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about Internal Error (downsample_ratio: network input that is shape tensor must have type Int32)

Open zhanghongyong123456 opened this issue 3 years ago • 5 comments

Description

I have an model and my inputs have a downsample ratio that must be Float32. when i onnx2trt , I have onnx parsing falid,What should I do

Environment

TensorRT Version: 8.4.3.1 NVIDIA GPU: cuda 11.1 NVIDIA Driver Version: 512.15 CUDA Version:
CUDNN Version: Operating System: windows Python Version (if applicable): 3.9 Tensorflow Version (if applicable):
PyTorch Version (if applicable): 1.9 cu111 Baremetal or Container (if so, version):

this is log: Succeeded converting model into onnx! [09/03/2022-13:53:25] [TRT] [I] [MemUsageChange] Init CUDA: CPU +323, GPU +0, now: CPU 7241, GPU 1139 (MiB) [09/03/2022-13:53:26] [TRT] [I] [MemUsageChange] Init builder kernel library: CPU +192, GPU +68, now: CPU 7537, GPU 1207 (MiB) Succeeded finding onnx file! [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::GridAnchor_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::GridAnchorRect_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::NMS_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::Reorg_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::Region_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::Clip_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::LReLU_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::PriorBox_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::Normalize_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::ScatterND version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::RPROI_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::BatchedNMS_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::BatchedNMSDynamic_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::BatchTilePlugin_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::FlattenConcat_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::CropAndResize version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::CropAndResizeDynamic version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::DetectionLayer_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::EfficientNMS_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::EfficientNMS_ONNX_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::EfficientNMS_Explicit_TF_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::EfficientNMS_Implicit_TF_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::ProposalDynamic version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::Proposal version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::ProposalLayer_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::PyramidROIAlign_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::ResizeNearest_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::Split version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::SpecialSlice_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::InstanceNormalization_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::InstanceNormalization_TRT version 2 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::CoordConvAC version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::DecodeBbox3DPlugin version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::GenerateDetection_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::MultilevelCropAndResize_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::MultilevelProposeROI_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::NMSDynamic_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::PillarScatterPlugin version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::VoxelGeneratorPlugin version 1 [09/03/2022-13:53:26] [TRT] [V] Registered plugin creator - ::MultiscaleDeformableAttnPlugin_TRT version 1 [09/03/2022-13:53:26] [TRT] [V] Adding network input: src with dtype: float32, dimensions: (-1, 3, -1, -1) [09/03/2022-13:53:26] [TRT] [V] Registering tensor: src for ONNX tensor: src [09/03/2022-13:53:26] [TRT] [V] Adding network input: r1i with dtype: float32, dimensions: (-1, -1, -1, -1) [09/03/2022-13:53:26] [TRT] [V] Registering tensor: r1i for ONNX tensor: r1i [09/03/2022-13:53:26] [TRT] [V] Adding network input: r2i with dtype: float32, dimensions: (-1, -1, -1, -1) [09/03/2022-13:53:26] [TRT] [V] Registering tensor: r2i for ONNX tensor: r2i [09/03/2022-13:53:26] [TRT] [V] Adding network input: r3i with dtype: float32, dimensions: (-1, -1, -1, -1) [09/03/2022-13:53:26] [TRT] [V] Registering tensor: r3i for ONNX tensor: r3i [09/03/2022-13:53:26] [TRT] [V] Adding network input: r4i with dtype: float32, dimensions: (-1, -1, -1, -1) [09/03/2022-13:53:26] [TRT] [V] Registering tensor: r4i for ONNX tensor: r4i [09/03/2022-13:53:26] [TRT] [V] Adding network input: downsample_ratio with dtype: float32, dimensions: (1) [09/03/2022-13:53:26] [TRT] [V] Registering tensor: downsample_ratio for ONNX tensor: downsample_ratio [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.4.block.2.fc1.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.4.block.2.fc1.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.4.block.2.fc2.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.4.block.2.fc2.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.5.block.2.fc1.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.5.block.2.fc1.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.5.block.2.fc2.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.5.block.2.fc2.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.6.block.2.fc1.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.6.block.2.fc1.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.6.block.2.fc2.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.6.block.2.fc2.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.11.block.2.fc1.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.11.block.2.fc1.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.11.block.2.fc2.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.11.block.2.fc2.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.12.block.2.fc1.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.12.block.2.fc1.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.12.block.2.fc2.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.12.block.2.fc2.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.13.block.2.fc1.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.13.block.2.fc1.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.13.block.2.fc2.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.13.block.2.fc2.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.14.block.2.fc1.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.14.block.2.fc1.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.14.block.2.fc2.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.14.block.2.fc2.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.15.block.2.fc1.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.15.block.2.fc1.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.15.block.2.fc2.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: backbone.features.15.block.2.fc2.bias [09/03/2022-13:53:26] [TRT] [V] Importing initializer: aspp.aspp2.1.weight [09/03/2022-13:53:26] [TRT] [V] Importing initializer: decoder.decode4.gru.ih.0.weight [09/03/2022-13:53:26] [TRT] [V] Importing 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950 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 952 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 953 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 955 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 956 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 958 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 959 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 961 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 962 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 964 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 965 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 967 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 968 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 970 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 971 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 973 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 974 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 976 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 977 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 978 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 979 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 980 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 981 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 982 [09/03/2022-13:53:26] [TRT] [V] Importing initializer: 983 [09/03/2022-13:53:26] [TRT] [V] Parsing node: Constant_0 [Constant] [09/03/2022-13:53:26] [TRT] [V] Constant_0 [Constant] inputs: [09/03/2022-13:53:26] [TRT] [V] Constant_0 [Constant] outputs: [388 -> (0)[FLOAT]], [09/03/2022-13:53:26] [TRT] [V] Parsing node: Constant_1 [Constant] [09/03/2022-13:53:26] [TRT] [V] Constant_1 [Constant] inputs: [09/03/2022-13:53:26] [TRT] [V] Constant_1 [Constant] outputs: [389 -> (2)[FLOAT]], [09/03/2022-13:53:26] [TRT] [V] Parsing node: Concat_2 [Concat] [09/03/2022-13:53:26] [TRT] [V] Searching for input: 389 [09/03/2022-13:53:26] [TRT] [V] Searching for input: downsample_ratio [09/03/2022-13:53:26] [TRT] [V] Searching for input: downsample_ratio [09/03/2022-13:53:26] [TRT] [V] Concat_2 [Concat] inputs: [389 -> (2)[FLOAT]], [downsample_ratio -> (1)[FLOAT]], [downsample_ratio -> (1)[FLOAT]], [09/03/2022-13:53:26] [TRT] [V] Registering layer: 389 for ONNX node: 389 [09/03/2022-13:53:26] [TRT] [V] Registering layer: Concat_2 for ONNX node: Concat_2 [09/03/2022-13:53:26] [TRT] [V] Registering tensor: 390 for ONNX tensor: 390 [09/03/2022-13:53:26] [TRT] [V] Concat_2 [Concat] outputs: [390 -> (4)[FLOAT]], [09/03/2022-13:53:26] [TRT] [V] Parsing node: Resize_3 [Resize] [09/03/2022-13:53:26] [TRT] [V] Searching for input: src [09/03/2022-13:53:26] [TRT] [V] Searching for input: 388 [09/03/2022-13:53:26] [TRT] [V] Searching for input: 390 [09/03/2022-13:53:26] [TRT] [V] Resize_3 [Resize] inputs: [src -> (-1, 3, -1, -1)[FLOAT]], [388 -> (0)[FLOAT]], [390 -> (4)[FLOAT]], [09/03/2022-13:53:26] [TRT] [V] Registering layer: Resize_3 for ONNX node: Resize_3 [09/03/2022-13:53:26] [TRT] [V] Running resize layer with: Transformation mode: pytorch_half_pixel Resize mode: linear

[09/03/2022-13:53:26] [TRT] [E] [graphShapeAnalyzer.cpp::nvinfer1::builder::anonymous-namespace'::ShapeNodeRemover::analyzeShapes::1237] Error Code 4: Internal Error (downsample_ratio: network input that is shape tensor must have type Int32) Failed parsing .onnx file! In node 3 (parseGraph): INVALID_NODE: Invalid Node - Resize_3 [graphShapeAnalyzer.cpp::nvinfer1::builder::anonymous-namespace'::ShapeNodeRemover::analyzeShapes::1237] Error Code 4: Internal Error (downsample_ratio: network input that is shape tensor must have type Int32)

Process finished with exit code 0

zhanghongyong123456 avatar Sep 07 '22 01:09 zhanghongyong123456

We don't support float shape tensor now but I know there is some development on it, @ttyio do we have a target release for this feature?

zerollzeng avatar Sep 07 '22 15:09 zerollzeng

We don't support float shape tensor now but I know there is some development on it, @ttyio do we have a target release for this feature?

We will have this feature in 8.5 release, thanks!

ttyio avatar Sep 08 '22 01:09 ttyio

We don't support float shape tensor now but I know there is some development on it, @ttyio do we have a target release for this feature?

We will have this feature in 8.5 release, thanks! 《1》How can I deal with my error 《2》Can I know when version 8.5 will be released， Thank you very much

zhanghongyong123456 avatar Sep 08 '22 01:09 zhanghongyong123456

@zhanghongyong123456 , before 8.5, maybe try constant folding using polygraphy:

    polygraphy surgeon sanitize model.onnx --fold-constants --output model_folded.onnx

If this cannot be folded, we have to wait 8.5, the schedule is in this month, or early next month. thanks!

ttyio avatar Sep 08 '22 02:09 ttyio

@zhanghongyong123456 , before 8.5, maybe try constant folding using polygraphy:

    polygraphy surgeon sanitize model.onnx --fold-constants --output model_folded.onnx

If this cannot be folded, we have to wait 8.5, the schedule is in this month, or early next month. thanks!

OK， thanks i will try it

zhanghongyong123456 avatar Sep 08 '22 05:09 zhanghongyong123456

8.5 release I would like to know when the 8.5 version is scheduled to be released. I am looking forward to it being available( about float shape )

zhanghongyong123456 avatar Oct 28 '22 02:10 zhanghongyong123456

@zhanghongyong123456 , it's around this week, thanks!

ttyio avatar Oct 31 '22 01:10 ttyio

@zhanghongyong123456 , it's around this week, thanks!

OK，[Thank you very much](It's can support float shape)

zhanghongyong123456 avatar Oct 31 '22 02:10 zhanghongyong123456

:anonymous-namespace'::ShapeNodeRemover::analyzeShapes::1237] Error Code 4: Internal Error (downsample_ratio: network input that is s

May I ask whether float data is supported? I tested TensorRT 8.5.2.2 and this problem still occurs. I am not sure whether there is a problem with my conversion or the new TensorRT still does not support float input

image

zhanghongyong123456 avatar Dec 24 '22 10:12 zhanghongyong123456

Hello @zhanghongyong123456 , we added float shape tensor support in 8.5 except:

  • plugin
  • network I/O

We need extra API changes to support these two. We have no bandwidth to do this yet. And your error message show that you are using shape tensor in the network, this is not supported.

ttyio avatar Dec 27 '22 01:12 ttyio

Hello @zhanghongyong123456 , we added float shape tensor support in 8.5 except:

  • plugin
  • network I/O

We need extra API changes to support these two. We have no bandwidth to do this yet. And your error message show that you are using shape tensor in the network, this is not supported.

Yes, my float input affects the network structure，https://github.com/PeterL1n/RobustVideoMatting，I am doing acceleration based on TensorRT and can implement acceleration with specified resolution (static model), I want to implement dynamic model what should I do, can you give me some advice, thank you

zhanghongyong123456 avatar Dec 27 '22 01:12 zhanghongyong123456

@zhanghongyong123456 could you use int32 shape tensor?

ttyio avatar Dec 27 '22 02:12 ttyio

@zhanghongyong123456 could you use int32 shape tensor?

I'm not sure what I should do, maybe converting onnx has to be FP32 or something else https://github.com/PeterL1n/RobustVideoMatting/blob/master/documentation/inference.md#onnx image

zhanghongyong123456 avatar Dec 27 '22 03:12 zhanghongyong123456

@zhanghongyong123456 could you use int32 shape tensor?

I'm not sure what I should do, maybe converting onnx has to be FP32 or something else https://github.com/PeterL1n/RobustVideoMatting/blob/master/documentation/inference.md#onnx image

https://github.com/PeterL1n/RobustVideoMatting/blob/onnx/model/model.py#L47 image

zhanghongyong123456 avatar Dec 27 '22 03:12 zhanghongyong123456

Closing inactive issues, thank all!

ttyio avatar Nov 23 '23 00:11 ttyio