关于“TensorFlow Dataset API”的评价
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Vikram M. · 评论over 2 years之前
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. · 评论over 2 years之前
Olha B. · 评论over 2 years之前
Need more clarity on where to run the commands - on Terminal or just click on the arrow of the instructions window?
ep m. · 评论over 2 years之前
Alejandro A. · 评论over 2 years之前
Adán T. · 评论over 2 years之前
Santosh S. · 评论over 2 years之前
Rafael G. · 评论over 2 years之前
Stepan G. · 评论over 2 years之前
Pablo Leonardo L. · 评论over 2 years之前
Tomas B. · 评论over 2 years之前
Sonali R. · 评论over 2 years之前
Николай К. · 评论over 2 years之前
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Tejas T. · 评论over 2 years之前
Siwatchara S. · 评论over 2 years之前
Sharad Kumar G. · 评论over 2 years之前
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. · 评论over 2 years之前
Walter D. · 评论over 2 years之前
Alfredo B. · 评论over 2 years之前
Marc N. · 评论over 2 years之前
W T. · 评论over 2 years之前
Anagha B. · 评论over 2 years之前
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. · 评论over 2 years之前
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. · 评论over 2 years之前
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