estimator API (which is the easiest way to build a TensorFlow model): inside the input_fn and while creating a feature_column. -bin-hadoop2. TensorBoard is a suite of tools designed to present TensorFlow data visually. View Tony Jacobs' profile on LinkedIn, the world's largest professional community. TensorFlow Lite for mobile and embedded devices For Production TensorFlow Extended for end-to-end ML components. Description. We will cover how to do this in a separate blog post. There are two approaches to normalizing inputs when using the tf. The standalone version of the Visual Profiler, nvvp, is included in the CUDA Toolkit for all supported OSes. Optionally, it can further retrain TensorFlow model on user data to adjust model parameters on the user data ( also know as "Transfer Learning"). FutureWarning: Conversion of the second argument of issubdtype from `float` to `np. How to use Estimator, Experiment and Dataset to train models The model function is a Python function which is passed as a first-class function to the Estimator. Anaconda Cloud. I need to use the Tensorflow profiler to profile some code that is running slowly for some reason. Mavericks | Helsinki, Finland | ONSITE | https://mavericks. Data 및 TensorFlow. For more information about training models using the generic estimator, see train models with Azure Machine Learning. TensorFlow About Converge360 Converge360, an 1105 Media Inc. I would be very grateful for any reply. Data 및 TensorFlow. WALS is included in the contrib. Download Spark. 使用方法: 在model中加入with context,生成profile文件:. It provides detailed performance metrics and API debugging via a user interface and command line tool. • Accountable to estimate, drive the test execution, status reporting and project management for Connectivity modules, i. In the presented setting, predictions of the remaining useful lifetime of more than 90 days can be expected on average, outperforming the closest state-of-the-art estimate by almost a factor of two on average. https://github. predict_keys: The types of predictions that should be produced, as an R list. View Tony Jacobs’ profile on LinkedIn, the world's largest professional community. Recommender Systems with Tensorflow Oliver Gindele @tinyoli oliver. If your system does not have. estimator of TensorFlow lets us concisely write deep neural network. TensorFlow London 12: Oliver Gindele 'Recommender systems in Tensorflow' 1. TensorFlow large model support (TFLMS) provides an approach to training large models that cannot be fit into GPU memory. Welcome to Part 3 of a blog series that introduces TensorFlow Datasets and Estimators. It takes a computational graph defined by users and automatically adds swap-in and swap-out nodes for transferring tensors from GPUs to the host and vice versa. feature_column. FutureWarning: Conversion of the second argument of issubdtype from `float` to `np. estimator API (which is the easiest way to build a TensorFlow model): inside the input_fn and while creating a feature_column. 0 RC2 Major Features and Improvements. Gallery About Documentation Support. Udacity and Google are launching a free introductory course on the subject, which naturally leans into TensorFlow, the open-source library for deep learning software developed by Google. WALS is included in the contrib. Package has 5458 files and 1331 directories. If NULL (the default), this function will either evaluate forever, or until the supplied input_fn() has provided all available data. 遺伝研スーパーコンピュータでは、Environment moduleをアプリケーション・ツールの 利用環境の動的な切り替えの為に導入しました。. Pre-made Estimator - These are predefined estimators, created to generate a specific type of model. OK, I Understand. The plugin supports performance visualization for an Cloud TPU nodes of all sizes. 2, it is now super easy to set up pyspark. In our business, only the best survive. In TensorFlow, feature columns are used to specify the ‘shapes’, or ‘types’, of inputs that can be expected by a particular model. Estimator New style vs Old. This post is a guide on how to use the Hamiltonian Monte Carlo (HMC) transition kernel provided by TensorFlow Probability to train Bayesian neural networks (BNN) by sampling from their posterior… This app works best with JavaScript enabled. The TensorFlow documentation spends a lot of time covering the ‘OLD style’ x, y, batch_size input parameters, but information about the ‘NEW style’ input_fn method (which is more flexible, and doesn’t complain about DEPRECATION) is scattered across multiple pages (and blog posts). View Tony Jacobs' profile on LinkedIn, the world's largest professional community. app, or the model function I use for the estimator? EDIT: If this helps, this is my main() function:. Se hela profilen på LinkedIn, upptäck Binays kontakter och hitta jobb på liknande företag. profiler import model_analyzer model_analyzer(options=model_analyzer. sequence_categorical_column_with_hash_bucket tf. CUDA Binary Utilities The application notes for cuobjdump, nvdisasm, and nvprune. com/Hvass-Labs/TensorFlow-Tutorials. Estimator, so I can't figure out how to inject the run metadata object into the session run() call in order to get the information that the profiler needs. Having worked primarily with image recognition using tensorflow, sklearn and opencv in Python. line_profiler is an excellent tool that can help you quickly profile your python code and find where the performance bottlenecks are. Additionally, create a dictionary script_params that contains the DNN hyperparameter settings. In our example, we define a single feature with name f1. company, is the leading B2B media and marketing solutions provider for today's most important technology issues and the go-to source. https://github. lite and source code is now under tensorflow/lite rather than tensorflow/contrib/lite. 8 the latest version at the time. About the TensorFlow Estimator. predict_keys: The types of predictions that should be produced, as an R list. It offers variety of Estimators that represent predefined models. Here is an example for a single dual-socket Skylake server system with HT enabled and sub-NUMA clustering. How to use the Estimator API to train your model in TensorFlow. Find bottlenecks and achieve high performance for parallel cluster applications. Additionally, create a dictionary script_params that contains the DNN hyperparameter settings. from tensorflow. 2 for Jetson AGX Xavier, Jetson TX2 and Jetson Nano is available now and there two ways to install it:. Materials that are as of a specific date, including but not limited to press releases, presentations, blog posts and webcasts, may have been superseded by subsequent events or disclosures. I will show you an example to perform the ladder, then I will show you to train multiple models using ML Engine. In this blog I aim to provide an introduction to TensorFlow and the SAP HANA integration, give you an understanding of the landscape and outline the process for using External Machine Learning with HANA. For example, in the following code, we define two simple feature columns: a numeric column called "drat" , and a indicator column called "am" with one-hot representation. The TensorFlow estimator is implemented through the generic estimator class, which can be used to support any framework. Download the spark tarball from the Spark website and untar it: $ tar zxvf spark-2. The plugin supports performance visualization for an Cloud TPU nodes of all sizes. In this post, I will show you how to turn a Keras image classification model to TensorFlow estimator and train it using the Dataset API to create input pipelines. Profiler This is the guide to the Profiler. This can also be used to load checkpoints from the directory into a estimator to continue training a previously saved model. When TensorFlow 1. Chief AI Officer Jatana januar 2018 - nu 1 år 11 måneder. Estimator, so I can't figure out how to inject the run metadata object into the session run() call in order to get the information that the profiler needs. We develop an estimator for spot and integrated betas of a multi-factor model, based on the Cholesky decomposition of the covariance. See the complete profile on LinkedIn and discover Tony’s connections. In this research, we investigate distance estimation in an indoor environment with the use of machine learning (ML) methodologies. 8 the latest version at the time. Add the estimator to load the TensorFlow model, and score it:. This page is a quick guide to setting up Cloud TPU with Google Kubernetes Engine. If you haven't read TensorFlow team's Introduction to TensorFlow Datasets and Estimators post. I would be very grateful for any reply. The TensorFlow documentation spends a lot of time covering the ‘OLD style’ x, y, batch_size input parameters, but information about the ‘NEW style’ input_fn method (which is more flexible, and doesn’t complain about DEPRECATION) is scattered across multiple pages (and blog posts). TensorFlow Lite for mobile and embedded devices For Production TensorFlow Extended for end-to-end ML components. Udacity and Google are launching a free introductory course on the subject, which naturally leans into TensorFlow, the open-source library for deep learning software developed by Google. Estimator requires you to write a model_fn and an input_fn that correspond to the model and input portions of your TensorFlow. TensorFlow Lite for mobile and embedded devices For Production TensorFlow Extended for end-to-end ML components. 8/ /usr/lib. tf_random_seed:TensorFlow初始化器的随机种子,设置此值可以实现重播之间的一致性. 0 RC2 Major Features and Improvements. clip_gradients_by_norm before performing stochastic gradient descent. tensorflow transmission. Installation. I did it look at the road map but I'm not sure it explicitly mentioned this topic. Mavericks | Helsinki, Finland | ONSITE | https://mavericks. Saturday May 6, 2017. The TensorFlow documentation spends a lot of time covering the ‘OLD style’ x, y, batch_size input parameters, but information about the ‘NEW style’ input_fn method (which is more flexible, and doesn’t complain about DEPRECATION) is scattered across multiple pages (and blog posts). python-tensorflow-opt 2. Jatana is a deep learning based Saas solution that integrates directly with your help desk software of choice to automate processes related to customer service. It provides detailed performance metrics and API debugging via a user interface and command line tool. Pre-made Estimator - These are predefined estimators, created to generate a specific type of model. learn is a high level API for machine learning process. The TensorFlow white paper talks about very advanced internal tools that Google have along these lines. The TensorFlow estimator provides a simple way of launching a TensorFlow training job on a compute target. I would be very grateful for any reply. -rc2 TensorFlow 1. Find bottlenecks and achieve high performance for parallel cluster applications. Purchase Order Number. The implementation of Monte Carlo in the TensorFlow Probability package included sample to run the Hamiltonian MCMC, which is a variation with input from the Hamiltonian dynamics to avoid slow exploration of state space. 3 "canned estimators" demo. feature_column. This can also be used to load checkpoints from the directory into a estimator to continue training a previously saved model. The tool converts a trained model's weights from floating-point. Use TensorFlow. FutureWarning: Conversion of the second argument of issubdtype from `float` to `np. Opsとオブジェクトはmodel_fnから返され、 Estimator渡され. checkpoint_path: The path to a specific model checkpoint to be used for prediction. There are two approaches to normalizing inputs when using the tf. I am running deeplab on the DeepFashion2 Dataset and am encountering problems when visualizing my results with vis. The implementation of Monte Carlo in the TensorFlow Probability package included sample to run the Hamiltonian MCMC, which is a variation with input from the Hamiltonian dynamics to avoid slow exploration of state space. When TensorFlow 1. Binay har angett 2 jobb i sin profil. However, to quickly check the benefits of scaling TensorFlow, one may simply use numactl to run on a single socket only; multiplying the achieved performance according to the number of sockets yields a quick estimate of scaling performance. Opsとオブジェクトはmodel_fnから返され、 Estimator渡され. tensorflow transmission. Please read the article below and official pages. Tutorials in this series. The tradition way to estimate distance is based on the signal propagation model. There are two approaches to normalizing inputs when using the tf. https://github. I understand the basic concepts involved in training and prediction of models, except for this one part where they use tf. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well. Se hela profilen på LinkedIn, upptäck Binays kontakter och hitta jobb på liknande företag. sequence_categorical_column_with_vocabulary_file tf. Chief AI Officer Jatana januar 2018 - nu 1 år 11 måneder. In addition, Estimator includes default behavior common to training jobs, such as saving and restoring checkpoints, creating summaries for TensorBoard, etc. tf_random_seed:TensorFlow初始化器的随机种子,设置此值可以实现重播之间的一致性. Qualcomm products referenced on this page are products of Qualcomm Technologies, Inc. This feature is available out of the box from TensorFlow. The recommendation system in the tutorial uses the weighted alternating least squares (WALS) algorithm. Any TensorFlow estimator can have its parameters be warm started from a provided “model checkpoint”: TensorFlow Profiler and. In our example, we define a single feature with name f1. py and visualizing with default vis. 3 was released the Estimator, and related high-level APIs, caught my eye. I design and build machine learning pipelines from idea to finished product. For scoring, the transform takes as inputs the pre-trained Tensorflow model, the names of the input nodes, and names of the output nodes whose values we want to extract. Tony has 9 jobs listed on their profile. linear_feature_columns : An iterable containing all the feature columns used by linear part of the model. This dataset provides information on the physical characteristics of a number of abalones (a type of sea snail), and use these characteristics to predict the number of rings in the shell. In addition, Estimator includes default behavior common to training jobs, such as saving and restoring checkpoints, creating summaries for TensorBoard, etc. It provides detailed performance metrics and API debugging via a user interface and command line tool. https://github. This can be done with tensorflow timeline module. tensorflow transmission. I design and build machine learning pipelines from idea to finished product. Collaborative project of CellProfiler (Broad Institute) and KNIME Image Processing (University of Konstanz). It compose of the following steps: Define the feature columns. https://github. Is this the way to go in the future?. 2 for Jetson AGX Xavier, Jetson TX2 and Jetson Nano is available now and there two ways to install it:. Back to Package. This book will help you understand and utilize the latest TensorFlow features. TensorFlow是谷歌基于DistBelief进行研发的第二代人工智能学习系统,而谷歌的工程师们也正在使用TensorFlow作为内部的机器学习系统。 现在,谷歌已经将其开源,并将他们使用TensorFlow的效果分享在许多的科研文章中。. dtype(float). A TensorFlow estimator. Udacity and Google are launching a free introductory course on the subject, which naturally leans into TensorFlow, the open-source library for deep learning software developed by Google. save_summary_steps:每隔这么多步骤保存摘要. feature_column. Path /usr/ /usr/bin/saved_model_cli /usr/bin/tf_upgrade_v2 /usr/bin/tflite_convert /usr/bin/toco /usr/bin/toco_from_protos /usr/lib/ /usr/lib/python3. , input from numpy [12]). Google announced new tooling for their TensorFlow Lite deep-learning framework that reduces the size of models and latency of inference. For scoring, the transform takes as inputs the pre-trained Tensorflow model, the names of the input nodes, and names of the output nodes whose values we want to extract. Smart and agile drones are fast becoming ubiquitous at the edge of the cloud. sequence_categorical_column_with_hash_bucket tf. {'StringIO': ,. It doesn't account for network traffic, it only records an estimate of the application data sent in responses. ProfileOptionBuilder函数 类 ProfileOptionBuilder定义在:tensorflow/python/profiler/option_builder. input_fn: An input function, typically generated by the input_fn() helper function. factorization package of the TensorFlow code base, and is used to factorize a large matrix of user and item ratings. This page is a quick guide to setting up Cloud TPU with Google Kubernetes Engine. Tensorflow - How to use the GPU instead of a CPU for tf. See the complete profile on LinkedIn and discover Tony’s connections. For example, in the following code, we define two simple feature columns: a numeric column called "drat" , and a indicator column called "am" with one-hot representation. dtype(float). ProfilerHook is only exposed in Tensorflow 1. • Accountable to estimate, drive the test execution, status reporting and project management for Connectivity modules, i. Memory and thread debugger. In this post, I will show you how to turn a Keras image classification model to TensorFlow estimator and train it using the Dataset API to create input pipelines. Rahul Malik , Software Engineer Bazel provides a seamless and consistent build interface for different languages in a single system. https://github. TensorFlow London 12: Oliver Gindele 'Recommender systems in Tensorflow' 1. Google announced new tooling for their TensorFlow Lite deep-learning framework that reduces the size of models and latency of inference. Tensorflow - How to use the GPU instead of a CPU for tf. This page is a quick guide to setting up Cloud TPU with Google Kubernetes Engine. TensorFlow can be configured to run on either CPUs or GPUs. 3 was released the Estimator, and related high-level APIs, caught my eye. checkpoint_path: The path to a specific model checkpoint to be used for prediction. In this blog post I will walk through a simple example and a few tips about using this tool within the Jupyter notebook. TensorFlow has the the function of converting Keras model to TensorFlow Estimator. has a valid residence visa in UAE, to work with us as a part time , ( project per project) Job Types: Part-time, Commission Experience:. TensorFlow Lite for mobile and embedded devices For Production TensorFlow Extended for end-to-end ML components. 8 the latest version at the time. Copenhagen Area, Denmark. Intel® Inspector. Higher-Level APIs in TensorFlow. The TensorFlow estimator provides a simple way of launching a TensorFlow training job on a compute target. Message passing interface (MPI) application profiler. Collaborative project of CellProfiler (Broad Institute) and KNIME Image Processing (University of Konstanz). TensorFlow Lite for mobile and embedded devices For Production TensorFlow Extended for end-to-end ML components. The Markov Chain Monte Carlo (MCMC) is a sampling method to sample from a probability distribution when direct sampling is not feasible. 2, it is now super easy to set up pyspark. This dataset provides information on the physical characteristics of a number of abalones (a type of sea snail), and use these characteristics to predict the number of rings in the shell. Recently the Tensorflow team announced that high-level API around Tensorflow was going to be Estimator. Additionally, create a dictionary script_params that contains the DNN hyperparameter settings. For more information about training models using the generic estimator, see train models with Azure Machine Learning using estimator. Se hela profilen på LinkedIn, upptäck Binays kontakter och hitta jobb på liknande företag. This means that Python modules are under tf. For scoring, the transform takes as inputs the pre-trained Tensorflow model, the names of the input nodes, and names of the output nodes whose values we want to extract. FutureWarning: Conversion of the second argument of issubdtype from `float` to `np. line_profiler is an excellent tool that can help you quickly profile your python code and find where the performance bottlenecks are. This is good news, since it was previously difficult to predict which neural network layer would stick, and which would slide off the wall. 3 "canned estimators" demo. Read it now to have an idea why we do what we do here. We have provided a set of Cloud TPU profiling tools that you can access from TensorBoard after you install the Cloud TPU profiler plugin. In this article, we’ll develop a custom estimator to be used with the Abalone dataset. Collaborative project of CellProfiler (Broad Institute) and KNIME Image Processing (University of Konstanz). Materials that are as of a specific date, including but not limited to press releases, presentations, blog posts and webcasts, may have been superseded by subsequent events or disclosures. I know in the normal pipline the runmeta will produce by the profiler, but under estimator, do not need the runmeta. Saturday May 6, 2017. The Markov Chain Monte Carlo (MCMC) is a sampling method to sample from a probability distribution when direct sampling is not feasible. TensorFlow provides a higher level Estimator API with pre-built model to train and predict data. CUDA Binary Utilities The application notes for cuobjdump, nvdisasm, and nvprune. How to use the Estimator API to train your model in TensorFlow. - mnist_estimator. Add the estimator to load the TensorFlow model, and score it:. ALL_ADVICE) here is a tip that: No RunMeta. Download the spark tarball from the Spark website and untar it: $ tar zxvf spark-2. A table tennis match will feature a variety of strokes. This work utilizes upon the volume of data to present a case study on main bearing failures for 108 turbines. 8/ /usr/lib. Locate the root-cause memory and threading errors early―before you release. I'm going to explain how to export "high level" Tensorflow models (using export_savedmodel). Higher-Level APIs in TensorFlow. A number of "canned estimators" are at tf. If no version is provided, the estimator will default to the latest version supported by Azure ML. Learn about yourself, the employment options available to you and the training that will prepare you for them. Fermi HW profiling support for CUDA C and OpenCL in Visual Profiler C++ Class Inheritance and Template Inheritance support for increased programmer productivity A new unified interoperability API for Direct3D and OpenGL, with support for:. Each generates different amounts and types. I would be very grateful for any reply. It doesn't account for network traffic, it only records an estimate of the application data sent in responses. In cases where collecting basic traces for individual steps isn’t enough, TensorFlow offers another great tool called Profiler that lets you do some advanced analysis. Collaborative project of CellProfiler (Broad Institute) and KNIME Image Processing (University of Konstanz). View Tony Jacobs’ profile on LinkedIn, the world's largest professional community. Find bottlenecks and achieve high performance for parallel cluster applications. TensorFlow Lite for mobile and embedded devices For Production TensorFlow Extended for end-to-end ML components. Message passing interface (MPI) application profiler. Simple Regression with a TensorFlow Estimator. has a valid residence visa in UAE, to work with us as a part time , ( project per project) Job Types: Part-time, Commission Experience:. The Visual Profiler is available as both a standalone application and as part of Nsight Eclipse Edition. line_profiler is an excellent tool that can help you quickly profile your python code and find where the performance bottlenecks are. tf_random_seed:TensorFlow初始化器的随机种子,设置此值可以实现重播之间的一致性. estimator feels clumsy. Download Spark. This can be done with tensorflow timeline module. See the complete profile on LinkedIn and discover Tony’s connections. In this research, we investigate distance estimation in an indoor environment with the use of machine learning (ML) methodologies. It compose of the following steps: Define the feature columns. I see it used on github a lot but can't find any official documentation on tensorflow. https://github. Tony has 9 jobs listed on their profile. I am especially interested in neural networks, transfer learning from deep nets (Inception, ResNet) and ensemble creation for performance gains. For scoring, the transform takes as inputs the pre-trained Tensorflow model, the names of the input nodes, and names of the output nodes whose values we want to extract. „e Estimator itself is con•gured using the model fn, a func-tion which builds a TensorFlow graph and returns the information necessary to train a model, evaluate it, and predict. Use TensorFlow. The TensorFlow white paper talks about very advanced internal tools that Google have along these lines. Pre-made Estimator - These are predefined estimators, created to generate a specific type of model. It provides detailed performance metrics and API debugging via a user interface and command line tool. I did it look at the road map but I'm not sure it explicitly mentioned this topic. sequence_categorical_column_with_identity tf. From version 1. 3 was released the Estimator, and related high-level APIs, caught my eye. Here is an example for a single dual-socket Skylake server system with HT enabled and sub-NUMA clustering. A few months ago I demonstrated how to install the Keras deep learning library with a Theano backend. 使用方法: 在model中加入with context,生成profile文件:. Using TensorFlow™ with Delphi - or how to use a TStack to simulate a RPN calculator. This page is a quick guide to setting up Cloud TPU with Google Kubernetes Engine. TensorFlow是谷歌基于DistBelief进行研发的第二代人工智能学习系统,而谷歌的工程师们也正在使用TensorFlow作为内部的机器学习系统。 现在,谷歌已经将其开源,并将他们使用TensorFlow的效果分享在许多的科研文章中。. The TensorFlow documentation spends a lot of time covering the ‘OLD style’ x, y, batch_size input parameters, but information about the ‘NEW style’ input_fn method (which is more flexible, and doesn’t complain about DEPRECATION) is scattered across multiple pages (and blog posts). Recently the Tensorflow team announced that high-level API around Tensorflow was going to be Estimator. Tony has 9 jobs listed on their profile. Recommender Systems with Tensorflow Oliver Gindele @tinyoli oliver. In this article, we'll develop a custom estimator to be used with the Abalone dataset. Performance Analysis Tools NVIDIA Nsight Systems NVIDIA® Nsight™ Systems is a system-wide performance analysis tool designed to visualize application's algorithm, help you select the largest opportunities to optimize, and tune to scale efficiently across any quantity of CPUs and GPUs in your computer; from laptops to DGX servers. 2, it is now super easy to set up pyspark. In the presented setting, predictions of the remaining useful lifetime of more than 90 days can be expected on average, outperforming the closest state-of-the-art estimate by almost a factor of two on average. profiler import model_analyzer model_analyzer(options=model_analyzer. input_fn: An input function, typically generated by the input_fn() helper function. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well. This post is a very simple example on how to use "Google's" TensorFlow - which is an open source Machine Learning library. 使用方法: 在model中加入with context,生成profile文件:. If NULL (the default), this function will either evaluate forever, or until the supplied input_fn() has provided all available data. 11ac 2x2 (MIMO), New WLAN Features like TDLS, DFS and SAP Channel Avoidance, BTLE. factorization package of the TensorFlow code base, and is used to factorize a large matrix of user and item ratings. Package has 5498 files and 633 directories. [email protected] Se hela profilen på LinkedIn, upptäck Binays kontakter och hitta jobb på liknande företag. Se Binay Mishras profil på LinkedIn, världens största yrkesnätverk. TensorFlow Estimators. py定義されています。. Example using TensorFlow Estimator, Experiment & Dataset on MNIST data. This can also be used to load checkpoints from the directory into a estimator to continue training a previously saved model. Copenhagen Area, Denmark. There are two approaches to normalizing inputs when using the tf. Hub에 관한 발표들을 정리한 내용입니다. tensorflow/python/estimator/model_fn. In future, it will be treated as `np. I design and build machine learning pipelines from idea to finished product. This book will help you understand and utilize the latest TensorFlow features. Profiler This is the guide to the Profiler. With a little tweak in the machine learning code, TensorFlow applications can store and report performance metrics of the learning process. , input from numpy [12]). tensorflow transmission. This is useful for performance profiling TensorFlow application with graphical visualization similar to the graphs generated from the CUDA Visual Profiler. An Open Source Machine Learning Framework for Everyone - tensorflow/tensorflow. Intel® Inspector. lite and source code is now under tensorflow/lite rather than tensorflow/contrib/lite. The TensorFlow estimator is implemented through the generic estimator class, which can be used to support any framework.