TFLite got Operator not supported

hi, I tried to apply deeplabv3+.
I built on Deeplab and I got frozen.pb frozen_inference_graph.pb.zip
input shape [1,257,257,3]
output shape [1,257,257,21]
When I converted, I got deeplab_257_quantized.tflite.zip

tflite_convert
--output_file=deeplab_${DIMENSION}_quantized.tflite
--graph_def_file=$PB_FILE
--output_format=TFLITE
--input_arrays=ImageTensor
--output_arrays=SemanticPredictions
--input_shapes=1,${DIMENSION},${DIMENSION},3
--inference_input_type=QUANTIZED_UINT8
--inference_type=FLOAT
--mean_values=128
--std_dev_values=127
--default_ranges_min=0 --default_ranges_max=255
--target_ops=TFLITE_BUILTINS,SELECT_TF_OPS

input shape [1,257,257,3]
output shape [257,257]
Finally, I ran on android (Samsung Note8, supported OpenCL + NEON) with below code

armnnTfLiteParser::ITfLiteParserPtr parser = armnnTfLiteParser::ITfLiteParser::Create();
armnn::INetworkPtr network = parser->CreateNetworkFromBinaryFile("test.tflite");

// Find the binding points for the input and output nodes
armnnTfLiteParser::BindingPointInfo inputBindingInfo = parser->GetNetworkInputBindingInfo(0, "ImageTensor");
armnnTfLiteParser::BindingPointInfo outputBindingInfo = parser->GetNetworkOutputBindingInfo(0, "SemanticPredictions");

armnn::IRuntime::CreationOptions options; // default options
armnn::IRuntimePtr runtime = armnn::IRuntime::Create(options);

armnn::IOptimizedNetworkPtr optNet = Optimize(*network, {device}, runtime->GetDeviceSpec());

armnn::NetworkId networkIdentifier;
runtime->LoadNetwork(networkIdentifier, std::move(optNet));

auto input = new float[1*257*257*3];
auto output = new float[257*257];

armnn::InputTensors inputTensor = MakeInputTensors(inputBindingInfo, &input[0]);
armnn::OutputTensors outputTensor = MakeOutputTensors(outputBindingInfo, &output[0]);

runtime->EnqueueWorkload(networkIdentifier, inputTensor, outputTensor);

and I got below error. I understood supported ops. Is that problem?

terminating with uncaught exception of type armnn::ParseException: Failed to parse operator #0 within subgraph #0 error: Operator not supported. subgraph:0 operator:0 opcode_index:7 opcode:53 / CAST  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #1 within subgraph #0 error: inputs.size() = 2 is not valid, not in {1}.  at function ParseReshape [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:1068]
Failed to parse operator #2 within subgraph #0 error: Operator not supported. subgraph:0 operator:2 opcode_index:6 opcode:41 / SUB  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #3 within subgraph #0 error: Operator not supported. subgraph:0 operator:3 opcode_index:11 opcode:34 / PAD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #4 within subgraph #0 error: Operator not supported. subgraph:0 operator:4 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #5 within subgraph #0 error: Operator not supported. subgraph:0 operator:5 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #6 within subgraph #0 error: Operator not supported. subgraph:0 operator:6 opcode_index:6 opcode:41 / SUB  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #7 within subgraph #0 error: inputs.size() = 2 is not valid, not in {1}.  at function ParseReshape [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:1068]
Failed to parse operator #17 within subgraph #0 error: Operator not supported. subgraph:0 operator:17 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #24 within subgraph #0 error: Operator not supported. subgraph:0 operator:24 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #28 within subgraph #0 error: Operator not supported. subgraph:0 operator:28 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #33 within subgraph #0 error: Operator not supported. subgraph:0 operator:33 opcode_index:9 opcode:38 / SPACE_TO_BATCH_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #35 within subgraph #0 error: Operator not supported. subgraph:0 operator:35 opcode_index:10 opcode:37 / BATCH_TO_SPACE_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #36 within subgraph #0 error: Operator not supported. subgraph:0 operator:36 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #37 within subgraph #0 error: Operator not supported. subgraph:0 operator:37 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #39 within subgraph #0 error: Operator not supported. subgraph:0 operator:39 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #41 within subgraph #0 error: Operator not supported. subgraph:0 operator:41 opcode_index:9 opcode:38 / SPACE_TO_BATCH_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #43 within subgraph #0 error: Operator not supported. subgraph:0 operator:43 opcode_index:10 opcode:37 / BATCH_TO_SPACE_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #44 within subgraph #0 error: Operator not supported. subgraph:0 operator:44 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #45 within subgraph #0 error: Operator not supported. subgraph:0 operator:45 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #47 within subgraph #0 error: Operator not supported. subgraph:0 operator:47 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #49 within subgraph #0 error: Operator not supported. subgraph:0 operator:49 opcode_index:9 opcode:38 / SPACE_TO_BATCH_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #51 within subgraph #0 error: Operator not supported. subgraph:0 operator:51 opcode_index:10 opcode:37 / BATCH_TO_SPACE_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #52 within subgraph #0 error: Operator not supported. subgraph:0 operator:52 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #53 within subgraph #0 error: Operator not supported. subgraph:0 operator:53 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #55 within subgraph #0 error: Operator not supported. subgraph:0 operator:55 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #57 within subgraph #0 error: Operator not supported. subgraph:0 operator:57 opcode_index:9 opcode:38 / SPACE_TO_BATCH_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #59 within subgraph #0 error: Operator not supported. subgraph:0 operator:59 opcode_index:10 opcode:37 / BATCH_TO_SPACE_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #60 within subgraph #0 error: Operator not supported. subgraph:0 operator:60 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #61 within subgraph #0 error: Operator not supported. subgraph:0 operator:61 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #64 within subgraph #0 error: Operator not supported. subgraph:0 operator:64 opcode_index:9 opcode:38 / SPACE_TO_BATCH_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #66 within subgraph #0 error: Operator not supported. subgraph:0 operator:66 opcode_index:10 opcode:37 / BATCH_TO_SPACE_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #67 within subgraph #0 error: Operator not supported. subgraph:0 operator:67 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #68 within subgraph #0 error: Operator not supported. subgraph:0 operator:68 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #70 within subgraph #0 error: Operator not supported. subgraph:0 operator:70 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #72 within subgraph #0 error: Operator not supported. subgraph:0 operator:72 opcode_index:9 opcode:38 / SPACE_TO_BATCH_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #74 within subgraph #0 error: Operator not supported. subgraph:0 operator:74 opcode_index:10 opcode:37 / BATCH_TO_SPACE_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #75 within subgraph #0 error: Operator not supported. subgraph:0 operator:75 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #76 within subgraph #0 error: Operator not supported. subgraph:0 operator:76 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #78 within subgraph #0 error: Operator not supported. subgraph:0 operator:78 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #80 within subgraph #0 error: Operator not supported. subgraph:0 operator:80 opcode_index:9 opcode:38 / SPACE_TO_BATCH_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #82 within subgraph #0 error: Operator not supported. subgraph:0 operator:82 opcode_index:10 opcode:37 / BATCH_TO_SPACE_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #83 within subgraph #0 error: Operator not supported. subgraph:0 operator:83 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #84 within subgraph #0 error: Operator not supported. subgraph:0 operator:84 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #87 within subgraph #0 error: Operator not supported. subgraph:0 operator:87 opcode_index:9 opcode:38 / SPACE_TO_BATCH_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #89 within subgraph #0 error: Operator not supported. subgraph:0 operator:89 opcode_index:10 opcode:37 / BATCH_TO_SPACE_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #90 within subgraph #0 error: Operator not supported. subgraph:0 operator:90 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #91 within subgraph #0 error: Operator not supported. subgraph:0 operator:91 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #93 within subgraph #0 error: Operator not supported. subgraph:0 operator:93 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #95 within subgraph #0 error: Operator not supported. subgraph:0 operator:95 opcode_index:9 opcode:38 / SPACE_TO_BATCH_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #97 within subgraph #0 error: Operator not supported. subgraph:0 operator:97 opcode_index:10 opcode:37 / BATCH_TO_SPACE_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #98 within subgraph #0 error: Operator not supported. subgraph:0 operator:98 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #99 within subgraph #0 error: Operator not supported. subgraph:0 operator:99 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #101 within subgraph #0 error: Operator not supported. subgraph:0 operator:101 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #103 within subgraph #0 error: Operator not supported. subgraph:0 operator:103 opcode_index:9 opcode:38 / SPACE_TO_BATCH_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #105 within subgraph #0 error: Operator not supported. subgraph:0 operator:105 opcode_index:10 opcode:37 / BATCH_TO_SPACE_ND  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #106 within subgraph #0 error: Operator not supported. subgraph:0 operator:106 opcode_index:5 opcode:18 / MUL  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #107 within subgraph #0 error: Operator not supported. subgraph:0 operator:107 opcode_index:0 opcode:0 / ADD  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #111 within subgraph #0 error: Operator not supported. subgraph:0 operator:111 opcode_index:8 opcode:23 / RESIZE_BILINEAR  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #116 within subgraph #0 error: Operator not supported. subgraph:0 operator:116 opcode_index:8 opcode:23 / RESIZE_BILINEAR  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #117 within subgraph #0 error: Operator not supported. subgraph:0 operator:117 opcode_index:8 opcode:23 / RESIZE_BILINEAR  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #118 within subgraph #0 error: Operator not supported. subgraph:0 operator:118 opcode_index:12 opcode:56 / ARG_MAX  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #119 within subgraph #0 error: Operator not supported. subgraph:0 operator:119 opcode_index:7 opcode:53 / CAST  at function ParseUnsupportedOperator [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:624]
Failed to parse operator #120 within subgraph #0 error: inputs.size() = 2 is not valid, not in {1}.  at function ParseReshape [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:1068]

Hi @ilous12 this is really good work, thank you. I think this is the first time someone has tried to run deeplabv3+ via TfLite on ArmNN, and actually the missing functionalilty is not that bad:
MUL, ADD, RESIZE_BILINEAR, BATCH_TO_SPACE_ND, SPACE_TO_BATCH_ND and SUB are all supported by ArmNN, and just need adding to the TfLite parser.  @brunomorishita actually added some of these recently, and his code is available in the development branch at https://review.mlplatform.org/#/admin/projects/ml/armnn

ARG_MAX recently got added to Compute Library but hasn't been integrated into ArmNN yet.
CAST is a bit harder, it depends what is actually happening in the model. We don't have this functionality in ArmNN yet, and it might not be present in Compute Library either.
Then we have the ParseReshape issue - I think this is a limitation just of the TfLite parser, as ArmNN can now handle all kinds of reshapes.
So some of this is "easy" to fix in ArmNN, some is harder.
deeplab v3 is a network that we are trying to support, but I can't confirm a timeline for it.  Are you in a position to help add support?
Many thanks,
Matthew

@MatthewARM
I understood a current status.
Unfortunately, I am deep learning new but If you want, try on

Hi @ilous12 if you are willing to help, a really good first step would be to get the latest master Arm NN and Compute Library and try your test again, that will give us a good picture of the remaining work.
The links to the master branches can be found on our new developer website here: https://mlplatform.org/contributing/

ok. I will try tomorrow.

Hi @MatteoArm I got a result. see below.

./TFLite 1
Optimisation mode: CpuAcc
terminating with uncaught exception of type armnn::ParseException: Buffer #89 has 0 bytes. For tensor: [1,33,33,256] expecting: 1115136 bytes and 278784 elements.  at function CreateConstTensor [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:1808]
Aborted

134|alphaplus:/data/local/tmp $ ./TFLite 2
Optimisation mode: GpuAcc
terminating with uncaught exception of type armnn::ParseException: Buffer #89 has 0 bytes. For tensor: [1,33,33,256] expecting: 1115136 bytes and 278784 elements.  at function CreateConstTensor [/Users/ilous12/armnn-devenv/armnn/src/armnnTfLiteParser/TfLiteParser.cpp:1808]
Aborted

my tflite file was  below
test.tflite.zip
input/output

input node is sub_7 and output node is ResizeBilinear_3

my code
TFLite.cpp.zip
what's #89. Is there verbose mode?

Hi, @MatthewARM
did you have any update related tensorflowlite lite?

Thanks @ilous12 we'll try those steps and see.  Buffer #89 will be one of the intermediate values in the network, and for some reason our Tensorflow Lite parser can't handle it. We'll take a look,

Hi @ilous12 ,
Recently I push some commits adding support for some of the operations in deeplab v3 model for tflite.
It should work now with this model: deeplabv3_257_mv_gpu
It is available at:
Please let me know if this works for you.

thanks @brunomorishita
How can I get your patches? can you guide?

thanks @brunomorishita
How can I get your patches? can you guide?

git fetch https://review.mlplatform.org/ml/armnn refs/changes/04/704/1 && git checkout FETCH_HEAD

I downloaded your patches
can you share your example for deeplab?
I want to compare your code and my test code.

Thanks. guys. you did.
finally it work. I will implement sample on android.

Hi. guys.
I tried to run deeplab. you see below.
Thanks @brunomorishita I tried next steps and I saw invalid semantic label
it work on tensorflow lite  with deeplabv3_257_mv_gpu.tflite

I uploaded my code.
Can you check this one? I thought code got problem.
test.zip

Hi @ilous12 where you have "    engineConfig_->device_ = armnn::Compute::GpuAcc;" it's probably worth a quick try with CpuRef to see if the output from our reference (non-accelerated) implementation is different. That will help track down the problem.

Unfortunately It didn't work. did you check my code have no problem?
CpuRef : Invalid
CpuAcc : Invalid
GpuAcc : Invalid

I thought my code looks fine, But I want to check that most likely something is going wrong with handling the input buffer or output.
src.zip

At armnnwrapper.cc_:143 you have "memcpy(engineConfig_->input_, input, 125725721);" which seems strange? Shouldn't that be 12572573*sizeof(float) to match the definition of  ArmnnEngineConfig::input_ at line 49?

You were right. I fixed. I try again.

We tried test but not enough.
We will test armnn and tensorflow lite then compare the results.
I expected same result. is it right?
<rgb input file: read, 12572573> -  - < 125725721, rgb output array>

I @ilous12 might not be exactly the same, if ArmNN does rounding differently to TfLite, but should be very close.

Hi @ilous12 I can't see anything else obviously wrong with the code so I don't know why you would get the wrong result.
The only thing I can suggest is that in the latest master branch (at https://review.mlplatform.org/#/admin/projects/ml/armnn) we have added a 'debug' flag to OptimizerOptions. Setting this flag will make ArmNN print the contents of all tensors to standard output, so that you can compare with similar debug output from Tensorflow Lite and figure out where it is going wrong inside the network.
Actually, if you haven't tried already, you should try with the latest master code anyway, just in case this is a bug that we've fixed without realising it.
Good luck,
Matthew

@ilous12 this is a floating-point model, isn't it? Not quantised?
I'm just trying to figure out what could be going wrong.

@MatthewARM I am @ilous12's coworker. Our source was patched at several places.
Also,  we updated the latest master branch(git clone "https://review.mlplatform.org/ml/armnn") by your recommendation.
As noted above, we use the "deeplabv3_257_mv_gpu". We know that model is a floating-point model.
After that, we achieved better results. But, we didn't satisfy that result(below picture).
If we can use tensorflow-lite's sample(https://github.com/dailystudio/ml/tree/master/deeplab) using by that model, we can achieve the perfect segmentation.
However, we want to get both speed and accuracy using armnn. We need your help!

Hi @oms1226 we should be getting something very close to Tensorflow Lite's answer - just small differences sometimes due to different arithmetic implementations.
As you are seeing something very different, it looks like there is perhaps a bug. If you can figure out which layer in the network is producing the wrong output, that would be very helpful.
Many thanks,
Matthew

Thank @MatthewARM.
I want to compare with similar debug output from Tensorflow Lite and figure out where it is going wrong inside the network.
So, m_Debug's default value changed false to true in .../include/armnn/INetwork.hpp as like below.
OptimizerOptions()
: m_ReduceFp32ToFp16(false)
, m_Debug(true)
{}
How can I figure out debug's log and so on?

Hi @oms1226 when you run with m_Debug set to true, it will print all tensor values on standard output, so you can capture them in a file for debugging.
By the way, changing the default value is overkill - it would be more usual to set it in your application with something like:
armnn::OptimizerOptions options;
options.m_Debug = true;
engineConfig_->optNet_ = Optimize(*(engineConfig_->network_), {engineConfig_->device_}, engineConfig_->runtime_->GetDeviceSpec(), options);

I feel so sorry for @MatthewARM .
I can't find out all tensor values on standard output.
I think standard output is adb log on android device.
As your advice, I let m_Debug true as below.
I wonder what's wrong?
And let me know print example for all tensor value. I am turning to you for help.
    engineConfig_->inputBindingInfo_ = engineConfig_->parser_->GetNetworkInputBindingInfo(0, "sub_7");     engineConfig_->outputBindingInfo_ = engineConfig_->parser_->GetNetworkOutputBindingInfo(0, "ResizeBilinear_3");     armnn::IRuntime::CreationOptions options; // default options     engineConfig_->options_ = options;     engineConfig_->runtime_ = armnn::IRuntime::Create(engineConfig_->options_);     engineConfig_->device_ = armnn::Compute::GpuAcc;     armnn::OptimizerOptions op_options;     op_options.m_Debug = true;     engineConfig_->optNet_ = Optimize(*(engineConfig_->network_), {engineConfig_->device_}, engineConfig_->runtime_->GetDeviceSpec(), op_options);

Hi, I uploaded network output file.  Can you figure out which layer in the network is producing the wrong output?
https://drive.google.com/open?id=1wJ4RGXJWllWXPj2vyawVDojApB9E3jKF

Hi, @MatthewARM  @brunomorishita
Please let us know the progress of the work.

Hi @MatthewARM
If you need help about this issue, contact us

Hello @ilous12 ,
I am a colleague of @MatthewARM  and have picked up a ticket which looks related to this issue. Have you now had success with perfect segmentation running the model on Armnn?

@ilous12 if the debug flag isn't working on Android, can you at least print the numbers coming out of your network and compare them to TfLite? At the moment I can't figure out if what we're seeing is a bug in ArmNN or some sort of numerical precision issue.

By the way, the debug flag eventually causes the code to get called in src/backends/reference/workloads/Debug.cpp which uses std::cout. If std::cout isn;t working, maybe you could hack in something that works. I'm sorry I don't really know much about what debug / printing features are available from an Android application.

Unfortunately, currently tensorflow-lite only supports to print output for input node and output node, We are looking for a way. If let us know all network output on tensorflow-lite.

@MatthewARM
If we write an armnn app and tensorflow app with console output for deeplab, can you check it?

Hi. @MatthewARM @kevmay01
We checked armnn and TfLite then compare the results. You will download the link below.
https://drive.google.com/open?id=1VXsSHYulFutt6uKorgWaQfX_lS43SgrV

I did not understand why the network numbers of armnn and TfLite were different
The output of most networks look different
Input node "sub_7" was rounding differently to TfLite, but It were very close.
TFlite had a MobilenetV2/expanded/conv/N/project/BatchNorm/FusedBatchNorm.

You will see the model's all network below.

Hello @ilous12
The problem appears to be that the offical Tensorflow Lite model deeplabv3_257_mv_gpu.tflite includes convolution layers with dilation values of 2 and 4 which Arm NN does not support. The current Arm NN master falls back to using a dilation value of 1 and this would appear to be the cause of the drop in accuracy that you are seeing.
However if you train and convert a model that only uses dilation values of 1 you should see the same results between Arm NN and Tensorflow Lite. I converted your frozen_inference_graph.pb which you attached here to a tflite file and was able to get the same results running on Arm NN and Tf Lite.

Thanks for reply. I understood your comment. I will try to train. after I will check and I share you.

Hi @kevmay01
What did you change for the dilation values to 1? Did you use tflite_convert? Can you share me?

I converted the file you attached to this ticket: frozen_inference_graph.pb
I removed the preprocessing layers and some of the last layers.
This creates a file which I think is not what you are ultimately looking for but I was able to use it to prove the output from TfLite and Armnn were the same.
tflite_convert
--graph_def_file=/home/kevmay01/Downloads/frozen_inference_graph.pb
--output_file=/home/kevmay01/test_new.tflite
--input_shapes=1,129,129,3
--input_arrays=sub_7
--output_arrays=ResizeBilinear_2
--inference_type=FLOAT
--inference_input_type=FLOAT
--std_dev_values=128
--mean_value=128
You will need to train a new model I think and figure out how to convert and optimize it to make a similar model to the official deeplabv3_257_mv_gpu.tflite file, but only using default dilation values.

@ilous12 I think the information you need regarding creating a model with dilation set to 1 is in this ticket: https://github.com/tensorflow/tensorflow/issues/26474
There is also an example attached to that ticket of an identical deeplabv3_257_mv_gpu.tflite, but with dilation values set to 1.

Hi @kevmay01 . Do you have a shchdule to work convolution layers with dilation values of 2 and 4? Or not?

Hi @MatthewARM @kevmay01
I created a model with dilation value to 1(by output_stride=32) and I saw my shape. nice work.
trained_deeplab_model.zip
But I got some problems. You will see below.
Tensorflow Lite Result

Armnn Result

Composite image (tflite + armnn)

I think the shape of the result is a little different, can you check?

Thanks @ilous12 I see what you mean about the output being different. I'll try to get someone to look at whether this indicates a bug but I'm not sure whether that will be this week or later.
Have you tried with the Arm NN CpuRef backend? That doesn't use Compute Library so it eliminates one possible source of errors.

Hi @MatthewARM I got a result and I will se belows
CpuRef

Gpu

We have a crash issue to run cpuAcc on Release 19.02.

Hi @MatthewARM
We measured elapsed times and I noticed delayed API. You will see belows.
parser_  = armnnTfLiteParser::ITfLiteParser::Create();  0ms
parser_->CreateNetworkFromBinaryFile(); 73ms
parser_->GetNetworkInputBindingInfo(); 0ms
optNet_ = Optimize(); 28ms
**runtime_->LoadNetwork(); 2270ms**

Can you check this problem?

Hi @MatthewARM
When I use "optimizerOptions.m_Debug = true" on 19.02,  I got a crash.
armnn/src/armnn/LoadedNetwork.cpp:192: const armnn::IWorkloadFactory &armnn::LoadedNetwork::GetWorkloadFactory(const armnn::Layer &) const: assertion "(IWorkloadFactory::IsLayerSupported(layer, {}, reasonIfUnsupported))&&("Factory does not support layer")" failed
Aborted (core dumped)
Thanks.

Hi @MatthewARM
we found wrong result using op "ResizeBilinear_2" in armnn for upscale

input
node
output
status

1x9x9x320
AvgPool2D
1x1x1x320
same

1x1x1x320
ResizeBilinear
1x9x9x256
same

1x9x9x21
ResizeBilinear_1
1x9x9x21
same

1x9x9x21
ResizeBilinear_2
1x257x257x21
wrong

Can you check "Up Scale" function by resizeBilinear op?
We attached output files.
resizeBilinear.zip

Hi @ilous12 sorry for the long delay in replying. The only question I know how to answer is this one:

We measured elapsed times and I noticed delayed API. You will see belows.
parser_  = armnnTfLiteParser::ITfLiteParser::Create();  0ms
parser_->CreateNetworkFromBinaryFile(); 73ms
parser_->GetNetworkInputBindingInfo(); 0ms
optNet_ = Optimize(); 28ms
runtime_->LoadNetwork(); 2270ms <------ so slow

Can you check this problem?

I expect that the 2.3  seconds here is spent compiling OpenCL kernels for the GpuAcc backend.  We're looking into various ways to cache those kernels so that it doesn't have to be done every time you run your program, but it's a hard problem.
I'm sorry but I don't yet have an answer for your other problems.

Hi @ilous12 the support for dilation in DepthwiseConvolution has been merged to master so hopefully your original model will now work!
On the 'upscale' issue, do you happen to know which resize method is in use? Should be one of:
BILINEAR = 0
NEAREST_NEIGHBOR = 1
BICUBIC = 2
AREA = 3
Many thanks,
Matthew

Many thanks to @brunomorishita for contributing the dilation support

Hi @ilous12 we have just fixed the crash with NEScale in this patch https://review.mlplatform.org/#/c/ml/ComputeLibrary/+/1141/ which is now on the master branch.

thanks guys. We will check soon.


ensure methods annotated with @MapperFactory defined the same dependencies

When multiple methods/constructors are annotated with @MapperFactory on a dedicated class, they must define the same set of parameters which qualifies as mapper dependencies.
The following dedicated classes are invalid because one method/constructor define a dependency and the other does not.
@Mapper
public class InconsistentMapperDependenciesOnStaticMethod {
  @MapperFactory
  publi f static InconsistentMapperDependenciesOnStaticMethod create(@MapperDependency Boolean top) {
    return null; // content does not matter
  }

  @MapperFactory
  public static InconsistentMapperDependenciesOnStaticMethod create() {
    return null; // content does not matter
  }

  public String map(Integer input) {
    return null;
  }
}

The
@Mapper
public class InconsistentMapperDependenciesOnConstructor {
  @MapperFactory
  public InconsistentMapperDependenciesOnConstructor() {
    // content does not matter
  }

  @MapperFactory
  public InconsistentMapperDependenciesOnConstructor(String someParam, @MapperDependency Boolean top, @MapperDependency String label) {
    // content does not matter
  }

  public String map(Integer input) {
    return null;
  }
}

Classes with methods both defining a dependency but which would not have the same type and name would also raise a compilation error.
On the contrary, the order of the parameter does not matter.

done


Interacting with Dashboard Elements

Is there currently any code within EasyRepro for interacting with the various columns in Dynamics? I believe this issue may have been defined in #388 , but I am unable to interact with elements on the dashboard, such as open activities.This is a very commonly used function of Dynamics that our end-user for our business uses, so we would like to include this in our automated test suite.
Thanks!

Hi @sammcquistan - To date, we do not have any specifics for interacting with elements within a dashboard.
If you could, could you provide a list of scenarios that you'd like to try and cover with dashboards via automation? Once I have this, I'll review with the team to see how we could try to implement this. The elements (grids, charts, etc) on the dashboard are rather generic compared to other areas of the system, which has proved difficult to provide an easy to use and reliable experience with EasyRepro.
Look forward to seeing your scenarios and how we can augment our roadmap with them.
Warm Regards,
Tyler

Hi @TYLEROL ,
Our use cases are fairly simple. Most of the elements we use that are interact-able are lists. These lists (grids as far as the code is concerned) contain what we call "Deals", where we staff a temp employee with a client. We have various stages of the deal and our career counselors are able to track the progress of where their temp is in the placement process. These grid rows are double clicked and open up to the "Deal" and it's detailed information. Here is an example:

Another example is our users adding a new activity. Often, temps contact our employees without much notice and need to log the activity quickly. It's easiest for them to open up the CRM and add the new activity from the dashboard. Here is an example:

There are a few more that I have, but these may be some fairly niche cases. If anything, I think that adding the activity would mostly have overlap with ActivityFeed, so I am more focused on working on a solution for opening records from the grid.
Thanks!
Sam

Thanks @sammcquistan . I've added some of these scenarios to our backlog of feature enhancements and will update if/when we're able to add these in the future.


Rich data enrichment v2

The goal here is to not only provide the minimum required fields to make a catalog dataset discoverable by google dataset search (this is already possible) but to now also include any optional fields to enrich the structured data for the dataset when  viewing it in a dataset search result.
The changes necessary to allow this include:

basic functions to map all optional fields from existing properties in a metadata entry
an update to the catalog-level config file to include fields for catalog_name and catalog_url that are used for mapping to the optional includedInDataCatalog rich data field

Any existing or new catalog that wants to make use of these features should ensure that their catalog-level config file is updated.

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 83.53%. Comparing base (53ac02a) to head (8e52e4c).

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #449      +/-   ##
==========================================
+ Coverage   83.50%   83.53%   +0.03%
==========================================
  Files          43       43
  Lines        2897     2897
==========================================
+ Hits         2419     2420       +1
+ Misses        478      477       -1

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.


execute also has interesting semantics

My expectation was that execute would also push the schedule. if I have a schedule to execute a job on a daily basis, and a job that is executed at 14:00 daily, if I do an execute at 18:00, my expectation was that in the future the job would be scheduled at 18:00.
Does this sound like a good plan?

Hmm. There is already builder-client reschedule. Maybe we can add a execute --reschedule-now or so, or reschedule --execute-now? If a build fails due to something that needs fixing it can be nice to execute without rescheduling after you've pushed a fix if you're otherwise happy with the schedule (e.g. low energy prices or high percentage of renewable energy available).
In short: I think it is worth adding this new semantics while keeping the old semantics. Either could be behind a flag.

Another approach is to introduce another subcommand ;)
But maybe given that reschedule exists, that's fine. I keep on forgetting about reschedule.

closing since we have reschedule, the semantics of execute as is are useful, and there's other things to spend our time on.


When using unsloth=True with autotrain, is it restricted to only 1 GPU usage?

Since unsloth does not support multi-gpus, if I set unsloth=True, will I then be capped to 1 GPU usage when using autotrain? @abhishekkrthakur
thanks!

it will probably fail


Construct position-dependent frequency profiles

Given a set of motifs and a set of sequences, construct a position-dependent frequency profile of occurrence of the motifs within reads. This can be done by scanning all the reads with a particular motif, looking for perfectly compatible matches. That is, if the motif occurs internally in the read, it should be found precisely, and if the motif occurs at the 3' or 5' end of the reads it should be matched perfectly over the bases that are present. Record all the positions in the reads where the motif occurs and construct a histogram. If the motif occurs more than once in a read, count it fractionally towards each of those positions (e.g. if the motif occurs at 2 positions, each of these positions gets a count of 1/2). The simple implementation of this procedure will be slow (nr motifs * nr reads * read length), so make use of multiprocessing to speed things up.

Hello, I would like to work on this issue

Thanks @mariapau189, assigning you

Hi! This is what I have so far, I still have to implement reading the different motifs from a file...and then the histogram. My idea is to print each sequence ID along with the positions where the motif is found. Each motif would output one position file. Then I would calculate the frequency of each position.
The following is printing only the the sequence IDs, without the positions, and I'm stuck here. I'm using the SRR11971558_2.fastq file to test, and there are 3 "ATA" in the second record.
#!/usr/bin/env python
import re
from Bio import SeqIO
import sys
sys.stdout=open("output_positions.txt","w")
def reader ():
motif = ("ATA") #This should also be read from a file
for record in SeqIO.parse("SRR_558.fastq", "fasta") :
print (record.id)
sequence = str(record.seq)
s = re.finditer(motif,sequence)
    for match in s:
        print (match.start())

sys.stdout.close()

Closing this for now as we chose to implement a brute force algorithm for 3' adapter extraction for the meantime.


Beacon inventory and stack count numbers

This adds the fully functional beacon inventory. I left out the red X button to close the inventory that is present in vanilla since you can just close the inventory the normal way.
This also adds the numbers to indicate how many items are in a stack. This is done by drawing a UI textbox on top of the item texture if there are multiple items on a stack.

oh no i force pushed the wrong commit to this branch :( i think i will have to open a new PR to sort this out

@cooltexture1 No need, you can reuse this one. Here is what you need to do:
NOTE: Stash any uncommitted changes before running this.
git checkout beacon-stack-count
git reset --hard <previous-good-commit>
git push --force

Before you did a force push, your commit was 6b242d299369e93d183a6976cb3503ff7e0241af, but I'm not sure if you wanted to push other changes here instead.

Before you did a force push, your commit was 6b242d299369e93d183a6976cb3503ff7e0241af, but I'm not sure if you wanted to push other changes here instead.

Thank you!
what i originally wanted to do is push a commit where i replaced the get and set functions with closures. The intention was to not have to pass basic_elements at every function call because the closures could capture basic_elements from the environment. But it actually doesnt work anyways, since multiple closures would have mutable borrows to basic_elements at the same time

Ive implemented the changes. Turns out i can just use a as cast as it is

But without specifying the ids i'm not sure the transmute above is sound (maybe it is tho), do you know if it is?

well according to the minecraft wiki articel the potion effect IDs the server will send us are always  numbers from 1-33 (with the darkness effect), which i just realized doesnt include the 0 so the range should actually be (1..34).

but really i just used a transmute to save some lines of code. as we could also just make a big match statement for every effect ID

Thanks for your work!


Lat/Lng data from touchstart event

I'm struggling for quite long time to get the Lat/Lng data from touch events but not successful yet.
If anyone knows how to do it, please share. Thanks in advance.

Check out their API-example: https://examples.webglearth.com/#apidemo
In the canvas-box, with the WebglEarth-demo in it, in the bottom right corner you see the coordinates on mouseover.
If you scroll down, you see the source-code of that demo.
There you will find some answers, specifically this bit looks relevant for you:
        // Print coordinates of the mouse
        map.on('mousemove', function(e) {
          document.getElementById('coords').innerHTML = e.latlng.lat + ', ' + e.latlng.lng;
        });

Something similar is also used in another API-example.
I think this should give you a good idea 👍

Thanks for the response.
That function is for mouse event which contains lat/lng data.
But touch event data seems no lat/lng data in it ;-(

Please for the future, it's best to provide a jsbin/codepen with a (not-)working example.
For now: I couldn't reproduce your issue, because it works for me.
WebGL Earth Touch Test:
https://codepen.io/sebastian-marinescu/pen/NWZWowv
I am guessing you where adding the event-listener on document/body?

The important thing in the JS:
 var lastTouchedLatLng = undefined;

  earth.on('touchstart', function(e) {
    console.log('onTouchstart: ', e);
    if (e.latlng) {
      lastTouchedLatLng = e.latlng;
    }
  });

  earth.on('touchmove', function(e) {
    console.log('onTouchmove: ', e);
    if (e.latlng) {
      lastTouchedLatLng = e.latlng;
    }
  });

  earth.on('touchend', function(e) {
    console.log('onTouchend: ', e);
    if (lastTouchedLatLng) {
     console.info('Last Latitude/Longitude: ', lastTouchedLatLng);
    }
  });

In touchend, there really aren't lat/lng-coordinates, but in touchstart and touchmove, there are.
So we save the last touched coordinates in theses two events, and in the end in "touchend" we do something with it.

I really appreciate your help. I found out the problem based on your advice :-)
It was caused by using earth.addEventListener instead of earth.on.
Thanks.

I'm glad it helped :)
Good luck with your project, and don't forget to close this issue 👍


Update classgraph dependency

The classgraph dependency update in 2.1.12 is labeled by that team as "Do not use". Please update to a more recent version.
I have found that it causes issues with the Java Security Manager. Updating to latest (currently 4.8.138) explicitly to override the dependency included with the swagger-integration JAR resolves the issue for me.
Thanks!

classgraph updated to 4.8.138 in https://github.com/swagger-api/swagger-core/pull/4117

Thanks! Any idea when this change will be released?

This is already released in 2.1.13

Thanks! Updating now!


Result postprocess

Summary
Fixes #1365, Fixes #755, Fixes #1420
All the logic for formatting result strings are factored out and placed into the result.postprocess module. The backends do not need to worry about multiple registers, inserting space, padding extra 0s, etc. All backends just run single-register qobjs, and return results for it (in hexadecimal).
Details
The hexadecimals are expanded to bitstrings
Spaces are inserted at register divisions.
Statevectors in the form of list[[re, im]] are turned into list[complex]

does this PR resolve the validation issue? It seems that the result object is not formatted to fit the schema.
I get error when running a simple circuit.
File "/usr/local/Cellar/python/3.6.5_1/Frameworks/Python.framework/Versions/3.6/lib/python3.6/concurrent/futures/_base.py", line 432, in result
    return self.__get_result()
  File "/usr/local/Cellar/python/3.6.5_1/Frameworks/Python.framework/Versions/3.6/lib/python3.6/concurrent/futures/_base.py", line 384, in __get_result
    raise self._exception
  File "/usr/local/Cellar/python/3.6.5_1/Frameworks/Python.framework/Versions/3.6/lib/python3.6/concurrent/futures/thread.py", line 56, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/Users/rchen/Developer/Quantum/qiskit-terra-chenrich/qiskit/backends/aer/statevector_simulator.py", line 88, in _run_job
    result = super()._run_job(job_id, qobj)
  File "/Users/rchen/Developer/Quantum/qiskit-terra-chenrich/qiskit/backends/aer/qasm_simulator.py", line 116, in _run_job
    return Result.from_dict(result)
  File "/Users/rchen/Developer/Quantum/qiskit-terra-chenrich/qiskit/validation/base.py", line 248, in _from_dict
    raise ValidationError(errors)
marshmallow.exceptions.ValidationError: {'backend_name': ['Missing data for required field.'], 'results': ['Missing data for required field.'], 'qobj_id': ['Missing data for required field.'], 'backend_version': ['Missing data for required field.']}

This is ready now.


[SymbolGraph] UnconditionallyUnavailable test should only run on macOS

NFC.

@swift-ci Please smoke test


Trying to get in touch regarding a security issue

Hey there!
I'd like to report a security issue but cannot find contact instructions on your repository.
If not a hassle, might you kindly add a SECURITY.md file with an email, or another contact method? GitHub recommends this best practice to ensure security issues are responsibly disclosed, and it would serve as a simple instruction for security researchers in the future.
Thank you for your consideration, and I look forward to hearing from you!
(cc @huntr-helper)

Hi Jamie,
You can contact me using m @ mario.fyi.
Thanks.
On Mon, Sep 13, 2021, 16:22 Jamie Slome @.***> wrote:

Hey there!
I'd like to report a security issue but cannot find contact instructions
on your repository.
If not a hassle, might you kindly add a SECURITY.md file with an email,
or another contact method? GitHub recommends
https://docs.github.com/en/code-security/getting-started/adding-a-security-policy-to-your-repository
this best practice to ensure security issues are responsibly disclosed, and
it would serve as a simple instruction for security researchers in the
future.
Thank you for your consideration, and I look forward to hearing from you!
(cc @huntr-helper https://github.com/huntr-helper)
—
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[PIO-158] Deprecate Scala 2.10 and Spark 1.x

@dszeto Could you take a look?

Looks like 2 major potentially breaking changes are in as well:

Dropping Java 7 support
Dropping Spark 1.3 to 1.5 support

Should we instead put out a deprecation notice for those as well before dropping?

Well...I don't think we need to put out a deprecation notice because these versions no longer meet prerequisites we expose.
https://github.com/apache/predictionio/blob/livedoc/docs/manual/source/install/index.html.md.erb#L22
or rather, it's a bug and should be fixed. Would you like me to separate it from this PR?

I am merging this.


window is not defined error with AOT

I'm submitting a ...  (check one with "x")
[x] bug report => search github for a similar issue or PR before submitting
[ ] feature request
[ ] support request => Please do not submit support request here, post on Stackoverflow or Gitter

Current behavior
My goal is to set up AOT compilation in my Angular 4 application, which includes ngx-datatable. I am using the template from https://github.com/damienbod/AngularWebpackVisualStudio. "npm run webpack-production" gives me the following error:
ERROR in E:/MyApp/Sources/Web/node_modules/@swimlane/ngx-datatable/release/components/datatable.component.css:219
return window && document && document.all && !window.atob;
^
ReferenceError: window is not defined
at E:/MyApp/Sources/Web/node_modules/@swimlane/ngx-datatable/release/components/datatable.component.css:219:9
at E:/MyApp/Sources/Web/node_modules/@swimlane/ngx-datatable/release/components/datatable.component.css:208:46
at module.exports (E:/MyApp/Sources/Web/node_modules/@swimlane/ngx-datatable/release/components/datatable.component.css:263:46)
at Object. (E:/MyApp/Sources/Web/node_modules/@swimlane/ngx-datatable/release/components/datatable.component.css:81:36)
at webpack_require (E:/MyApp/Sources/Web/node_modules/@swimlane/ngx-datatable/release/components/datatable.component.css:20:30)
at E:/MyApp/Sources/Web/node_modules/@swimlane/ngx-datatable/release/components/datatable.component.css:63:18
at E:/MyApp/Sources/Web/node_modules/@swimlane/ngx-datatable/release/components/datatable.component.css:66:10
at ContextifyScript.Script.runInContext (vm.js:53:29)
at WebpackResourceLoader._evaluate (E:\MyApp\Sources\Web\node_modules@ngtools\webpack\src\resource_loader.js:84:34)
at _compile.then (E:\MyApp\Sources\Web\node_modules@ngtools\webpack\src\resource_loader.js:96:36)
Expected behavior
No error
Reproduction of the problem
Clone https://github.com/damienbod/AngularWebpackVisualStudio, add ngx-datatable to it, run "npm run webpack-production"
What is the motivation / use case for changing the behavior?

Please tell us about your environment:
"dependencies": {
"@angular/common": "4.4.4",
"@angular/compiler": "4.4.4",
"@angular/core": "4.4.4",
"@angular/forms": "4.4.4",
"@angular/http": "4.4.4",
"@angular/platform-browser": "4.4.4",
"@angular/platform-browser-dynamic": "4.4.4",
"@angular/router": "4.4.4",
"@swimlane/ngx-datatable": "10.2.3",
"systemjs": "0.20.19",
"types": "0.1.1",
"zone.js": "0.8.18"
},
"devDependencies": {
"@ngtools/webpack": "^1.7.1",
"@types/node": "^8.0.28",
"@types/jasmine": "^2.6.0",
"angular-router-loader": "^0.6.0",
"angular2-template-loader": "^0.6.2",
"awesome-typescript-loader": "^3.2.2",
"clean-webpack-plugin": "^0.1.16",
"codelyzer": "^3.1.2",
"concurrently": "^3.5.0",
"copy-webpack-plugin": "4.1.0",
"css-loader": "^0.28.4",
"file-loader": "1.1.5",
"html-webpack-plugin": "^2.30.1",
"jasmine-core": "^2.7.0",
"jquery": "^3.2.1",
"json-loader": "^0.5.7",
"karma": "^1.7.0",
"karma-chrome-launcher": "^2.2.0",
"karma-jasmine": "^1.1.0",
"karma-sourcemap-loader": "^0.3.7",
"karma-spec-reporter": "^0.0.31",
"karma-webpack": "^2.0.4",
"node-sass": "^4.5.3",
"raw-loader": "^0.5.1",
"rimraf": "^2.6.1",
"sass-loader": "^6.0.6",
"source-map-loader": "0.2.2",
"style-loader": "0.19.0",
"tslint": "^5.6.0",
"tslint-loader": "^3.5.3",
"typescript": "2.3.4",
"url-loader": "0.6.2",
"webpack": "^3.6.0",
"webpack-dev-server": "2.9.1"
},

Table version:
10.2.3

Angular version:
4.4.3

Browser:
all

Language:
TypeScript 2.3.4

@IonPopescu I can't find in the source code that refers to your error message. Where ever that code is referenced is probably where the issue is since referring to window does not work with AOT.

return window && document && document.all && !window.atob;

Same error with Angular 5 and V11.0.0 while AOT compilation
Excluding node_modules also does not help

@ashutoshagg nopes (or maybe yes?) I had to remove AOT support. In my opinion, it is not reliable enough at this stage.

I am facing the same issue ....
I am currently using Angular 4.3.0
along with ngx-datatable 10.2.2


Switch between receive & send modes?

Would this library be able to listen to the DMX input until there was no data for 1000 ms, then send DMX output once every 1000ms while listening/monitoring the DMX for data inbetween?

Thanks for the work on the output flag. Sending is working but I am unable to receive any DMX packets. I'm using the Sparkfun ESP32 Thing DMX Shield and it works with the Sparkfun DMX library to send or receive but with your library I am unable to receive any DMX data. The inputTest example only displays zeros for the 3 test_slots once, then nothing. I'm not using a new Arduino installation on my w10 laptop. I installed the ESP32 core via the boards manager and I followed the instructions for the esp32 core and modified hal file in the sketch folder but I don't think it's working. How can I confirm it's using the modified hal file? Extracting the esp32 core into my sketch folder gives me a different folder structure then the readme mentions, but I just searched and replaced the existing hal file.


feat: bump some dependencies

What is the goal of this change?
Bump some dependencies.
Is there any issue related?
GitHub's Dependabot were alerting on some security vulnerabilities. This bump should fix them.
How does the changes address the issue?
N/A

Codecov Report

Merging #4 into master will not change coverage.
The diff coverage is n/a.

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##            master        #4   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files            1         1
  Lines           11        11
=========================================
  Hits            11        11

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:tada: This PR is included in version 1.1.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


My username is EthanAndme

Send a message already. it Says that it was four days ago...

Sorry I meant. I Send a message already. it Says that it was four days ago...


selenium: 2.52.0 -> 3.6.0

Also brings into scope the geckodriver on which it depends.
Motivation for this change
Selenium was incompatible with latest firefox version.
Things done

[ ] Tested using sandboxing (nix.useSandbox on NixOS, or option build-use-sandbox in nix.conf on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[x] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[x] Fits CONTRIBUTING.md.

Related to #30186.

Can you move both of these to ../development/python-modules and use callPackage? We're trying to move away from having a bunch of package definitions in the top-level python file.

@disassembler : done.

As requested, moved selenium into its own file.
Also moved geckodriver into its own file and changeset and compiled it instead of taking binaries.
Added missing meta and multiple littles fixes.

I just looked at the unsucessful checks reported by travis. Those are totally unrelated. Odd.

a nox-review showed inginious as the only failing build, and it appears that's failing on master anyways. I'm good with this, merging!

Thanks.


Don't work after eo update

mcjohn974@mcjohn974-ASUS-TUF-Gaming-A15-FA506IV-FA506IV:~$ rm -rf sandbox/
mcjohn974@mcjohn974-ASUS-TUF-Gaming-A15-FA506IV-FA506IV:~$ git clone https://github.com/objectionary/sandbox
Cloning into 'sandbox'...
remote: Enumerating objects: 38, done.
remote: Counting objects: 100% (38/38), done.
remote: Compressing objects: 100% (23/23), done.
remote: Total 38 (delta 13), reused 31 (delta 8), pack-reused 0
Unpacking objects: 100% (38/38), 9.62 KiB | 94.00 KiB/s, done.
mcjohn974@mcjohn974-ASUS-TUF-Gaming-A15-FA506IV-FA506IV:~$ cd sandbox/
mcjohn974@mcjohn974-ASUS-TUF-Gaming-A15-FA506IV-FA506IV:~/sandbox$ mvn clean compile
[INFO] Scanning for projects...
[INFO]
[INFO] -------------------------< org.eolang:sandbox >-------------------------
[INFO] Building sandbox 1.0-SNAPSHOT
[INFO] --------------------------------[ jar ]---------------------------------
Downloading from central: https://repo.maven.apache.org/maven2/org/eolang/eo-maven-plugin/0.23.15/eo-maven-plugin-0.23.15.pom
Downloaded from central: https://repo.maven.apache.org/maven2/org/eolang/eo-maven-plugin/0.23.15/eo-maven-plugin-0.23.15.pom (9.7 kB at 10 kB/s)
Downloading from central: https://repo.maven.apache.org/maven2/org/eolang/eo-parent/0.23.15/eo-parent-0.23.15.pom
Downloaded from central: https://repo.maven.apache.org/maven2/org/eolang/eo-parent/0.23.15/eo-parent-0.23.15.pom (6.0 kB at 17 kB/s)
Downloading from central: https://repo.maven.apache.org/maven2/org/eolang/eo-maven-plugin/0.23.15/eo-maven-plugin-0.23.15.jar
Downloaded from central: https://repo.maven.apache.org/maven2/org/eolang/eo-maven-plugin/0.23.15/eo-maven-plugin-0.23.15.jar (93 kB at 253 kB/s)
[INFO]
[INFO] --- maven-clean-plugin:2.5:clean (default-clean) @ sandbox ---
[INFO]
[INFO] --- eo-maven-plugin:0.23.15:register (default) @ sandbox ---
Downloading from central: https://repo.maven.apache.org/maven2/org/eolang/eo-parser/0.23.15/eo-parser-0.23.15.pom
Downloaded from central: https://repo.maven.apache.org/maven2/org/eolang/eo-parser/0.23.15/eo-parser-0.23.15.pom (4.0 kB at 14 kB/s)
Downloading from central: https://repo.maven.apache.org/maven2/com/yegor256/xsline/0.5.2/xsline-0.5.2.pom
Downloaded from central: https://repo.maven.apache.org/maven2/com/yegor256/xsline/0.5.2/xsline-0.5.2.pom (4.4 kB at 20 kB/s)
Downloading from central: https://repo.maven.apache.org/maven2/com/yegor256/tojos/0.9.1/tojos-0.9.1.pom
Downloaded from central: https://repo.maven.apache.org/maven2/com/yegor256/tojos/0.9.1/tojos-0.9.1.pom (2.4 kB at 24 kB/s)
Downloading from central: https://repo.maven.apache.org/maven2/org/eolang/eo-parser/0.23.15/eo-parser-0.23.15.jar
Downloading from central: https://repo.maven.apache.org/maven2/com/yegor256/xsline/0.5.2/xsline-0.5.2.jar
Downloading from central: https://repo.maven.apache.org/maven2/com/yegor256/tojos/0.9.1/tojos-0.9.1.jar
Downloaded from central: https://repo.maven.apache.org/maven2/com/yegor256/tojos/0.9.1/tojos-0.9.1.jar (17 kB at 55 kB/s)
Downloaded from central: https://repo.maven.apache.org/maven2/com/yegor256/xsline/0.5.2/xsline-0.5.2.jar (25 kB at 65 kB/s)
Downloaded from central: https://repo.maven.apache.org/maven2/org/eolang/eo-parser/0.23.15/eo-parser-0.23.15.jar (105 kB at 261 kB/s)
[INFO] Registered 2 EO sources from ./eo to ./target/eo-foreign.csv, included [**.eo], excluded []
[INFO]
[INFO] --- eo-maven-plugin:0.23.15:assemble (default) @ sandbox ---
[INFO] 54 attributes loaded from 59 stream(s) in 85ms, 54 saved, 642 ignored: ["Agent-Class", "Ant-Version", "Archiver-Version", "Automatic-Module-Name", "Bnd-LastModified", "Build-Jdk", "Build-Jdk-Spec", "Built-By", "Bundle-Copyright", "Bundle-Description", "Bundle-Developers", "Bundle-DocURL", "Bundle-License", "Bundle-ManifestVersion", "Bundle-Name", "Bundle-RequiredExecutionEnvironment", "Bundle-SCM", "Bundle-SymbolicName", "Bundle-Vendor", "Bundle-Version", "CLDR-Version", "Can-Redefine-Classes", "Can-Retransform-Classes", "Can-Set-Native-Method-Prefix", "Created-By", "Dependencies", "EO-Version", "Eclipse-ExtensibleAPI", "Eclipse-SourceReferences", "Export-Package", "Extension-Name", "Implementation-Build", "Implementation-Title", "Implementation-URL", "Implementation-Vendor", "Implementation-Vendor-Id", "Implementation-Version", "Import-Package", "Include-Resource", "JCabi-Build", "JCabi-Date", "JCabi-Version", "Main-Class", "Manifest-Version", "Multi-Release", "Premain-Class", "Project-Name", "Require-Capability", "Specification-Title", "Specification-Vendor", "Specification-Version", "Tool", "X-Compile-Source-JDK", "X-Compile-Target-JDK"]
[INFO] Parsed 2 .EO sources to XMIRs
[INFO] Optimized 2 out of 2 XMIR program(s)
[INFO] Discovered 7 foreign objects in 2 programs: [org.eolang.io.stdout, org.eolang.txt.sprintf, sandbox.fibonacci, org.eolang.txt.sscanf, org.eolang.string, org.eolang.array, org.eolang.int]
[INFO] 6 program(s) pulled from [/home/mcjohn974/.eo (master)]+[fallback to [https://raw.githubusercontent.com/objectionary/home/master/objects/%s.eo]+(master cache to /home/mcjohn974/.eo)]
[INFO] The directory is absent, nothing to place: ./target/06-resolve
[INFO] Assemble cycle #1 (eo:2/xmir:0/xmir2:0/discovered:0 -> eo:8/xmir:2/xmir2:2/discovered:2)
[INFO] Parsed 6 .EO sources to XMIRs
[INFO] Optimized 6 out of 8 XMIR program(s)
[INFO] Discovered 5 foreign objects in 6 programs: [org.eolang.bool, org.eolang.memory, org.eolang.int, org.eolang.seq, org.eolang.array]
[INFO] 3 program(s) pulled from [/home/mcjohn974/.eo (master)]+[fallback to [https://raw.githubusercontent.com/objectionary/home/master/objects/%s.eo]+(master cache to /home/mcjohn974/.eo)]
[INFO] Dependency found for org.eolang.array/*.*.*: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.int/*.*.*: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.io.stdout/*.*.*: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.string/*.*.*: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.txt.sprintf/*.*.*: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.txt.sscanf/*.*.*: org.eolang:eo-runtime:0.23.15
[INFO] Configured Artifact: org.eolang:eo-runtime:0.23.15:jar
[INFO] Unpacking /home/mcjohn974/.m2/repository/org/eolang/eo-runtime/0.23.15/eo-runtime-0.23.15.jar to /home/mcjohn974/sandbox/target/06-resolve/org.eolang/eo-runtime/0.23.15 with includes "" and excludes ""
[INFO] org.eolang unpacked to eo-runtime:0.23.15:./target/06-resolve/org.eolang/eo-runtime/0.23.15
[INFO] Found 229 new file(s) after unpacking of org.eolang:eo-runtime:0.23.15
[INFO] New 1 dependenc(ies) unpacked
[INFO] Found 22 sources in ./target/06-resolve/org.eolang/eo-runtime/0.23.15/EO-SOURCES, 22 program(s) registered with version 0.23.15
[INFO] New 22 objects found in 1 unpacked dependencies
[INFO] Placed 204 binary file(s) out of 229, found in org.eolang/eo-runtime/0.23.15
[INFO] Placed 204 binary files found in 1 dependencies
[INFO] Assemble cycle #2 (eo:8/xmir:2/xmir2:2/discovered:2 -> eo:11/xmir:8/xmir2:8/discovered:8)
[INFO] Parsed 3 .EO sources to XMIRs
[INFO] Optimized 3 out of 11 XMIR program(s)
[INFO] Discovered 2 foreign objects in 3 programs: [org.eolang.array, org.eolang.bytes]
[INFO] 13 program(s) pulled from [/home/mcjohn974/.eo (master)]+[fallback to [https://raw.githubusercontent.com/objectionary/home/master/objects/%s.eo]+(master cache to /home/mcjohn974/.eo)]
[INFO] Dependency found for org.eolang.bool/*.*.*: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.memory/*.*.*: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.seq/*.*.*: org.eolang:eo-runtime:0.23.15
[INFO] New 1 dependenc(ies) unpacked
[INFO] Found 22 sources in ./target/06-resolve/org.eolang/eo-runtime/0.23.15/EO-SOURCES, 22 program(s) registered with version 0.23.15
[INFO] New 22 objects found in 1 unpacked dependencies
[INFO] No binary file(s) out of 229 were placed from org.eolang/eo-runtime/0.23.15
[INFO] No binary files placed from 1 dependencies
[INFO] Assemble cycle #3 (eo:11/xmir:8/xmir2:8/discovered:8 -> eo:24/xmir:11/xmir2:11/discovered:11)
[INFO] Parsed 13 .EO sources to XMIRs
[INFO] Optimized 13 out of 24 XMIR program(s)
[INFO] Discovered 4 foreign objects in 13 programs: [org.eolang.bool, org.eolang.int, org.eolang.float, org.eolang.string]
[INFO] Dependency found for org.eolang.as-phi/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.txt.regex/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.txt.text/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.goto/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.float/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.try/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.heap/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.cage/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.math.number/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.math.random/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.math.angle/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.bytes/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] Dependency found for org.eolang.ram/0.23.15: org.eolang:eo-runtime:0.23.15
[INFO] New 1 dependenc(ies) unpacked
[INFO] Found 22 sources in ./target/06-resolve/org.eolang/eo-runtime/0.23.15/EO-SOURCES, 22 program(s) registered with version 0.23.15
[INFO] New 22 objects found in 1 unpacked dependencies
[INFO] No binary file(s) out of 229 were placed from org.eolang/eo-runtime/0.23.15
[INFO] No binary files placed from 1 dependencies
[INFO] Assemble cycle #4 (eo:24/xmir:11/xmir2:11/discovered:11 -> eo:24/xmir:24/xmir2:24/discovered:24)
[WARNING] No .EO sources parsed to XMIRs
[WARNING] Nothing to discover, since there are no programs
[INFO] Found 22 sources in ./target/06-resolve/org.eolang/eo-runtime/0.23.15/EO-SOURCES, 22 program(s) registered with version 0.23.15
[INFO] New 22 objects found in 1 unpacked dependencies
[INFO] No binary file(s) out of 229 were placed from org.eolang/eo-runtime/0.23.15
[INFO] No binary files placed from 1 dependencies
[INFO] Assemble cycle #5 (eo:24/xmir:24/xmir2:24/discovered:24 -> eo:24/xmir:24/xmir2:24/discovered:24)
[INFO] 5 assemble cycle(s) produced some new object(s): eo:24/xmir:24/xmir2:24/discovered:24
[INFO]
[INFO] --- eo-maven-plugin:0.23.15:transpile (default) @ sandbox ---
[INFO] Transpiled ./target/03-optimize/sandbox/app.xmir to ./target/generated-sources, created 1 .java file(s)
[INFO] Transpiled ./target/03-optimize/sandbox/fibonacci.xmir to ./target/generated-sources, created 3 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/array.xmir to ./target/generated-sources, created 15 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/int.xmir to ./target/generated-sources, created 7 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/io/stdout.xmir but no .java files created
[INFO] Transpiled ./target/03-optimize/org/eolang/string.xmir to ./target/generated-sources, created 2 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/txt/sprintf.xmir but no .java files created
[INFO] Transpiled ./target/03-optimize/org/eolang/txt/sscanf.xmir but no .java files created
[INFO] Transpiled ./target/03-optimize/org/eolang/bool.xmir to ./target/generated-sources, created 4 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/memory.xmir but no .java files created
[INFO] Transpiled ./target/03-optimize/org/eolang/seq.xmir but no .java files created
[INFO] Transpiled ./target/03-optimize/org/eolang/as-phi.xmir but no .java files created
[INFO] Transpiled ./target/03-optimize/org/eolang/txt/regex.xmir to ./target/generated-sources, created 2 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/txt/text.xmir to ./target/generated-sources, created 1 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/goto.xmir but no .java files created
[INFO] Transpiled ./target/03-optimize/org/eolang/float.xmir to ./target/generated-sources, created 7 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/try.xmir but no .java files created
[INFO] Transpiled ./target/03-optimize/org/eolang/heap.xmir to ./target/generated-sources, created 4 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/cage.xmir but no .java files created
[INFO] Transpiled ./target/03-optimize/org/eolang/math/number.xmir to ./target/generated-sources, created 19 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/math/random.xmir but no .java files created
[INFO] Transpiled ./target/03-optimize/org/eolang/math/angle.xmir to ./target/generated-sources, created 1 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/bytes.xmir to ./target/generated-sources, created 3 .java file(s)
[INFO] Transpiled ./target/03-optimize/org/eolang/ram.xmir to ./target/generated-sources, created 1 .java file(s)
[INFO] Transpiled 24 XMIRs, created 70 Java files in ./target/generated-sources
[INFO] The directory added to Maven 'compile-source-root': ./target/generated-sources
[INFO]
[INFO] --- maven-resources-plugin:2.6:resources (default-resources) @ sandbox ---
[INFO] Using 'UTF-8' encoding to copy filtered resources.
[INFO] skip non existing resourceDirectory /home/mcjohn974/sandbox/src/main/resources
[INFO]
[INFO] --- maven-compiler-plugin:3.8.1:compile (default-compile) @ sandbox ---
[INFO] Changes detected - recompiling the module!
[INFO] Compiling 70 source files to /home/mcjohn974/sandbox/target/classes
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time:  25.458 s
[INFO] Finished at: 2022-07-01T19:21:03+03:00
[INFO] ------------------------------------------------------------------------
mcjohn974@mcjohn974-ASUS-TUF-Gaming-A15-FA506IV-FA506IV:~/sandbox$ ./run.sh
Error at "EOorg.EOeolang.EOerror#Δ" attribute
Can't get(), attribute "Δ" is absent among other 3 attrs (msg, ρ, σ) and φ is absent
mcjohn974@mcjohn974-ASUS-TUF-Gaming-A15-FA506IV-FA506IV:~/sandbox$ mvn --v
Apache Maven 3.6.3
Maven home: /usr/share/maven
Java version: 1.8.0_312, vendor: Private Build, runtime: /usr/lib/jvm/java-8-openjdk-amd64/jre
Default locale: en_US, platform encoding: UTF-8
OS name: "linux", version: "5.13.0-51-generic", arch: "amd64", family: "unix"
mcjohn974@mcjohn974-ASUS-TUF-Gaming-A15-FA506IV-FA506IV:~/sandbox$ java -v
Unrecognized option: -v
Error: Could not create the Java Virtual Machine.
Error: A fatal exception has occurred. Program will exit.
mcjohn974@mcjohn974-ASUS-TUF-Gaming-A15-FA506IV-FA506IV:~/sandbox$ java -version
openjdk version "1.8.0_312"
OpenJDK Runtime Environment (build 1.8.0_312-8u312-b07-0ubuntu1~20.04-b07)
OpenJDK 64-Bit Server VM (build 25.312-b07, mixed mode)
mcjohn974@mcjohn974-ASUS-TUF-Gaming-A15-FA506IV-FA506IV:~/sandbox$

I fully reinstall sandbox as you can see above and it don't work. Before updates it worked correctly

@MCJOHN974 I think you forgot to add a parameter to bash script

@


Use x86_64 architechure for fedora/redhat rpms

Fedora/redhat based 64-bit systems use the architechure 'x86_64'.
Packages of the architechure amd64 will be unable to be installed using
default package management tools, such as dnf or yum.
This should resolve https://github.com/MarshallOfSound/Google-Play-Music-Desktop-Player-UNOFFICIAL-/issues/883

Tests are obviously failing for reasons other than this PR, however I'm kind of torn as to just have it be formatted as just:
    arch === '32' ? 'i386' : prefix === 'rpm' ? 'x86_64' : 'amd64'

where the original line was to avoid the lines and variable above.

Sorry, I don't usually write nodejs. I can make that change.
On May 27, 2016 6:28 PM, "Jesse Ostrander"<EMAIL_ADDRESS>wrote:

Tests are obviously failing for reasons other than this PR, however I'm
kind of torn as to just have it be formatted as just:
arch === '32' ? 'i386' : prefix === 'rpm' ? 'x86_64' : 'amd64'

where the original line was to avoid the lines and variable above.
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I just ran into this problem as well.  dnf install ./google-play-music-desktop-player-3.2.4.amd64.rpm doesn't work with the same random error mentioned in #883. It works with rpm -Uvh google-play-music-desktop-player-3.2.4.amd64.rpm. It's because of this amd64 vs x86_64 issue most likely.  Somehow though I think dnf worked on my laptop but fails like I would expect on my desktop.  Could be I used rpm and just forgot.

@jostrander FYI nested ternary expressions violate the linting rules :+1:
@tiwillia Once small comment to fix up then this can go to master

@MarshallOfSound, I made your recommended change, let me know if there is anything else needed.


TemplateCompiler interface / Sparkle config tweaks

Move sparkle_pack_template out of StackDefinition to compiler_options, with template containing the sparkle pack template (as it was originally earlier in the sparkle pack template PR).
Improve SparkleFormation compiler specs. They were very brittle. Changed them to run SparkleFormation without stubbing it out.
Changed TemplateCompiler interface to take the template dir and the template (name), instead of the dir and the full path. Although, I wonder if passing template_file_path alone would suffice, and use File.basename in SparkleFormation compiler to get template dir. It wouldn't work for a template in a subdirectory like template: vpc/vpc.rb but this was how it was working before.

 [SECRETS] StackMaster tweaks around sparkle pack templates


Expose generic configuration

The HttpClientBuilder + RequestConfig expose setters for various properties, including but not limited to:

connectTimeout (in millis)
socketTimeout (in millis)
connectionTimeToLive (time + unit)
maxConnPerRoute
maxConnTotal

Would be nice if we support those things natively in yaml:
rest:
  clients:
    example:
      default-request-config:
        connect-timeout: 10000
        socket-timeout: 10000
      conn-time-to-live: 30
      conn-time-to-live-unit: seconds
      max-conn-per-route: 10
      max-conn-total: 10

It's unfortunate that the HttpClient in itself is not consistent with the naming and data types but at least it would remove the need to specify/document everything. We just pass things along as-is.

Will I also be able to specify this on the top-most level and put-it-to-rest merges this default configuration with any client-specific one?

Great idea!

I'd propose that we release the first RC after resolving this issue :wink:


Determine how to handle different sources

It seems an ontology generated by EMMOntoPy and subsequently imported and re-saved from Protégé has more triples.
The triples usually come from making implicit connections explicit (like linking up concepts from the EMMO to base concepts of OWL).
What should happen here? What the ultimate truth when it comes to such cases? Are the triples the ultimate form of truth? In which case one cannot properly canonize an ontology generated between different sources.
Is a reasoned ontology equal in content to its non-reasoned counterpart? Especially from the view of canonization?
This is related to #15.
Tagging @jesper-friis, @francescalb, @emanueleghedini, @quaat

I don't think that there exists an ultimate truth in these cases. Protege clearly does some simple reasoning just by opening a file. FaCT++ does more, but neither are complete.
Semantic equivalence is not the same as logical equivalence.
For the point of view of canonising turtle, I think you should limit yourselves to semantic equivalence and not walk into the deep scary forest of logical reasoning. Hence, a (partly) reasonened turtle file is simply different from the unreasoned one.

For the point of view of canonising turtle, I think you should limit yourselves to semantic equivalence and not walk into the deep scary forest of logical reasoning. Hence, a (partly) reasonened turtle file is simply different from the unreasoned one.

Right. Then that'll be the limit at this point in time.
It's given me an idea for a turtle-canon diff functionality, however, which could nicely show the set of triples that differ from one ontology to the other. In the future this might be useful as an interactive way to add/remove/update triples, if so desired. I.e., one could remove the explicit triples interactively added by Protégé, in this case.

I also think that a (partly) reasoned ontology is different from the non-reasoned one, so we should have differences between them. I guess this brings on the question whether we shold try to emulate the reasoning that is happening in protege in EMMOntoPy


Needs all versions

Needs samsung s3 Support, bing support, and Yahoo support for milkdrop

I'm not sure what this means. Please give more details about what exactly you are asking for. Closing for now.


Persist Auth

Actually, client details and tokens are stored in memory. Naturally this is not the best as it creates a strong coupling between the service and the data it manages.
Hence, I made this pull request to manage the authentication data on a separate container. I also shared the image on a docker repo (feel free to use your own repo if you prefer).
At your disposition for further information and/or discussion :)

In my opinion, persistent client store is best suitable when there are dynamic clients registration or when clients details can be updated in a running application. Since all clients are known upfront there is no need for such functionality. It introduces a new container just to store "static" oauth2 client configuration.

Hi @vasilaio I agree with you about client details. Even if using mysql allow to change client informations without needing to restart the auth service. It is true that it's also a use case that shouldn't happen often but it's a plus.
On the other hand, it's better to store tokens (and refresh tokens) on a database in spite of having them on memory. Thus, we keep the information even if auth stops for some reason. Of course, keeping tokens in memory should be okay for demo purpose, but it's hard to use the app that way on production.


Extract version_type methods for Manual and Section

Extracting Manual#version_type and Section#version_type from ManualPublishingAPIExporter and SectionPublishingAPIExporter respectively makes the logic more explicit/intention-revealing and the combinatorial explosion of examples in the specs for these classes is somewhat reduced. These changes should help with the larger goal of extracting API adapters from exporters.
In particular, this PR introduces the idea of a distinct version type for a new document as opposed to a major or minor version. This means we can make the logic which sets the Publishing API update type to "major" for a new version, even if it is marked as a minor update, more explicit.
Ideally it probably should be possible to have new/first version which is also marked as a minor update, i.e. I think some of the Section or SectionEdition state (flags, etc) could be combined to avoid non-allowed states existing in the first place.

Rebased against master and force-pushed in preparation for merging.

Rebased against master and force-pushed in preparation for merging.


DO NOT MERGE YET: [Clang Importer] Defer module imports to end of bridging-header parse.

There is a subtle incompatibility between the way bridging headers handle
module imports and the way clang's normal module-loading works (as done
by -emit-pch in bridging PCH, in particular).
When importing a submodule, Swift implicitly imports its supermodule. This
is part of Swift's treatment of modules and fine, we're not changing it
here.
But if client code imports a submodule, then tries to use a type that is
only defined in its supermodule, not the submodule, this should cause
a parse error (and does in clang alone, or when generating a PCH).
Unfortunately Swift's "implicit parent import" currently happens
eagerly, so the supermodule is imported and its type is defined as soon
as the submodule is imported, which in turn suppresses the error.
This in turn means that client code thinks their code "works" and then
"breaks" when they turn on bridging PCH. What should happen here is
that the (actually broken) client code should not be accepted in the first
place, neither bridging PCH nor textual bridging-header import.
This commit merely changes textual bridging-header import from eager
import to deferred parent-import, like bridging PCH does. This reconciles
the difference in behaviour between the two, at the cost of a source-compat
break.
rdar://30615193

Remaining to deal with:

[ ] A narrow test illustrating the problem & solution
[ ] A decision on whether and how to take the source-compat break (possibly put behind swift-4 mode?)

@swift-ci please test

Build failed
Jenkins build - Swift Test Linux Platform
Git Commit - 13d9569a10bd64441391d9e0433847fb4250c398
Test requested by - @graydon

Build failed
Jenkins build - Swift Test OS X Platform
Git Commit - 13d9569a10bd64441391d9e0433847fb4250c398
Test requested by - @graydon

Decision was to land this for swift 4 timeframe, not swift 3.1, but consider it just a bug fix (with release note), not a behaviour to preserve under compat flag.

@swift-ci please test and merge


#2561 corrected side space

Description

Related Issue :
#2561
How Has This Been Tested?

Log in as admin.
Management - Explore Data - Metadata - Metadata Details - Lineage tab

the spacing of the page should be shown according to the design document
Need additional checks?
Types of changes

[x] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Checklist:

[ ] I have read the CONTRIBUTING document.
[ ] My code follows the code style of this project.
[ ] My change requires a change to the documentation.
[ ] I have added tests to cover my changes.

Additional Context

Close this issue because the design code owner will handle the work.


Modularize code to add arche to bar/ribbon and reuse.

Fixes #45

looks good works great!

I’ve checked in a new branch ‘perspectives’ that separate the scenario building from the data exploration.
Before we merge it in, we need to check that it works correctly with Cycic. I’ve only tried to bring the Cycic main window.
The save and restore of the workspace should work correctly with your current workspaces but I can’t do a full test. One thing to note is that on the first run all your previous windows will open in the Data Exploration workspace. I you had any Cycic windows, you’ll need to manually close recreate them in Scenario Builder. Again, only one the first run  using previously existing working directories.
Can you guys give it a try and let me know if there are any issues?
Thanks,
Yarden


perf(reactivity): optimize triggerEffects

optimize triggerEffects logic

Not sure if this is optimisation, you save a few loops but you spending more resources by creating an array and pushing into it then looping.
I don't think this will bring any performance benefits, can you provide benchmarks to confirm this is an improvement over the current code.
I'll close this just to keep the clear lingering PRs, we can reopen later if you want.


go faster by caching writes per thread and merging as we go.

changes hashy to keep a separate unordered set for each thread and occasionally merge them so it can go faster.
gets us pretty close to single threaded performance on while multi threaded.
before changes:
/pullrequests/nsch0e/cpp$ ./cubes 12 16
loading cache file "cubes_11.bin" (110990969 bytes) with N = 11
  num polycubes loading: 2522522
  loaded 2522522 cubes
N = 12 || generating new cubes from 2522522 base cubes.
converting to vector
sorting vector
starting 16 threads
  start from 0 to 157657
  start from 315315 to 472972
  start from 472972 to 630630
  start from 630630 to 788288
  start from 788288 to 945945
  start from 157657 to 315315
  start from 1103603 to 1261261
  start from 1891891 to 2049549
  start from 2049549 to 2207206
  start from 1418918 to 1576576
  start from 1261261 to 1418918
  start from 1576576 to 1734233
  start from 945945 to 1103603
  start from 1734233 to 1891891
  start from 2207206 to 2364864
  start from 2364864 to 2522522
  done from 157657 to 315315: found 18556407
  took 176.29 s
  done from 315315 to 472972: found 18557086
  took 176.46 s
  done from 0 to 157657: found 18562477
  took 176.98 s
  done from 945945 to 1103603: found 18575680
  took 179.51 s
  done from 1103603 to 1261261: found 18577250
  took 179.88 s
  done from 630630 to 788288: found 18578524
  took 180.18 s
  done from 1418918 to 1576576: found 18580358
  took 180.53 s
  done from 472972 to 630630: found 18581515
  took 180.78 s
  done from 788288 to 945945: found 18585166
  took 181.23 s
  done from 1261261 to 1418918: found 18589276
  took 181.88 s
  done from 1576576 to 1734233: found 18590585
  took 182.15 s
  done from 2049549 to 2207206: found 18591246
  took 182.42 s
  done from 1891891 to 2049549: found 18592482
  took 182.71 s
  done from 1734233 to 1891891: found 18592997
  took 182.80 s
  done from 2207206 to 2364864: found 18595011
  took 183.01 s
  done from 2364864 to 2522522: found 18598427
  took 183.26 s
  num cubes: 18598427

after
/pullrequests/bertie2/cpp$ ./cubes 12 16
loading cache file "cubes_11.bin" (110990969 bytes) with N = 11
  num polycubes loading: 2522522
  loaded 2522522 cubes
N = 12 || generating new cubes from 2522522 base cubes.
converting to vector
sorting vector
starting 16 threads
  start from 0 to 157657
  start from 157657 to 315315
  start from 315315 to 472972
  start from 472972 to 630630
  start from 1261261 to 1418918
  start from 1103603 to 1261261
  start from 945945 to 1103603
  start from 1576576 to 1734233
  start from 788288 to 945945
  start from 1418918 to 1576576
  start from 630630 to 788288
  start from 1734233 to 1891891
  start from 1891891 to 2049549
  start from 2049549 to 2207206
  start from 2207206 to 2364864
  start from 2364864 to 2522522
  done from 315315 to 472972: found 18551591
  took 54.29 s
  done from 157657 to 315315: found 18551757
  took 54.30 s
  done from 0 to 157657: found 18557105
  took 54.63 s
  done from 945945 to 1103603: found 18571278
  took 55.16 s
  done from 1103603 to 1261261: found 18573501
  took 55.38 s
  done from 630630 to 788288: found 18575023
  took 55.46 s
  done from 1418918 to 1576576: found 18578232
  took 55.63 s
  done from 472972 to 630630: found 18580322
  took 55.77 s
  done from 788288 to 945945: found 18587963
  took 56.04 s
  done from 1261261 to 1418918: found 18589049
  took 56.12 s
  done from 1576576 to 1734233: found 18589572
  took 56.16 s
  done from 2049549 to 2207206: found 18589579
  took 56.16 s
  done from 1891891 to 2049549: found 18592226
  took 56.38 s
  done from 1734233 to 1891891: found 18592238
  took 56.38 s
  done from 2207206 to 2364864: found 18593772
  took 56.54 s
  done from 2364864 to 2522522: found 18598378
  took 56.86 s
  num cubes: 18598427

is there a reason why you put hashy into namespace std? I think separate sets per shape is more interesting, because by clearing the cache we accept cubes which are already in the total set and the rejection just comes later when we merge the cache...

please checkout my branch "subhashy". There I group sets by same shape.
Results for N = 12, Threads = 16:
cpp: ~81s
yours: ~50s
subhashy: ~26s
is subhashy also faster for you?

agreed the multisets are they way to go but have an improvement and more comments, closing this pr and raising a more relevant one.


SetStakingAuthority instruction removed

This looks good to me.  I'm going to hold off on merging until we get another opinion.

Let's merge! @joncinque

@ysavchenko Could you rebase your branch?  There was a small change in the set-staking-authority.rs which isn't consequential since the file is getting deleted anyway :-)


Create dependabot.yml

Summary
@yahoo/ychaos-dev

This pull request adds a dependabot config file that is used to auto fix any vulnerable packages / update them.

Fixes: #22

Checklist
Checklist (Developer)
Prerequisites

[x] I have read the contribution guidelines

Code Analysis

[ ] Covered by Unittests
[ ] Security warnings ignored (Why?!)

Project related

[ ] Schema changed and is backward compatible.
[ ] Introduces a new sub-command for ychaos CLI

Autogenerated Files

[ ] Auto generated schema

Pre-Merge Checklist

[ ] All the build jobs are passing

Checklist (Reviewer 1)

[ ] Reviewed Source Code
[ ] Reviewed Tests (If applicable)
[ ] Reviewed Documentation (If applicable)

Checklist (Reviewer 2)

[ ] Reviewed Source Code
[ ] Reviewed Tests (If applicable)
[ ] Reviewed Documentation (If applicable)

Can you verify the behaviour by configuring dependabot on your fork?

Hey @nafri-irfan96 . Is this under progress?


feat: build against SPDK 21.04

Sync with upstream changes to bdev_nvme_create(), bdev_nvme_delete(),
spdk_nvme_poll_group_create(), and spdk_sock_impl_opts.
The nbd code has moved on so the reversion of commit d2704a0 had to be
dropped. This causes the create, publish, un-publish, destroy of an
nbd nexus test in test_nexus.js to fail so skip all nbd tests there as
nbd is not supported anyway.
Also cherry-pick da976633 ("nvmf: delay remove subsystem cb until no
qpairs remain")
Fixes CAS-831, CAS-914

bors try

bors merge


slice: Tests are failing on Mac OS

    --- FAIL: TestAllPrograms/slice_append_assign.go (0.07s)
    	compiler_test.go:89: Expected:
    		---
    		'2
    		2
    		3
    		3
    		1 2 4
    		1 2 3'
    		---
    		Result:
    		---
    		'2
    		2
    		3
    		3
    		1 2 4
    		1 2 1'
    		---

Doesn't seem to happen anymore.


Fix issue with parsing docker images with a tag in the _. format

This pull request includes changes to the Docker package, primarily focusing on improving version handling and adding new test cases. The most significant changes involve modifying the version method in tag.rb to better handle year-month-day formatted versions, adjusting the correct? method in version.rb to correctly parse versions with hyphens, and adding new test scenarios in update_checker_spec.rb and version_spec.rb.
Version handling improvements:

docker/lib/dependabot/docker/tag.rb: Modified the version method to handle year-month-day formatted versions with 5 to 7 digits instead of only 5 digits. This allows for better handling of versions formatted as year-month-day.
docker/lib/dependabot/docker/version.rb: Adjusted the correct? method to correctly parse versions with hyphens, converting them into dots. This change improves the ability to correctly identify and handle versions that use hyphens as separators.

Test case additions:

docker/spec/dependabot/docker/update_checker_spec.rb: Added new test scenarios to handle dependencies with a version format of <prefix>_<year><month><day>.<version>. These tests ensure that the version handling changes function correctly.
docker/spec/dependabot/docker/version_spec.rb: Added new test cases to check the correctness of versions formatted as <prefix>_<year><month><day>.<version>, and to test their sorting order. These tests further validate the changes in version handling. [1] [2] [3]

File additions:

docker/spec/fixtures/docker/registry_tags/fulldate_in_tag.json: Added a new fixture file for testing purposes. This file contains example tags for a "dated_image", which are used in the new test cases added in update_checker_spec.rb and version_spec.rb.

For anyone reviewing, it looks like since I made this change initially, other things have changed so that this doesn't currently work. Will try to resolve tomorrow, but if anyone has any ideas please let me know!


Regex filtering not working as intended.

FFUF 1.5.0 Kali
I've noticed on several occasions that the -fr argument does not seem to properly filter regex from the response. Below is an example with the Mr. Robot box:

The box has a wordpress login page that outputs "Invalid Username" on POST response.

On using the -fr argument to filter the regex, ffuf still outputs anything that includes this regex

Hi @DBonacich,
Ffuf will not set the Content-Type for you, the lack of Content-Type could give you some problems in POST requests, the best option is to use raw requests (-request file request-proto https).
In case you don't want to use raw requests, you can try setting the Content type header like below, but you also need to check what other headers the server expects to receive.
-H "Content-Type: application/x-www-form-urlencoded"

Maybe after setting the header it still don't works, so I suggest you to proxy ffuf to your Burp and read the error in the HTML response (I'm sure you need a pre-setted cookie to Bruteforce wordpress, but is better if you could check it)
This is not a ffuf error, but you need to setup it a bit more.
Happy hacking.

A really common mistake when handling POST data for HTML forms is to not to
include the proprer Content-Type header, which I think is the issue here
too.
On Tue 26. Apr 2022 at 19.48, DBonacich @.***> wrote:

I've noticed on several occasions that the -fr argument does not seem to
properly filter regex from the response. Below is an example with the Mr.
Robot box:

The box has a wordpress login page that outputs "Invalid Username" on
POST response.
[image: 1]
https://user-images.githubusercontent.com/81584492/165360849-4c76174d-efd5-4673-a815-31ee5859d469.png
[image: 2]
https://user-images.githubusercontent.com/81584492/165360909-d3e908a0-6d89-4b1a-9123-d57908e5fc31.png
On using the -fr argument to filter the regex, ffuf still outputs
anything that includes this regex
[image: 3]
https://user-images.githubusercontent.com/81584492/165361117-fad1d072-ade4-4b8f-bdc7-2124fee70fc5.png
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Hi @DBonacich, closing this by now, the documentation is being improved to cover this case.
https://github.com/ffuf/ffuf/pull/775
Feel free to re-open if it has not resolved your case.


Media3

Hi, are you planning to migrate to Media3 anytime soon?

I was waiting for a stable release of Media3 but I might migrate sooner because of https://github.com/dburckh/Media3Avi

Migrated.


Update handlebars links

Handlebars link changed. They had to add /guide/ for some reason or another!

Thanks for the fix!

@nickofthyme
Could you also update handlebars link here:
https://github.com/fbaligand/kibana-enhanced-table/blob/master/public/enhanced-table-vis-params.html#L162
Thanks!

Sorry, should have checked for more. Fixed!

Nice!
Don’t be sorry, that’s why review is useful ;)

LGTM!


updated recipe for pescador 1.1

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.