Hello David, thank you for your interest,
Here is a very minimal exemple :
step 1 in python :
input1 = tf.keras.layers.Input(shape=(1,1024,4))
x_conv_sep = tf.keras.layers.SeparableConv2D(4,
[1,3],
strides=(1, 1),
padding='same',
data_format="channels_last",
dilation_rate=(1,1),
depth_multiplier=2,
use_bias=False,
input_shape =[1,1024, 4],
depthwise_initializer='he_normal',
pointwise_initializer='truncated_normal',
name = "conv_dilatation",
)(input1)
model.save("conv2d_sep.h5")
step 2 in EIQ:
import model
Convert to tflite with quantization (int8) (see picture)

import tflite model
try to profile...
It seems to be the same as explain in the eIQ Toolkit User Guide 1.5.2 (sec. 4.1) but it doesn't work.
Do you see where is the problem ?
Thanks in advance,
Hadrien