Are there examples of how to split the data using : os.makedirs... : os.makedirs is not used in notebook (Lab 1) the

Course Q&A TensorFlow Developer Professional Convolutional Neural Networks in TensorFlow
1

Are there examples of how to split the data using : os.makedirs… : os.makedirs is not used in notebook (Lab 1) the

2

Please read the markdown for split_data in the notebook. If you have further questions, please be specific about it.

3

which notebook – Lab1 (ungraded) or Cats vs Dogs (graded) ?

4

I’m referring to the graded version.

5

Yes- I see this section; however, is this available in any of the videos or other labs… I would like to understand it in more detail before writing it…

6

Week 2 graded assignment in the course 2 also has the function to split data.

7

are you referring to “C2W2_Assignment-Week 2: Tackle Overfitting with Data Augmentation” – if so I do not see the function there…

8

There is a function called
def split_data(SOURCE_DIR, TRAINING_DIR, VALIDATION_DIR, SPLIT_SIZE): in C2W2 notebook.

9

Me too , i do not see the function split_data

10

have you resolved your problem??

11

@smd_motion See Refresh your Lab Workspace section here
If you’ve already done this and still don’t see split_data function in course2 week 1 assignment notebook, contact coursera help

12

i have done it is ok
so when train my model i have
UnknownError: Graph execution error:
and the training stop

13

2 root error(s) found.

14

@smd_motion
My response was with respect to you not seeing split_data function in the notebook. Please click my name and message your notebook as an attachment for me to better understand your current issue.

15

i just send you the docuement

16

@smd_motion
Please fix the following:

create_train_val_dirs

  1. Indentation is incorrect.
  2. Make use of root_path instead of root_dir inside the function.

split_data:

  1. Don’t rely on files global variable. Use a local variable instead.
  2. Splits should be calculated only after discarding empty files and not for every iteration of the for loop.