netadapt | repo contains the official Pytorch reimplementation | Machine Learning library

 by   denru01 Python Version: Current License: MIT

kandi X-RAY | netadapt Summary

kandi X-RAY | netadapt Summary

netadapt is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. netadapt has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications.

            kandi-support Support

              netadapt has a low active ecosystem.
              It has 134 star(s) with 37 fork(s). There are 6 watchers for this library.
              It had no major release in the last 6 months.
              There are 2 open issues and 1 have been closed. On average issues are closed in 1 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of netadapt is current.

            kandi-Quality Quality

              netadapt has 0 bugs and 0 code smells.

            kandi-Security Security

              netadapt has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              netadapt code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              netadapt is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              netadapt releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              netadapt saves you 1464 person hours of effort in developing the same functionality from scratch.
              It has 3267 lines of code, 158 functions and 27 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed netadapt and discovered the below as its top functions. This is intended to give you an instant insight into netadapt implemented functionality, and help decide if they suit your requirements.
            • The main function
            • Launch a worker
            • Finds the best model for the given iteration
            • Save the history of the network
            • Build a lookup table
            • Measure the latency of the model
            • Update progress bar
            • Create a network definition dict from a model
            • Extracts feature map sizes
            • Main function
            • Train the model
            • Firesune the given model
            • Perform a fine - tune fitting
            • Simplify a network definition
            • Measure the duration of the model
            • Evaluate the model
            • Evaluate a model
            • Evaluate a trained model
            • Simplify simplified_network
            • Compute the resource based on the given resource type
            • Builds a lookup table
            • Simplify a model based on a model definition
            • Get keys from ordered dict
            • Compute the latency from a lookup table
            • Get a network definition from a model
            • Construct a network definition from a model
            • Compute weights and flattens
            • Compute weights and flushes
            • Get network definition from model
            • Return the keys from an ordered dictionary
            Get all kandi verified functions for this library.

            netadapt Key Features

            Python 3.7.0
            CUDA 10.0
            Pytorch 1.2.0
            torchvision 0.4.0
            numpy 1.17.0
            scipy 1.3.1
            working_folder: Root folder where models, related files and history information are saved. You can see how models are pruned progressively in working_folder/master/history.txt.
            input_data_shape: Input data shape (C, H, W) (default: 3 224 224). If you want to apply NetAdapt to different tasks, you might need to change data shape.
            -h, --help: Show this help message and exit.
            -gp GPUS [GPUS …​], --gpus GPUS [GPUS …​]: Indices of available gpus (default: 0).
            -re, --resume: Resume from previous iteration. In order to resume, specify --resume and specify working_folder as the one you want to resume. The resumed arguments will overwrite the arguments provided here. For example, if you want to simplify a model by pruning and finetuning for 30 iterations (under working_folder), however, your program terminated after 20 iterations. Then you can use --resume to restore and continue for the last 10 iterations.
            -im INIT_MODEL_PATH, --init_model_path INIT_MODEL_PATH: Path to pretrained model.
            -mi MAX_ITERS, --max_iters MAX_ITERS: Maximum iteration of removing filters and short-term fine-tune (default: 10).
            -lr FINETUNE_LR, --finetune_lr FINETUNE_LR: Short-term fine-tune learning rate (default: 0.001).
            -bu BUDGET, --budget BUDGET: Resource constraint. If resource < budget, the process is terminated.
            -bur BUDGET_RATIO, --budget_ratio BUDGET_RATIO: If --budget is not specified, buget = budget_ratio\*(pretrained model resource) (default: 0.25).
            -rt RESOURCE_TYPE, --resource_type RESOURCE_TYPE: Resource constraint type (default: FLOPS). We currently support FLOPS, WEIGHTS, and LATENCY (device cuda:0). If you want to add other resource types, please modify def compute_resource(…​) in network_util python files (e.g. network_utils/network_utils_alexnet).
            -ir INIT_RESOURCE_REDUCTION, --init_resource_reduction INIT_RESOURCE_REDUCTION: For each iteration, target resource = current resource - init_resource_reduction*(resource_reduction_decay\*\*(iteration-1)).
            -irr INIT_RESOURCE_REDUCTION_RATIO, --init_resource_reduction_ratio INIT_RESOURCE_REDUCTION_RATIO: If --init_resource_reduction is not specified, init_resource_reduction = init_resource_reduction_ratio\*(pretrained model resource) (default: 0.025).
            -rd RESOURCE_REDUCTION_DECAY, --resource_reduction_decay RESOURCE_REDUCTION_DECAY: For each iteration, target resource = current resource - init_resource_reduction*(resource_reduction_decay\*\*(iteration-1)) (default: 0.96).
            -st SHORT_TERM_FINE_TUNE_ITERATION, --short_term_fine_tune_iteration SHORT_TERM_FINE_TUNE_ITERATION: Short-term fine-tune iteration (default: 10).
            -lt LOOKUP_TABLE_PATH, --lookup_table_path LOOKUP_TABLE_PATH: Path to lookup table.
            -dp DATASET_PATH, --dataset_path DATASET_PATH: Path to dataset.
            -a ARCH, --arch ARCH network_utils: Defines how networks are pruned, fine-tuned, and evaluated. If you want to use your own method, please see [Customization](#customization) and specify here. (default: alexnet)
            -si SAVE_INTERVAL, --save_interval SAVE_INTERVAL: Interval of iterations that all pruned models at the same iteration will be saved. Use -1 to save only the best model at each iteration. Use 1 to save all models at each iteration. (default: -1).
            Training AlexNet on CIFAR-10. Train from scratch: ```bash python data/ --dir models/alexnet/no-pretrain/checkpoint.pth.tar --arch alexnet ``` Use Imagenet-pretrained model: ```bash python data/ --dir models/alexnet/pretrain/checkpoint.pth.tar --pretrained --lr 0.01 --arch alexnet ``` Evaluation: ```bash python data/ --dir models/alexnet/no-pretrain/checkpoint.pth.tar --arch alexnet ``` ```bash python data/ --dir models/mobilenet/model.pth.tar --arch mobilenet ``` 2. **Measuring Latency** Here we build the latency lookup table for `cuda:0` device: ```bash python --dir latency_lut/lut_alexnet.pkl --arch alexnet ``` It measures latency of different layers contained in the network (i.e. **AlexNet** here). For conv layers, the sampled numbers of feature channels are multiples of `MIN_CONV_FEATURE_SIZE`. For fc layers, the sampled numbers of features are multiples of `MIN_FC_FEATURE_SIZE`.
            Applying NetAdapt Modify which GPUs will be utilized (`-gp`) in `` and run the script to apply NetAdapt to a pretrained model: ```bash sh ``` After obtaining the adapted model, we need to finetune the model: ```bash python data/ --arch alexnet --resume models/alexnet/no-pretrain/prune-by-mac/iter_100_best_model.pth.tar --dir models/alexnet/no-pretrain/checkpoint-adapt.pth.tar ``` <p align="center"> <img src="fig/netadapt_algo.png" alt="photo not available" width="90%" height="90%"> </p>
            Evaluation Using Adapted Models After applying NetAdapt to a pretrained model, we can evaluate this adapted model using: ```bash python data/ --dir models/alexnet/no-pretrain/checkpoint-adapt.pth.tar --arch alexnet ``` The adapted model can be restored **without modifying the orignal python file**.
            Create your own network_utils python file (said and place it under network_utils.
            Implement functions described in [](network_utils/
            As we provide an example of applying NetAdapt to AlexNet, you can also build your network_utils based on [](network_utils/ ```bash cd network_utils cp ./ ```
            Add from .network_utils_yourNetworkOrTask import * to, which is under [the same directory](network_utils/
            Modify class networkUtils_alexnet(…​) in [line 44](network_utils/ in to class networkUtils_yourNetworkOrTask(…​).
            Modify def alexnet(…​) in [line 325-326](network_utils/ to: bash def yourNetworkOrTask(model, input_data_shape, dataset_path, finetune_lr=1e-3): return networkUtils_yourNetworkOrTask(model, input_data_shape, dataset_path, finetune_lr)
            Specify training/validation data loader, loss functions, optimizers, network architecture, training method, and evaluation method in if there is any difference from the AlexNet example: Modify data loader and loss functionsin function def init(…​): in [line 52](network_utils/ Specify additive skip connections if there is any and modify def simplify_network_def_based_on_constraint(…​) in You can see how our implementation uses additive skip connections [here]( Modify training method (short-term finetune) in function def fine_tune(…​): in [line 245](network_utils/ Modify evaluation method in function def evaluate(…​): in [line 291](network_utils/ You can see how these methods are utilized by the framework [here](
            Our current code base supports pruning Conv2d, ConvTranspose2d, and Linear with additive skip connection. If your network architecture is not supported, please modify [this](network_utils/ If you want to use other metrics (resource type) to prune networks, please modify [this](network_utils/
            We can apply NetAdapt to different networks or tasks by using --arch yourNetworkOrTask in scripts/ As for the values of other arguments, please see [Usage](#usage). Generally, if you want to apply NetAdapt to a different task, you might change input_data_shape. If your network architecture is very different from that of MobileNet, you would have to modify the values of --init_resource_reduction_ratio and --resource_reduction_decay to get a different resource reduction schedule.

            netadapt Examples and Code Snippets

            No Code Snippets are available at this moment for netadapt.

            Community Discussions


            Get lowest mac address
            Asked 2022-Apr-08 at 01:42

            What is the best way to get the network adapter with the lowest mac address? There are multiple network adapters named Intel(R) I210, just need the one with the lowest mac address.



            Answered 2022-Apr-08 at 01:42

            You can use Sort-Object to sort the output from Get-NetAdapter based on the .MacAddress property and then get the lowest Mac Address based on that sort.



            PowerShell | Getting a Specific Value from a Property
            Asked 2022-Apr-04 at 16:10

            I have been trying to find out how I can get the value of a property in PowerShell.

            For instance, the line below will display the LinkSpeed of the Network Adapter ...

            Get-NetAdapter | Select LinkSpeed | Where {$_.LinkSpeed -like '*Gbps'}




            Answered 2022-Mar-25 at 19:32
            (Get-NetAdapter | Where {$_.LinkSpeed -like '*Gbps'}).Linkspeed



            Can the -eq function compare against a variable
            Asked 2022-Mar-03 at 22:54

            It appears that -eq can only compare against a literal. I am trying to compare against a variable like this. This code does not work



            Answered 2022-Mar-03 at 22:54

            The /fo csv option makes getmac.exe quote the mac addresses, so the literal string value is not 00-01-02-03-04-05, but "00-01-02-03-04-05" (including the quotation marks), and they're obviously different:



            get content - Powershell
            Asked 2022-Jan-12 at 15:23

            i wanna change mtu with powershell script and the value in this txt file

            • when i get content it gives me this error
            • Invalid mtu parameter (1492 ).
            • what's wrong in this code ?


            Answered 2022-Jan-12 at 15:23

            It looks like there's a trailing space after the last digit. You can use string.Trim() to remove leading or trailing whitespace:



            Detect Ethernet adapter(s) - PowerShell
            Asked 2022-Jan-06 at 00:32

            I am using this code to detect network adapters:


            The problem with this code is that it detects all network adapters (including Wi-Fi and virtual adapters by VMware).

            I just want to detect the ethernet adapters installed in the device.

            Could PowerShell do this at all?



            Answered 2022-Jan-06 at 00:09

            Get-NetAdapter | Where-Object {$_.InterfaceDescription -match "Ethernet"}

            This will show onboard ethernet adapters as well as docking station/USB Ethernet adapters.



            Build a script to check-uncheck sharing boxes at Ethernet adapter
            Asked 2021-Dec-15 at 16:56

            We have P2P connection between a host computer and some target, because of stability issues, the connection sometimes dead, and we need to uncheck "allow other network users to connect through this computer's internet connection" with adding "Home networking connection:" as "p2p" and also uncheck-check the "Allow other network users to control or disable the shared Internet connection" to solve the connection issue.

            We don't want to try to find the root cause, we decide to build this workarround.

            Here are the steps i want to build a PS script to do:

            1. go to the properties of Ethernet adapter: Enter properties

            2. uncheck at "Sharing" section this check-box: un-check

            3. re-check these boxes (at the picture at step 4)

            4. add to "Home networking connection "p2p". re-check

            I tried to build a script that will do this, but, It broke my host and we had to re-build the host after trying running it, please don't run it on your computer:



            Answered 2021-Dec-12 at 09:59

            To be constructive taking a mish mash of scripts and using them, without applying logic to each individual script is not logical.

            If you look at this webpage - Configure Internet Connection Sharing with PowerShell


            It steps out what you seek.

            Step 1 Use the function Get-MrInternetConnectionSharing to retrieve the current settings

            Step 2 Use the Get-MrInternetConnectionSharing function to specify the network adapters used in my Internet connection.



            Enumerate all NICs with IP and MAC addresses in powershell
            Asked 2021-Nov-21 at 13:09

            How can I list all NICs with name, MAC and IP address in PowerShell?

            I know that I can combine Get-NetIPAddress and Get-NetAdapter but is there a simple way to do it because it seems to be one of the most common things in network management.

            I've also found that Get-NetIPConfiguration -Detailed, but I don't understand why Get-NetIPConfiguration -Detailed | select InterfaceAlias,NetAdapter.LinkLayerAddress,IPv4Address returns empty MAC addresses.



            Answered 2021-Nov-21 at 13:09

            The WMI class Win32_NetworkAdapterConfiguration contains this information:



            Serialization differences between PowerShell's Format-List and ConvertTo-Json
            Asked 2021-Nov-17 at 15:07

            I'm trying to parse the results of PowerShell's Get-NetIPConfiguration in Python.

            The results contain the values I want in the default formatting (Format-List), but not when converted to JSON, which is the format I would like to consume.

            Note how DNSServer is serialized by Format-List:



            Answered 2021-Nov-17 at 15:07

            Note how DNSServer is serialized by Format-List

            The Format-* cmdlets do not serialize, they produce for-display string representations, using PowerShell's output-formatting system (as opposed to its serialization infrastructure).

            These representations are not meant to be used for programmatic processing, but if you do want to process them as strings, you can pipe them to Out-String:



            Enable VLAN and set VLAN ID with powershell script if VLAN is not yet enabled
            Asked 2021-Sep-14 at 11:09

            I'm right now trying to write a powershell script in Windows 11, that should automatically configure an usb to ethernet adapter. For this I need to automatically configure the VLAN of the adapter.

            Everything works fine in case the VLAN was already activated in the network dialog using



            Answered 2021-Sep-14 at 11:09

            Try running the following command:



            -PipelineVariable not working on Get-NetIPAddress
            Asked 2021-Sep-01 at 13:18

            I'm obviously failing to understand the nuances to -PipelineVariable

            If I pass Get-NetIPAddress into Get-NetAdapter it shows the associated adapters.



            Answered 2021-Sep-01 at 13:18

            It seems that you're seeing a bug in Windows PowerShell that affects all so-called CDXML cmdlets, of which Get-NetIPAddress is one instance.

            • CDXML cmdlets are implemented declaratively via *.cdxml XML documents that define a "mapping between PowerShell cmdlets and CIM class operations or methods."

            Seemingly, in Windows PowerShell no CDXML cmdlets support the common -PipelineVariable parameter and report the Cannot retrieve the dynamic parameters for the cmdlet error you saw:


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install netadapt

            You can download it from GitHub.
            You can use netadapt like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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