MNIST implementation in stm32h743 issue 1. this is my python script to build weight for MNIST.
import tensorflow
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers, models
import numpy as np
(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()
x_train = x_train / 255
x_test = x_test / 255
x_train = x_train[..., tf.newaxis]
x_test = x_test[..., tf.newaxis]
model = models.Sequential([
layers.Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=(28, 28, 1)),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Conv2D(64, kernel_size=(3, 3), activation='relu'),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Flatten(),
layers.Dense(128, activation='relu'),
layers.Dropout(0.25),
layers.Dense(10, activation='softmax')
])
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
model.fit(x_train, y_train, epochs=50, batch_size=64, validation_split=0.1)
model.save("mni
