Webb21 maj 2024 · TensorFlow - ValueError: Shapes (None, 1) and (None, 10) are incompatible. I am trying to implement an image classifier using "The Street View House Numbers … Webb9 maj 2024 · I got this error ValueError: Shapes (None, 1) and (None, 3) are incompatible when training my Sequential model. I could not figure out which shapes are actually incompatible. This is the first time I do image classification. Here are my codes:
CSV MNIST data set: ValueError: Shapes (None, 10) and (None, 28, 10 …
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 … 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... how to say goat in russian
tensorflow - Keras/TF error: Incompatible shapes - Stack Overflow
Webb30 jan. 2024 · Incompatible shapes (None, 1) and (None, 5) with Keras VGGFace Finetuning. 0. Tensorflow - I don't get the right shapes - `ValueError: Shapes (100, 10, 10) and (100, 10) are incompatible` 0. Keras loss object and shapes. Hot Network Questions Approximation of pseudogeometric progression Webb27 feb. 2024 · 1. If you want your y to be between 0 and 1 then you can use sigmoid activation function. You can also keep it blank and try to run and see the results. Also, I just choose batch_size 8, you can use whatever you want. If the example worked for you, you can accept the answer so that other could benifit from it as well. Webb23 mars 2024 · 1 Answer. For the model you are building, the dimensions of your training data needs to be constant - it cannot vary from one training example to the other. When you create a model with Sequential (), the input shape of your model will be defined when you do the training for the first time by calling model.fit or model.train_on_batch. For ... north greenville university faculty