TensorFlow Dataset API Reviews

Vikram M. · Reviewed أكثر من سنتين 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 أكثر من سنتين ago

Olha B. · Reviewed أكثر من سنتين 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 أكثر من سنتين ago

Alejandro A. · Reviewed أكثر من سنتين ago

Adán T. · Reviewed أكثر من سنتين ago

Santosh S. · Reviewed أكثر من سنتين ago

Rafael G. · Reviewed أكثر من سنتين ago

Stepan G. · Reviewed أكثر من سنتين ago

Pablo Leonardo L. · Reviewed أكثر من سنتين ago

Tomas B. · Reviewed أكثر من سنتين ago

Sonali R. · Reviewed أكثر من سنتين ago

Николай К. · Reviewed أكثر من سنتين ago

Gaurav P. · Reviewed أكثر من سنتين ago

Tejas T. · Reviewed أكثر من سنتين ago

Siwatchara S. · Reviewed أكثر من سنتين ago

Sharad Kumar G. · Reviewed أكثر من سنتين 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 أكثر من سنتين ago

Walter D. · Reviewed أكثر من سنتين ago

Alfredo B. · Reviewed أكثر من سنتين ago

Marc N. · Reviewed أكثر من سنتين ago

W T. · Reviewed أكثر من سنتين ago

Anagha B. · Reviewed أكثر من سنتين 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 أكثر من سنتين 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 أكثر من سنتين ago