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Nov 23, 2018 · Contrib. Deprecate parts of tf.contrib where preferred implementations exist outside of tf.contrib. As much as possible, move large projects inside tf.contrib to separate repositories. The tf.contrib module will be discontinued in its current form with TensorFlow 2.0. Experimental development will happen in other repositories in the future.
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conda install linux-64 v2.2.0; win-64 v2.3.0; To install this package with conda run: conda install -c anaconda tensorflow-gpu
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Defined in tensorflow/contrib/timeseries/python/timeseries/input_pipeline.py.
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Tensorflow.contrib is a home of volatile or experimental code. It grew rapidly from version to version and got enormously large. Tensorflow 2.0 brought some braking code changes such as deprecation of scopes, eager execution and focus on keras code. Tensorflow team decided to deprecate tensorflow.contrib while salvaging some of it's parts.
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The following are 5 code examples for showing how to use tensorflow.contrib.seq2seq.LuongAttention().These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.
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Jan 06, 2018 · I have a bunch of machine learning models built using the “original” Estimator API, the one in tf.contrib.learn. In Tensorflow 1.2, parts of it moved to core and in Tensorflow 1.4, the remaining pieces I need finally arrived in core Tensorflow. So, time for me to begin the process of moving to the core Estimator API.
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tf.contrib.framework.get_unique_variable(var_op_name) Gets the variable uniquely identified by that var_op_name. Args: var_op_name: the full name of the variable op, including the scope. Returns: a tensorflow variable. Raises: ValueError: if no variable uniquely identified by the name exists.
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This video uses tensorflow.contrib. But when I execute the code I get No module named 'tensorflow.contrib'. from sklearn import metrics from sklearn.model_selection import cross_validate...
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tensorflow的contrib的基本用法,tensorflow的contrib的自定义模型,TensorFlow中contrib基本操作_来自TensorFlow官方文档,w3cschool编程狮。
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Tensorflow contrib.layers 模块介绍 本文转载自 u011007180 查看原文 2017-07-13 3041 tensorflow
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WARNING:tensorflow:From 190403.py:6: read_data_sets (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. 解决思路. 警告:tensorflow:read_data_set(from tensorflow.contrib.learn.python.learn.data sets.mnist)方法已弃用,将在将来的版本中删除。 解决方法


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TensorFlow 的 contrib 模块已经超越了单个存储库中可以维护和支持的模块。 因此,作为发布 TensorFlow 2.0 的一部分,我们将停止分发 tf.contrib。

  1. Sep 10, 2020 · TensorFlow 2.0 includes many API changes, such as reordering arguments, renaming symbols, and changing default values for parameters. Manually performing all of these modifications would be tedious and prone to error. See contrib/learn/README.md for general migration instructions. Currently, only linear SVMs are supported. For the underlying optimization problem, the SDCAOptimizer is used.
  2. ModuleNotFoundError: No module named 'tensorflow.contrib' The offending line is. import tensorflow.contrib.tensorrt as trt. Here are my setup specs. Windows 10. Python 3.6.8. CUDA 10.0. cuDNN v 7.6.2. Tensorflow (gpu) 1.14.0. GeForce GTX 960M. Driver version 431.60. Intel Core i7-6700HQ 2.6 GHz* Any feedback or troubleshooting steps appreciated! TensorFlow is an open source Machine Intelligence library for numerical computation using Neural So I am trying to get tensorflow to run, but I always get an error that there is no module named...
  3. tensorflow 2.0中tf.contrib已经被移除,大部分内容不是被移到contrib以外就是被转移到了tensorflow addons。经过无数人的努力之后tfa已经逐步完善(甚至可以在Windows上用),建议手动升级原有代码。 如果原有代码依赖tf.contrib.slim,请 ... contrib模块的成长,超出了TensorFlow团队 (在一个repo里) 能维护的范围。 Wicke说,更大的项目,分开维护可能会更好。 不过,团队依然会在2.0里孵化一些 小型 的扩展。
  4. import tensorflow.contrib.eager as tfe Python already has 'tensorflow' imported (your module!), so it expects to find any sub-modules in the same directory as the loaded tensorflow.py. In particular, it expects that directory to be a Python package (have __init__.py in it), but it obviously does not, hence the "... is not a package" error message. See contrib/learn/README.md for general migration instructions. Currently, only linear SVMs are supported. For the underlying optimization problem, the SDCAOptimizer is used.
  5. In this tutorial, we will demonstrate the fine-tune previously train VGG16 model in TensorFlow Keras to classify own image. VGG16 won the 2014 ImageNet competition this is basically computation where...
  6. Pastebin.com is the number one paste tool since 2002. Pastebin is a website where you can store text online for a set period of time. 一.TensorFlow高层次机器学习API (tf.contrib.learn) 1.tf.contrib.learn.datasets.base.load_csv_with_header 加载csv格式数据 2.tf.contrib.learn.DNNClassifier 建立DNN模型(classifier) Jul 23, 2019 · Moving from tf.contrib. The project’s objective may sound quite familiar, and Addons is indeed the landing place for much of tf.contrib which has been moved out of the central TensorFlow ... TensorFlow is an open-source software library for Machine Intelligence provided by Google. I searched the internet a lot but did not find a simple way or a simple example to build TensorFlow for Android. After going through many resources, I was able to build it. Then, I decided to write on it so that it would not take time for others.
  7. Metrics (contrib) [TOC] Ops for evaluation metrics and summary statistics. API. This module provides functions for computing streaming metrics: metrics computed on dynamically valued Tensors.
  8. The TensorFlow contrib module will not be included in TensorFlow 2.0.
  9. TensorFlow: Constants, Variables, and Placeholders. TensorFlow is a framework developed by Google The name TensorFlow is derived from the operations, such as adding or multiplying, that...Node-RED nodes for pre-trained TensorFlow models. Example of object detection (Demonstration) Install. To install the stable version use the Menu - Manage palette - Install option and search for node-red-contrib-tensorflow, or run the following command in your Node-RED user directory, typically ~/.node-red. npm install node-red-contrib-tensorflow
  10. TensorFlow is an open-source library for machine learning applications. It's the Google Brain's TensorFlow applications can be written in a few languages: Python, Go, Java and C. This post is...The following are 30 code examples for showing how to use tensorflow.contrib.slim.conv2d().These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.
  11. With tensorboard inline, I had the same issue of "Module 'tensorflow' has no attribute 'contrib'". It was able to run training when rebuild and reinstall the model using setup.py (research folder) after initialising tensorboard.
  12. Defined in tensorflow/contrib/timeseries/python/timeseries/input_pipeline.py.

 

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The tf.contrib.cudnn_rnn should always be used in NVIDIA GPUs while in CPUs when tf.contrib.cudnn_rnn is not available, the fastest alternative is the tf.contrib.rnn.LSTMBlockFusedCell. The other cell types which are less common, we can implement the graph like tf.contrib.rnn.BasicLSTMCell and will have same characteristics including degraded performance and usage of high memory. The TensorFlow contrib module will not be included in TensorFlow 2.0. tensorflow Python notebook using data from Facebook V: Predicting Check Ins · 493 views · 4y ago. cross_validation #. from tensorflow.contrib import learn.这套TensorFlow入门教程通俗易懂,深入浅出,详细讲解了如何使用TensorFlow进行深度学习。该教程既适合没有基础的读者入门,也适合有经验的程序员进阶。 Tensorflow contrib.layers 模块介绍 本文转载自 u011007180 查看原文 2017-07-13 3041 tensorflow import tensorflow as tf tf.enable_eager_execution(). tfe = tf.contrib.eager # Shorthand for some 我们强烈建议使用 tf.keras 中的高级 API 构建神经网络,也就是说大多数的 Tensorflow API 对于...Aug 06, 2016 · TensorFlow provides a wide range of loss functions to choose inside tf.contrib.losses, such as sigmoid and softmax cross entropy, log-loss, hinge loss, sum of squares, sum of pairwise squares, etc. A variety types of metrics are available in tf.contrib.metrics , such as precision, recall, accuracy, auc, MSE, as well as their streaming versions. Jun 10, 2020 · License TensorFlow Addons is a repository of contributions that conform to well-established API patterns, but implement new functionality not available in core TensorFlow. TensorFlow natively supports a large number of operators, layers, metrics, losses, and optimizers.

Aug 22, 2020 · Only the public APIs of TensorFlow are backwards compatible across minor and patch versions. The public APIs consist of. All the documented Python functions and classes in the tensorflow module and its submodules, except for. Private symbols: any function, class, etc., whose name start with _ Experimental and tf.contrib symbols, see below for ... python code examples for tensorflow.contrib.layers.python.tf_layers.layer_norm.import tensorflow as tf from tensorflow.contrib.tensorboard.plugins import projector from tensorflow.examples.tutorials.mnist import input_data. The next step was to read the fashion dataset...The TensorFlow notebooks were published for DB Community Edition. If you have a larger cluster, you will have to use an init script. Here is a piece of code you can run in a python notebook that will install TensorFlow on all the nodes of a given cluster:

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I installed tensorflow on my arch linux computer via pacman. I tried to run the official example code for the mnist problem, but I get this error: Traceback (most recent call last): File "mnist_example.py", line 27, in <module> from tensorflow.examples.tutorials.mnist import inpu tf.contrib.eager.defun caches graphs for your convenience, letting you define TensorFlow functions without explicitly specifying their signatures. However, this policy is conservative and potentially expensive; for example, when different invocations of your function have differently-shaped Tensor inputs, this policy might generate more graph ... A large amount of older TensorFlow 1.x code uses the Slim library, which was packaged with TensorFlow 1.x as tf.contrib.layers. As a contrib module, this is no longer available in TensorFlow 2.0, even in tf.compat.v1. Converting code using Slim to TF 2.0 is more involved than converting repositories that use v1.layers.

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TensorFlow 代理; 简介 TensorFlow 针对 JavaScript 针对移动设备和 IoT 设备 针对生产环境 Swift for TensorFlow(Beta 版) TensorFlow (r2.4) r1.15 Versions… TensorFlow.js TensorFlow Lite TFX 负责任的 AI 模型和数据集 工具 库和扩展程序 TensorFlow 认证计划 Besides the different types of optimizers, Tensorflow also contains different flavours of RNN's. We can choose from different types of cells and wrappers use them to reconstruct different types of Recurrent...global_step = tf.train.get_or_create_global_step() summary_writer = tf.contrib.summary.create_file_writer( train_dir, flush_millis=10000) with summary_writer.as_default(), tf.contrib.summary.always_record_summaries(): # model definition code goes here # and in it call tf.contrib.summary.scalar("loss", my_loss) # In this case every call to tf ... An introduction to tensorflow and Implementing deep learning using tensorflow. Learn how to implement neural networks using TensorFlow in python.TensorFlow 2.0 is here! With the Keras integration, and Eager Execution enabled by default, 2.0 is all about ease of use, and simplicity. We want to provide ... The machine learning library TensorFlow has had a long history of releases starting from the initial open-source release from the Google Brain team back in November 2015.

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Nov 06, 2019 · However, contrib is used widely in TensorFlow 1.x, Google does no provides an integrated solution to the contrib issue. For instance, it is another solution to the specific contrib case. # -initializer = tf.contrib.layers.xavier_initializer (seed = 1) initializer = tf.truncated_normal_initializer (stddev=0.1) 重现更新下tensorflow看看,是不是The TensorFlow contrib module will not be included in TensorFlow 2.0.这里的问题 1 day ago · I downloaded anaconda which has a python 3.8 version. and i installed tensorflow with pip install tensorflow. from tensorflow.contrib import learn in my code did not work as tensorflow 1.x doesnt work in python 3.8. I downgraded to python 3.7 by conda install python==3.7. and then pip install tensorflow==1.15. But it still did not work and ... TensorFlow: Constants, Variables, and Placeholders. TensorFlow is a framework developed by Google The name TensorFlow is derived from the operations, such as adding or multiplying, that...Tensorflow系列:tf.contrib.layers.batch_norm; tf.nn.batch_normalization() tf.layers.batch_normalization使用中遇到的坑 ... tf.contrib.framework.get_unique_variable(var_op_name) Gets the variable uniquely identified by that var_op_name. Args: var_op_name: the full name of the variable op, including the scope. Returns: a tensorflow variable. Raises: ValueError: if no variable uniquely identified by the name exists. Hold on a sec, all of the solutions posted on the net point to using tensorflow 1.x. I don't get it. We are well into tensorflow 2.x, trying to migrate all the outdated modules over... going backwards seems counterproductive. Isn't there a solution (disregarding its complexity) to keep using tensorflow 2.x and fix this issue with contrib ? Jan 06, 2018 · I have a bunch of machine learning models built using the “original” Estimator API, the one in tf.contrib.learn. In Tensorflow 1.2, parts of it moved to core and in Tensorflow 1.4, the remaining pieces I need finally arrived in core Tensorflow. So, time for me to begin the process of moving to the core Estimator API. 定义 给定优化器的损失和参数,返回 training op。 参数定义 loss:损失函数 global_step:获取训练步数并在训练时更新 learning_rate:学... Inherits From: InitializableLookupTableBase . Class HashTable. Inherits From: InitializableLookupTableBase Defined in tensorflow/python/ops/lookup_ops.py.. A generic ... See full list on pypi.org

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TensorFlow.js nodes using pre-trained models module 'tensorflow' has no attribute 'ConfigProto' hot 6 TF 2.0 'Tensor' object has no attribute 'numpy' while using .numpy() although eager execution enabled by default hot 6 tensorflow-gpu CUPTI errors

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Hold on a sec, all of the solutions posted on the net point to using tensorflow 1.x. I don't get it. We are well into tensorflow 2.x, trying to migrate all the outdated modules over... going backwards seems counterproductive. Isn't there a solution (disregarding its complexity) to keep using tensorflow 2.x and fix this issue with contrib ? tf.contrib.cudnn_rnn.CudnnLSTM. Defined in tensorflow/contrib/cudnn_rnn/python/layers/cudnn_rnn.py.

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Use the TensorFlow Lite Converter tflite_convert to optimize the TensorFlow graphs and convert them to the TensorFlow Lite format for 8-bit inference. This tool is installed as standard in your path with TensorFlow 1.9 or later. To use the TensorFlow Lite Converter: Use the tflite_convert command-line program using the command: On Mon, Dec 16, 2019, 4:37 PM Divanshu Tak ***@***.***> wrote: This is not a big issue its just change of tenserflow version you are using just Uninstall the installed the current version and install 1.8.0 Because in latest realese tensorflow does not contain the package called Contrib — You are receiving this because you commented. Tensorflow (optional: can be skipped) Install. To install the latest version use the Menu - Manage palette option and search for node-red-contrib-machine-learning, or run the following command in your Node-RED user directory (typically ~/.node-red): npm i node-red-contrib-machine-learning Usage Python tensorflow.contrib.layers.fully_connected() Examples. The following are 30 code examples for showing how to use tensorflow.contrib.layers.fully_connected().Jan 06, 2018 · I have a bunch of machine learning models built using the “original” Estimator API, the one in tf.contrib.learn. In Tensorflow 1.2, parts of it moved to core and in Tensorflow 1.4, the remaining pieces I need finally arrived in core Tensorflow. So, time for me to begin the process of moving to the core Estimator API. conda-forge / packages / sklearn-contrib-lightning 0.6.0 7 lightning is a library for large-scale linear classification, regression and ranking in Python. Class DistributionStrategy. Defined in tensorflow/python/training/distribute.py. A list of devices with a state & compute distribution policy. The intent is that you ...

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See contrib/learn/README.md for general migration instructions. Currently, only linear SVMs are supported. For the underlying optimization problem, the SDCAOptimizer is used. Jun 10, 2020 · License TensorFlow Addons is a repository of contributions that conform to well-established API patterns, but implement new functionality not available in core TensorFlow. TensorFlow natively supports a large number of operators, layers, metrics, losses, and optimizers. <div dir="ltr" style="text-align: left;" trbidi="on"><span style="font-size: large;">Purchase Order Number</span><br /><br /><span style="font-family: Courier New ... Pastebin.com is the number one paste tool since 2002. Pastebin is a website where you can store text online for a set period of time. The following are 5 code examples for showing how to use tensorflow.contrib.learn.infer_real_valued_columns_from_input(). These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. import numpy as np import tensorflow as tf num_points = 100 dimensions = 2 points = np.random.uniform(0, 1000, [num_points, dimensions]) def input_fn(): return tf.train.limit_epochs( tf.convert_to_tensor(points, dtype=tf.float32), num_epochs=1) num_clusters = 5 kmeans = tf.contrib.factorization.KMeansClustering( num_clusters=num_clusters, use ...

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Feb 27, 2019 · Furthermore, due to module deprecations (for example, tf.flags and tf.contrib), TensorFlow 2.0 will include changes that cannot be worked around by switching to compat.v1. 要让TensorFlow的数据集包含TFRecord文件记录,需要使用到TFRecordDataset类,使用该类即可得到含有一个或者多个TFRecord文件的记录的TensorFlow数据集。本节中介绍了详细的属性与设置方法。_来自TensorFlow官方文档,w3cschool编程狮。 WARNING:tensorflow:From d:\ProgramData\Anaconda3\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:267: extract_labels (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version. import tensorflow as tf from tensorflow.contrib import slim ウェイトの初期化 weights = slim . variables . variable ( 'weights' , shape = [ 10 , 10 , 3 , 3 ], initializer = tf . truncated_normal_initializer ( stddev = 0.1 ), regularizer = slim . l2_regularizer ( 0.05 ), device = '/CPU:0' ) <div dir="ltr" style="text-align: left;" trbidi="on"><span style="font-size: large;">Purchase Order Number</span><br /><br /><span style="font-family: Courier New ... A year ago, TensorFlow open-sourced a platform that enables sliced evaluation of machine learning (ML) model performance, called Fairness Indicators. Response evaluation is a first step toward avoiding bias and allowing the company to determine how the models work for various users.

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import numpy as np import tensorflow as tf num_points = 100 dimensions = 2 points = np.random.uniform(0, 1000, [num_points, dimensions]) def input_fn(): return tf.train.limit_epochs( tf.convert_to_tensor(points, dtype=tf.float32), num_epochs=1) num_clusters = 5 kmeans = tf.contrib.factorization.KMeansClustering( num_clusters=num_clusters, use ...

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Tensorflow has a few optimization functions like RMSPropOptimizer, AdaGradOptimizer, etc. We choose AdamOptimzer and we set minimize to the function that shall minimize the cross_entropy loss...The tf.contrib.cudnn_rnn should always be used in NVIDIA GPUs while in CPUs when tf.contrib.cudnn_rnn is not available, the fastest alternative is the tf.contrib.rnn.LSTMBlockFusedCell. The other cell types which are less common, we can implement the graph like tf.contrib.rnn.BasicLSTMCell and will have same characteristics including degraded performance and usage of high memory. Pastebin.com is the number one paste tool since 2002. Pastebin is a website where you can store text online for a set period of time. Dec 15, 2020 · This TensorRT 7.2.2 Developer Guide demonstrates how to use the C++ and Python APIs for implementing the most common deep learning layers. It shows how you can take an existing model built with a deep learning framework and use that to build a TensorRT engine using the provided parsers.

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Dec 15, 2020 · This TensorRT 7.2.2 Developer Guide demonstrates how to use the C++ and Python APIs for implementing the most common deep learning layers. It shows how you can take an existing model built with a deep learning framework and use that to build a TensorRT engine using the provided parsers. Pastebin.com is the number one paste tool since 2002. Pastebin is a website where you can store text online for a set period of time. 官网上介绍在window下编译tensorflow源码的文章较少,大部分都是介绍在linux下bazel如何编译源码的,但是在github tensorflow主目录tensorflow\tensorflow\contrib\cmake下有详细的网页介绍Windows环境编译方法,其实这个介绍有写到源代码目录C:\TF\tensorflow\tensorflow\contrib\cmake下的 ... TensorFlow 的 contrib 模块已经超越了单个存储库中可以维护和支持的模块。 因此,作为发布 TensorFlow 2.0 的一部分,我们将停止分发 tf.contrib。

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If TensorFlow is your primary framework, and you are looking for a simple & high-level model definition interface to make your life easier, this tutorial is for you. Keras layers and models are fully compatible...Working With TensorFlow RNN Weights. 14.1.4.1. TensorFlow RNN Cells Supported In TensorRT. 14.1.4.2. Maintaining Model Consistency Between TensorFlow And TensorRT.* This Edureka TensorFlow Full Course video is a complete guide to Deep Learning using TensorFlow. It covers in-depth knowledge about Deep Leaning, Tensorflow & Neural Networks.The following are 30 code examples for showing how to use tensorflow.contrib.slim.conv2d().These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. Jul 04, 2016 · Here, y is a list of our predictions sorted by score in descending order, and y_test is the actual label. For example, a y of [0,3,1,2,5,6,4,7,8,9] Would mean that the utterance number 0 got the highest score, and utterance 9 got the lowest score. Oct 27, 2020 · Example TensorFlow script for finetuning a VGG model on your own data. Uses tf.contrib.data module which is in release v1.2 Based on PyTorch example from Justin Johnson (https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c) TensorFlow 2.3.0 API documentation with instant search, offline support, keyboard shortcuts, mobile version, and more. AttributeError: module 'tensorflow_core.compat.v1' has no attribute 'contrib' tf2.0 can perfectly solve the problem of module ‘tensorflow’ has no attribute ‘contrib’ without downgrading; opencv-contrib-Python compile module 'cv2.cv2' has no attribute 'xfeatures2d' module 'tensorflow' has no attribute 'get_default_graph' I installed tensorflow on my arch linux computer via pacman. I tried to run the official example code for the mnist problem, but I get this error: Traceback (most recent call last): File "mnist_example.py", line 27, in <module> from tensorflow.examples.tutorials.mnist import inpu TensorFlow includes functions like tf.contrib.layers that produce layered operations of weights and biases and also provide batch normalization, convolution layer, dropout layer, etc.