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import torch
from brevitas.nn import QuantLinear, QuantReLU
import torch.nn as nn
import numpy as np
from brevitas.core.quant import QuantType
from brevitas.nn import QuantIdentity
import brevitas.onnx as bo
from finn.core.modelwrapper import ModelWrapper
from finn.core.datatype import DataType
import finn.builder.build_dataflow as build
import finn.builder.build_dataflow_config as build_cfg
import os
import shutil
from finn.util.test import get_build_env, load_test_checkpoint_or_skip
import pytest
from finn.util.basic import make_build_dir
import pkg_resources as pk
import json
import wget
import subprocess

target_clk_ns = 10
build_kind = "zynq"
build_dir = os.environ["FINN_BUILD_DIR"]
onnx_zip_url = "https://github.com/Xilinx/finn-examples/releases/download/v0.0.1a/onnx-models-bnn-pynq.zip"
onnx_zip_local = build_dir + "/onnx-models-bnn-pynq.zip"

def get_checkpoint_name(step):
    if step == "build":
        # checkpoint for build step is an entire dir
        return build_dir + "/end2end_ext_weights_build"
    else:
        # other checkpoints are onnx files
        return build_dir + "/end2end_ext_weights_%s.onnx" % (step)


def test_end2end_ext_weights_download():
    if not os.path.isfile(onnx_zip_local):
        wget.download(onnx_zip_url, out=onnx_zip_local)
    assert os.path.isfile(onnx_zip_local)
    subprocess.check_output(['unzip', onnx_zip_local])