Do you have sample training code and its training loss? Or do you see any errors in my training code?
if __name__ == "__main__":
print("begin ...")
input_test = tf.zeros([2, 224, 224, 3])
num_classes = 1000
if 0:
model, end_points = mobilenet_v3_small(input_test, num_classes, multiplier=1.0, is_training=True, reuse=None)
else:
t_steps = 1000
t_batch = 128
tf.random.set_random_seed(1)
input_rand = tf.random.uniform(shape=(t_batch, 224, 224, 3), minval=0, maxval=1)
x_batch = input_rand
y_batch = tf.random.uniform(shape=(t_batch,), minval=0, maxval=1000, dtype=tf.int32)
logits, end_points = mobilenet_v3_small(x_batch, num_classes, multiplier=1.0, is_training=True, reuse=None)
loss = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(logits=logits, labels=y_batch))
#train_ops = tf.train.AdamOptimizer(learning_rate=0.0001).minimize(loss)
train_ops = tf.train.GradientDescentOptimizer(learning_rate=0.01).minimize(loss)
sess = tf.Session()
sess.run(tf.global_variables_initializer())
for s in range(t_steps):
_, loss_batch = sess.run([train_ops, loss])
print("steps {:05d} loss {:03f}".format(s, loss_batch))
print("done !")
steps 00000 loss 6.914634
steps 00001 loss 6.907555
steps 00002 loss 6.905149
steps 00003 loss 6.905774
steps 00004 loss 6.904990
Hi @frotms , @mttbx, @MenSanYan,
Based on your mobilenet_v3.py, I added training code below but I cannot reduce training loss from 6.9.
Do you have sample training code and its training loss? Or do you see any errors in my training code?
Thanks.
tf_mobilenetv3.zip