pintrend导出onnx模型精度问题

[aiwenzhu]

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训练好的pointrend模型使用官方的额export_onnx.py导出onnx发现在np.testing.assert_allclose(onnx_out, paddle_out, rtol=0, atol=1e-03)报错，代码如下，也使用了paddle2onnx来导出模型实测发现精度不一致

def export_onnx(args):
args.config = '/workspace/PaddleSeg/configs/pointrend/pointrend_resnet50_os8_voc12aug_512x512_40k.yml'
args.model_path = '/workspace/PaddleSeg/output/best_model118/model.pdparams'
args.width = 800
args.height = 640
assert args.config is not None,
'Please set --config path/to/yml'
cfg = Config(args.config)
builder = SegBuilder(cfg)
model = builder.model
if args.model_path is not None:
utils.load_entire_model(model, args.model_path)
logger.info('Loaded trained params of model successfully')

model.eval()
if args.print_model:
    print(model)

input_shape = [1, 3, args.height, args.width]
print("input shape:", input_shape)
input_data = np.random.random(input_shape).astype('float32')
model_name = os.path.basename(args.config).split(".")[0]

paddle_out = run_paddle(model, input_data)
print("out shape:", paddle_out.shape)
print("The paddle model has been predicted by PaddlePaddle.\n")

input_spec = paddle.static.InputSpec(input_shape, 'float32', 'x')
onnx_model_path = os.path.join(args.save_dir, model_name + "_model")
paddle.onnx.export(
    model, onnx_model_path, input_spec=[input_spec], opset_version=11)
print("Completed export onnx model.\n")

onnx_model_path = onnx_model_path + ".onnx"
onnx_out = check_and_run_onnx(onnx_model_path, input_data)
assert onnx_out.shape == paddle_out.shape
np.testing.assert_allclose(onnx_out, paddle_out, rtol=0, atol=1e-03)
print("The paddle and onnx models have the same outputs.\n")

[liuhongen1234567]

您好，可以提供一下paddle的版本和GPU环境吗？