BBIT-Kai
95 lines
4.2 KiB
Python
95 lines
4.2 KiB
Python
################################################################################
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# SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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################################################################################
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import sys
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import platform
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from threading import Lock
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from cuda.bindings import runtime
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from cuda.bindings import driver
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guard_platform_info = Lock()
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class PlatformInfo:
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def __init__(self):
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self.is_wsl_system = False
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self.wsl_verified = False
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self.is_integrated_gpu_system = False
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self.is_integrated_gpu_verified = False
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self.is_aarch64_platform = False
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self.is_aarch64_verified = False
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def is_wsl(self):
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with guard_platform_info:
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# Check if its already verified as WSL system or not.
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if not self.wsl_verified:
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try:
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# Open /proc/version file
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with open("/proc/version", "r") as version_file:
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# Read the content
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version_info = version_file.readline()
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version_info = version_info.lower()
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self.wsl_verified = True
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# Check if "microsoft" is present in the version information
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if "microsoft" in version_info:
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self.is_wsl_system = True
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except Exception as e:
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print(f"ERROR: Opening /proc/version failed: {e}")
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return self.is_wsl_system
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def is_integrated_gpu(self):
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#Using cuda apis to identify whether integrated/discreet
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#This is required to distinguish Tegra and ARM_SBSA devices
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with guard_platform_info:
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#Cuda initialize
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if not self.is_integrated_gpu_verified:
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cuda_init_result, = driver.cuInit(0)
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if cuda_init_result == driver.CUresult.CUDA_SUCCESS:
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#Get cuda devices count
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device_count_result, num_devices = driver.cuDeviceGetCount()
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if device_count_result == driver.CUresult.CUDA_SUCCESS:
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#If atleast one device is found, we can use the property from
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#the first device
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if num_devices >= 1:
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#Get properties from first device
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property_result, properties = runtime.cudaGetDeviceProperties(0)
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if property_result == runtime.cudaError_t.cudaSuccess:
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print("Is it Integrated GPU? :", properties.integrated)
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self.is_integrated_gpu_system = properties.integrated
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self.is_integrated_gpu_verified = True
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else:
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print("ERROR: Getting cuda device property failed: {}".format(property_result))
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else:
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print("ERROR: No cuda devices found to check whether iGPU/dGPU")
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else:
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print("ERROR: Getting cuda device count failed: {}".format(device_count_result))
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else:
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print("ERROR: Cuda init failed: {}".format(cuda_init_result))
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return self.is_integrated_gpu_system
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def is_platform_aarch64(self):
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#Check if platform is aarch64 using uname
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if not self.is_aarch64_verified:
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if platform.uname()[4] == 'aarch64':
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self.is_aarch64_platform = True
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self.is_aarch64_verified = True
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return self.is_aarch64_platform
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sys.path.append('/opt/nvidia/deepstream/deepstream/lib')
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