TensorFlow Dataset API avis

Vikram M. · Examiné il y a plus de 2 ans

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. · Examiné il y a plus de 2 ans

Olha B. · Examiné il y a plus de 2 ans

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

ep m. · Examiné il y a plus de 2 ans

Alejandro A. · Examiné il y a plus de 2 ans

Adán T. · Examiné il y a plus de 2 ans

Santosh S. · Examiné il y a plus de 2 ans

Rafael G. · Examiné il y a plus de 2 ans

Stepan G. · Examiné il y a plus de 2 ans

Pablo Leonardo L. · Examiné il y a plus de 2 ans

Tomas B. · Examiné il y a plus de 2 ans

Sonali R. · Examiné il y a plus de 2 ans

Николай К. · Examiné il y a plus de 2 ans

Gaurav P. · Examiné il y a plus de 2 ans

Tejas T. · Examiné il y a plus de 2 ans

Siwatchara S. · Examiné il y a plus de 2 ans

Sharad Kumar G. · Examiné il y a plus de 2 ans

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. · Examiné il y a plus de 2 ans

Walter D. · Examiné il y a plus de 2 ans

Alfredo B. · Examiné il y a plus de 2 ans

Marc N. · Examiné il y a plus de 2 ans

W T. · Examiné il y a plus de 2 ans

Anagha B. · Examiné il y a plus de 2 ans

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. · Examiné il y a plus de 2 ans

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. · Examiné il y a plus de 2 ans