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Edge TPU `tf.lite.experimental.load_delegate` fix (#6536) 

* Edge TPU `tf.lite.experimental.load_delegate` fix

Fix attempt for #6535

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pull/6504/head^2
Glenn Jocher 2022-02-04 09:30:01 +01:00 committed by GitHub
parent 9bc72a3ac2
commit 079b36d72b
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1 changed files with 6 additions and 5 deletions
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11
models/common.py
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@ -374,19 +374,20 @@ class DetectMultiBackend(nn.Module):
graph_def.ParseFromString(open(w, 'rb').read()) graph_def.ParseFromString(open(w, 'rb').read())
frozen_func = wrap_frozen_graph(gd=graph_def, inputs="x:0", outputs="Identity:0") frozen_func = wrap_frozen_graph(gd=graph_def, inputs="x:0", outputs="Identity:0")
elif tflite: # https://www.tensorflow.org/lite/guide/python#install_tensorflow_lite_for_python elif tflite: # https://www.tensorflow.org/lite/guide/python#install_tensorflow_lite_for_python
try: try: # prefer tflite_runtime if installed
import tflite_runtime.interpreter as tfl # prefer tflite_runtime if installed from tflite_runtime.interpreter import Interpreter, load_delegate
except ImportError: except ImportError:
import tensorflow.lite as tfl import tensorflow.lite.experimental.load_delegate as load_delegate
import tensorflow.lite.Interpreter as Interpreter
if 'edgetpu' in w.lower(): # Edge TPU https://coral.ai/software/#edgetpu-runtime if 'edgetpu' in w.lower(): # Edge TPU https://coral.ai/software/#edgetpu-runtime
LOGGER.info(f'Loading {w} for TensorFlow Lite Edge TPU inference...') LOGGER.info(f'Loading {w} for TensorFlow Lite Edge TPU inference...')
delegate = {'Linux': 'libedgetpu.so.1', delegate = {'Linux': 'libedgetpu.so.1',
'Darwin': 'libedgetpu.1.dylib', 'Darwin': 'libedgetpu.1.dylib',
'Windows': 'edgetpu.dll'}[platform.system()] 'Windows': 'edgetpu.dll'}[platform.system()]
interpreter = tfl.Interpreter(model_path=w, experimental_delegates=[tfl.load_delegate(delegate)]) interpreter = Interpreter(model_path=w, experimental_delegates=[load_delegate(delegate)])
else: # Lite else: # Lite
LOGGER.info(f'Loading {w} for TensorFlow Lite inference...') LOGGER.info(f'Loading {w} for TensorFlow Lite inference...')
interpreter = tfl.Interpreter(model_path=w) # load TFLite model interpreter = Interpreter(model_path=w) # load TFLite model
interpreter.allocate_tensors() # allocate interpreter.allocate_tensors() # allocate
input_details = interpreter.get_input_details() # inputs input_details = interpreter.get_input_details() # inputs
output_details = interpreter.get_output_details() # outputs output_details = interpreter.get_output_details() # outputs