Webb18 juni 2024 · I'm trying to execute a small code for NN using the MNIST dataset for characters recognition. When it comes to the fit line I get ValueError: Shapes (None, 1) and (None, 10) are incompatible im... Webb16 juli 2024 · CSV MNIST data set: ValueError: Shapes (None, 10) and (None, 28, 10) are incompatible Ask Question Asked 1 year, 8 months ago Modified 1 year, 8 months ago Viewed 437 times -1 I want to classify the MINST data set (csv) with keras. This is my code but after running it I got this error.
Tensorflow ValueError Shapes are incompatible - Stack …
Webb18 apr. 2024 · Tensorflow VGG19 Error: ValueError: Shapes (None, 128, 128, 10) and (None, 10) are incompatible Ask Question Asked 1 year, 11 months ago Modified 1 year, 11 months ago Viewed 304 times 0 I'm trying to use VGG-19 model as a semantic segmentation model i.e. pixel-wise classification. I have the following dataset ready: Webb17 apr. 2024 · I am training a Tensorflow model with LSTMs for predictive maintenance. For each instance I create a matrix (50,4) where 50 is the length of the hisotry sequence, and 4 is the number of features for each records, so for training the model I use e.g. (55048, 50, 4) tensor and a (55048, 1) as labels. the peter nutting charitable trust
tensorflow - Keras/TF error: Incompatible shapes - Stack Overflow
Webb11 mars 2024 · import numpy as np import tensorflow as tf from keras.models import Sequential from keras.layers import Dense, Dropout, LSTM, Flatten from keras.preprocessing.text import Tokenizer train_data = ['o by no means honest ventidius i gave it freely ever and theres none can truly say he gives if our betters play at that game … WebbI have a 3 dimensional dataset of audio files where X.shape is (329,20,85). I want to have a simpl bare-bones model running, so please don't nitpick and address only the issue at hand. Here is ... Shapes (2, 1) and are incompatible. Related. 3259. What does ** (double star/asterisk) and * (star/asterisk) do for parameters? 7175. What are ... Webb30 juni 2024 · Since you are using categorical_crossentropy and there are 4 units for your output layer, your model expects labels in one hot encoded form and as a vector of length 4. However, your labels are vectors of length 2. Therefore, if your labels are integers, you can do. Y_train = tf.one_hot (Y_train, 4) and the resulting shape will be (5000, 4). the peter oliver house