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Dense object is not iterable

WebOct 19, 2024 · It may be a late answer, but I got the same problem and below is the solution # Don't use categorical_features= [10] in encoder init from sklearn.preprocessing import OneHotEncoder onehotencoder=OneHotEncoder () Y= onehotencoder.fit_transform (X [:, [10]]).toarray () Share Improve this answer Follow answered Feb 13, 2024 at 7:40 vikas … WebJul 3, 2024 · I'm using linear model on MNIST dataset searching for optimal regularization parameters. >>> Imports: #coding=utf-8 try: import keras except: pass try: from keras …

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WebAttributeError: 'Dense' object has no attribute 'kernel' Any idea what's wrong? Related Topics . Machine learning Computer science Information & communications technology … WebJul 2, 2024 · 1 Answer Sorted by: 2 I had this same problem this week. It seems that the tf.keras Additive attention does not return the attention weights, only the context vector. Therefore you just need to eliminate "attention_weights" when calling AdditiveAttention () and you should be good. Share Improve this answer Follow answered Jul 12, 2024 at 7:20 fastest pitches mlb the show 22 https://ods-sports.com

WebMay 30, 2024 · You're adding a type to your list, not an instance of the type. What you're doing is essentially the same as this: class Experience: pass buffer = [] buffer.append(Experience) WebAug 27, 2024 · You are mixing the usage/imports of the keras and tf.keras packages, these packages are not compatible with each other, you must make all relevant imports from one package only. Share Improve this answer Follow answered Aug 27, 2024 at 21:30 Dr. Snoopy 54.7k 7 120 140 Add a comment Your Answer Post Your Answer WebOct 31, 2024 · If your input data is univariate (e.g. 1D sequence), then num_channels=1 - thus: model.add (LSTM (128, activation='relu', input_shape= (1000, 1), return_sequences=True)) Lastly, for 'binary_crossentropy', a better output layer would be Dense (1, activation='sigmoid'). For more info, see this answer. fastest pitchers in baseball

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Dense object is not iterable

issue with oneHotEncoding - Data Science Stack Exchange

Web2 Answers. Sorted by: 5. There are several problems with your code: indentation. if you are on python 2, you should have defined next () method instead of __next__ () (leave it as is if on python 3) ++self.i should be replaced with self.i += 1. self.l [i … WebApr 25, 2024 · There is a simple fix if, like me, you get frustrated by this. Simply use Category Encoders' OneHotEncoder. This is a Sklearn Contrib package, so plays super nicely with the scikit-learn API. This works as a direct replacement and does the boring label encoding for you.

Dense object is not iterable

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WebNov 22, 2024 · TypeError: 'Var' object is not iterable in line: m.addConstrs (quicksum (x [k, i, j]) + demand [k, i] == quicksum (x [k, j, i])for k in product for i, j in link) What is my mistake?Wrong in my dictionary? I try to build a dictionary to store the "link" imformation,and the optimal solution is obtained by the constraint conditions. WebYour while-statement is missing a : at the end. It is considered very dangerous to use input like that, since it evaluates its input as real Python code. It would be better here to use raw_input and then convert the input to an integer with int. To split up the digits and then add them like you want, I would first make the number a string.

WebNo you have to use either keras or tf.keras. Mixing them with cause trouble. Tf.keras has its own issues. WebAug 19, 2024 · inputs = model.inputs[:2] dense = model.get_layer('NSP-Dense').output outputs = keras.layers.Dense(units=2, activation='softmax')(dense) model = …

WebMar 23, 2024 · Iterable are objects which generate an iterator. For instance, standard python iterable are list, tuple, string, and dictionaries. All these data types are iterable. In other words, they can be iterated over using a for-loop. For instance, check this example. Outputs of different iterables Trending Tracing the Untraceable with Python Tracer WebJul 9, 2024 · 1 Answer. Sorted by: 1. input_shape should be a tuple, but input_dim is an integer. You have passed input_dim, and since you have not specified it by name, it considers it as input_shape. So, just specify it by name: tf.keras.layers.Input (input_dim=input_dim) Or if you want to specify the shape, use it like: …

WebJun 7, 2024 · Let the RNN cell generate its own initial state. You would usually only do 1. if you wanted to override default behavior. In this case you are using the default (zero) initial state so you can do 2. lstm_outputs, final_state = tf.nn.dynamic_rnn (cell=lstm, inputs=lstm_inputs, dtype=tf.float32) Share. Improve this answer.

WebAug 7, 2024 · The accepted answer is great. However, in case anyone is trying to access history without storing it during fit, try the following: Since val_loss is not an attribute on the History object and not a key that you can index with, the way you wrote it won't work. fastest pitcher in mlb everWebTry this and you will get the same error: v1, v2 = np.float64 (1.3) # numpy.float64 object, cannot be unpacked because it is not an iterable. result [0] is a numpy float, just as np.float64. I'm not sure what results holds, but removing the [0] index might fix your problem, if the data you want is in the array result. Share. Improve this answer. frenchbourneWebJul 23, 2024 · File "", line 8, in TypeError: 'int' object is not iterable. It works when I convert list object to string but not working in int. python; iterable; python-zip; Share. Follow edited Jul 23, 2024 at 18:21. ThePyGuy. 17.5k 5 5 gold badges 18 18 silver badges 44 44 bronze badges. asked Apr 10, 2024 at 6:38. french boutique clothing