TensorFlow Dataset API Reviews

Vikram M. · Reviewed over 2 years ago

I had some difficulty following along with this lab since the previous lab exercise was not included in this course. I would recommend adding the first lab in that folder to the course since future labs reference it.

Charles B. · Reviewed over 2 years ago

Olha B. · Reviewed over 2 years ago

Need more clarity on where to run the commands - on Terminal or just click on the arrow of the instructions window?

ep m. · Reviewed over 2 years ago

Alejandro A. · Reviewed over 2 years ago

Adán T. · Reviewed over 2 years ago

Santosh S. · Reviewed over 2 years ago

Rafael G. · Reviewed over 2 years ago

Stepan G. · Reviewed over 2 years ago

Pablo Leonardo L. · Reviewed over 2 years ago

Tomas B. · Reviewed over 2 years ago

Sonali R. · Reviewed over 2 years ago

Николай К. · Reviewed over 2 years ago

Gaurav P. · Reviewed over 2 years ago

Tejas T. · Reviewed over 2 years ago

Siwatchara S. · Reviewed over 2 years ago

Sharad Kumar G. · Reviewed over 2 years ago

quite messy unclear how to do tutorials with this part, and functions are not working as expected. lab task #2 --------------------------------------------------------------------------- AssertionError Traceback (most recent call last) Cell In[66], line 26 23 loss =loss_mse(X_batch, Y_batch, w0, w1) # TODO -- Your code here. 24 print(MSG.format(step=step, loss=loss, w0=w0.numpy(), w1=w1.numpy())) ---> 26 assert loss < 0.0001 27 assert abs(w0 - 2) < 0.001 28 assert abs(w1 - 10) < 0.001 AssertionError: part 4b AttributeError Traceback (most recent call last) Cell In[108], line 5 1 BATCH_SIZE = 2 3 tempds = create_dataset('../toy_data/taxi-train*', batch_size=2) ----> 5 for X_batch, Y_batch in tempds.take(2): 6 pprint({k: v.numpy() for k, v in X_batch.items()}) 7 print(Y_batch.numpy(), "\n") AttributeError: 'tuple' object has no attribute 'take' part 4c --------------------------------------------------------------------------- TypeError Traceback (most recent call last) Cell In[112], line 1 ----> 1 tempds = create_dataset('../toy_data/taxi-train*', 2, 'train') 2 print(list(tempds.take(1))) Cell In[111], line 6, in create_dataset(pattern, batch_size, mode) 2 def create_dataset(pattern, batch_size=1, mode='eval'): 3 dataset = tf.data.experimental.make_csv_dataset( 4 pattern, batch_size, CSV_COLUMNS, DEFAULTS) ----> 6 dataset = tf.data(pattern) # TODO -- Your code here. 8 if mode == 'train': 9 dataset = dataset.shuffle() # TODO -- Your code here. TypeError: 'module' object is not callable

Mika K. · Reviewed over 2 years ago

Walter D. · Reviewed over 2 years ago

Alfredo B. · Reviewed over 2 years ago

Marc N. · Reviewed over 2 years ago

W T. · Reviewed over 2 years ago

Anagha B. · Reviewed over 2 years ago

Sometimes during coding you just do not know what you have to do if you are not familiar with Tensorflow syntax. But still small enough steps to test and try!

Daniel S. · Reviewed over 2 years ago

Good practice, some instructions could've been more clear ( e.g. about desired way of implementing things like filtering feature columns, buffer size for shuffling ). Also it instructed to set "batch_size, column_names and column_defaults" in the first create_dataset which apparently wasn't actually desired ( batch_size shouldn't be set yet, only in the second time, otherwise there'll be an assertion error as it's expecting just scalars in the aserts )

Jasper v. · Reviewed over 2 years ago