ONE - On-device Neural Engine
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part_eval_one.py File Reference

Go to the source code of this file.

Namespaces

namespace  part_eval_one
 

Variables

 part_eval_one.parser = argparse.ArgumentParser()
 
 part_eval_one.type
 
 part_eval_one.str
 
 part_eval_one.required
 
 part_eval_one.args = parser.parse_args()
 
 part_eval_one.driver = args.driver
 
str part_eval_one.tflite_model = args.name + ".tflite"
 
str part_eval_one.circle_model = args.name + ".circle"
 
str part_eval_one.partition_conn_ini = args.name + ".conn.ini"
 
str part_eval_one.partition_conn_json = args.name + ".conn.json"
 
str part_eval_one.expected_count = args.name + ".excnt"
 
 part_eval_one.expected_count_line = expected_count_file.readline()
 
 part_eval_one.json_data = json.load(json_file)
 
 part_eval_one.parts_value = json_data["parts"]
 
 part_eval_one.interpreter = tf.lite.Interpreter(tflite_model)
 
 part_eval_one.full_signatures = interpreter._get_full_signature_list()
 
 part_eval_one.full_signatures_outputs_remap = None
 
 part_eval_one.signature_serving_default = full_signatures.get('serving_default', None)
 
 part_eval_one.signature_outputs = signature_serving_default['outputs']
 
 part_eval_one.num_inputs = len(interpreter.get_input_details())
 
 part_eval_one.input_details = interpreter.get_input_details()[i]
 
 part_eval_one.input_details_dtype = input_details["dtype"]
 
 part_eval_one.input_details_shape = input_details["shape"]
 
 part_eval_one.input_data
 
list part_eval_one.partition_command
 
 part_eval_one.flush
 
 part_eval_one.check
 
 part_eval_one.inpt_output_details = interpreter.get_output_details()
 
 part_eval_one.output_details = inpt_output_details[idx]
 
 part_eval_one.output_dtype = output_details["dtype"]
 
 part_eval_one.output_data = np.fromfile(circle_model + ".output" + str(idx), output_dtype)
 
 part_eval_one.shape_file = open(circle_model + ".output" + str(idx) + ".shape", 'r')
 
list part_eval_one.output_shape = [int(i) for i in shape_file.read().split(',')]
 
 part_eval_one.luci_output_data = np.reshape(output_data, output_shape)
 
 part_eval_one.output_tensor = output_details["index"]
 
 part_eval_one.intp_output_data = interpreter.get_tensor(output_tensor)
 
 part_eval_one.rtol
 
 part_eval_one.atol