SeparableConv1D fail CSynth with Vitis backend

[qberthet]

Prerequisites

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• Test that the bug appears on the current version of the master branch. Make sure to include the commit hash of the commit you checked out.
• Check that the issue hasn't already been reported, by checking the currently open issues.
• If there are steps to reproduce the problem, make sure to write them down below.

Quick summary

Model using SeparableConv1D fail CSynth when using Vitis backend.

Steps to Reproduce

Using Vitis 2022.2:

1. Clone the hls4ml repository
2. Checkout the main branch, with commit hash: d035738
3. Run the following script:

from keras.layers import Input
from keras.models import Model
from qkeras import *
import hls4ml

def get_model():
    # Define a dummy model with only one QSeparableConv1D layer
    input_layer = Input(shape=(32, 3))
    layer = QSeparableConv1D(
                filters=16,
                kernel_size=3,
                depthwise_quantizer=quantized_bits(16, 6, alpha=1),
                pointwise_quantizer=quantized_bits(16, 6, alpha=1),
                bias_quantizer=quantized_bits(16, 6, alpha=1)
            )(input_layer)
    model = Model(inputs=input_layer, outputs=layer)
    return model

model = get_model()

model.summary()

config = hls4ml.utils.config_from_keras_model(model, granularity="name")

# Configure the project to be SeparableConv1D compatible
config['Model']['Precision'] = 'ap_fixed<16,6>'
config['Model']['ReuseFactor'] = 1
config['Model']['Strategy'] = 'Latency'

# Use the Vivado backend (2020.1)
cfg = hls4ml.converters.create_config(backend='Vitis')
cfg['IOType'] = 'io_stream'
cfg['HLSConfig'] = config
cfg['KerasModel'] = model
cfg['OutputDir'] = 'hls4ml_prj'
cfg['Part'] = 'xcku115-flvb2104-2-i'

hls_model = hls4ml.converters.keras_to_hls(cfg)

hls_model.compile()

hls_model.build(reset=True, csim=False, synth=True)

Expected behavior

Successful CSynt.

Actual behavior

CSytnh fail with the following error:
ERROR: [HLS 214-272] In function 'void nnet::depthwise_product<ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>, config2_depthwise>(ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>*, ap_fixed<16, 6, (ap_q_mode)5, (ap_o_mode)3, 0>*, config2_depthwise::weight_t*, config2_depthwise::bias_t*)', Pragma conflict happens on 'INLINE' and 'PIPELINE'FUNCTION_INSTANTIATE' pragmas: same function (firmware/nnet_utils/nnet_sepconv_stream.h:13:0)