Method setUp

tests/test_quantize_model.py:113–151

(self)

class TestPostTrainingQuantization(unittest.TestCase):
    def setUp(self):
        self.int8_download = "int8/download"
        self.cache_folder = os.path.expanduser(
            "~/.cache/paddle/dataset/" + self.int8_download
        )
        self.data_cache_folder = ""
        data_urls = []
        data_md5s = []
        if os.environ.get("DATASET") == "full":
            data_urls.append(
                "https://paddle-inference-dist.bj.bcebos.com/int8/ILSVRC2012_img_val.tar.gz.partaa"
            )
            data_md5s.append("60f6525b0e1d127f345641d75d41f0a8")
            data_urls.append(
                "https://paddle-inference-dist.bj.bcebos.com/int8/ILSVRC2012_img_val.tar.gz.partab"
            )
            data_md5s.append("1e9f15f64e015e58d6f9ec3210ed18b5")
            self.data_cache_folder = self.download_data(
                data_urls, data_md5s, "full_data", False
            )
        else:
            data_urls.append(
                "http://paddle-inference-dist.bj.bcebos.com/int8/calibration_test_data.tar.gz"
            )
            data_md5s.append("1b6c1c434172cca1bf9ba1e4d7a3157d")
            self.data_cache_folder = self.download_data(
                data_urls, data_md5s, "small_data", False
            )

        # reader/decorator.py requires the relative path to the data folder
        if not os.path.exists("./data/ILSVRC2012"):
            cmd = "rm -rf {0} && ln -s {1} {0}".format("data", self.data_cache_folder)
            os.system(cmd)

        self.batch_size = 1 if os.environ.get("DATASET") == "full" else 50
        self.sample_iterations = 50 if os.environ.get("DATASET") == "full" else 2
        self.infer_iterations = 50000 if os.environ.get("DATASET") == "full" else 2

        self.int8_model = "./post_training_quantize_model/"

    def tearDown(self):
        pass