I am about to learn about Neural Networks and I am about to reproduce a tutorial which trains a Neural Network with the target to identify handwritten letters. The training of the Neural Network should be done with the MNIST data set. Unfortunately, exactly where my issue comes as I am not able to read in the MNIST data set.
The environment I am using is a Jupyter Notebook and Python 3.
These are the lines of code I have (line 2 causes the issue):
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("/tmp/data/", one_hot = True)
Line 2 causes this error message:
ModuleNotFoundError: No module named 'tensorflow.contrib'
Ok, what the error tells me, is clear. Reason is, that in my tensorflow installation folder a directory /tensorflow/contrib/... does not exist.
The issues is caused by line 2, as the module input_data.py contains this line of code:
from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets
So, the core of my issue is, that I do not know, where to get the module read_data_sets from. I was searching at GitHub, but the path
/tensorflow/contrib/learn/python/learn/datasets/mnist/
does not exist there.
In detail: Subfolder 'mnist' is not to be found in GitHub. Therefore, I also do not find the file read_data_sets.py.
So, where do I find the missing module 'read_data_sets'?
Would be great, if someone could help me as this issue stops my attempt to deal with Neural Networks already at the very beginning.
Thanks a lot and kind regards,
Matthias
It seems that you are using a new version of tensorflow >= 1.13.0 so you may follow this link if you want to load MNIST dataset
Related
I am using some code based on Tensorflow 1.x and I am using the latest version of TensorFlow (2.8).
I have run tf_upgrade_v2 (following these migration instructions) on the python file to generate a new compatible file.
However, this doesn't work with the line of code; from TensorFlow.contrib import training as contrib_training.
Getting the error ModuleNotFoundError: No module named 'tensorflow.contrib'
I understand that contrib has been deprecated, so the modules have been moved around. But I haven't been able to find where this training module has moved to or if it has been deleted. I have looked for information first on this document on the status of tf.contrib and after this spreadsheet on TF2.0 Symbols map and haven't found any information on the fate of this training module;
I have also tried looking around TensforFlow/tf.compat.v1 but with no success.
Of course uninstalling this version of TensorFlow and instead installing an earlier version is an option. But not an option that I am overly keen on.
I feel like I may be missing something fairly obvious here...
Thanks in advance!!
The reason behind this error - ModuleNotFoundError: No module named 'tensorflow.contrib' is, tf.contrib has been deprected to use in Tensorflow 2.x. You can use Tensorflow Addons or Tensorflow Slim in the pace of tf.contrib api.
Please check this link for more details.
I have a Deep Learning Code for Object Detection. What I did is that I ran the code on Google Colab and then Exported the model to use it locally. Now to run the model I have to again install whole Tensorflow package which is quite heavy for my system.
I want to ask if there is a way to download and run only specific parts of Tensorflow Library?
I am using Tensorflow at only 2 places in my code and I have to install whole Tensorflow library for it.
This is where I am loading the model.
detect_fn = tf.saved_model.load(PATH_TO_SAVED_MODEL)
This is where I am using Tensorflow 2nd time.
input_tensor = tf.convert_to_tensor(image_rgb)
These are the only 2 functions required to me from the Tensorflow Library and not the whole library... Thanks in anticipation.
Though I'm not entirely sure on the library as a whole, there is a Lite version of Tensorflow (I guess they realised 430MB is a bit much too).
Information regarding this can be found here:
https://www.tensorflow.org/lite/
A guide here seems to detail how to pick and choose parts of the Lite library and although not used myself, I should expect some degree of compatibility between the two...
https://www.tensorflow.org/lite/guide/reduce_binary_size
I'm trying to train an object detection model, but I can't make it work. I'm trying based on this:
htps://gilberttanner.com/blog/tensorflow-object-detection-with-tensorflow-2-creating-a-custom-model
but in pycharm.
My issue is that I got the following error when running model_main_tf2.py:
utf-8 error
Python version is the latest 3.8 Pycharm 2020.2.3 and tensorflow 2.3.1. I had to add the object_detection folder to the tensorflow manually because pycharm couldn't manage to get it right.
Project
The main problem is here:
self._read
I tried creating the .record files with latin-1 encoding but no luck
Edit:
Used this to convert the labelled images to .csv files:xml_to_csv
This to create the tf files:tfpic1 tfpic2 tfpic3
Main_module I used: https://github.com/tensorflow/models/blob/master/research/object_detection/model_main.py
With 2 changes: import tensorflow as tf instead of the one in this.
And tf.compat.v1.app.run() instead of the one at the end of this. I had to change a lot of tf functions in the files for object detection because it only works when i call the functions as tf.compat.v1. rather than tf
I encountered the similar issue while following tensorflow object detection guide.
In my case the problem was in the incorrect pipeline.config PATHs (I thought PATHs were already specified for me when i copied them, but I was wrong).
Not sure if it will help you, but it would be nice if it works.
I get the ValueError: bad marshal data (unknown type code) above when trying to load a previously saved Keras model (I think it's a Python error though that has nothing to do with Keras, but not quite sure.)
from keras.models import load_model
from keras import __version__ as keras_version
model = load_model("model.h5")
I searched on Google but didn't find a working solution. I tried deleting pya-files with: sudo find /usr -name '*.pyc' -delete but that didn't help either.
Do you have an idea how I can fix this error? Thank you!
I know the post is a bit older, but I just ran into the same problem.
As #Daniel Möller said, it was because I had installed different versions of Python, Tensorflow and Keras. Try to train the model again, in the same environment that you use to load the model afterwards. Or at least make sure that the Python version and the modules used are installed in the same version.
I'm learning TensorFlow, running version r0.10 on Ubuntu 16.04. I am working on the CIFAR-10 Tutorial and have trained the CNN in the example.
Where is the image data stored for this tutorial?
The data path is defined on this line, in cifar10.py:
tf.app.flags.DEFINE_string('data_dir', '/tmp/cifar10_data',
"""Path to the CIFAR-10 data directory.""")
However I am confused as to why I cannot find this directory. I have attempted to manually search for it, and also look through all the example directories for it.
It is getting saved in a relative path for your OS, not your working directory. Take a look at my answer here and see if that helps.