Convert onnx model error

when convert onnx model I got the error as follows:

@fusu1992 Hello, I think maybe your graph have some unsupported layer . The docs in SDK have describe what are the supported layers

I have successfully converted onnx model, and got .data .json files. But when i quantize I got the error:
`(a311d) orbbec@orbbec:~/$ sh 1_quantize_model.sh

I Namespace(action=‘quantization’, batch_size=100, caffe_mean_file=None, capture_format=‘nchw’, capture_quantized=False, channel_mean_value=‘128 128 128 128’, config=None, data_output=None, debug=False, device=None, dtype=‘float32’, epochs=1, epochs_per_decay=100, force_gray=False, fpfs_delta0=1, fpfs_epochs=0, fpfs_reduce_target=0, input_fitting=‘scale’, input_normalization=None, lr=0.1, mean_file=None, model_data=‘model_UnetBased_0624.data’, model_data_format=‘zone’, model_input=‘model_UnetBased_0624.json’, model_quantize=‘model_UnetBased_0624.quantize’, optimizer=‘momentum’, output_dir=None, output_num=5, pb_name=None, pfps_delta0=1, pfps_epochs=0, pfps_reduce_target=0, prune_epochs=10, prune_loss=1, quantized_algorithm=‘normal’, quantized_divergence_nbins=1024, quantized_dtype=‘asymmetric_affine-u8’, quantized_hybrid=False, quantized_moving_alpha=0.0, quantized_rebuild=True, quantized_rebuild_all=False, random_brightness=None, random_contrast=None, random_crop=False, random_flip=False, random_mirror=False, reorder_channel=None, restart=False, samples=-1, source=‘text’, source_file=’./data/model_UnetBased.txt’, task=‘classification’, validation_output=‘validation.csv’, without_update_masked_grad=False)
2020-06-30 13:51:43.921726: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 AVX512F FMA
2020-06-30 13:51:43.957300: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2300000000 Hz
2020-06-30 13:51:43.964918: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x56eb750 executing computations on platform Host. Devices:
2020-06-30 13:51:43.964983: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): Host, Default Version
I Load net in model_UnetBased_0624.json
D Load layer attach_Tanh_341/out0_0 …
D Load layer attach_Conv_342/out0_1 …
D Load layer Conv_342_2 …
D Load layer Tanh_341_3 …
D Load layer Relu_339_4 …
D Load layer Conv_340_5 …
D Load layer Relu_334_7 …
D Load layer Conv_337_8 …
D Load layer Upsample_336_10 …
D Load layer Conv_332_11 …
D Load layer Relu_329_12 …
D Load layer Upsample_331_13 …
D Load layer Relu_323_15 …
D Load layer Conv_327_16 …
D Load layer Concat_326_18 …
D Load layer Conv_321_19 …
D Load layer Upsample_325_20 …
D Load layer Relu_225_21 …
D Load layer Upsample_320_22 …
D Load layer Relu_318_23 …
D Load layer Conv_223_25 …
D Load layer Conv_316_27 …
D Load layer Relu_315_28 …
D Load layer Conv_313_30 …
D Load layer Concat_312_31 …
D Load layer Upsample_311_32 …
D Load layer Relu_298_33 …
D Load layer Relu_309_34 …
D Load layer Add_297_35 …
D Load layer Add_308_36 …
D Load layer Conv_291_41 …
D Load layer Conv_295_42 …
D Load layer Conv_302_43 …
D Load layer Conv_306_44 …
D Load layer Relu_290_45 …
D Load layer AveragePool_294_46 …
D Load layer Relu_301_47 …
D Load layer AveragePool_305_48 …
D Load layer Concat_287_50 …
D Load layer Conv_299_52 …
D Load layer Conv_288_53 …
D Load layer Relu_249_54 …
D Load layer Relu_282_55 …
D Load layer Relu_286_56 …
D Load layer Conv_284_58 …
D Load layer Add_248_59 …
D Load layer Concat_283_61 …
D Load layer Relu_242_63 …
D Load layer Conv_280_64 …
D Load layer Concat_279_65 …
D Load layer Relu_278_66 …
D Load layer Conv_246_67 …
D Load layer Add_241_68 …
D Load layer Relu_267_70 …
D Load layer Add_277_71 …
D Load layer Relu_245_72 …
D Load layer Conv_239_74 …
D Load layer Add_266_75 …
D Load layer Conv_235_79 …
D Load layer AveragePool_238_80 …
D Load layer Relu_260_82 …
D Load layer Conv_271_83 …
D Load layer Conv_275_84 …
D Load layer Conv_243_85 …
D Load layer Relu_234_86 …
D Load layer Conv_264_88 …
D Load layer Add_259_89 …
D Load layer Relu_270_90 …
D Load layer AveragePool_274_91 …
D Load layer Relu_231_92 …
D Load layer Conv_232_93 …
D Load layer Relu_263_94 …
D Load layer Conv_229_99 …
D Load layer Conv_253_101 …
D Load layer Conv_257_102 …
D Load layer Conv_268_103 …
D Load layer AveragePool_256_104 …
D Load layer Conv_261_105 …
D Load layer Relu_252_106 …
D Load layer Relu_228_107 …
D Load layer Conv_226_110 …
D Load layer Conv_250_111 …
D Load layer 2_112 …
D Load layer 1_113 …
D Load layer 0_114 …
I Load model_UnetBased_0624.json complete.
I Load data in model_UnetBased_0624.data
W:tensorflow:From acuitylib/app/tensorzone/workspace.py:24: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.
Instructions for updating:
tf.py_func is deprecated in TF V2. Instead, there are two
options available in V2.
- tf.py_function takes a python function which manipulates tf eager
tensors instead of numpy arrays. It’s easy to convert a tf eager tensor to
an ndarray (just call tensor.numpy()) but having access to eager tensors
means tf.py_functions can use accelerators such as GPUs as well as
being differentiable using a gradient tape.
- tf.numpy_function maintains the semantics of the deprecated tf.py_func
(it is not differentiable, and manipulates numpy arrays). It drops the
stateful argument making all functions stateful.

I Fitting image with scale.
I Channel mean value [128.0, 128.0, 128.0, 128.0]
I [TRAINER]Quantization start…
[TRAINER]Quantization start…
I Init validate tensor provider.
I Enqueue samples 1
I Init provider with 1 samples.
D set up a quantize net
D Process 0_114 …
D Acuity output shape(input): (1 288 288 3)
E Input layer “0_114” tensor is not set.
I ----------------Warning(0)----------------
Traceback (most recent call last):
File “tensorzonex.py”, line 446, in
File “tensorzonex.py”, line 383, in main
File “acuitylib/app/tensorzone/quantization.py”, line 156, in run
File “acuitylib/app/tensorzone/quantization.py”, line 103, in _run_quantization
File “acuitylib/app/tensorzone/workspace.py”, line 172, in _setup_graph
File “acuitylib/app/tensorzone/graph.py”, line 59, in generate
File “acuitylib/acuitynetbuilder.py”, line 282, in build
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 312, in build_layer
File “acuitylib/acuitynetbuilder.py”, line 344, in build_layer
File “acuitylib/layer/input.py”, line 38, in compute_tensor
File “acuitylib/acuitylog.py”, line 251, in e
ValueError: Input layer “0_114” tensor is not set.
[47779] Failed to execute script tensorzonex`