def get_backend(backend):
if backend == "tensorflow":
from backend_tf import BackendTensorflow
backend = BackendTensorflow()
elif backend == "onnxruntime":
from backend_onnxruntime import BackendOnnxruntime
backend = BackendOnnxruntime()
elif backend == "null":
from backend_null import BackendNull
backend = BackendNull()
elif backend == "pytorch":
from backend_pytorch import BackendPytorch
backend = BackendPytorch()
elif backend == "pytorch-native":
from backend_pytorch_native import BackendPytorchNative
backend = BackendPytorchNative()
elif backend == "tflite":
from backend_tflite import BackendTflite
backend = BackendTflite()
elif backend == "tflite-calibrate":
from backend_tflite_calibrate import BackendTflite
backend = BackendTflite()
elif backend == "tflite-ncore":
from backend_tflite_ncore import BackendTfliteNcore
backend = BackendTfliteNcore()
elif backend == "tflite-ncore-offline-imagenet":
from backend_tflite_ncore_offline_imagenet import BackendTfliteNcoreOfflineImagenet
backend = BackendTfliteNcoreOfflineImagenet()
elif backend == "tflite-ncore-offline-ssd":
from backend_tflite_ncore_offline_ssd import BackendTfliteNcoreOfflineSSD
backend = BackendTfliteNcoreOfflineSSD()
else:
raise ValueError("unknown backend: " + backend)
return backend
def get_backend(backend):
if backend == "tensorflow":
from backend_tf import BackendTensorflow
backend = BackendTensorflow()
elif backend == "onnxruntime":
from backend_onnxruntime import BackendOnnxruntime
backend = BackendOnnxruntime()
elif backend == "null":
from backend_null import BackendNull
backend = BackendNull()
elif backend == "pytorch":
from backend_pytorch import BackendPytorch
backend = BackendPytorch()
elif backend == "pytorch-native":
from backend_pytorch_native import BackendPytorchNative
backend = BackendPytorchNative()
elif backend == "tflite":
from backend_tflite import BackendTflite
backend = BackendTflite()
elif backend == "tvm":
from backend_tvm import BackendTvm
backend = BackendTvm()
else:
raise ValueError("unknown backend: " + backend)
return backend
def get_backend(backend):
if backend == "tensorflow":
from backend_tf import BackendTensorflow
backend = BackendTensorflow()
elif backend == "onnxruntime":
from backend_onnxruntime import BackendOnnxruntime
backend = BackendOnnxruntime()
elif backend == "null":
from backend_null import BackendNull
backend = BackendNull()
elif backend == "pytorch":
from backend_pytorch import BackendPytorch
backend = BackendPytorch()
elif backend == "pytorch-native":
from backend_pytorch_native import BackendPytorchNative
backend = BackendPytorchNative()
elif backend == "pytorch-centaur":
from backend_pytorch_centaur import BackendPytorchCentaur
backend = BackendPytorchCentaur()
elif backend == "pytorch-native-calibrate":
from backend_pytorch_native_calibrate import BackendPytorchNativeCalibrate
backend = BackendPytorchNativeCalibrate()
elif backend == "tflite":
from backend_tflite import BackendTflite
backend = BackendTflite()
elif backend == "tflite-calibrate":
from backend_tflite_calibrate import BackendTflite
backend = BackendTflite()
elif backend == "tflite-ncore":
from backend_tflite_ncore import BackendTfliteNcore
backend = BackendTfliteNcore()
elif backend == "tflite-ncore-mobilenet":
from backend_libncoretflite import BackendTfliteNcoreMobileNetV1
backend = BackendTfliteNcoreMobileNetV1()
backend.inputs = ["image_tensor:0"]
elif backend == "tflite-ncore-resnet":
from backend_libncoretflite import BackendTfliteNcoreResnet
backend = BackendTfliteNcoreResnet()
backend.inputs = ["image_tensor:0"]
elif backend == "tflite-ncore-ssd":
from backend_libncoretflite import BackendTfliteNcoreSSD
backend = BackendTfliteNcoreSSD()
backend.inputs = ["image_tensor:0"]
elif backend == "tflite-ncore-mobilenet-offline":
from backend_libncoretflite import BackendTfliteNcoreMobileNetV1Offline
backend = BackendTfliteNcoreMobileNetV1Offline()
backend.inputs = ["image_tensor:0"]
elif backend == "tflite-ncore-resnet-offline":
from backend_libncoretflite import BackendTfliteNcoreResnetOffline
backend = BackendTfliteNcoreResnetOffline()
backend.inputs = ["image_tensor:0"]
elif backend == "tflite-ncore-ssd-offline":
from backend_libncoretflite import BackendTfliteNcoreSSDOffline
backend = BackendTfliteNcoreSSDOffline()
backend.inputs = ["image_tensor:0"]
else:
raise ValueError("unknown backend: " + backend)
return backend
def get_backend(backend):
if backend == "tensorflow":
from backend_tf import BackendTensorflow
backend = BackendTensorflow()
elif backend == "null":
from backend_null import BackendNull
backend = BackendNull()
elif backend == "openvino":
from backend_openvino import BackendOpenvino
backend = BackendOpenvino()
else:
raise ValueError("unknown backend: " + backend)
return backend
def get_backend(backend, dataset_path, dataset_calibration_list):
if backend == "tensorflow":
from backend_tf import BackendTensorflow
backend = BackendTensorflow()
elif backend == "onnxruntime":
from backend_onnxruntime import BackendOnnxruntime
backend = BackendOnnxruntime()
elif backend == "null":
from backend_null import BackendNull
backend = BackendNull()
elif backend == "pytorch":
from backend_pytorch import BackendPytorch
backend = BackendPytorch()
elif backend == "pytorch-native":
from backend_pytorch_native import BackendPytorchNative
backend = BackendPytorchNative()
elif backend == "pytorch-jit-traced":
from backend_pytorch_jit_traced import BackendPytorchJITTraced
backend = BackendPytorchJITTraced()
elif backend == "pytorch-fp32":
from backend_pytorch_fp32 import BackendPytorchFP32
backend = BackendPytorchFP32()
elif backend == "pytorch-ssd-jit-traced":
from backend_pytorch_ssd_jit_traced import BackendPytorchSSDJITTraced
backend = BackendPytorchSSDJITTraced()
elif backend == "pytorch-yolov3-jit-traced":
from backend_pytorch_yolov3_jit_traced import BackendPytorchYOLOv3JITTraced
backend = BackendPytorchYOLOv3JITTraced()
elif backend == "pytorch-yolov3-fp32":
from backend_pytorch_yolov3_fp32 import BackendPytorchYOLOv3FP32
backend = BackendPytorchYOLOv3FP32()
elif backend == "tflite":
from backend_tflite import BackendTflite
backend = BackendTflite()
elif backend == "edgecortix":
from backend_edgecortix import BackendEdgecortix
backend = BackendEdgecortix(dataset_path, dataset_calibration_list)
else:
raise ValueError("unknown backend: " + backend)
return backend
def create_backend_instance(backend_type, args):
if backend_type == "tensorflow":
from backend_tf import BackendTensorflow
backend = BackendTensorflow(model_path,
batchsize,
inputs=None,
outputs=None)
backend.load(model_path, inputs=args.inputs, outputs=args.outputs)
elif backend_type == "onnxruntime":
from backend.onnx_backend import BackendOnnxruntime
backend = BackendOnnxruntime(args.batchsize)
elif backend_type == "null":
from backend_null import BackendNull
backend = BackendNull()
elif backend_type == "acl":
from backend.acl_backend import BackendAcl
backend = BackendAcl(args.batchsize)
backend.load(args.model,
inputs=args.inputs,
outputs=args.outputs,
device_id=args.device_id)
else:
raise ValueError("unknown backend: ", backend_type)
return backend