# Tensorflow Memory Error **URL:** \ **Category:** Jetson TX2\ **Created:** [August 9, 2017, 11:04am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380 "2017-08-09T11:04:48Z")\ **Posts on this page:** 20\ **Page:** 1
**Author:** ![JArchy](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@JArchy](https://forums.developer.nvidia.com/u/JArchy)\ **Post date:** [August 9, 2017, 11:04am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/1 "2017-08-09T11:04:48Z")
Hello, seeming to have an error when running Tensorflow based models. From general google searches it seems that this is a GPU memory issue, however none of the fixes for other architectures worked. I am running the TX2 with the latest Jetpack (3.1): #define CUDNN\_MAJOR 6 #define CUDNN\_MINOR 0 #define CUDNN\_PATCHLEVEL 21 Cuda compilation tools, release 8.0, V8.0.72 bazel-0.5.1 > > > import tensorflow as tf > > > tf. **version** > > > ‘1.2.1’ and this is the error: ```auto 2017-08-09 11:02:04.230621: E tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:879] could not open file to read NUMA node: /sys/bus/pci/devices/0000:00:00.0/numa_node Your kernel may have been built without NUMA support. 2017-08-09 11:02:04.230736: I tensorflow/core/common_runtime/gpu/gpu_device.cc:940] Found device 0 with properties: name: NVIDIA Tegra X2 major: 6 minor: 2 memoryClockRate (GHz) 1.3005 pciBusID 0000:00:00.0 Total memory: 7.67GiB Free memory: 3.24GiB 2017-08-09 11:02:04.230790: I tensorflow/core/common_runtime/gpu/gpu_device.cc:961] DMA: 0 2017-08-09 11:02:04.230815: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0: Y 2017-08-09 11:02:04.230856: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Creating TensorFlow device (/gpu:0) -> (device: 0, name: NVIDIA Tegra X2, pci bus id: 0000:00:00.0) 2017-08-09 11:02:04.230891: I tensorflow/core/common_runtime/gpu/gpu_device.cc:642] Could not identify NUMA node of /job:localhost/replica:0/task:0/gpu:0, defaulting to 0. Your kernel may not have been built with NUMA support. 2017-08-09 11:02:05.303591: E tensorflow/stream_executor/cuda/cuda_dnn.cc:359] could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR 2017-08-09 11:02:05.303663: E tensorflow/stream_executor/cuda/cuda_dnn.cc:326] could not destroy cudnn handle: CUDNN_STATUS_BAD_PARAM 2017-08-09 11:02:05.303694: F tensorflow/core/kernels/conv_ops.cc:671] Check failed: stream->parent()->GetConvolveAlgorithms(&algorithms) Aborted (core dumped) ``` I have tried previous version of Jetpack as well as tensorflow with the same error, and have tried completely separate Tensorflow models. ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [August 10, 2017, 1:50am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/2 "2017-08-10T01:50:00Z")
Hi, Please try to enable following options: ```auto config = tf.ConfigProto() config.gpu_options.allow_growth = True sess = tf.Session(config=config) ``` Thanks. ---
**Author:** ![JArchy](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@JArchy](https://forums.developer.nvidia.com/u/JArchy)\ **Post date:** [August 10, 2017, 8:12am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/3 "2017-08-10T08:12:54Z")
Nope, no dice unfortunately, with much the same error. I also previously tried: ```auto config = tf.ConfigProto() config.gpu_options.per_process_gpu_memory_fraction = 0.4 ... ``` With various differing values of both high and low and received the same error. ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [August 11, 2017, 2:41am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/4 "2017-08-11T02:41:37Z")
Hi, Two things want to confirm first: **1.** Do you follow the steps below to build your TX2? [https://syed-ahmed.gitbooks.io/nvidia-jetson-tx2-recipes/content/first-question.html](https://syed-ahmed.gitbooks.io/nvidia-jetson-tx2-recipes/content/first-question.html) **2.** Does this error also occur with MNIST? We want to confirm this is a resource issue(memory…) or frameworks(build architecture…) issue first. Thanks. ---
**Author:** ![JArchy](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@JArchy](https://forums.developer.nvidia.com/u/JArchy)\ **Post date:** [August 11, 2017, 9:04am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/5 "2017-08-11T09:04:56Z")
1. The first build i followed that but using the JetsonHacks scripts based on github (basically those instructions), however for the tf 1.2 i followed Andrey1984’s instructions on this post [url][https://devtalk.nvidia.com/default/topic/1016294/tensorflow-1-2-0-gpu-on-tx2/[/url]](https://devtalk.nvidia.com/default/topic/1016294/tensorflow-1-2-0-gpu-on-tx2/%5B/url%5D) and the build prompts on this [url][https://gist.github.com/csarron/a265280010faeecae3e8c204c5749a67[/url]](https://gist.github.com/csarron/a265280010faeecae3e8c204c5749a67%5B/url%5D) 1. No i havent seen this error on minst, or other run examples. (Simple tests such as at the bottom of the link you posted run correctly with no errors.) ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [August 14, 2017, 2:32am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/6 "2017-08-14T02:32:54Z")
Hi, NUMA is for multi-GPU. It looks like your model wants to enable multi-GPU options. But NUMA is turn off (by default) when building, and TX2 only have one GPU. Could you try to disable the related option in your source and check it again? ---
**Author:** ![JArchy](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@JArchy](https://forums.developer.nvidia.com/u/JArchy)\ **Post date:** [August 14, 2017, 12:46pm UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/7 "2017-08-14T12:46:11Z")
Rebuilt tensorflow following the instructions you provided based on disabling the NUMA node. It didnt work, even tried with original and the additional config. options. ```auto python detect.py h786poj.jpg weights.npz out3.jpg [[ 0.40392157 0.44313725 0.4627451 ..., 0.17254902 0.17647059 0.18431373] [ 0.42352941 0.45882353 0.47058824 ..., 0.17647059 0.18431373 0.19215686] [ 0.44705882 0.47058824 0.47843137 ..., 0.18431373 0.19215686 0.20392157] ..., [ 0.58431373 0.58431373 0.59215686 ..., 0.54117647 0.5254902 0.50588235] [ 0.58823529 0.57647059 0.56470588 ..., 0.52941176 0.51764706 0.49411765] [ 0.59215686 0.56862745 0.54117647 ..., 0.5254902 0.51372549 0.49411765]] 2017-08-14 12:41:15.428733: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:856] ARM has no NUMA node, hardcoding to return zero 2017-08-14 12:41:15.428852: I tensorflow/core/common_runtime/gpu/gpu_device.cc:940] Found device 0 with properties: name: NVIDIA Tegra X2 major: 6 minor: 2 memoryClockRate (GHz) 1.3005 pciBusID 0000:00:00.0 Total memory: 7.67GiB Free memory: 4.59GiB 2017-08-14 12:41:15.428947: I tensorflow/core/common_runtime/gpu/gpu_device.cc:961] DMA: 0 2017-08-14 12:41:15.428998: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0: Y 2017-08-14 12:41:15.429024: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Creating TensorFlow device (/gpu:0) -> (device: 0, name: NVIDIA Tegra X2, pci bus id: 0000:00:00.0) 2017-08-14 12:41:15.554341: I tensorflow/compiler/xla/service/platform_util.cc:58] platform CUDA present with 1 visible devices 2017-08-14 12:41:15.554406: I tensorflow/compiler/xla/service/platform_util.cc:58] platform Host present with 4 visible devices 2017-08-14 12:41:15.555134: I tensorflow/compiler/xla/service/service.cc:198] XLA service 0x30c2d40 executing computations on platform Host. Devices: 2017-08-14 12:41:15.555184: I tensorflow/compiler/xla/service/service.cc:206] StreamExecutor device (0): , 2017-08-14 12:41:15.555849: I tensorflow/compiler/xla/service/platform_util.cc:58] platform CUDA present with 1 visible devices 2017-08-14 12:41:15.555894: I tensorflow/compiler/xla/service/platform_util.cc:58] platform Host present with 4 visible devices 2017-08-14 12:41:15.556610: I tensorflow/compiler/xla/service/service.cc:198] XLA service 0x3112ff0 executing computations on platform CUDA. Devices: 2017-08-14 12:41:15.556652: I tensorflow/compiler/xla/service/service.cc:206] StreamExecutor device (0): NVIDIA Tegra X2, Compute Capability 6.2 2017-08-14 12:41:18.518643: E tensorflow/stream_executor/cuda/cuda_dnn.cc:359] could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR 2017-08-14 12:41:18.518718: E tensorflow/stream_executor/cuda/cuda_dnn.cc:326] could not destroy cudnn handle: CUDNN_STATUS_BAD_PARAM 2017-08-14 12:41:18.518749: F tensorflow/core/kernels/conv_ops.cc:671] Check failed: stream->parent()->GetConvolveAlgorithms(&algorithms) Aborted (core dumped) ``` ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [August 15, 2017, 1:56am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/8 "2017-08-15T01:56:57Z")
Hi, Thanks for the testing. It looks like more complicated than a building issue. Could you tell me how to reproduce this issue? Do you use a public GitHub code or could you share your source? Thanks. ---
**Author:** ![JArchy](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@JArchy](https://forums.developer.nvidia.com/u/JArchy)\ **Post date:** [August 15, 2017, 7:18am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/9 "2017-08-15T07:18:13Z")
Hey, Yeah sure, its using this as standard ```auto https://github.com/matthewearl/deep-anpr ``` . Happy to share weights if that is needed. The training works correctly, it is just running the detect.py where the issue is present. ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [August 16, 2017, 1:45am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/10 "2017-08-16T01:45:50Z")
Hi, Yes, please share weight for us. Thanks. ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [August 16, 2017, 1:47am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/11 "2017-08-16T01:47:22Z")
Hi, If you have tensorflow x86 environment. Could you also help us give it a try? Thanks. ---
**Author:** ![JArchy](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@JArchy](https://forums.developer.nvidia.com/u/JArchy)\ **Post date:** [August 16, 2017, 7:40am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/12 "2017-08-16T07:40:49Z")
Here is the weights on google drive: [url][https://drive.google.com/file/d/0B3TAQ6gwtBNmZVVDTnAySHB3eU0/view?usp=sharing[/url]](https://drive.google.com/file/d/0B3TAQ6gwtBNmZVVDTnAySHB3eU0/view?usp=sharing%5B/url%5D) ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [August 17, 2017, 1:50am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/13 "2017-08-17T01:50:16Z")
Thanks. We will try to reproduce this issue, and update more information to you later. ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [August 21, 2017, 3:05am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/14 "2017-08-21T03:05:11Z")
Hi, Good news! I can run deep\_anpr sample with this whl (JetPack3.1): > **[GitHub - peterlee0127/tensorflow-nvJetson: TensorFlow for NVIDIA Jetson, also include patch...](https://github.com/peterlee0127/tensorflow-nvJetson)** > > TensorFlow for NVIDIA Jetson, also include patch and script for building. $ sudo pip install tensorflow-1.3.0rc0-cp27-cp27mu-linux\_aarch64.whl $ sudo reboot $ cd [deep\_anpr folder] $ ./detect.py in.jpeg weights.npz out.jpg Thanks. ---
**Author:** ![JArchy](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@JArchy](https://forums.developer.nvidia.com/u/JArchy)\ **Post date:** [August 21, 2017, 10:11am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/15 "2017-08-21T10:11:00Z")
Hmmm hasnt appeared to work on this jetson, with a slightly different error in the last line: ```auto 2017-08-21 10:07:38.406485: E tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:879] could not open file to read NUMA node: /sys/bus/pci/devices/0000:00:00.0/numa_node Your kernel may have been built without NUMA support. 2017-08-21 10:07:38.406598: I tensorflow/core/common_runtime/gpu/gpu_device.cc:955] Found device 0 with properties: name: NVIDIA Tegra X2 major: 6 minor: 2 memoryClockRate (GHz) 1.3005 pciBusID 0000:00:00.0 Total memory: 7.67GiB Free memory: 5.67GiB 2017-08-21 10:07:38.406654: I tensorflow/core/common_runtime/gpu/gpu_device.cc:976] DMA: 0 2017-08-21 10:07:38.406683: I tensorflow/core/common_runtime/gpu/gpu_device.cc:986] 0: Y 2017-08-21 10:07:38.406708: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1045] Creating TensorFlow device (/gpu:0) -> (device: 0, name: NVIDIA Tegra X2, pci bus id: 0000:00:00.0) 2017-08-21 10:07:38.406740: I tensorflow/core/common_runtime/gpu/gpu_device.cc:657] Could not identify NUMA node of /job:localhost/replica:0/task:0/gpu:0, defaulting to 0. Your kernel may not have been built with NUMA support. 2017-08-21 10:07:39.100041: E tensorflow/stream_executor/cuda/cuda_dnn.cc:371] could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR 2017-08-21 10:07:39.100116: E tensorflow/stream_executor/cuda/cuda_dnn.cc:338] could not destroy cudnn handle: CUDNN_STATUS_BAD_PARAM 2017-08-21 10:07:39.100146: F tensorflow/core/kernels/conv_ops.cc:672] Check failed: stream->parent()->GetConvolveAlgorithms( conv_parameters.ShouldIncludeWinogradNonfusedAlgo(), &algorithms) Aborted (core dumped) ``` Weirdly enough our other jetson is working following the previous identical install instructions and versions. I think out next step will be to reflash the non-working jetson and attempt to reinstall from scratch to ensure nothing was done differently. ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [August 22, 2017, 1:31am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/16 "2017-08-22T01:31:00Z")
Hi, The link in comment #14 is built with cuDNNv6. Please flash device with JetPack3.1. Thanks. ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [August 22, 2017, 1:32am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/17 "2017-08-22T01:32:31Z")
Hi, The link in comment #14 is built with cuDNNv6. Please flash device with JetPack3.1. Thanks. ---
**Author:** ![JArchy](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@JArchy](https://forums.developer.nvidia.com/u/JArchy)\ **Post date:** [August 23, 2017, 2:37pm UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/18 "2017-08-23T14:37:13Z")
Reflashed the jetson and installed tensorflow with that .whl and it worked! Thanks for the help. ---
**Author:** ![Arlen0615](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@Arlen0615](https://forums.developer.nvidia.com/u/Arlen0615)\ **Post date:** [October 17, 2017, 5:49am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/19 "2017-10-17T05:49:12Z")
Hi AastaLLL, I have the same issue with [https://github.com/igul222/improved\_wgan\_training](https://github.com/igul222/improved_wgan_training) when you try gan\_mnist.py ```auto python gan_mnist.py ``` I got this… ```auto nvidia@tegra-ubuntu:~/improved_wgan_training$ python gan_mnist.py Uppercase local vars: BATCH_SIZE: 50 CRITIC_ITERS: 5 DIM: 64 ITERS: 200000 LAMBDA: 10 MODE: wgan-gp OUTPUT_DIM: 784 2017-10-17 05:31:07.423028: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:857] ARM64 does not support NUMA - returning NUMA node zero 2017-10-17 05:31:07.423174: I tensorflow/core/common_runtime/gpu/gpu_device.cc:955] Found device 0 with properties: name: NVIDIA Tegra X2 major: 6 minor: 2 memoryClockRate (GHz) 1.3005 pciBusID 0000:00:00.0 Total memory: 7.67GiB Free memory: 2.72GiB 2017-10-17 05:31:07.423231: I tensorflow/core/common_runtime/gpu/gpu_device.cc:976] DMA: 0 2017-10-17 05:31:07.423259: I tensorflow/core/common_runtime/gpu/gpu_device.cc:986] 0: Y 2017-10-17 05:31:07.423286: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1045] Creating TensorFlow device (/gpu:0) -> (device: 0, name: NVIDIA Tegra X2, pci bus id: 0000:00:00.0) WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/python/util/tf_should_use.py:175: initialize_all_variables (from tensorflow.python.ops.variables) is deprecated and will be removed after 2017-03-02. Instructions for updating: Use `tf.global_variables_initializer` instead. 2017-10-17 05:31:12.753831: E tensorflow/stream_executor/cuda/cuda_dnn.cc:371] could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR 2017-10-17 05:31:12.753904: E tensorflow/stream_executor/cuda/cuda_dnn.cc:338] could not destroy cudnn handle: CUDNN_STATUS_BAD_PARAM 2017-10-17 05:31:12.753941: F tensorflow/core/kernels/conv_ops.cc:672] Check failed: stream->parent()->GetConvolveAlgorithms( conv_parameters.ShouldIncludeWinogradNonfusedAlgo(), &algorithms) Aborted (core dumped) ``` and I try #14, but it not working because I already install with same version ```auto nvidia@tegra-ubuntu:~/tensorflow-tx2$ sudo pip install tensorflow-1.3.0-cp27-cp27mu-linux_aarch64.whl The directory '/home/nvidia/.cache/pip/http' or its parent directory is not owned by the current user and the cache has been disabled. Please check the permissions and owner of that directory. If executing pip with sudo, you may want sudo's -H flag. The directory '/home/nvidia/.cache/pip' or its parent directory is not owned by the current user and caching wheels has been disabled. check the permissions and owner of that directory. If executing pip with sudo, you may want sudo's -H flag. Requirement already satisfied: tensorflow==1.3.0 from file:///home/nvidia/tensorflow-tx2/tensorflow-1.3.0-cp27-cp27mu-linux_aarch64.whl in /usr/local/lib/python2.7/dist-packages Requirement already satisfied: protobuf>=3.3.0 in /usr/local/lib/python2.7/dist-packages (from tensorflow==1.3.0) Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python2.7/dist-packages (from tensorflow==1.3.0) Requirement already satisfied: tensorflow-tensorboard<0.2.0,>=0.1.0 in /usr/local/lib/python2.7/dist-packages (from tensorflow==1.3.0) Requirement already satisfied: wheel in /usr/lib/python2.7/dist-packages (from tensorflow==1.3.0) Requirement already satisfied: backports.weakref>=1.0rc1 in /usr/local/lib/python2.7/dist-packages (from tensorflow==1.3.0) Requirement already satisfied: numpy>=1.11.0 in /usr/lib/python2.7/dist-packages (from tensorflow==1.3.0) Requirement already satisfied: mock>=2.0.0 in /usr/local/lib/python2.7/dist-packages (from tensorflow==1.3.0) Requirement already satisfied: setuptools in /usr/local/lib/python2.7/dist-packages (from protobuf>=3.3.0->tensorflow==1.3.0) Requirement already satisfied: werkzeug>=0.11.10 in /usr/local/lib/python2.7/dist-packages (from tensorflow-tensorboard<0.2.0,>=0.1.0->tensorflow==1.3.0) Requirement already satisfied: html5lib==0.9999999 in /usr/local/lib/python2.7/dist-packages (from tensorflow-tensorboard<0.2.0,>=0.1.0->tensorflow==1.3.0) Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python2.7/dist-packages (from tensorflow-tensorboard<0.2.0,>=0.1.0->tensorflow==1.3.0) Requirement already satisfied: bleach==1.5.0 in /usr/local/lib/python2.7/dist-packages (from tensorflow-tensorboard<0.2.0,>=0.1.0->tensorflow==1.3.0) Requirement already satisfied: pbr>=0.11 in /usr/local/lib/python2.7/dist-packages (from mock>=2.0.0->tensorflow==1.3.0) Requirement already satisfied: funcsigs>=1; python_version < "3.3" in /usr/local/lib/python2.7/dist-packages (from mock>=2.0.0->tensorflow==1.3.0) ``` ---
**Author:** ![AastaLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/aastalll/32/14043_2.png) [@AastaLLL](https://forums.developer.nvidia.com/u/AastaLLL)\ **Post date:** [October 18, 2017, 2:58am UTC](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380/20 "2017-10-18T02:58:14Z")
Hi, Could you run this command and share the result with us? ```auto ll /home/nvidia/.cache/pip/ ``` Please remember to flash TX2 with JetPack3.1. This [**wheel**](https://github.com/peterlee0127/tensorflow-tx2) file is built with the JetPack3.1 package. Thanks. [Next page](https://forums.developer.nvidia.com/t/tensorflow-memory-error/52380.md?page=2)