples/slurm/dask-rapids/files/sum.py |
#!/usr/bin/env python3
'''
Kubeflow documentation: https://kubeflow-pipelines.readthedocs.io/en/latest/_modules/kfp/dsl/_container_op.html
K8S documentation: https://github.com/kubernetes-client/python/blob/02ef5be4ecead787961037b236ae498944040b43/kubernetes/docs/V1Container.md
Example Triton Inference Server Models: ... | deepops-master | workloads/examples/k8s/kubeflow-pipeline-deploy/triton.py |
deepops-master | workloads/examples/k8s/kubeflow-pipeline-deploy/__init__.py | |
#!/usr/bin/env python3
import kfp.dsl as dsl
from kubernetes import client as k8s_client
import yaml
__TRITON_CONTAINER_VERSION__ = 'nvcr.io/nvidia/tritonserver:21.02-py3'
__TRITON_POD_LABEL__ = 'triton-kubeflow'
__TRITON_SERVICE_MANIFEST___ = '''
apiVersion: v1
kind: Service
metadata:
name: {}
spec:
selector:
... | deepops-master | workloads/examples/k8s/kubeflow-pipeline-deploy/triton_ops.py |
import kfp
import kfp_server_api
import json
import time
# Define and build a Kubeflow Pipeline
@kfp.dsl.pipeline(
name="kubeflow-quick-test",
description="Verify Kubeflow can launch a container via a pipeline")
def test_kubeflow_op():
op = kfp.dsl.ContainerOp(
name='kubeflow-test-op',
image='b... | deepops-master | workloads/jenkins/scripts/test-kubeflow-pipeline.py |
#!/usr/bin/env python
'''Because there is currently no clean way to update this config through ks this script exists.
The purpose of this script is to dynamically update Kubeflow to point at the latest NGC containers.
In addition to that it changes default resource requests to optimize for GPUs
TODO: Do this with Ans... | deepops-master | scripts/k8s/update_kubeflow_config.py |
#!/usr/bin/python
import datetime, bisect
def parse_timestamp(raw_str):
tokens = raw_str.split()
if len(tokens) == 1:
if tokens[0].lower() == 'never':
return 'never';
else:
raise Exception('Parse error in timestamp')
... | deepops-master | src/containers/dgxie/get_hosts.py |
#!/usr/bin/python
from flask import Flask, abort, request
import json
import datetime
import re
import os
app = Flask(__name__)
@app.route('/v1/boot/<mac>')
def pxe(mac):
'''See https://github.com/danderson/netboot/blob/master/pixiecore/README.api.md for API specs'''
# load machine profiles for each call so w... | deepops-master | src/containers/dgxie/api.py |
#!/usr/bin/python
from flask import Flask, request
from subprocess import check_output as run
import datetime
file = "/www/install.log"
with open(file, "a") as install_file:
install_file.write("== LOG OPENED ==\n")
app = Flask(__name__)
@app.route('/hosts')
def hosts():
return run("/usr/local/bin/get_hosts.... | deepops-master | src/containers/dgxie/rest_api.py |
#!/usr/bin/env python
"""
Get a list of Ansible playbooks and roles that have changes staged in Git.
Run ansible-lint on only those playbooks and roles.
"""
from __future__ import print_function
import subprocess
import re
import sys
def get_changed_ansible_paths():
"""
Get a list of playbook files and role... | deepops-master | src/repo/githooks/check-ansible.py |
#!/usr/bin/env python
"""
Get a list of changed python scripts that are staged for commit.
Run shellcheck on only those files.
"""
from __future__ import print_function
import subprocess
import re
import sys
def get_changed_paths():
git_diff = subprocess.check_output("git diff --name-only --cached".split())
... | deepops-master | src/repo/githooks/check-python.py |
#!/usr/bin/env python
"""
Get a list of changed bash scripts that are staged for commit.
Run shellcheck on only those files.
"""
from __future__ import print_function
import subprocess
import re
import sys
def get_changed_shell_paths():
git_diff = subprocess.check_output("git diff --name-only --cached".split())... | deepops-master | src/repo/githooks/check-shell.py |
#!/usr/bin/python3
#*****************************************************************************
# Copyright 2020 NVIDIA Corporation. All rights reserved.
#*****************************************************************************
import subprocess
import argparse
import datetime
import json
import time
def get_... | nvindex-cloud-master | provision/gke/finalize.py |
import websocket
import random
import logging
import sys
import json
import base64
import ssl
import time
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
def get_websocket(ws_cmd_url, credentials=None):
""" Generate a WebSocket connection to the service """
if credentials:
b64 = base64.b6... | nvindex-cloud-master | notebooks/nvindex_util.py |
#!/usr/bin/env python2
import sys, subprocess
if len(sys.argv) > 2:
ifile = sys.argv[1]
encopt = sys.argv[2:-1]
ofile = sys.argv[-1]
else:
print 'usage: %s <input> [encode_options] <output>' % sys.argv[0]
sys.exit(1)
analysis_cmd = 'ffprobe -v error -of compact=p=0:nk=1 '
analysis_cmd += '-sho... | GMAT-main | ffmpeg-gpu/tools/normalize.py |
#!/usr/bin/env python2
import sys, zmq, cmd
class LavfiCmd(cmd.Cmd):
prompt = 'lavfi> '
def __init__(self, bind_address):
context = zmq.Context()
self.requester = context.socket(zmq.REQ)
self.requester.connect(bind_address)
cmd.Cmd.__init__(self)
def onecmd(self, cmd):
... | GMAT-main | ffmpeg-gpu/tools/zmqshell.py |
# Copyright (c) 2019 Guo Yejun
#
# This file is part of FFmpeg.
#
# FFmpeg is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
#... | GMAT-main | ffmpeg-gpu/tools/python/convert_from_tensorflow.py |
# Copyright (c) 2019 Guo Yejun
#
# This file is part of FFmpeg.
#
# FFmpeg is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
#... | GMAT-main | ffmpeg-gpu/tools/python/convert.py |
# Copyright (c) 2019
#
# This file is part of FFmpeg.
#
# FFmpeg is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
# FFmpeg is... | GMAT-main | ffmpeg-gpu/tools/python/convert_header.py |
# Copyright (c) 2021
#
# This file is part of FFmpeg.
#
# FFmpeg is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
# FFmpeg is... | GMAT-main | ffmpeg-gpu/tools/python/tf_sess_config.py |
import torch
import torch.cuda as cuda
from frame_extractor import FrameExtractor
import threading
from functools import reduce
import time
import sys
import ctypes
cudaFree = ctypes.CDLL('libcudart.so').cudaFree
dev = torch.device("cuda:0")
# initialize cuda runtime
dummy = torch.empty((1,), device=dev)
def extract... | GMAT-main | metrans/python/app_extract_perf.py |
import torch
import torch.cuda as cuda
from frame_extractor import FrameExtractor
import ctypes
libnvToolsExt = ctypes.CDLL('libnvToolsExt.so')
nvtxRangePush = libnvToolsExt.nvtxRangePushA
nvtxRangePop = libnvToolsExt.nvtxRangePop
dev = torch.device("cuda:0")
dummy = torch.empty((1,), device=dev)
file_path = '../bui... | GMAT-main | metrans/python/app_extract.py |
import ctypes
CSwscale = ctypes.CDLL("../build/CSwscale.so")
SwscaleCuda_Nv12ToRgbpf32_Init = CSwscale.SwscaleCuda_Nv12ToRgbpf32_Init
SwscaleCuda_Nv12ToRgbpf32_Convert = CSwscale.SwscaleCuda_Nv12ToRgbpf32_Convert
SwscaleCuda_Nv12ToRgbpf32_Delete = CSwscale.SwscaleCuda_Nv12ToRgbpf32_Delete
SwscaleCuda_Nv12ToRgbpf32_I... | GMAT-main | metrans/python/swscale.py |
import numpy as np
import torch
import torch.cuda as cuda
from frame_extractor import FrameExtractor
import heif_format
import swscale
import ctypes
libnvToolsExt = ctypes.CDLL('libnvToolsExt.so')
nvtxRangePush = libnvToolsExt.nvtxRangePushA
nvtxRangePop = libnvToolsExt.nvtxRangePop
dev = torch.device("cuda:0")
dummy... | GMAT-main | metrans/python/app_extract_heif.py |
import ctypes
libavutil = ctypes.CDLL('libavutil.so')
libavutil.av_log_set_level(24)
CFrameExtractor = ctypes.CDLL('../build/CFrameExtractor.so')
FrameExtractor_InitFromFile = CFrameExtractor.FrameExtractor_InitFromFile
FrameExtractor_InitFromBuffer = CFrameExtractor.FrameExtractor_InitFromBuffer
FrameExtractor_Dele... | GMAT-main | metrans/python/frame_extractor.py |
import torch
import torch.cuda as cuda
import threading
from functools import reduce
import time
import sys
import ctypes
import pdb
from frame_extractor import FrameExtractor
import heif_format
import swscale
cudaFree = ctypes.CDLL('libcudart.so').cudaFree
cudaSetDevice = ctypes.CDLL('libcudart.so').cudaSetDevice
d... | GMAT-main | metrans/python/app_extract_heif_perf.py |
import ctypes
import numpy as np
CHeif = ctypes.CDLL('../build/CHeif.so')
NvEncLite_InitStill = CHeif.NvEncLite_InitStill
NvEncLite_EncodeDeviceFrame = CHeif.NvEncLite_EncodeDeviceFrame
NvHeifWriter_Init = CHeif.NvHeifWriter_Init
NvHeifWriter_WriteStillImage = CHeif.NvHeifWriter_WriteStillImage
NvHeifReader_Init = CH... | GMAT-main | metrans/python/heif_format.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.... | spark-rapids-benchmarks-dev | nds/nds_bench.py |
#!/usr/bin/env python3
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy... | spark-rapids-benchmarks-dev | nds/check.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lic... | spark-rapids-benchmarks-dev | nds/nds_transcode.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.... | spark-rapids-benchmarks-dev | nds/nds_rollback.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.... | spark-rapids-benchmarks-dev | nds/nds_power.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.... | spark-rapids-benchmarks-dev | nds/PysparkBenchReport.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.... | spark-rapids-benchmarks-dev | nds/nds_validate.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.... | spark-rapids-benchmarks-dev | nds/nds_maintenance.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.... | spark-rapids-benchmarks-dev | nds/nds_gen_data.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.... | spark-rapids-benchmarks-dev | nds/nds_schema.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.... | spark-rapids-benchmarks-dev | nds/nds_gen_query_stream.py |
#!/usr/bin/env python3
from pyspark import SparkContext
from pyspark.java_gateway import ensure_callback_server_started
class PythonListener(object):
package = "com.nvidia.spark.rapids.listener"
@staticmethod
def get_manager():
jvm = SparkContext.getOrCreate()._jvm
manager = getattr(jvm, "... | spark-rapids-benchmarks-dev | nds/python_listener/PythonListener.py |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# SPDX-FileCopyrightText: Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.... | spark-rapids-benchmarks-dev | nds/python_listener/__init__.py |
# 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 appli... | tao_launcher-main | release/__init__.py |
# 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 appli... | tao_launcher-main | release/utils.py |
# Copyright (c) 2016-2018, NVIDIA CORPORATION. All rights reserved.
"""Modules required to build the TAO CLI package."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
| tao_launcher-main | release/tao/__init__.py |
# Copyright (c) 2016-2018, NVIDIA CORPORATION. All rights reserved.
"""Setup script to build the TAO Toolkit CLI package."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import glob
import os
import setuptools
import sys
from release import utils
# De... | tao_launcher-main | release/tao/setup.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/version.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/__init__.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/config/__init__.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/__init__.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/types/task.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/types/__init__.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/instance_handler/base_instance.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/instance_handler/local_instance.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/instance_handler/__init__.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/instance_handler/builder.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/instance_handler/utils.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/instance_handler/whl_instance.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/docker_handler/docker_handler.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/components/docker_handler/__init__.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/entrypoint/__init__.py |
# 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 appli... | tao_launcher-main | nvidia_tao_cli/entrypoint/tao_launcher.py |
#!/usr/bin/python
import sys
import re
from submodules.rules import rules
def main():
with open(sys.argv[1], "r") as fp:
lines = fp.readlines()
for idx, line in enumerate(lines):
if line.strip() == "# ------------------------ >8 ------------------------":
break
if line[0] == "#":
continue
if... | tao_launcher-main | scripts/git-hooks/commit-msg.py |
tao_launcher-main | scripts/git-hooks/submodules/__init__.py | |
rules = """
# Failing to add message in the mentioned format will
# cause your local commit fail.
#
# Please follow these rules for commit messages:
# ==============================================
# 1. Commit message format - first line is mandatory
# [YOUR_MODULE_NAME] Subject line here not exceeding 50 characters... | tao_launcher-main | scripts/git-hooks/submodules/rules.py |
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | cloud-native-docs-master | conf.py |
# Use this file to bootstrap packman into your Python environment (3.7.x). Simply
# add the path by doing sys.insert to where packmanconf.py is located and then execute:
#
# >>> import packmanconf
# >>> packmanconf.init()
#
# It will use the configured remote(s) and the version of packman in the same folder,
# giving y... | cloud-native-docs-master | tools/packman/packmanconf.py |
# Copyright 2019 NVIDIA CORPORATION
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this 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 writi... | cloud-native-docs-master | tools/packman/bootstrap/install_package.py |
import os
import sys
import io
import contextlib
import packmanapi
REPO_ROOT = os.path.join(os.path.dirname(os.path.realpath(__file__)), "../..")
REPO_DEPS_FILE = os.path.join(REPO_ROOT, "deps/repo-deps.packman.xml")
def bootstrap():
"""
Bootstrap all omni.repo modules.
Pull with packman from repo.packm... | cloud-native-docs-master | tools/repoman/repoman.py |
# Use this file to bootstrap packman into your Python environment (3.7.x). Simply
# add the path by doing sys.insert to where packmanconf.py is located and then execute:
#
# >>> import packmanconf
# >>> packmanconf.init()
#
# It will use the configured remote(s) and the version of packman in the same folder,
# giving y... | cub-master | docs/tools/packman/packmanconf.py |
# Copyright 2019 NVIDIA CORPORATION
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this 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 writi... | cub-master | docs/tools/packman/bootstrap/install_package.py |
import os
import sys
import io
import contextlib
import packmanapi
REPO_ROOT = os.path.join(os.path.dirname(os.path.realpath(__file__)), "../..")
REPO_DEPS_FILE = os.path.join(REPO_ROOT, "deps/repo-deps.packman.xml")
def bootstrap():
"""
Bootstrap all omni.repo modules.
Pull with packman from repo.packm... | cub-master | docs/tools/repoman/repoman.py |
#!/usr/bin/env python
import hpccm
hpccm.config.set_container_format('docker')
Stage0 += hpccm.primitives.baseimage(image='nvidia/cuda:12.1.0-devel-ubuntu22.04')
Stage0 += hpccm.building_blocks.apt_get(ospackages=['git', 'tmux', 'gcc', 'g++', 'vim', 'python3', 'python-is-python3', 'ninja-build'])
Stage0 += hpccm.bui... | cub-master | benchmarks/docker/recipe.py |
#!/usr/bin/env python3
import cub.bench as bench
# TODO:
# - driver version
# - host compiler + version
# - gpu clocks / pm
# - ecc
def main():
center_estimator = bench.MedianCenterEstimator()
bench.search(bench.BruteForceSeeker(center_estimator, center_estimator))
if __name__ == "__main__":
main()
| cub-master | benchmarks/scripts/search.py |
#!/usr/bin/env python3
import sys
import argparse
import cub.bench
def parse_arguments():
parser = argparse.ArgumentParser(description='Verify tuning variant')
parser.add_argument('--variant', type=str, help='Variant to verify', default=None, required=True)
variant = parser.parse_known_args()[0].varian... | cub-master | benchmarks/scripts/verify.py |
#!/usr/bin/env python3
import os
import re
import cub
import math
import argparse
import itertools
import functools
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from scipy.stats import mannwhitneyu
from scipy.stats.mstats import hdquantiles
pd.options.display.max_colwid... | cub-master | benchmarks/scripts/analyze.py |
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