# Utility functions for performing image inference
#
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import os
import sys
import time

import tensorrt as trt
import tensorflow as tf
from PIL import Image
import pycuda.driver as cuda
import pycuda.autoinit
import numpy as np

import utils.engine as engine_utils # TRT Engine creation/save/load utils
import utils.model as model_utils # UFF conversion uttils

# ../../common.py
sys.path.insert(1,
    os.path.join(
        os.path.dirname(os.path.realpath(__file__)),
        os.pardir,
        os.pardir
    )
)
import common


# TensorRT logger singleton
TRT_LOGGER = trt.Logger(trt.Logger.WARNING)


class TRTInference(object):
    """Manages TensorRT objects for model inference."""
    def __init__(self, trt_engine_path, uff_model_path, trt_engine_datatype=trt.DataType.FLOAT, batch_size=1):
        """Initializes TensorRT objects needed for model inference.

        Args:
            trt_engine_path (str): path where TensorRT engine should be stored
            uff_model_path (str): path of .uff model
            trt_engine_datatype (trt.DataType):
                requested precision of TensorRT engine used for inference
            batch_size (int): batch size for which engine
                should be optimized for
        """