The speed of our model with submission ID 833911 is 0.06s, however, it is a very big model ran on my own device with 6~7s.
Yes, the results look really strange, we will contact Samsung regarding this issue.
The speed of our model with submission ID 833911 is 0.06s, however, it is a very big model ran on my own device with 6~7s.
Could update the run time results of these two days, please ? thx a lot.The results were updated today.
Yes.
Any tips or suggestions would be helpful..
experimental_new_converter
option?Thank you very much for the fast reply.1. Are you using TF-nightly?
2. Have you enabled theexperimental_new_converter
option?
def Generator():
inputs = tf.keras.layers.Input(shape=[256, 256, 3])
down_stack = [
downsample(64, 4, apply_batchnorm=False), # (bs, 128, 128, 64)
downsample(128, 4), # (bs, 64, 64, 128)
downsample(256, 4), # (bs, 32, 32, 256)
downsample(512, 4), # (bs, 16, 16, 512)
downsample(512, 4), # (bs, 8, 8, 512)
downsample(512, 4), # (bs, 4, 4, 512)
downsample(512, 4), # (bs, 2, 2, 512)
downsample(512, 4), # (bs, 1, 1, 512)
]
up_stack = [
upsample(512, 4, apply_dropout=True), # (bs, 2, 2, 1024)
upsample(512, 4, apply_dropout=True), # (bs, 4, 4, 1024)
upsample(512, 4, apply_dropout=True), # (bs, 8, 8, 1024)
upsample(512, 4), # (bs, 16, 16, 1024)
upsample(256, 4), # (bs, 32, 32, 512)
upsample(128, 4), # (bs, 64, 64, 256)
upsample(64, 4), # (bs, 128, 128, 128)
]
initializer = tf.random_normal_initializer(0., 0.02)
last = tf.keras.layers.Conv2DTranspose(OUTPUT_CHANNELS, 4,
strides=2,
padding='same',
kernel_initializer=initializer,
activation='tanh') # (bs, 256, 256, 3)
x = inputs
# Downsampling through the model
skips = []
for down in down_stack:
x = down(x)
skips.append(x)
skips = reversed(skips[:-1])
# Upsampling and establishing the skip connections
for up, skip in zip(up_stack, skips):
x = up(x)
x = tf.keras.layers.Concatenate()([x, skip])
x = last(x)
return tf.keras.Model(inputs=inputs, outputs=x)
I am struggling with this issue...
Thank you for the quick reply!Just checked - your model converts without any issues when using TF-nightly and the provided instructions. Make sure you read them carefully.
Hello,could update the run time results of these two days, please ?
Okay got it! Thanks a lot@Msss, all submitted final models are running fine on our Samsung S21 dev phone, we are now waiting for the results from Samsung. In case they are unable to run some models - our runtime values will be used then.