Where is the collection tf_utils invoked in the assignment?
If I attempt to import it to my local environment, via
from tensorflow import tf_utils
the file is not found. I believe this means that it is written by Coursera. How can I incorporate it to the local environment?
Hi EduardoChicago,
After opening an assignment notebook, you can go to File â OpenâŚ
This will show files and folders used as utilities for the assignment. You can download from there and subsequently incorporate files in your local env.
Hi Reinoud, and Mentors.
No luck. When I âFile â Openâ the directory (below), I donât find a tensorflow package, from which tf_utils is imported.
Can you dig deeper, please? (As I may have explained, I ask because I intend to make this lab work in the local environment --so that I can use my own training sets).
Thanks.
(this is what I find :
[datasets]
[images]
[Residual_Networks training my set.ipynb]
[Residual_Networks.ipynb]
[outputs.py]
[public_tests.py]
[resnet50.h5]
[resnets_utils.py][test_utils.py])
Hi EduardoChicago,
In the residual networks assignment, tf_utils is not imported. So you cannot find it in the local folder used by that assignment. If you need tf_utils, you can reach it from an assignment that uses it.
See also python - How to fix the error as 'tf_utils module not found' - Stack Overflow
Thanks again Reinoud. Sorry to keep asking, but you answer, and no good deed goes unpunished.
So, here is a related one. Itâs so related that it does not deserve to be labeled as a ânew topicâ.
When testing the Identity_block function, the lab test includes these lines
A3np = A3.numpy()
print(np.around(A3.numpy()[:,(0,-1),:,:].mean(axis = 3), 5))
resume = A3np[:,(0,-1),:,:].mean(axis = 3)
print(resume[1, 1, 0] , resume[1, 1, 0])
This causes the creation of A3np, which we are told is not a tensor (A3 is a tensor).
When I try to execute these lines in my (tf) environment, I get an error
----> 1 A3np = A3.numpy()
AttributeError: âTensorâ object has no attribute ânumpyâ
Evidently, the rules in my environment are different. How do I change the local environment to match Courseraâs? Or, how do I reformulate
A3np = A3.numpy()
in a way that is more universally interpretable?
(I keep digging deeper the hole of indebtedness to youâŚ)
What version of TensorFlow are you using locally? Hereâs what I get when I run this code in the ResidualNet notebook:
tf.__version__
'2.3.0'Good point, Paul. You can also have a look here, EduardoChicago:
I had the version 1.4 that comes with conda. Seeing that the conventional wisdom is against installing the update with PIL, I did it with
conda install tensorflow==2.0
and then tried the simple
import tensorflow as tf
I got a scary error
ERROR! Session/line number was not unique in database. History logging moved to new session 59
After that, I got more errors (actually, 3) , of the type
ERROR:root:Internal Python error in the inspect module.
Below is the traceback from this internal error.
Here is a sample piece of the long traceback.
ImportError: cannot import name ârandom_uniformâ from âtensorflow.keras.initializersâ (C:.âŚpy)
During handling of the above exception, another exception occurred:
âŚ
AttributeError: âImportErrorâ object has no attribute ârender_tracebackâ
During handling of the above exception, another exception occurred: etc.
Obviously, updating tensorflow is above my pay grade 
Any suggestions?
Paul: If I ask
tf.version
I get
AttributeError Traceback (most recent call last)
in
----> 1 tf.versionAttributeError: module âtensorflowâ has no attribute âversionâ
but I understand that tensorflow 2.0 is necessary to run the ResNets exercises. Itâs just that I cannot install it in my Anaconda3 system. Should I uninstall Anaconda and start again? I just need an environment similar to what is used in Coursera courses. After the update to tensorflow.keras I lost much of what I had achieved.
Please have another look at the code that I gave you. Itâs not just âtf.versionâ itâs bracketed with double underscores on both ends. Or to put it in words, itâs âunder under version under underâ. Maybe that got confused by the rendering logic as Markdown.
Or try googling âhow do I find what TensorFlow version I haveâ.
Well, if you want to play that game, then youâre going to have to get your hands dirty. The course gives you an environment which is complete and usable. If you want to create your own environment, then you need to develop the skills to solve problems like this. The point is that it never ends, right? Next youâll be asking us how to deal with whatever whacko version of Windows youâve got. Speaking of âbeyond pay gradeâ, please realize the mentors do not get paid to do this. Weâre here to be answering questions about the course material, not teaching you how to install software in your own environment. Maybe youâll get lucky and someone else who is listening here might be a nicer person than I am or actually enjoy solving problems like this, in which case I will be happy to let them handle it.
The good news is that there is copious information of this sort on the web. Just google âhow do I install TensorFlow 2.0â. Iâm sure that will take you to either StackExchange or the TF website.
I so agree that it never ends. You are nicer than you think. I would be equally mad if a postdoc were asking me how to âcorrect a z stack of images for blurring by the imaging systemâ, or an open q like that.
The alternative question, perhaps less irritating, would be how to implement training/testing on oneâs own set of images in the Coursera working environment. Would you give this a thought? (Students are the worst!)
sure. the double underscores were invisible in the rendering. thanks.
Doing things in the course environment is pretty easy by comparison. Start with one of the notebooks that uses the same dataset and just make a copy of it for your experiments. Just click âFile â Make a copyâ or âFile â Openâ and then use the âDuplicateâ and âRenameâ functions there. Then you can change the code to run whatever experiments you want. As far as I can tell over several years of using the online Coursera environment, they donât seem to put any limit on making copies of the various notebooks and keeping them around. The only downside is that you need to keep paying the subscription fee or else you lose access to the online environment. But there are other alternatives for executing Jupyter Notebooks: Google Colab is probably the most famous one. You can download the âipynbâ file and upload it to Colab. They have all the standard python, pytorch, tf, keras and so forth available, but you might need to bring over any of the custom utility routines that are here.
Oh, sorry, I see that I misinterpreted your question a bit. You are talking about using your own datasets. The same âcopy a relevant notebookâ strategy is the starting point, but then you just need to upload your datasets. From the notebook, click âFile â Openâ and then youâll find an âUploadâ button in the resulting âfile navigationâ view.
Thanks Paul. The problem is that my âtraining setâ is a collection of images (i.e. a few hundred separate jpg files, with labels). I donât think that is the same as a dataset, which I would not know how to make. Perhaps I havenât taken enough courses.
As for the other approach (build my environment), Iâm almost there. I still get a couple of errors (NameError: name âEagerTensorâ is not defined), but they donât seem to affect the performance. Iâm sure I will find more issues, but there is progress⌠I thank you again.
There are various ways to turn a directory full of files into a compound file or âdatabaseâ. In this course, they prefer using the âh5â file format but there are other simpler alternatives like zip or tar.
Try googling âcreate a zip file from a set of images in pythonâ and then âhow do I read a zip file in pythonâ.
Or google âhow do I convert a set of images into an h5 database file in pythonâ.
There is a theme here: this type of question is covered in great detail on the web and modern search engines can do NLP. âAsk and ye shall findâ.
But I also realize that knowing the right question to ask is not always obvious. It is legitimate to ask for help at that level, so that we can help you scope out the options. On that general topic, a followup question is what is the form of the labels that you have for your data? Are they individual files with names that express the correspondence with the image files or some other format? Itâs easy to use âzipâ to create a compound file containing a collection of image files, but you also need to coordinate that with the labels.
Given the scaling issues that are fundamental to the online education model, itâs my goal to give âfishing lessonsâ whenever possible instead of handing people a fish, in the sense of the famous proverb most commonly attributed to the philosopher Lao Tzu:
If I give a man a fish, he will not be hungry today. If I teach a man to fish, then he will never be hungry again.
Hence the theme of suggesting the search terms to be used âŚ
Thanks again. I managed to input all files individually, via an inelegant for loop (one more inelegance in my local environment 
). Now dealing with âshapingâ issues. Please see a LinkedIn message on a âprofessionalâ issue.
There are plenty of examples of how to resize and reshape images in these courses. E.g. see the Logistic Regression exercise in Week 2 Course 1 or the Application exercise in Week 4 Course 1. Both have the reshape logic to convert 3D image tensors into vectors as well as the âResizeâ logic to create standard sizes. See the âTest with Your Own Imageâ section of both assignments.