TensorFlow Dataset API Reviews

Vikram M. · Reviewed больше 2 лет 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 больше 2 лет ago

Olha B. · Reviewed больше 2 лет 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 больше 2 лет ago

Alejandro A. · Reviewed больше 2 лет ago

Adán T. · Reviewed больше 2 лет ago

Santosh S. · Reviewed больше 2 лет ago

Rafael G. · Reviewed больше 2 лет ago

Stepan G. · Reviewed больше 2 лет ago

Pablo Leonardo L. · Reviewed больше 2 лет ago

Tomas B. · Reviewed больше 2 лет ago

Sonali R. · Reviewed больше 2 лет ago

Николай К. · Reviewed больше 2 лет ago

Gaurav P. · Reviewed больше 2 лет ago

Tejas T. · Reviewed больше 2 лет ago

Siwatchara S. · Reviewed больше 2 лет ago

Sharad Kumar G. · Reviewed больше 2 лет 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 больше 2 лет ago

Walter D. · Reviewed больше 2 лет ago

Alfredo B. · Reviewed больше 2 лет ago

Marc N. · Reviewed больше 2 лет ago

W T. · Reviewed больше 2 лет ago

Anagha B. · Reviewed больше 2 лет 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 больше 2 лет 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 больше 2 лет ago