TensorFlow Dataset API Reviews

Vikram M. · Reviewed 2 yıldan fazla 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 2 yıldan fazla ago

Olha B. · Reviewed 2 yıldan fazla 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 2 yıldan fazla ago

Alejandro A. · Reviewed 2 yıldan fazla ago

Adán T. · Reviewed 2 yıldan fazla ago

Santosh S. · Reviewed 2 yıldan fazla ago

Rafael G. · Reviewed 2 yıldan fazla ago

Stepan G. · Reviewed 2 yıldan fazla ago

Pablo Leonardo L. · Reviewed 2 yıldan fazla ago

Tomas B. · Reviewed 2 yıldan fazla ago

Sonali R. · Reviewed 2 yıldan fazla ago

Николай К. · Reviewed 2 yıldan fazla ago

Gaurav P. · Reviewed 2 yıldan fazla ago

Tejas T. · Reviewed 2 yıldan fazla ago

Siwatchara S. · Reviewed 2 yıldan fazla ago

Sharad Kumar G. · Reviewed 2 yıldan fazla 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 2 yıldan fazla ago

Walter D. · Reviewed 2 yıldan fazla ago

Alfredo B. · Reviewed 2 yıldan fazla ago

Marc N. · Reviewed 2 yıldan fazla ago

W T. · Reviewed 2 yıldan fazla ago

Anagha B. · Reviewed 2 yıldan fazla 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 2 yıldan fazla 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 2 yıldan fazla ago