量化build之后报reshape的错误 - Toybrick

import numpy as np
import re
import math
import random
import cv2
import time
import os
os.environ["CUDA_VISIBLE_DEVICES"] = ""
from rknn.api import RKNN
INPUT_SIZE_X = 512
INPUT_SIZE_Y = 512
SCALE = 2
CHANLE = 14
if __name__ == '__main__':
# Create RKNN object
rknn = RKNN()
rknn.list_devices()
#rknn.get_sdk_version()
# # Config for Model Input PreProcess
#rknn.config(channel_mean_value='123.68 116.78 103.94 58.82', reorder_channel='2 1 0')
rknn.config(batch_size = 1,channel_mean_value='123.68 116.78 103.94 58.82', epochs = 5000,reorder_channel='2 1 0') #bgr to rgb
# Load TensorFlow Model
print('--> Loading model')#lightweight_openpose_5stage_462007_noelu lightweight_openpose_5stage_820019
import pdb
#pdb.set_trace()
ret = rknn.load_onnx(model='./models/xxx.onnx')
print('load model {}'.format(ret))
# Build Model
print('--> Building model')
start = time.time()
ret = rknn.build(do_quantization=True, dataset='./dataset_coco_val.txt', pre_compile=False)
print('build time {}'.format(time.time() - start))
print('build model {}'.format(ret))
# Export RKNN Model
print('--> Export model')
ret = rknn.export_rknn('../rknn_models/xxx.rknn')
if ret == -1:
print('export failed')
# Load RKNN Model
print('--> loading model')
ret = rknn.load_rknn('../rknn_models/xxx.rknn')
# Set inputs
input_data = np.expand_dims(img, axis=0)#.astype(np.float32)
# init runtime environment
print('--> Init runtime environment')
ret = rknn.init_runtime(async_mode=False, target='rk1808',device_id='xxx')
if ret != 0:
print('Init runtime environment failed')
exit(ret)
sdk_verson = rknn.get_sdk_version()
print(sdk_verson)
# Inference
print('--> Running model')
import pdb
#pdb.set_trace()
outputs = rknn.inference(inputs=[input_data], data_format='nchw', data_type='uint8',inputs_pass_through=[0])
rknn.eval_perf(inputs=[img], is_print=True)
# Release RKNN Context
rknn.release()