ONNXTransform Upgrade to Enable Non-tensor Types - #3881

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ONNXTransform Upgrade to Enable Non-tensor Types#3881
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@wschinwschin commented Jun 19, 2019•
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The current ONNXTransform only operates on tensor types. As many ONNX models (especially classifiers) produce Seq<Map<T, float>> where T can be either int or string, we should remove that limitation.

This should fix#3900.

@wschinwschin changed the title [WIP] ONNXTransform Upgrade to Enable Non-tensor TypesONNXTransform Upgrade to Enable Non-tensor TypesJun 24, 2019
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs Outdated
/// Its underlying type is <see cref="IEnumerable{T}"/>, where the generic type "T" is the input argument of
/// <see cref="OnnxSequenceType.OnnxSequenceType(Type)"/>.
/// </summary>
public sealed class OnnxSequenceType : StructuredDataViewType

@eerhardteerhardtJun 27, 2019•
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Can you put top-level classes in their own file? One class per file is usually a good recommendation.

Here, the first class in the file is "internal", which makes it look like there are no public APIs being added. But the public APIs are later in the file. #Resolved

@wschinwschinJul 1, 2019

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No problem. Btw, I still put "...DataViewType" and its "...DataViewTypeAttribute" in the same file for emphasizing that they are dual of each other.

In reply to: 298374249 [](ancestors = 298374249)

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Comment threadtest/Microsoft.ML.OnnxTransformerTest/OnnxTransformTests.cs

private class ZipMapStringOutput
{
[OnnxSequenceType(typeof(IDictionary<string, float>))]

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How about tests for the new OnnxMap type as well? #Resolved

@wschinwschinJun 29, 2019•
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Unfortunately, ONNXRuntime doesn't allow us to create Map value as input and the Map value is always used as input of ONNX operator... I can add some smoke tests for sure.

[Update] A test using custom mapping is added.

In reply to: 298374926 [](ancestors = 298374926)

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Remove it if possible. #Resolved

Refers to: src/Microsoft.ML.OnnxConverter/AssemblyInfo.cs:11 in 9e539b6. [](commit_id = 9e539b6, deletion_comment = False)

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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
Inputs = (options.InputColumns.Count() == 0) ? Model.InputNames.ToArray() : options.InputColumns;
Outputs = (options.OutputColumns.Count() == 0) ? Model.OutputNames.ToArray() : options.OutputColumns;
Inputs = (options.InputColumns.Count() == 0) ? Model.ModelInfo.InputNames.ToArray() : options.InputColumns;
Outputs = (options.OutputColumns.Count() == 0) ? Model.ModelInfo.OutputNames.ToArray() : options.OutputColumns;

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options.OutputColumns.Count() == 0 [](start = 23, length = 34)

Check if we have test. #Resolved

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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Reviewed this in person and signing off assuming you will fix my comments that we made in your office with your account.

@wschin
wschin merged commit 0c0789f into dotnet:masterJul 1, 2019
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wschin deleted the ot-upgrade branch July 1, 2019 19:55
Dmitry-A pushed a commit to Dmitry-A/machinelearning that referenced this pull request Jul 24, 2019
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ONNXTransform Upgrade to Enable Non-tensor Types (dotnet#3881)
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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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ONNXTransform Upgrade to Enable Non-tensor Types - #3881
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wschin merged 23 commits into
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ONNXTransform Upgrade to Enable Non-tensor Types#3881
wschin merged 23 commits into
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Jun 19, 2019•

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The current ONNXTransform only operates on tensor types. As many ONNX models (especially classifiers) produce Seq<Map<T, float>> where T can be either int or string, we should remove that limitation.
This should fix#3900.
@wschinwschin
changed the title
[WIP] ONNXTransform Upgrade to Enable Non-tensor TypesONNXTransform Upgrade to Enable Non-tensor TypesJun 24, 2019
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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 /// Its underlying type is <see cref="IEnumerable{T}"/>, where the generic type "T" is the input argument of
 /// <see cref="OnnxSequenceType.OnnxSequenceType(Type)"/>.
 /// </summary>
 public sealed class OnnxSequenceType : StructuredDataViewType
@eerhardteerhardtJun 27, 2019•

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Can you put top-level classes in their own file? One class per file is usually a good recommendation.
Here, the first class in the file is "internal", which makes it look like there are no public APIs being added. But the public APIs are later in the file. #Resolved
@wschinwschinJul 1, 2019

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No problem. Btw, I still put "...DataViewType" and its "...DataViewTypeAttribute" in the same file for emphasizing that they are dual of each other.
In reply to: 298374249 [](ancestors = 298374249)
eerhardt
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Comment threadtest/Microsoft.ML.OnnxTransformerTest/OnnxTransformTests.cs

 private class ZipMapStringOutput
 {
 [OnnxSequenceType(typeof(IDictionary<string, float>))]
@eerhardteerhardtJun 27, 2019•

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How about tests for the new OnnxMap type as well? #Resolved
@wschinwschinJun 29, 2019•

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Unfortunately, ONNXRuntime doesn't allow us to create Map value as input and the Map value is always used as input of ONNX operator... I can add some smoke tests for sure.
[Update] A test using custom mapping is added.
In reply to: 298374926 [](ancestors = 298374926)
eerhardt
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Remove it if possible. #Resolved
Refers to: src/Microsoft.ML.OnnxConverter/AssemblyInfo.cs:11 in 9e539b6. [](commit_id = 9e539b6, deletion_comment = False)
wschin
wschin
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Jun 28, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
 Inputs = (options.InputColumns.Count() == 0) ? Model.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.OutputNames.ToArray() : options.OutputColumns;
 Inputs = (options.InputColumns.Count() == 0) ? Model.ModelInfo.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.ModelInfo.OutputNames.ToArray() : options.OutputColumns;
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options.OutputColumns.Count() == 0 [](start = 23, length = 34)
Check if we have test. #Resolved
wschin
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Reviewed this in person and signing off assuming you will fix my comments that we made in your office with your account.
@wschin
wschin
merged commit 0c0789f
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dotnet:masterJul 1, 2019
@wschin
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ot-upgrade

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Dmitry-A pushed a commit
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ONNXTransform Upgrade to Enable Non-tensor Types (dotnet#3881)
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"Onnx Type not supported" error while importing Custom Vision ONNX model


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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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ONNXTransform Upgrade to Enable Non-tensor Types - #3881
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wschin merged 23 commits into
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Merged
ONNXTransform Upgrade to Enable Non-tensor Types#3881
wschin merged 23 commits into
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Jun 19, 2019•

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The current ONNXTransform only operates on tensor types. As many ONNX models (especially classifiers) produce Seq<Map<T, float>> where T can be either int or string, we should remove that limitation.
This should fix#3900.
@wschinwschin
changed the title
[WIP] ONNXTransform Upgrade to Enable Non-tensor TypesONNXTransform Upgrade to Enable Non-tensor TypesJun 24, 2019
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mentioned this pull request
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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 /// Its underlying type is <see cref="IEnumerable{T}"/>, where the generic type "T" is the input argument of
 /// <see cref="OnnxSequenceType.OnnxSequenceType(Type)"/>.
 /// </summary>
 public sealed class OnnxSequenceType : StructuredDataViewType
@eerhardteerhardtJun 27, 2019•

edited by wschin

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Can you put top-level classes in their own file? One class per file is usually a good recommendation.
Here, the first class in the file is "internal", which makes it look like there are no public APIs being added. But the public APIs are later in the file. #Resolved
@wschinwschinJul 1, 2019

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No problem. Btw, I still put "...DataViewType" and its "...DataViewTypeAttribute" in the same file for emphasizing that they are dual of each other.
In reply to: 298374249 [](ancestors = 298374249)
eerhardt
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Comment threadtest/Microsoft.ML.OnnxTransformerTest/OnnxTransformTests.cs

 private class ZipMapStringOutput
 {
 [OnnxSequenceType(typeof(IDictionary<string, float>))]
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How about tests for the new OnnxMap type as well? #Resolved
@wschinwschinJun 29, 2019•

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Unfortunately, ONNXRuntime doesn't allow us to create Map value as input and the Map value is always used as input of ONNX operator... I can add some smoke tests for sure.
[Update] A test using custom mapping is added.
In reply to: 298374926 [](ancestors = 298374926)
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Remove it if possible. #Resolved
Refers to: src/Microsoft.ML.OnnxConverter/AssemblyInfo.cs:11 in 9e539b6. [](commit_id = 9e539b6, deletion_comment = False)
wschin
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View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
 Inputs = (options.InputColumns.Count() == 0) ? Model.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.OutputNames.ToArray() : options.OutputColumns;
 Inputs = (options.InputColumns.Count() == 0) ? Model.ModelInfo.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.ModelInfo.OutputNames.ToArray() : options.OutputColumns;
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options.OutputColumns.Count() == 0 [](start = 23, length = 34)
Check if we have test. #Resolved
wschin
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Reviewed this in person and signing off assuming you will fix my comments that we made in your office with your account.
@wschin
wschin
merged commit 0c0789f
into
dotnet:masterJul 1, 2019
@wschin
wschin
deleted the

ot-upgrade

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July 1, 2019 19:55
Dmitry-A pushed a commit
to Dmitry-A/machinelearning
that referenced
this pull request
Jul 24, 2019
@wschin@Dmitry-A
ONNXTransform Upgrade to Enable Non-tensor Types (dotnet#3881)
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"Onnx Type not supported" error while importing Custom Vision ONNX model


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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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ONNXTransform Upgrade to Enable Non-tensor Types - #3881
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wschin:ot-upgrade
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ONNXTransform Upgrade to Enable Non-tensor Types#3881
wschin merged 23 commits into
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Jun 19, 2019•

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The current ONNXTransform only operates on tensor types. As many ONNX models (especially classifiers) produce Seq<Map<T, float>> where T can be either int or string, we should remove that limitation.
This should fix#3900.
@wschinwschin
changed the title
[WIP] ONNXTransform Upgrade to Enable Non-tensor TypesONNXTransform Upgrade to Enable Non-tensor TypesJun 24, 2019
@wschinwschin
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Jun 24, 2019
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Comment threadsrc/Microsoft.ML.OnnxTransformer/Microsoft.ML.OnnxTransformer.csproj
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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 /// Its underlying type is <see cref="IEnumerable{T}"/>, where the generic type "T" is the input argument of
 /// <see cref="OnnxSequenceType.OnnxSequenceType(Type)"/>.
 /// </summary>
 public sealed class OnnxSequenceType : StructuredDataViewType
@eerhardteerhardtJun 27, 2019•

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Can you put top-level classes in their own file? One class per file is usually a good recommendation.
Here, the first class in the file is "internal", which makes it look like there are no public APIs being added. But the public APIs are later in the file. #Resolved
@wschinwschinJul 1, 2019

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No problem. Btw, I still put "...DataViewType" and its "...DataViewTypeAttribute" in the same file for emphasizing that they are dual of each other.
In reply to: 298374249 [](ancestors = 298374249)
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Comment threadtest/Microsoft.ML.OnnxTransformerTest/OnnxTransformTests.cs

 private class ZipMapStringOutput
 {
 [OnnxSequenceType(typeof(IDictionary<string, float>))]
@eerhardteerhardtJun 27, 2019•

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How about tests for the new OnnxMap type as well? #Resolved
@wschinwschinJun 29, 2019•

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Unfortunately, ONNXRuntime doesn't allow us to create Map value as input and the Map value is always used as input of ONNX operator... I can add some smoke tests for sure.
[Update] A test using custom mapping is added.
In reply to: 298374926 [](ancestors = 298374926)
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Remove it if possible. #Resolved
Refers to: src/Microsoft.ML.OnnxConverter/AssemblyInfo.cs:11 in 9e539b6. [](commit_id = 9e539b6, deletion_comment = False)
wschin
wschin
commented
Jun 28, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
 Inputs = (options.InputColumns.Count() == 0) ? Model.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.OutputNames.ToArray() : options.OutputColumns;
 Inputs = (options.InputColumns.Count() == 0) ? Model.ModelInfo.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.ModelInfo.OutputNames.ToArray() : options.OutputColumns;
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options.OutputColumns.Count() == 0 [](start = 23, length = 34)
Check if we have test. #Resolved
wschin
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/Microsoft.ML.OnnxTransformer.csproj
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Reviewed this in person and signing off assuming you will fix my comments that we made in your office with your account.
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merged commit 0c0789f
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ONNXTransform Upgrade to Enable Non-tensor Types (dotnet#3881)
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"Onnx Type not supported" error while importing Custom Vision ONNX model


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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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ONNXTransform Upgrade to Enable Non-tensor Types - #3881
Merged
wschin merged 23 commits into
dotnet:masterfrom 
wschin:ot-upgrade
Jul 1, 2019
Merged
ONNXTransform Upgrade to Enable Non-tensor Types#3881
wschin merged 23 commits into
dotnet:masterfrom 
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@wschin
@wschinwschin
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Jun 19, 2019•

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The current ONNXTransform only operates on tensor types. As many ONNX models (especially classifiers) produce Seq<Map<T, float>> where T can be either int or string, we should remove that limitation.
This should fix#3900.
@wschinwschin
changed the title
[WIP] ONNXTransform Upgrade to Enable Non-tensor TypesONNXTransform Upgrade to Enable Non-tensor TypesJun 24, 2019
@wschinwschin
mentioned this pull request
Jun 24, 2019
 Merged

@wschinwschin
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Jun 24, 2019

Closed

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Jun 26, 2019
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eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/Microsoft.ML.OnnxTransformer.csproj
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
Outdated

 /// Its underlying type is <see cref="IEnumerable{T}"/>, where the generic type "T" is the input argument of
 /// <see cref="OnnxSequenceType.OnnxSequenceType(Type)"/>.
 /// </summary>
 public sealed class OnnxSequenceType : StructuredDataViewType
@eerhardteerhardtJun 27, 2019•

edited by wschin

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Can you put top-level classes in their own file? One class per file is usually a good recommendation.
Here, the first class in the file is "internal", which makes it look like there are no public APIs being added. But the public APIs are later in the file. #Resolved
@wschinwschinJul 1, 2019

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No problem. Btw, I still put "...DataViewType" and its "...DataViewTypeAttribute" in the same file for emphasizing that they are dual of each other.
In reply to: 298374249 [](ancestors = 298374249)
eerhardt
eerhardt
reviewed
Jun 27, 2019
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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eerhardt
eerhardt
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Comment threadtest/Microsoft.ML.OnnxTransformerTest/OnnxTransformTests.cs

 private class ZipMapStringOutput
 {
 [OnnxSequenceType(typeof(IDictionary<string, float>))]
@eerhardteerhardtJun 27, 2019•

edited by wschin

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How about tests for the new OnnxMap type as well? #Resolved
@wschinwschinJun 29, 2019•

edited

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Unfortunately, ONNXRuntime doesn't allow us to create Map value as input and the Map value is always used as input of ONNX operator... I can add some smoke tests for sure.
[Update] A test using custom mapping is added.
In reply to: 298374926 [](ancestors = 298374926)
eerhardt
eerhardt
reviewed
Jun 27, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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eerhardt
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxUtils.cs
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eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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@wschin
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Remove it if possible. #Resolved
Refers to: src/Microsoft.ML.OnnxConverter/AssemblyInfo.cs:11 in 9e539b6. [](commit_id = 9e539b6, deletion_comment = False)
wschin
wschin
commented
Jun 28, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
 Inputs = (options.InputColumns.Count() == 0) ? Model.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.OutputNames.ToArray() : options.OutputColumns;
 Inputs = (options.InputColumns.Count() == 0) ? Model.ModelInfo.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.ModelInfo.OutputNames.ToArray() : options.OutputColumns;
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options.OutputColumns.Count() == 0 [](start = 23, length = 34)
Check if we have test. #Resolved
wschin
wschin
commented
Jun 28, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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wschin
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
wschin
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/Microsoft.ML.OnnxTransformer.csproj
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Reviewed this in person and signing off assuming you will fix my comments that we made in your office with your account.
@wschin
wschin
merged commit 0c0789f
into
dotnet:masterJul 1, 2019
@wschin
wschin
deleted the

ot-upgrade

branch
July 1, 2019 19:55
Dmitry-A pushed a commit
to Dmitry-A/machinelearning
that referenced
this pull request
Jul 24, 2019
@wschin@Dmitry-A
ONNXTransform Upgrade to Enable Non-tensor Types (dotnet#3881)
2f2d0d0
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locked as resolved and limited conversation to collaborators
Mar 21, 2022
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Reviewers

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"Onnx Type not supported" error while importing Custom Vision ONNX model


4 participants

@wschin@codemzs@eerhardt@artidoro

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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ONNXTransform Upgrade to Enable Non-tensor Types - #3881
Merged
wschin merged 23 commits into
dotnet:masterfrom 
wschin:ot-upgrade
Jul 1, 2019
Merged
ONNXTransform Upgrade to Enable Non-tensor Types#3881
wschin merged 23 commits into
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wschin:ot-upgrade
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commented
Jun 19, 2019•

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The current ONNXTransform only operates on tensor types. As many ONNX models (especially classifiers) produce Seq<Map<T, float>> where T can be either int or string, we should remove that limitation.
This should fix#3900.
@wschinwschin
changed the title
[WIP] ONNXTransform Upgrade to Enable Non-tensor TypesONNXTransform Upgrade to Enable Non-tensor TypesJun 24, 2019
@wschinwschin
mentioned this pull request
Jun 24, 2019
 Merged

@wschinwschin
mentioned this pull request
Jun 24, 2019

Closed

@safernsafern
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Jun 26, 2019
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eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/Microsoft.ML.OnnxTransformer.csproj
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eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
Outdated

 /// Its underlying type is <see cref="IEnumerable{T}"/>, where the generic type "T" is the input argument of
 /// <see cref="OnnxSequenceType.OnnxSequenceType(Type)"/>.
 /// </summary>
 public sealed class OnnxSequenceType : StructuredDataViewType
@eerhardteerhardtJun 27, 2019•

edited by wschin

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Can you put top-level classes in their own file? One class per file is usually a good recommendation.
Here, the first class in the file is "internal", which makes it look like there are no public APIs being added. But the public APIs are later in the file. #Resolved
@wschinwschinJul 1, 2019

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No problem. Btw, I still put "...DataViewType" and its "...DataViewTypeAttribute" in the same file for emphasizing that they are dual of each other.
In reply to: 298374249 [](ancestors = 298374249)
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadtest/Microsoft.ML.OnnxTransformerTest/OnnxTransformTests.cs

 private class ZipMapStringOutput
 {
 [OnnxSequenceType(typeof(IDictionary<string, float>))]
@eerhardteerhardtJun 27, 2019•

edited by wschin

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How about tests for the new OnnxMap type as well? #Resolved
@wschinwschinJun 29, 2019•

edited

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Unfortunately, ONNXRuntime doesn't allow us to create Map value as input and the Map value is always used as input of ONNX operator... I can add some smoke tests for sure.
[Update] A test using custom mapping is added.
In reply to: 298374926 [](ancestors = 298374926)
eerhardt
eerhardt
reviewed
Jun 27, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
Outdated

eerhardt
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxUtils.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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@wschin
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Remove it if possible. #Resolved
Refers to: src/Microsoft.ML.OnnxConverter/AssemblyInfo.cs:11 in 9e539b6. [](commit_id = 9e539b6, deletion_comment = False)
wschin
wschin
commented
Jun 28, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
 Inputs = (options.InputColumns.Count() == 0) ? Model.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.OutputNames.ToArray() : options.OutputColumns;
 Inputs = (options.InputColumns.Count() == 0) ? Model.ModelInfo.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.ModelInfo.OutputNames.ToArray() : options.OutputColumns;
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options.OutputColumns.Count() == 0 [](start = 23, length = 34)
Check if we have test. #Resolved
wschin
wschin
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Jun 28, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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wschin
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/Microsoft.ML.OnnxTransformer.csproj
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Reviewed this in person and signing off assuming you will fix my comments that we made in your office with your account.
@wschin
wschin
merged commit 0c0789f
into
dotnet:masterJul 1, 2019
@wschin
wschin
deleted the

ot-upgrade

branch
July 1, 2019 19:55
Dmitry-A pushed a commit
to Dmitry-A/machinelearning
that referenced
this pull request
Jul 24, 2019
@wschin@Dmitry-A
ONNXTransform Upgrade to Enable Non-tensor Types (dotnet#3881)
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"Onnx Type not supported" error while importing Custom Vision ONNX model


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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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ONNXTransform Upgrade to Enable Non-tensor Types - #3881
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wschin merged 23 commits into
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Merged
ONNXTransform Upgrade to Enable Non-tensor Types#3881
wschin merged 23 commits into
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wschin:ot-upgrade
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@wschin
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Jun 19, 2019•

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The current ONNXTransform only operates on tensor types. As many ONNX models (especially classifiers) produce Seq<Map<T, float>> where T can be either int or string, we should remove that limitation.
This should fix#3900.
@wschinwschin
changed the title
[WIP] ONNXTransform Upgrade to Enable Non-tensor TypesONNXTransform Upgrade to Enable Non-tensor TypesJun 24, 2019
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Comment threadsrc/Microsoft.ML.OnnxTransformer/Microsoft.ML.OnnxTransformer.csproj
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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 /// Its underlying type is <see cref="IEnumerable{T}"/>, where the generic type "T" is the input argument of
 /// <see cref="OnnxSequenceType.OnnxSequenceType(Type)"/>.
 /// </summary>
 public sealed class OnnxSequenceType : StructuredDataViewType
@eerhardteerhardtJun 27, 2019•

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Can you put top-level classes in their own file? One class per file is usually a good recommendation.
Here, the first class in the file is "internal", which makes it look like there are no public APIs being added. But the public APIs are later in the file. #Resolved
@wschinwschinJul 1, 2019

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No problem. Btw, I still put "...DataViewType" and its "...DataViewTypeAttribute" in the same file for emphasizing that they are dual of each other.
In reply to: 298374249 [](ancestors = 298374249)
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadtest/Microsoft.ML.OnnxTransformerTest/OnnxTransformTests.cs

 private class ZipMapStringOutput
 {
 [OnnxSequenceType(typeof(IDictionary<string, float>))]
@eerhardteerhardtJun 27, 2019•

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How about tests for the new OnnxMap type as well? #Resolved
@wschinwschinJun 29, 2019•

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Unfortunately, ONNXRuntime doesn't allow us to create Map value as input and the Map value is always used as input of ONNX operator... I can add some smoke tests for sure.
[Update] A test using custom mapping is added.
In reply to: 298374926 [](ancestors = 298374926)
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxUtils.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Remove it if possible. #Resolved
Refers to: src/Microsoft.ML.OnnxConverter/AssemblyInfo.cs:11 in 9e539b6. [](commit_id = 9e539b6, deletion_comment = False)
wschin
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Jun 28, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
 Inputs = (options.InputColumns.Count() == 0) ? Model.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.OutputNames.ToArray() : options.OutputColumns;
 Inputs = (options.InputColumns.Count() == 0) ? Model.ModelInfo.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.ModelInfo.OutputNames.ToArray() : options.OutputColumns;
@wschinwschinJun 28, 2019•

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options.OutputColumns.Count() == 0 [](start = 23, length = 34)
Check if we have test. #Resolved
wschin
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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wschin
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
wschin
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/Microsoft.ML.OnnxTransformer.csproj
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Reviewed this in person and signing off assuming you will fix my comments that we made in your office with your account.
@wschin
wschin
merged commit 0c0789f
into
dotnet:masterJul 1, 2019
@wschin
wschin
deleted the

ot-upgrade

branch
July 1, 2019 19:55
Dmitry-A pushed a commit
to Dmitry-A/machinelearning
that referenced
this pull request
Jul 24, 2019
@wschin@Dmitry-A
ONNXTransform Upgrade to Enable Non-tensor Types (dotnet#3881)
2f2d0d0
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Reviewers

@codemzscodemzscodemzs approved these changes

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@artidoroartidoroartidoro approved these changes
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Successfully merging this pull request may close these issues.

"Onnx Type not supported" error while importing Custom Vision ONNX model


4 participants

@wschin@codemzs@eerhardt@artidoro

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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ONNXTransform Upgrade to Enable Non-tensor Types - #3881
Merged
wschin merged 23 commits into
dotnet:masterfrom 
wschin:ot-upgrade
Jul 1, 2019
Merged
ONNXTransform Upgrade to Enable Non-tensor Types#3881
wschin merged 23 commits into
dotnet:masterfrom 
wschin:ot-upgrade
Conversation
@wschin
@wschinwschin
commented
Jun 19, 2019•

edited

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The current ONNXTransform only operates on tensor types. As many ONNX models (especially classifiers) produce Seq<Map<T, float>> where T can be either int or string, we should remove that limitation.
This should fix#3900.
@wschinwschin
changed the title
[WIP] ONNXTransform Upgrade to Enable Non-tensor TypesONNXTransform Upgrade to Enable Non-tensor TypesJun 24, 2019
@wschinwschin
mentioned this pull request
Jun 24, 2019
 Merged

@wschinwschin
mentioned this pull request
Jun 24, 2019

Closed

@safernsafern
mentioned this pull request
Jun 26, 2019
 Merged

eerhardt
eerhardt
reviewed
Jun 27, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/Microsoft.ML.OnnxTransformer.csproj
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eerhardt
eerhardt
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Jun 27, 2019
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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 /// Its underlying type is <see cref="IEnumerable{T}"/>, where the generic type "T" is the input argument of
 /// <see cref="OnnxSequenceType.OnnxSequenceType(Type)"/>.
 /// </summary>
 public sealed class OnnxSequenceType : StructuredDataViewType
@eerhardteerhardtJun 27, 2019•

edited by wschin

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Can you put top-level classes in their own file? One class per file is usually a good recommendation.
Here, the first class in the file is "internal", which makes it look like there are no public APIs being added. But the public APIs are later in the file. #Resolved
@wschinwschinJul 1, 2019

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No problem. Btw, I still put "...DataViewType" and its "...DataViewTypeAttribute" in the same file for emphasizing that they are dual of each other.
In reply to: 298374249 [](ancestors = 298374249)
eerhardt
eerhardt
reviewed
Jun 27, 2019
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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eerhardt
eerhardt
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Comment threadtest/Microsoft.ML.OnnxTransformerTest/OnnxTransformTests.cs

 private class ZipMapStringOutput
 {
 [OnnxSequenceType(typeof(IDictionary<string, float>))]
@eerhardteerhardtJun 27, 2019•

edited by wschin

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How about tests for the new OnnxMap type as well? #Resolved
@wschinwschinJun 29, 2019•

edited

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Unfortunately, ONNXRuntime doesn't allow us to create Map value as input and the Map value is always used as input of ONNX operator... I can add some smoke tests for sure.
[Update] A test using custom mapping is added.
In reply to: 298374926 [](ancestors = 298374926)
eerhardt
eerhardt
reviewed
Jun 27, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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eerhardt
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxUtils.cs
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eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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@wschin
wschin
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edited

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Remove it if possible. #Resolved
Refers to: src/Microsoft.ML.OnnxConverter/AssemblyInfo.cs:11 in 9e539b6. [](commit_id = 9e539b6, deletion_comment = False)
wschin
wschin
commented
Jun 28, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
 Inputs = (options.InputColumns.Count() == 0) ? Model.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.OutputNames.ToArray() : options.OutputColumns;
 Inputs = (options.InputColumns.Count() == 0) ? Model.ModelInfo.InputNames.ToArray() : options.InputColumns;
 Outputs = (options.OutputColumns.Count() == 0) ? Model.ModelInfo.OutputNames.ToArray() : options.OutputColumns;
@wschinwschinJun 28, 2019•

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options.OutputColumns.Count() == 0 [](start = 23, length = 34)
Check if we have test. #Resolved
wschin
wschin
commented
Jun 28, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
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wschin
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
wschin
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTypes.cs
wschin
wschin
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Jun 28, 2019
View reviewed changes
Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
eerhardt
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reviewed
Jun 28, 2019
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Comment threadsrc/Microsoft.ML.OnnxTransformer/Microsoft.ML.OnnxTransformer.csproj
eerhardt
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Comment threadsrc/Microsoft.ML.OnnxTransformer/OnnxTransform.cs
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Reviewed this in person and signing off assuming you will fix my comments that we made in your office with your account.
@wschin
wschin
merged commit 0c0789f
into
dotnet:masterJul 1, 2019
@wschin
wschin
deleted the

ot-upgrade

branch
July 1, 2019 19:55
Dmitry-A pushed a commit
to Dmitry-A/machinelearning
that referenced
this pull request
Jul 24, 2019
@wschin@Dmitry-A
ONNXTransform Upgrade to Enable Non-tensor Types (dotnet#3881)
2f2d0d0
@ghostghost
locked as resolved and limited conversation to collaborators
Mar 21, 2022
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Reviewers

@codemzscodemzscodemzs approved these changes

+2 more reviewers

@eerhardteerhardteerhardt left review comments
@artidoroartidoroartidoro approved these changes
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"Onnx Type not supported" error while importing Custom Vision ONNX model


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