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This release is compatible with DeepStream SDK 7.0 Ubuntu 22.04 Python 3.10 DeepStream SDK 7.0 Features: - New module platform_info() has been added for checking for WSL, integrated GPU, and aarch64. All apps and integration tests have been updated to use this module when checking for platform. See deepstream_test1 for simple usage. - SBSA is now supported. Check bindings/README.md for quick build instructions. - Apps have been updated to use request_pad_simple() instead of the deprecated method get_request_pad(). See gst-python API documentation for details. - New API nvds_measure_buffer_latency() has been added for pipeline and component latency measurement. See deepstream-test3 app and bindfunctions.cpp for reference.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,94 @@ | ||
| ################################################################################ | ||
| # SPDX-FileCopyrightText: Copyright (c) 2024 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 of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| ################################################################################ | ||
|
|
||
| import sys | ||
| import platform | ||
| from threading import Lock | ||
| from cuda import cudart | ||
| from cuda import cuda | ||
|
|
||
| guard_platform_info = Lock() | ||
|
|
||
| class PlatformInfo: | ||
| def __init__(self): | ||
| self.is_wsl_system = False | ||
| self.wsl_verified = False | ||
| self.is_integrated_gpu_system = False | ||
| self.is_integrated_gpu_verified = False | ||
| self.is_aarch64_platform = False | ||
| self.is_aarch64_verified = False | ||
|
|
||
| def is_wsl(self): | ||
| with guard_platform_info: | ||
| # Check if its already verified as WSL system or not. | ||
| if not self.wsl_verified: | ||
| try: | ||
| # Open /proc/version file | ||
| with open("/proc/version", "r") as version_file: | ||
| # Read the content | ||
| version_info = version_file.readline() | ||
| version_info = version_info.lower() | ||
| self.wsl_verified = True | ||
|
|
||
| # Check if "microsoft" is present in the version information | ||
| if "microsoft" in version_info: | ||
| self.is_wsl_system = True | ||
| except Exception as e: | ||
| print(f"ERROR: Opening /proc/version failed: {e}") | ||
|
|
||
| return self.is_wsl_system | ||
|
|
||
| def is_integrated_gpu(self): | ||
| #Using cuda apis to identify whether integrated/discreet | ||
| #This is required to distinguish Tegra and ARM_SBSA devices | ||
| with guard_platform_info: | ||
| #Cuda initialize | ||
| if not self.is_integrated_gpu_verified: | ||
| cuda_init_result, = cuda.cuInit(0) | ||
| if cuda_init_result == cuda.CUresult.CUDA_SUCCESS: | ||
| #Get cuda devices count | ||
| device_count_result, num_devices = cuda.cuDeviceGetCount() | ||
| if device_count_result == cuda.CUresult.CUDA_SUCCESS: | ||
| #If atleast one device is found, we can use the property from | ||
| #the first device | ||
| if num_devices >= 1: | ||
| #Get properties from first device | ||
| property_result, properties = cudart.cudaGetDeviceProperties(0) | ||
| if property_result == cuda.CUresult.CUDA_SUCCESS: | ||
| print("Is it Integrated GPU? :", properties.integrated) | ||
| self.is_integrated_gpu_system = properties.integrated | ||
| self.is_integrated_gpu_verified = True | ||
| else: | ||
| print("ERROR: Getting cuda device property failed: {}".format(property_result)) | ||
| else: | ||
| print("ERROR: No cuda devices found to check whether iGPU/dGPU") | ||
| else: | ||
| print("ERROR: Getting cuda device count failed: {}".format(device_count_result)) | ||
| else: | ||
| print("ERROR: Cuda init failed: {}".format(cuda_init_result)) | ||
|
|
||
| return self.is_integrated_gpu_system | ||
|
|
||
| def is_platform_aarch64(self): | ||
| #Check if platform is aarch64 using uname | ||
| if not self.is_aarch64_verified: | ||
| if platform.uname()[4] == 'aarch64': | ||
| self.is_aarch64_platform = True | ||
| self.is_aarch64_verified = True | ||
| return self.is_aarch64_platform | ||
|
|
||
| sys.path.append('/opt/nvidia/deepstream/deepstream/lib') |
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