ValueError on first run

Hey there,

I was following the README code snippet and ran into a bit of trouble. My code is word-for-word is being run on MNIST.

import tensorflow as tf
from tensorflow.keras.datasets import mnist
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.optimizers import Adam
from kerastuner.tuners import RandomSearch

(xtrain, ytrain), (xtest, ytest) = mnist.load_data()
xtrain = xtrain.reshape([-1, 784, 1]) / 255
xtest = xtest.reshape([-1, 784, 1]) / 255

ytrain = tf.keras.utils.to_categorical(ytrain, 10)
ytest = tf.keras.utils.to_categorical(ytest, 10)

print (xtrain.shape, ytrain.shape)

def build(hp):
	model = tf.keras.models.Sequential()
	model.add(Dense(units=hp.Int('units', min_value=32, max_value=512, step=32), activation="relu"))
	model.add(Dense(10, activation="softmax"))

	model.compile(loss="sparse_categorical_crossentropy", optimizer=Adam(hp.Choice("learning_rate", values=[1e-2, 1e-3, 1e-4])), metrics=["accuracy"])

	return model

tuner = RandomSearch(build, objective='val_accuracy', max_trials=5, executions_per_trial=3, directory="bin", project_name="tuner_test")

tuner.search_space_summary()
tuner.search(xtrain, ytrain, epochs=10, validation_data=(xtest, ytest))
model = tuner.get_best_models(num_models=5)
tuner.results_summary()

I keep getting this error, causing my build to fail.

ValueError: Shape mismatch: The shape of labels (received (32, 10)) should equal the shape of logits except for the last dimension (received (32, 784, 10)).

Any help would be greatly appreciated 😃

Cheers!

[mickeyhs]

just found the issue of mismatch change loss=“sparse_categorical_crossentropy” to loss=“categorical_crossentropy” will work. since the label had called to_categorica()

[rish-16]

I’ll go take a look. Appreciate your help!