ML example bad
This commit is contained in:
Mikhalkovich Stanislav
parent
88c9ac464a
commit
7f73d91024
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W/Debug_Folder/ConsoleApp1.exe
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W/Debug_Folder/ConsoleApp1.exe
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W/Debug_Folder/ConsoleApp1.exe.config
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W/Debug_Folder/ConsoleApp1.exe.config
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<?xml version="1.0" encoding="utf-8"?>
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<configuration>
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<startup>
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<supportedRuntime version="v4.0" sku=".NETFramework,Version=v4.8" />
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</startup>
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<runtime>
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<assemblyBinding xmlns="urn:schemas-microsoft-com:asm.v1">
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<dependentAssembly>
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<assemblyIdentity name="System.Threading.Tasks.Extensions" publicKeyToken="cc7b13ffcd2ddd51" culture="neutral" />
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<bindingRedirect oldVersion="0.0.0.0-4.2.0.1" newVersion="4.2.0.1" />
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</dependentAssembly>
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</assemblyBinding>
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</runtime>
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</configuration>
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W/Debug_Folder/ConsoleApp1.pdb
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W/Debug_Folder/ConsoleApp1.pdb
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W/Debug_Folder/CpuMathNative.dll
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W/Debug_Folder/CpuMathNative.dll
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W/Debug_Folder/LdaNative.dll
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W/Debug_Folder/LdaNative.dll
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W/Debug_Folder/Microsoft.ML.Core.dll
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W/Debug_Folder/Microsoft.ML.Core.dll
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W/Debug_Folder/Microsoft.ML.Core.xml
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W/Debug_Folder/Microsoft.ML.Core.xml
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W/Debug_Folder/Microsoft.ML.CpuMath.dll
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W/Debug_Folder/Microsoft.ML.CpuMath.dll
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W/Debug_Folder/Microsoft.ML.CpuMath.xml
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W/Debug_Folder/Microsoft.ML.CpuMath.xml
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<?xml version="1.0"?>
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<doc>
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<assembly>
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<name>Microsoft.ML.CpuMath</name>
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</assembly>
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<members>
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<member name="T:Microsoft.ML.Internal.CpuMath.AlignedArray">
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<summary>
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This implements a logical array of floats that is automatically aligned for SSE/AVX operations.
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To pin and force alignment, call the GetPin method, typically wrapped in a using (since it
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returns a Pin struct that is IDisposable). From the pin, you can get the IntPtr to pass to
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native code.
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The ctor takes an alignment value, which must be a power of two at least sizeof(float).
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</summary>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.AlignedArray.#ctor(System.Int32,System.Int32)">
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<summary>
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Allocate an aligned vector with the given alignment (in bytes).
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The alignment must be a power of two and at least sizeof(Float).
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</summary>
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</member>
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<member name="T:Microsoft.ML.Internal.CpuMath.CpuAlignedVector">
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<summary>
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This implements a logical array of Floats that is automatically aligned for SSE/AVX operations.
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This is a thin wrapper around the AlignedArray type implemented in C++. This simply couples
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the AlignedArray with a logical size, which does not include padding, while the AlignedArray
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size does include padding.
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.ValueCount">
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<summary>
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The value count.
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.VectorSize">
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<summary>
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The logical size of the vector.
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</summary>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.#ctor(System.Int32,System.Int32)">
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<summary>
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Allocate an aligned vector with the given alignment (in bytes).
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The alignment must be a power of two and at least sizeof(Float).
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.Items">
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<summary>
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The physical AligenedArray items.
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.CbAlign">
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<summary>
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The alignment.
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.Item(System.Int32)">
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<summary>
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Set and get the value of the vector at the given index.
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</summary>
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<param name="index">The index</param>
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<returns>The value at the given index</returns>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.GetValue(System.Int32)">
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<summary>
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Get the value of the vector at the given index.
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</summary>
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<param name="i">The index</param>
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<returns>The value at the given index</returns>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.Randomize(System.Func{System.Single})">
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<summary>
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Assign randomized values to the vector elements via the input function.
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</summary>
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<param name="rand">The input rand om function that takes no arguments and returns a float value</param>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.Zero">
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<summary>
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Assign zeros to the vector elements.
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</summary>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.CopyTo(System.Single[],System.Int32@)">
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<summary>
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Copy the values into dst, starting at slot ivDst and advancing ivDst.
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</summary>
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<param name="dst">The destination array</param>
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<param name="ivDst">The starting index in the destination array</param>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.CopyTo(System.Int32,System.Single[],System.Int32,System.Int32)">
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<summary>
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Copy the values from this vector starting at slot ivSrc into dst, starting at slot ivDst.
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The number of values that are copied is determined by count.
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</summary>
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<param name="ivSrc">The staring index in this vector</param>
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<param name="dst">The destination array</param>
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<param name="ivDst">The starting index in the destination array</param>
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<param name="count">The number of elements to be copied</param>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.CopyFrom(System.Single[],System.Int32@)">
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<summary>
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Copy the values from src, starting at slot index and advancing index, into this vector.
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</summary>
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<param name="src">The source array</param>
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<param name="index">The starting index in the source array</param>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.CopyFrom(System.Int32,System.Single[],System.Int32,System.Int32)">
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<summary>
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Copy the values from src, starting at slot index and advancing index, into this vector, starting at slot ivDst.
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The number of values that are copied is determined by count.
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</summary>
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<param name="ivDst">The staring index in this vector</param>
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<param name="src">The source array</param>
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<param name="ivSrc">The starting index in the source array</param>
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<param name="count">The number of elements to be copied</param>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.CopyFrom(Microsoft.ML.Internal.CpuMath.CpuAlignedVector)">
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<summary>
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Copy the values of src vector into this vector. The src vector must have the same size as this vector.
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</summary>
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<param name="src">The source vector</param>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedVector.GetEnumerator">
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<summary>
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Get the underlying AlignedArray as IEnumerator<Float>.
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</summary>
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</member>
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<member name="T:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase">
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<summary>
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This implements a logical matrix of Floats that is automatically aligned for SSE/AVX operations.
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The ctor takes an alignment value, which must be a power of two at least sizeof(Float).
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase.ValueCount">
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<summary>
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The logical number values in the matrix
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase.RowCount">
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<summary>
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The logical number of rows
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase.ColCount">
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<summary>
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The logical number of columns
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase.RowCountPhy">
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<summary>
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The physical number of rows
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase.ColCountPhy">
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<summary>
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The physical number of columns
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</summary>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase.#ctor(System.Int32,System.Int32,System.Int32)">
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<summary>
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Allocate an aligned matrix with the given alignment (in bytes).
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</summary>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase.Randomize(System.Func{System.Single})">
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<summary>
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Assign randomized values to the matrix elements via the input function.
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</summary>
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<param name="rand">The input rand om function that takes no arguments and returns a float value</param>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase.Zero">
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<summary>
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Assign zeros to the matrix elements.
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</summary>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase.CopyFrom(Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixBase)">
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<summary>
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Copy the values of src matrix into this matrix. The src matrix must have the same physical and logical size as this matrix.
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</summary>
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<param name="src">The source matrix</param>
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</member>
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<member name="T:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRowBase">
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<summary>
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This implements a logical row-major matrix of Floats that is automatically aligned for SSE/AVX operations.
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The ctor takes an alignment value, which must be a power of two at least sizeof(Float).
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRowBase.RowCount">
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<summary>
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The logical number of rows
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRowBase.ColCount">
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<summary>
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The logical number of columns
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRowBase.RowCountPhy">
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<summary>
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The physical number of rows
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRowBase.ColCountPhy">
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<summary>
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The physical number of columns
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</summary>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRowBase.CopyTo(System.Single[],System.Int32@)">
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<summary>
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Copy the values into dst, starting at slot ivDst and advancing ivDst.
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</summary>
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<param name="dst">The destination array</param>
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<param name="ivDst">The starting index in the destination array</param>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRowBase.CopyFrom(System.Single[],System.Int32@)">
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<summary>
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Copy the values from src, starting at slot ivSrc and advancing ivSrc.
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</summary>
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<param name="src">The source array</param>
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<param name="ivSrc">The starting index in the source array</param>
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRowBase.GetEnumerator">
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<summary>
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Get the underlying AlignedArray as IEnumerator<Float>.
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</summary>
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</member>
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<member name="T:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRow">
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<summary>
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This implements a row-major matrix of Floats that is automatically aligned for SSE/AVX operations.
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The ctor takes an alignment value, which must be a power of two at least sizeof(Float).
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</summary>
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRow.RowCount">
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<summary>
|
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The logical number of rows
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</summary>
|
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</member>
|
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRow.ColCount">
|
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<summary>
|
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The logical number of columns
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</summary>
|
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</member>
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRow.RowCountPhy">
|
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<summary>
|
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The physical number of rows
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</summary>
|
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</member>
|
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<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRow.ColCountPhy">
|
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<summary>
|
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The physical number of columns
|
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</summary>
|
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</member>
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRow.CopyTo(System.Int32,System.Single[],System.Int32@)">
|
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<summary>
|
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Copy the values from this matrix, starting from the row into dst, starting at slot ivDst and advancing ivDst.
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</summary>
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<param name="row">The starting row in this matrix</param>
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<param name="dst">The destination array</param>
|
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<param name="ivDst">The starting index in the destination array</param>
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</member>
|
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixRow.ZeroItems(System.Int32[])">
|
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<summary>
|
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Assign zeros to the values at the indices
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||||
</summary>
|
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<param name="indices">The indices</param>
|
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</member>
|
||||
<member name="T:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol">
|
||||
<summary>
|
||||
This implements a logical matrix of Floats that is automatically aligned for SSE/AVX operations.
|
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The ctor takes an alignment value, which must be a power of two at least sizeof(Float).
|
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</summary>
|
||||
</member>
|
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<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol.#ctor(System.Int32,System.Int32,System.Int32)">
|
||||
<summary>
|
||||
Allocate an aligned matrix with the given alignment (in bytes).
|
||||
</summary>
|
||||
</member>
|
||||
<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol.RowCount">
|
||||
<summary>
|
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The logical number of rows
|
||||
</summary>
|
||||
</member>
|
||||
<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol.ColCount">
|
||||
<summary>
|
||||
The logical number of columns
|
||||
</summary>
|
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</member>
|
||||
<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol.RowCountPhy">
|
||||
<summary>
|
||||
The physical number of rows
|
||||
</summary>
|
||||
</member>
|
||||
<member name="P:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol.ColCountPhy">
|
||||
<summary>
|
||||
The physical number of columns
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol.CopyTo(System.Single[],System.Int32@)">
|
||||
<summary>
|
||||
Copy the values into dst, starting at slot ivDst and advancing ivDst.
|
||||
</summary>
|
||||
<param name="dst">The destination array</param>
|
||||
<param name="ivDst">The starting index in the destination array</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol.CopyTo(System.Int32,System.Single[],System.Int32@)">
|
||||
<summary>
|
||||
Copy the values from this matrix, starting from the row into dst, starting at slot ivDst and advancing ivDst.
|
||||
</summary>
|
||||
<param name="row">The starting row in this matrix</param>
|
||||
<param name="dst">The destination array</param>
|
||||
<param name="ivDst">The starting index in the destination array</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol.CopyFrom(System.Single[],System.Int32@)">
|
||||
<summary>
|
||||
Copy the values from src, starting at slot ivSrc and advancing ivSrc.
|
||||
</summary>
|
||||
<param name="src">The source array</param>
|
||||
<param name="ivSrc">The starting index in the source array</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol.ZeroItems(System.Int32[])">
|
||||
<summary>
|
||||
Assign zeros to the values at the indices
|
||||
</summary>
|
||||
<param name="indices">The indices</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuAlignedMatrixCol.GetEnumerator">
|
||||
<summary>
|
||||
Get the underlying AlignedArray as IEnumerator<Float>.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuAligenedMathUtils`1.AssertCompatible(Microsoft.ML.Internal.CpuMath.ICpuFullMatrix)">
|
||||
<summary>
|
||||
Assert the compatibility of the underlying AlignedArray for the input matrix in terms of alignment amount.
|
||||
</summary>
|
||||
<param name="values">The input matrix</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuAligenedMathUtils`1.AssertCompatible(Microsoft.ML.Internal.CpuMath.ICpuVector)">
|
||||
<summary>
|
||||
Assert the compatibility of the underlying AlignedArray for the input vector in terms of alignment amount.
|
||||
</summary>
|
||||
<param name="values">The input vector</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuAligenedMathUtils`1.AssertCompatible(Microsoft.ML.Internal.CpuMath.ICpuFullMatrix,Microsoft.ML.Internal.CpuMath.ICpuVector,Microsoft.ML.Internal.CpuMath.ICpuVector)">
|
||||
<summary>
|
||||
Asserts the following:
|
||||
1. The compatibility of the underlying AlignedArray for mat in terms of alignment amount.
|
||||
2. The compatibility of the underlying AlignedArray for src in terms of alignment amount.
|
||||
3. The compatibility of the underlying AlignedArray for dst in terms of alignment amount.
|
||||
4. The compatibility of the matrix-vector multiplication mat * src = dst.
|
||||
</summary>
|
||||
<param name="mat"></param>
|
||||
<param name="src"></param>
|
||||
<param name="dst"></param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuAligenedMathUtils`1.MatTimesSrc(Microsoft.ML.Internal.CpuMath.ICpuFullMatrix,Microsoft.ML.Internal.CpuMath.ICpuVector,Microsoft.ML.Internal.CpuMath.ICpuVector)">
|
||||
<summary>
|
||||
Matrix multiplication:
|
||||
dst = mat * src
|
||||
</summary>
|
||||
<param name="mat">The multiplier matrix</param>
|
||||
<param name="src">The source vector</param>
|
||||
<param name="dst">The destination vector</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuAligenedMathUtils`1.MatTranTimesSrc(Microsoft.ML.Internal.CpuMath.ICpuFullMatrix,Microsoft.ML.Internal.CpuMath.ICpuVector,Microsoft.ML.Internal.CpuMath.ICpuVector)">
|
||||
<summary>
|
||||
Matrix transpose multiplication:
|
||||
dst = mat' * src
|
||||
</summary>
|
||||
<param name="mat">The multiplier matrix</param>
|
||||
<param name="src">The source vector</param>
|
||||
<param name="dst">The destination vector</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.GeneralUtils.CbitLowZero(System.UInt32)">
|
||||
<summary>
|
||||
Count the number of zero bits in the lonest string of zero's from the lowest significant bit of the input integer.
|
||||
</summary>
|
||||
<param name="u">The input integer</param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuMathUtils.Compat(Microsoft.ML.Internal.CpuMath.AlignedArray)">
|
||||
<summary>
|
||||
|
||||
|
||||
if <paramref name="a"/>'s alignment is suitable to SSE instructions. Returns <see langword="true"/>
|
||||
if <paramref name="a"/>'s alignment is ok and <see langword="false"/> otherwise.
|
||||
</summary>
|
||||
<param name="a">The vector being checked.</param>
|
||||
<returns>Whether <paramref name="a"/> is aligned well.</returns>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.CpuMathUtils.MatrixTimesSource(System.Boolean,Microsoft.ML.Internal.CpuMath.AlignedArray,Microsoft.ML.Internal.CpuMath.AlignedArray,Microsoft.ML.Internal.CpuMath.AlignedArray,System.Int32)">
|
||||
<summary>
|
||||
Compute the product of matrix <paramref name="mat"/> (the matrix is flattened because its type is <see cref="T:Microsoft.ML.Internal.CpuMath.AlignedArray"/> instead of a matrix)
|
||||
and a vector <paramref name="src"/>.
|
||||
</summary>
|
||||
<param name="tran">Whether to transpose <paramref name="mat"/> before doing any computation.</param>
|
||||
<param name="mat">If <paramref name="tran"/> is <see langword="false"/>, <paramref name="mat"/> is a m-by-n matrix, and the value at the i-th row and the j-th column is indexed by i * n + j in <paramref name="mat"/>.
|
||||
If <paramref name="tran"/> is <see langword="true"/>, <paramref name="mat"/> would be viewed a n-by-m matrix, and the value at the i-th row and the j-th column in the transposed matrix is indexed by j * m + i in the
|
||||
original <paramref name="mat"/>.</param>
|
||||
<param name="src">A n-by-1 matrix, which is also a vector.</param>
|
||||
<param name="dst">A m-by-1 matrix, which is also a vector.</param>
|
||||
<param name="crun">The truncation level of <paramref name="dst"/>. For example, if <paramref name="crun"/> is 2, <paramref name="dst"/>
|
||||
will be considered as a 2-by-1 matrix and therefore elements after its 2nd element will be ignored. If no truncation should happen,
|
||||
set <paramref name="crun"/> to the length of <paramref name="dst"/>.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ICpuBuffer`1.Randomize(System.Func{`0})">
|
||||
<summary>
|
||||
Assign random values using the given random function.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ICpuBuffer`1.Zero">
|
||||
<summary>
|
||||
Set all values to zero.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ICpuBuffer`1.CopyTo(`0[],System.Int32@)">
|
||||
<summary>
|
||||
Copy the values into dst, starting at slot ivDst and advancing ivDst.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ICpuBuffer`1.CopyFrom(`0[],System.Int32@)">
|
||||
<summary>
|
||||
Copy values from the given src array into this buffer, starting at the given index in src,
|
||||
</summary>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Internal.CpuMath.ICpuVector">
|
||||
<summary>
|
||||
A logical math vector.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="P:Microsoft.ML.Internal.CpuMath.ICpuVector.VectorSize">
|
||||
<summary>
|
||||
The vector size
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ICpuVector.GetValue(System.Int32)">
|
||||
<summary>
|
||||
Get the i'th component of the vector.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="P:Microsoft.ML.Internal.CpuMath.ICpuMatrix.RowCount">
|
||||
<summary>
|
||||
The row count
|
||||
</summary>
|
||||
</member>
|
||||
<member name="P:Microsoft.ML.Internal.CpuMath.ICpuMatrix.ColCount">
|
||||
<summary>
|
||||
the column count
|
||||
</summary>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Internal.CpuMath.ICpuFullMatrix">
|
||||
<summary>
|
||||
A 2-dimensional matrix.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ICpuFullMatrix.CopyTo(System.Int32,System.Single[],System.Int32@)">
|
||||
<summary>
|
||||
Copy the values for the given row into dst, starting at slot ivDst.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ICpuFullMatrix.ZeroItems(System.Int32[])">
|
||||
<summary>
|
||||
Zero out the items with the given indices.
|
||||
The indices contain the logical indices to the vectorized representation of the matrix,
|
||||
which can be different depending on whether the matrix is row-major or column-major.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.IntUtils.Add(System.UInt64@,System.UInt64@,System.UInt64)">
|
||||
<summary>
|
||||
Add src to the 128 bits contained in dst. Ignores overflow, that is, the addition is done modulo 2^128.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.IntUtils.Add(System.UInt64@,System.UInt64@,System.UInt64,System.UInt64)">
|
||||
<summary>
|
||||
Add src to dst. Ignores overflow, that is, the addition is done modulo 2^128.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.IntUtils.Sub(System.UInt64@,System.UInt64@,System.UInt64)">
|
||||
<summary>
|
||||
Subtract src from the 128 bits contained in dst. Ignores overflow, that is, the subtraction is
|
||||
done modulo 2^128.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.IntUtils.Sub(System.UInt64@,System.UInt64@,System.UInt64,System.UInt64)">
|
||||
<summary>
|
||||
Subtract src from dst. Ignores overflow, that is, the subtraction is done modulo 2^128.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.IntUtils.LessThan(System.UInt64,System.UInt64,System.UInt64,System.UInt64)">
|
||||
<summary>
|
||||
Return true if a is less than b.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.IntUtils.Mul64(System.UInt64,System.UInt64,System.UInt64@)">
|
||||
<summary>
|
||||
Multiple the two 64-bit values to produce 128 bit result.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.IntUtils.CbitHighZero(System.UInt64)">
|
||||
<summary>
|
||||
Return the number of zero bits on the high end.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Internal.CpuMath.ProbabilityFunctions">
|
||||
<summary>
|
||||
Probability Functions.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ProbabilityFunctions.Erfc(System.Double)">
|
||||
<summary>
|
||||
The approximate complimentary error function (i.e., 1-erf).
|
||||
</summary>
|
||||
<param name="x">The input parameter, of infinite range.</param>
|
||||
<returns>Evaluation of the function</returns>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ProbabilityFunctions.Erf(System.Double)">
|
||||
<summary>
|
||||
The approximate error function.
|
||||
</summary>
|
||||
<param name="x">The input parameter, of infinite range.</param>
|
||||
<returns>Evaluation of the function</returns>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ProbabilityFunctions.Erfinv(System.Double)">
|
||||
<summary>
|
||||
The inverse error function.
|
||||
</summary>
|
||||
<param name="x">Parameter in the range 1 to -1.</param>
|
||||
<returns>Evaluation of the function.</returns>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.ProbabilityFunctions.Probit(System.Double)">
|
||||
<summary>
|
||||
The probit function. This has many applications, the most familiar being perhaps
|
||||
that this is the point "x" at which the standard normal CDF evaluates to the indicated
|
||||
p value. It is used in establishing confidence intervals.
|
||||
</summary>
|
||||
<param name="p">The input p value, so in the range 0 to 1.</param>
|
||||
<returns>One interpretation is, the value at which the standard normal CDF evaluates to p.</returns>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Internal.CpuMath.Core.IExceptionContext">
|
||||
<summary>
|
||||
Interface for "processing" exceptions before they are thrown. This can
|
||||
be used to add context to the exception, wrap the exception in another one,
|
||||
totally replace the exception, etc. It is not legal to return null from
|
||||
Process (unless null was passed in, which really shouldn't happen).
|
||||
</summary>
|
||||
</member>
|
||||
<member name="P:Microsoft.ML.Internal.CpuMath.Core.IExceptionContext.ContextDescription">
|
||||
<summary>
|
||||
A string describing the context itself.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.Process``1(``0,Microsoft.ML.Internal.CpuMath.Core.IExceptionContext)">
|
||||
<summary>
|
||||
Does standard processing of an exception (typically called after construction
|
||||
but before it is thrown).
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.Mark``1(``0)">
|
||||
<summary>
|
||||
Mark the exception by setting <see cref="F:Microsoft.ML.Internal.CpuMath.Core.Contracts.IsMarkedKey"/> in the exception
|
||||
<see cref="P:System.Exception.Data"/> to 1.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.IsMarked(System.Exception)">
|
||||
<summary>
|
||||
Indicates whether the exception was "marked" the Contracts code.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.MarkSensitive``1(``0,Microsoft.ML.Internal.CpuMath.Core.MessageSensitivity)">
|
||||
<summary>
|
||||
Exceptions whose message communicates potentially sensitive information should be
|
||||
marked using this method, before they are thrown. Note that if the exception already
|
||||
had this flag set, the message will be flagged with the bitwise or of the existing
|
||||
flag, alongside the passed in sensitivity.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.Sensitivity(System.Exception)">
|
||||
<summary>
|
||||
This is a convenience method to get the sensitivity of an exception,
|
||||
as encoded with <see cref="F:Microsoft.ML.Internal.CpuMath.Core.Contracts.SensitivityKey"/>. If there is no key, then
|
||||
the message is assumed to be of unknown sensitivity, i.e., it is assumed
|
||||
that it might contain literally anything.
|
||||
</summary>
|
||||
<param name="ex">The exception to query</param>
|
||||
<returns>The value encoded at the <see cref="F:Microsoft.ML.Internal.CpuMath.Core.Contracts.SensitivityKey"/>, if it is
|
||||
a <see cref="T:Microsoft.ML.Internal.CpuMath.Core.MessageSensitivity"/> value. If neither of these conditions
|
||||
hold then <see cref="F:Microsoft.ML.Internal.CpuMath.Core.MessageSensitivity.Unknown"/> is returned.</returns>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.SetAssertHandler(System.Action{System.String,Microsoft.ML.Internal.CpuMath.Core.IExceptionContext})">
|
||||
<summary>
|
||||
Sets the assert handler to the given function, returning the previous handler.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.Except">
|
||||
<summary>
|
||||
Default exception type (currently InvalidOperationException)
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.ExceptUserArg(System.String)">
|
||||
<summary>
|
||||
For signaling bad user input.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.ExceptParam(System.String)">
|
||||
<summary>
|
||||
For signaling bad function parameters.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.ExceptValue(System.String)">
|
||||
<summary>
|
||||
For signaling null function parameters.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.ExceptEmpty(System.String)">
|
||||
<summary>
|
||||
For signaling null or empty function parameters (strings, arrays, collections, etc).
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.ExceptWhiteSpace(System.String)">
|
||||
<summary>
|
||||
For signaling null, empty or white-space function parameters (strings, arrays, collections, etc).
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.ExceptDecode">
|
||||
<summary>
|
||||
For signaling errors in decoding information, whether while reading from a file,
|
||||
parsing user input, etc.
|
||||
</summary>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.ExceptIO">
|
||||
<summary>
|
||||
For signaling IO failures.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.ExceptNotImpl">
|
||||
<summary>
|
||||
For signaling functionality that is not YET implemented.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.ExceptNotSupp">
|
||||
<summary>
|
||||
For signaling functionality that is not implemented by design.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.ExceptSchemaMismatch(System.String,System.String,System.String)">
|
||||
<summary>
|
||||
For signaling schema validation issues.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.CheckUserArg(System.Boolean,System.String)">
|
||||
<summary>
|
||||
CheckUserArg / ExceptUserArg should be used when the validation of user-provided arguments failed.
|
||||
Typically, this is shortly after the arguments are parsed using CmdParser.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.CheckValueOrNull``1(``0)">
|
||||
<summary>
|
||||
This documents that the parameter can legally be null.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.CheckValueOrNull``1(Microsoft.ML.Internal.CpuMath.Core.IExceptionContext,``0)">
|
||||
<summary>
|
||||
This documents that the parameter can legally be null.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Internal.CpuMath.Core.Contracts.AssertValueOrNull``1(``0)">
|
||||
<summary>
|
||||
This documents that the parameter can legally be null.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Internal.CpuMath.Core.BestFriendAttribute">
|
||||
<summary>
|
||||
Intended to be applied to types and members with internal scope to indicate that friend access of this
|
||||
internal item is OK from another assembly. This restriction applies only to assemblies that declare the
|
||||
<see cref="T:Microsoft.ML.Internal.CpuMath.Core.WantsToBeBestFriendsAttribute"/> assembly level attribute. Note that this attribute is not
|
||||
transferable: an internal member with this attribute does not somehow make a containing internal type
|
||||
accessible. Conversely, neither does marking an internal type make any unmarked internal members accessible.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Internal.CpuMath.Core.WantsToBeBestFriendsAttribute">
|
||||
<summary>
|
||||
This is an assembly level attribute to signal that friend accesses on this assembly should be checked
|
||||
for usage of <see cref="T:Microsoft.ML.Internal.CpuMath.Core.BestFriendAttribute"/>. If this attribute is missing, normal access rules for
|
||||
friends should apply.
|
||||
</summary>
|
||||
</member>
|
||||
</members>
|
||||
</doc>
|
||||
BIN
W/Debug_Folder/Microsoft.ML.Data.dll
Normal file
BIN
W/Debug_Folder/Microsoft.ML.Data.dll
Normal file
Binary file not shown.
14072
W/Debug_Folder/Microsoft.ML.Data.xml
Normal file
14072
W/Debug_Folder/Microsoft.ML.Data.xml
Normal file
File diff suppressed because it is too large
Load diff
BIN
W/Debug_Folder/Microsoft.ML.DataView.dll
Normal file
BIN
W/Debug_Folder/Microsoft.ML.DataView.dll
Normal file
Binary file not shown.
1156
W/Debug_Folder/Microsoft.ML.DataView.xml
Normal file
1156
W/Debug_Folder/Microsoft.ML.DataView.xml
Normal file
File diff suppressed because it is too large
Load diff
BIN
W/Debug_Folder/Microsoft.ML.KMeansClustering.dll
Normal file
BIN
W/Debug_Folder/Microsoft.ML.KMeansClustering.dll
Normal file
Binary file not shown.
383
W/Debug_Folder/Microsoft.ML.KMeansClustering.xml
Normal file
383
W/Debug_Folder/Microsoft.ML.KMeansClustering.xml
Normal file
|
|
@ -0,0 +1,383 @@
|
|||
<?xml version="1.0"?>
|
||||
<doc>
|
||||
<assembly>
|
||||
<name>Microsoft.ML.KMeansClustering</name>
|
||||
</assembly>
|
||||
<members>
|
||||
<member name="T:Microsoft.ML.KMeansClusteringExtensions">
|
||||
<summary>
|
||||
Collection of extension methods for the <see cref="T:Microsoft.ML.ClusteringCatalog.ClusteringTrainers"/> to create
|
||||
instances of KMeans trainers.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.KMeansClusteringExtensions.KMeans(Microsoft.ML.ClusteringCatalog.ClusteringTrainers,System.String,System.String,System.Int32)">
|
||||
<summary>
|
||||
Train a KMeans++ clustering algorithm using <see cref="T:Microsoft.ML.Trainers.KMeansTrainer"/>.
|
||||
</summary>
|
||||
<param name="catalog">The clustering catalog trainer object.</param>
|
||||
<param name="featureColumnName">The name of the feature column.</param>
|
||||
<param name="exampleWeightColumnName">The name of the example weight column (optional).</param>
|
||||
<param name="numberOfClusters">The number of clusters to use for KMeans.</param>
|
||||
<example>
|
||||
<format type="text/markdown">
|
||||
<]
|
||||
]]></format>
|
||||
</example>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.KMeansClusteringExtensions.KMeans(Microsoft.ML.ClusteringCatalog.ClusteringTrainers,Microsoft.ML.Trainers.KMeansTrainer.Options)">
|
||||
<summary>
|
||||
Train a KMeans++ clustering algorithm using <see cref="T:Microsoft.ML.Trainers.KMeansTrainer"/>.
|
||||
</summary>
|
||||
<param name="catalog">The clustering catalog trainer object.</param>
|
||||
<param name="options">Algorithm advanced options.</param>
|
||||
<example>
|
||||
<format type="text/markdown">
|
||||
<]
|
||||
]]></format>
|
||||
</example>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Trainers.KMeansModelParameters">
|
||||
<example>
|
||||
<format type="text/markdown">
|
||||
<]
|
||||
]]></format>
|
||||
</example>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansModelParameters.GetVersionInfo">
|
||||
<summary>
|
||||
Version information to be saved in binary format
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansModelParameters.#ctor(Microsoft.ML.Runtime.IHostEnvironment,System.Int32,Microsoft.ML.Data.VBuffer{System.Single}[],System.Boolean)">
|
||||
<summary>
|
||||
Initialize predictor with a trained model.
|
||||
</summary>
|
||||
<param name="env">The host environment</param>
|
||||
<param name="k">Number of centroids</param>
|
||||
<param name="centroids">Coordinates of the centroids</param>
|
||||
<param name="copyIn">If true then the <paramref name="centroids"/> vectors will be subject to
|
||||
a deep copy, if false then this constructor will take ownership of the passed in centroid vectors.
|
||||
If false then the caller must take care to not use or modify the input vectors once this object
|
||||
is constructed, and should probably remove all references.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansModelParameters.#ctor(Microsoft.ML.Runtime.IHostEnvironment,Microsoft.ML.ModelLoadContext)">
|
||||
<summary>
|
||||
Initialize predictor from a binary file.
|
||||
</summary>
|
||||
<param name="ctx">The load context</param>
|
||||
<param name="env">The host environment</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansModelParameters.SaveCore(Microsoft.ML.ModelSaveContext)">
|
||||
<summary>
|
||||
Save the predictor in binary format.
|
||||
</summary>
|
||||
<param name="ctx">The context to save to</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansModelParameters.Create(Microsoft.ML.Runtime.IHostEnvironment,Microsoft.ML.ModelLoadContext)">
|
||||
<summary>
|
||||
This method is called by reflection to instantiate a predictor.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansModelParameters.InitPredictor">
|
||||
<summary>
|
||||
Initialize internal parameters: L2 norms of the _centroids.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansModelParameters.GetClusterCentroids(Microsoft.ML.Data.VBuffer{System.Single}[]@,System.Int32@)">
|
||||
<summary>
|
||||
Copies the centroids to a set of provided buffers.
|
||||
</summary>
|
||||
<param name="centroids">The buffer to which to copy. Will be extended to
|
||||
an appropriate length, if necessary.</param>
|
||||
<param name="k">The number of clusters, corresponding to the logical size of
|
||||
<paramref name="centroids"/>.</param>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Trainers.KMeansTrainer">
|
||||
<summary>
|
||||
The <see cref="T:Microsoft.ML.IEstimator`1"/> for training a KMeans clusterer
|
||||
</summary>
|
||||
<remarks>
|
||||
<format type="text/markdown"><)
|
||||
or [Kmeans(Options)](xref:Microsoft.ML.KMeansClusteringExtensions.KMeans(Microsoft.ML.ClusteringCatalog.ClusteringTrainers,Microsoft.ML.Trainers.KMeansTrainer.Options)).
|
||||
|
||||
[!include[io](~/../docs/samples/docs/api-reference/io-columns-clustering.md)]
|
||||
|
||||
### Trainer Characteristics
|
||||
| | |
|
||||
| -- | -- |
|
||||
| Machine learning task | Clustering |
|
||||
| Is normalization required? | Yes |
|
||||
| Is caching required? | Yes |
|
||||
| Required NuGet in addition to Microsoft.ML | None |
|
||||
| Exportable to ONNX | Yes |
|
||||
|
||||
### Training Algorithm Details
|
||||
[K-means](https://en.wikipedia.org/wiki/K-means_clustering) is a popular clustering algorithm.
|
||||
With K-means, the data is clustered into a specified number of clusters in order to minimize the within-cluster sum of squared distances.
|
||||
This implementation follows the [Yinyang K-means method](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/ding15.pdf).
|
||||
For choosing the initial cluster centeroids, one of three options can be used:
|
||||
- Random initialization. This might lead to potentially bad approximations of the optimal clustering.
|
||||
- The K-means++ method. This is an [improved initialization algorithm](https://en.wikipedia.org/wiki/K-means%2b%2b#Improved_initialization_algorithm)
|
||||
introduced [here](http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf) by Ding et al., that guarantees to find
|
||||
a solution that is $O(log K)$ competitive to the optimal K-means solution.
|
||||
- The K-means|| method. This method was introduced [here](https://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf) by Bahmani et al., and uses
|
||||
a parallel method that drastically reduces the number of passes needed to obtain a good initialization.
|
||||
|
||||
K-means|| is the default initialization method. The other methods can be specified in the [Options](xref:Microsoft.ML.Trainers.KMeansTrainer.Options)
|
||||
when creating the trainer using
|
||||
[KMeansTrainer(Options)](xref:Microsoft.ML.KMeansClusteringExtensions.KMeans(Microsoft.ML.ClusteringCatalog.ClusteringTrainers,Microsoft.ML.Trainers.KMeansTrainer.Options)).
|
||||
|
||||
### Scoring Function
|
||||
The output Score column contains the square of the $L_2$-norm distance (i.e., [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance)) of the given input vector $\textbf{x}\in \mathbb{R}^n$ to each cluster's centroid.
|
||||
Assume that the centriod of the $c$-th cluster is $\textbf{m}_c \in \mathbb{R}^n$.
|
||||
The $c$-th value at the Score column would be $d_c = || \textbf{x} - \textbf{m}\_c ||\_2^2$.
|
||||
The predicted label is the index with the smallest value in a $K$ dimensional vector $[d\_{0}, \dots, d\_{K-1}]$, where $K$ is the number of clusters.
|
||||
|
||||
For more information on K-means, and K-means++ see:
|
||||
[K-means](https://en.wikipedia.org/wiki/K-means_clustering)
|
||||
[K-means++](https://en.wikipedia.org/wiki/K-means%2b%2b)
|
||||
|
||||
Check the See Also section for links to usage examples.
|
||||
]]>
|
||||
</format>
|
||||
</remarks>
|
||||
<seealso cref="T:Microsoft.ML.Trainers.KMeansTrainer" />
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Trainers.KMeansTrainer.Defaults.NumberOfClusters">
|
||||
<value>The number of clusters.</value>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Trainers.KMeansTrainer.Options">
|
||||
<summary>
|
||||
Options for the <see cref="T:Microsoft.ML.Trainers.KMeansTrainer"/> as used in [KMeansTrainer(Options)](xref:Microsoft.ML.KMeansClusteringExtensions.KMeans(Microsoft.ML.ClusteringCatalog.ClusteringTrainers,Microsoft.ML.Trainers.KMeansTrainer.Options)).
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Trainers.KMeansTrainer.Options.NumberOfClusters">
|
||||
<summary>
|
||||
The number of clusters.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Trainers.KMeansTrainer.Options.InitializationAlgorithm">
|
||||
<summary>
|
||||
Cluster initialization algorithm.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Trainers.KMeansTrainer.Options.OptimizationTolerance">
|
||||
<summary>
|
||||
Tolerance parameter for trainer convergence. Low = slower, more accurate.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Trainers.KMeansTrainer.Options.MaximumNumberOfIterations">
|
||||
<summary>
|
||||
Maximum number of iterations.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Trainers.KMeansTrainer.Options.AccelerationMemoryBudgetMb">
|
||||
<summary>
|
||||
Memory budget (in MBs) to use for KMeans acceleration.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Trainers.KMeansTrainer.Options.NumberOfThreads">
|
||||
<summary>
|
||||
Degree of lock-free parallelism. Defaults to automatic. Determinism not guaranteed.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansTrainer.#ctor(Microsoft.ML.Runtime.IHostEnvironment,Microsoft.ML.Trainers.KMeansTrainer.Options)">
|
||||
<summary>
|
||||
Initializes a new instance of <see cref="T:Microsoft.ML.Trainers.KMeansTrainer"/>
|
||||
</summary>
|
||||
<param name="env">The <see cref="T:Microsoft.ML.Runtime.IHostEnvironment"/> to use.</param>
|
||||
<param name="options">The advanced options of the algorithm.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansPlusPlusInit.Initialize(Microsoft.ML.Runtime.IHost,System.Int32,Microsoft.ML.Runtime.IChannel,Microsoft.ML.Trainers.FeatureFloatVectorCursor.Factory,System.Int32,System.Int32,Microsoft.ML.Data.VBuffer{System.Single}[],System.Int64@,System.Int64@,System.Boolean)">
|
||||
<summary>
|
||||
Initialize starting centroids via KMeans++ algorithm. This algorithm will always run single-threaded,
|
||||
regardless of the value of <paramref name="numThreads" />.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Trainers.KMeansAcceleratedRowMap">
|
||||
<summary>
|
||||
An instance of this class is used by SharedStates in YinYangTrainer
|
||||
and KMeansBarBarInitialization. It effectively bounds MaxInstancesToAccelerate and
|
||||
initializes RowIndexGetter.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansAcceleratedRowMap.BuildParallelIndexLookup(Microsoft.ML.Trainers.FeatureFloatVectorCursor.Factory)">
|
||||
<summary>
|
||||
Initializes the parallel index lookup HashArray using a sequential RowCursor. We
|
||||
preinitialize the HashArray so we can perform lock-free lookup operations during
|
||||
the primary KMeans pass.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Trainers.KMeansBarBarInitialization.SharedState">
|
||||
<summary>
|
||||
Data for optimizing KMeans|| initialization. Very similar to SharedState class
|
||||
For every instance, there is a space for the best weight and best cluster computed.
|
||||
|
||||
In this class, new clusters mean the clusters that were added to the cluster set
|
||||
in the previous round of KMeans|| and old clusters are the rest of them (the ones
|
||||
that were added in the rounds before the previous one).
|
||||
|
||||
In every round of KMeans||, numSamplesPerRound new clusters are added to the set of clusters.
|
||||
There are 'numRounds' number of rounds. We compute and store the distance of each new
|
||||
cluster from every round to all of the previous clusters and use it
|
||||
to avoid unnecessary computation by applying the triangle inequality.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansBarBarInitialization.SharedState.SetInstanceCluster(System.Int32,System.Single,System.Int32)">
|
||||
<summary>
|
||||
When assigning an accelerated row to a cluster, we store away the weight
|
||||
to its closest cluster, as well as the identity of the new
|
||||
closest cluster. Note that bestWeight can be negative since it is
|
||||
corresponding to the weight of a distance which does not have
|
||||
the L2 norm of the point itself.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansBarBarInitialization.SharedState.SetClusterDistance(System.Int32,Microsoft.ML.Data.VBuffer{System.Single}@,System.Single,System.Int32,Microsoft.ML.Data.VBuffer{System.Single}@,System.Single)">
|
||||
<summary>
|
||||
Computes and stores the distance of a new cluster to an old cluster
|
||||
<paramref name="newClusterFeatures"/> must be between 0..numSamplesPerRound-1.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansBarBarInitialization.SharedState.CanWeightComputationBeAvoided(System.Single,System.Int32,System.Int32)">
|
||||
<summary>
|
||||
This function is the key to use triangle inequality. Given an instance x distance to the best
|
||||
old cluster, cOld, and distance of a new cluster, cNew, to cOld, this function evaluates whether
|
||||
the distance computation of dist(x,cNew) can be avoided.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansBarBarInitialization.FindBestCluster(Microsoft.ML.Data.VBuffer{System.Single}@,System.Int32,Microsoft.ML.Trainers.KMeansBarBarInitialization.SharedState,System.Int32,System.Int32,Microsoft.ML.Data.VBuffer{System.Single}[],System.Single[],System.Boolean,System.Boolean,System.Single@,System.Int32@)">
|
||||
<summary>
|
||||
This function finds the best cluster and the best weight for an instance using
|
||||
smart triangle inequality to avoid unnecessary weight computations.
|
||||
|
||||
Note that <paramref name="needToStoreWeight"/> is used to avoid the storing the new cluster in
|
||||
final round. After the final round, best cluster information will be ignored.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansBarBarInitialization.ComputeAccelerationMemoryRequirement(System.Int64,System.Int32,System.Int32,System.Boolean,System.Int64@,System.Int64@)">
|
||||
<summary>
|
||||
This method computes the memory requirement for _clusterDistances in SharedState (clusterBytes) and
|
||||
the maximum number of instances whose weight to the closest cluster can be memorized in order to avoid
|
||||
recomputation later.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansBarBarInitialization.Initialize(Microsoft.ML.Runtime.IHost,System.Int32,Microsoft.ML.Runtime.IChannel,Microsoft.ML.Trainers.FeatureFloatVectorCursor.Factory,System.Int32,System.Int32,Microsoft.ML.Data.VBuffer{System.Single}[],System.Int64,System.Int64@,System.Int64@)">
|
||||
<summary>
|
||||
KMeans|| Implementation, see https://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf
|
||||
This algorithm will require:
|
||||
- (k * overSampleFactor * rounds * dimensionality * 4) bytes for the final sampled clusters.
|
||||
- (k * overSampleFactor * numThreads * dimensionality * 4) bytes for the per-round sampling.
|
||||
|
||||
Uses memory in initializationState to cache distances and avoids unnecessary distance computations
|
||||
akin to YinYang-KMeans paper.
|
||||
|
||||
Everywhere in this function, weight of an instance x from a cluster c means weight(x,c) = dist(x,c)^2-norm(x)^2.
|
||||
We store weight in most cases to avoid unnecessary computation of norm(x).
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansRandomInit.Initialize(Microsoft.ML.Runtime.IHost,System.Int32,Microsoft.ML.Runtime.IChannel,Microsoft.ML.Trainers.FeatureFloatVectorCursor.Factory,System.Int32,Microsoft.ML.Data.VBuffer{System.Single}[],System.Int64@,System.Int64@)">
|
||||
<summary>
|
||||
Initialize starting centroids via reservoir sampling.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansLloydsYinYangTrain.WorkChunkStateBase.Reduce(Microsoft.ML.Trainers.KMeansLloydsYinYangTrain.WorkChunkState[],Microsoft.ML.Trainers.KMeansLloydsYinYangTrain.ReducedWorkChunkState)">
|
||||
<summary>
|
||||
Reduces the array of work chunks into this chunk, coalescing the
|
||||
results from multiple worker threads partitioned over a parallel cursor set and
|
||||
clearing their values to prepare them for the next iteration.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansLloydsYinYangTrain.ReducedWorkChunkState.UpdateClusters(Microsoft.ML.Data.VBuffer{System.Single}[],System.Single[],System.Single[],System.Single@)">
|
||||
<summary>
|
||||
Updates all the passed in variables with the results of the most recent iteration
|
||||
of cluster assignment. It is assumed that centroids will contain the previous results
|
||||
of this call.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansLloydsYinYangTrain.SharedState.SetYinYangCluster(System.Int32,Microsoft.ML.Data.VBuffer{System.Single}@,System.Single,System.Int32,System.Single)">
|
||||
<summary>
|
||||
When assigning an accelerated row to a cluster, we store away the distance
|
||||
to its closer and second closed cluster, as well as the identity of the new
|
||||
closest cluster. This method returns the last known closest cluster.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansLloydsYinYangTrain.SharedState.UpdateYinYangBounds(System.Int32)">
|
||||
<summary>
|
||||
Updates the known YinYang bounds for the given row using the centroid position
|
||||
deltas from the previous iteration.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansLloydsYinYangTrain.SharedState.IsYinYangGloballyBound(System.Int32)">
|
||||
<summary>
|
||||
Determines if the triangle distance inequality still applies to the given row,
|
||||
allowing us to avoid per-cluster distance computation.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansLloydsYinYangTrain.ProcessChunk(Microsoft.ML.Trainers.FeatureFloatVectorCursor,Microsoft.ML.Trainers.KMeansLloydsYinYangTrain.SharedState,Microsoft.ML.Trainers.KMeansLloydsYinYangTrain.WorkChunkStateBase,System.Int32,Microsoft.ML.Data.VBuffer{System.Single}[],System.Single[])">
|
||||
<summary>
|
||||
Performs the 'update' step of KMeans. This method is passed a WorkChunkState. In the parallel version
|
||||
this chunk will be one of _numThreads chunks and the RowCursor will be part of a RowCursorSet. In the
|
||||
unthreaded version, this chunk will be the final chunk and hold state for the entire data set.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansUtils.ParallelWeightedReservoirSample(Microsoft.ML.Runtime.IHost,System.Int32,System.Int32,Microsoft.ML.Trainers.FeatureFloatVectorCursor.Factory,Microsoft.ML.Trainers.KMeansUtils.WeightFunc,Microsoft.ML.Trainers.KMeansUtils.RowIndexGetter,Microsoft.ML.Data.VBuffer{System.Single}[]@,Microsoft.ML.Internal.Utilities.Heap{Microsoft.ML.Trainers.KMeansUtils.WeightedPoint}[]@)">
|
||||
<summary>
|
||||
Performs a multithreaded version of weighted reservoir sampling, returning
|
||||
an array of numSamples, where each sample has been selected from the
|
||||
data set with a probability of numSamples/N * weight/(sum(weight)). Buffer
|
||||
is sized to the number of threads plus one and stores the minheaps needed to
|
||||
perform the per-thread reservoir samples.
|
||||
|
||||
This method assumes that the numSamples is much smaller than the full dataset as
|
||||
it expects to be able to sample numSamples * numThreads.
|
||||
|
||||
This is based on the 'A-Res' algorithm in 'Weighted Random Sampling', 2005; Efraimidis, Spirakis:
|
||||
https://utopia.duth.gr/~pefraimi/research/data/2007EncOfAlg.pdf
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansUtils.ParallelMapReduce``2(System.Int32,Microsoft.ML.Runtime.IHost,Microsoft.ML.Trainers.FeatureFloatVectorCursor.Factory,Microsoft.ML.Trainers.KMeansUtils.RowIndexGetter,Microsoft.ML.Trainers.KMeansUtils.InitAction{``0},Microsoft.ML.Trainers.KMeansUtils.MapAction{``0},Microsoft.ML.Trainers.KMeansUtils.ReduceAction{``0,``1},``0[]@,``1@)">
|
||||
<summary>
|
||||
Takes a data cursor and perform an in-memory parallel aggregation operation on it. This
|
||||
helper wraps some of the behavior common to parallel operations over a <see cref="T:Microsoft.ML.DataViewRowCursor"/> set,
|
||||
including building the set, creating separate Random instances, and <see cref="T:Microsoft.ML.DataViewRowCursor"/> disposal.
|
||||
</summary>
|
||||
<typeparam name="TPartitionState">The type that each parallel cursor will be expected to aggregate to.</typeparam>
|
||||
<typeparam name="TGlobalState">The type of the final output from combining each per-thread instance of TInterAgg.</typeparam>
|
||||
<param name="numThreads"></param>
|
||||
<param name="baseHost"></param>
|
||||
<param name="factory"></param>
|
||||
<param name="rowIndexGetter"></param>
|
||||
<param name="initChunk">Initializes an instance of TInterAgg, or prepares/clears it if it is already allocated.</param>
|
||||
<param name="mapper">Invoked for every row, should update TInterAgg using row cursor data.</param>
|
||||
<param name="reducer">Invoked after all row cursors have completed, combines the entire array of TInterAgg instances into a final TAgg result.</param>
|
||||
<param name="buffer">A reusable buffer array of TInterAgg.</param>
|
||||
<param name="result">A reusable reference to the final result.</param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansUtils.FindBestCluster(Microsoft.ML.Data.VBuffer{System.Single}@,Microsoft.ML.Data.VBuffer{System.Single}[],System.Single[],System.Int32,System.Boolean,System.Single@,System.Int32@,System.Single@,System.Int32@)">
|
||||
<summary>
|
||||
Given a point and a set of centroids this method will determine the closest centroid
|
||||
using L2 distance. It will return a value equivalent to that distance, the index of the
|
||||
closest cluster, and a value equivalent to the distance to the second-nearest cluster.
|
||||
</summary>
|
||||
<param name="features"></param>
|
||||
<param name="centroids"></param>
|
||||
<param name="centroidL2s">The L2 norms of the centroids. Used for efficiency and expected to be computed up front.</param>
|
||||
<param name="centroidCount">The number of centroids. Must be less than or equal to the length of the centroid array.</param>
|
||||
<param name="needRealDistance">Whether to return a real L2 distance, or a value missing the L2 norm of <paramref name="features"/>.</param>
|
||||
<param name="minDistance">The distance between <paramref name="features"/> and the nearest centroid in <paramref name="centroids" />.</param>
|
||||
<param name="cluster">The index of the nearest centroid.</param>
|
||||
<param name="secMinDistance">The second nearest distance, or PosInf if <paramref name="centroids" /> only contains a single point.</param>
|
||||
<param name="secCluster">The index of the second nearest centroid, or -1 if <paramref name="centroids" /> only contains a single point.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.KMeansUtils.VerifyModelConsistency(Microsoft.ML.Data.VBuffer{System.Single}[])">
|
||||
<summary>
|
||||
Checks that all coordinates of all centroids are finite, and throws otherwise
|
||||
</summary>
|
||||
</member>
|
||||
</members>
|
||||
</doc>
|
||||
BIN
W/Debug_Folder/Microsoft.ML.PCA.dll
Normal file
BIN
W/Debug_Folder/Microsoft.ML.PCA.dll
Normal file
Binary file not shown.
330
W/Debug_Folder/Microsoft.ML.PCA.xml
Normal file
330
W/Debug_Folder/Microsoft.ML.PCA.xml
Normal file
|
|
@ -0,0 +1,330 @@
|
|||
<?xml version="1.0"?>
|
||||
<doc>
|
||||
<assembly>
|
||||
<name>Microsoft.ML.PCA</name>
|
||||
</assembly>
|
||||
<members>
|
||||
<member name="T:Microsoft.ML.PcaCatalog">
|
||||
<summary>
|
||||
Collection of extension methods used by the <see cref="T:Microsoft.ML.AnomalyDetectionCatalog.AnomalyDetectionTrainers"/>,
|
||||
and <see cref="T:Microsoft.ML.TransformsCatalog"/> catalogs to create instances of Principal Component Analysis (PCA) components.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.PcaCatalog.ProjectToPrincipalComponents(Microsoft.ML.TransformsCatalog,System.String,System.String,System.String,System.Int32,System.Int32,System.Boolean,System.Nullable{System.Int32})">
|
||||
<summary>Initializes a new instance of <see cref="T:Microsoft.ML.Transforms.PrincipalComponentAnalyzer"/>.</summary>
|
||||
<param name="catalog">The transform's catalog.</param>
|
||||
<param name="outputColumnName">Name of the column resulting from the transformation of <paramref name="inputColumnName"/>.</param>
|
||||
<param name="inputColumnName">Name of column to transform. If set to <see langword="null"/>, the value of the <paramref name="outputColumnName"/> will be used as source.</param>
|
||||
<param name="exampleWeightColumnName">The name of the example weight column (optional).</param>
|
||||
<param name="rank">The number of principal components.</param>
|
||||
<param name="overSampling">Oversampling parameter for randomized PrincipalComponentAnalysis training.</param>
|
||||
<param name="ensureZeroMean">If enabled, data is centered to be zero mean.</param>
|
||||
<param name="seed">The seed for random number generation.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.PcaCatalog.ProjectToPrincipalComponents(Microsoft.ML.TransformsCatalog,Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions[])">
|
||||
<summary>Initializes a new instance of <see cref="T:Microsoft.ML.Transforms.PrincipalComponentAnalyzer"/>.</summary>
|
||||
<param name="catalog">The transform's catalog.</param>
|
||||
<param name="columns">Input columns to apply PrincipalComponentAnalysis on.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.PcaCatalog.RandomizedPca(Microsoft.ML.AnomalyDetectionCatalog.AnomalyDetectionTrainers,System.String,System.String,System.Int32,System.Int32,System.Boolean,System.Nullable{System.Int32})">
|
||||
<summary>
|
||||
Create <see cref="T:Microsoft.ML.Trainers.RandomizedPcaTrainer"/>, which trains an approximate principal component analysis (PCA) model using randomized singular value decomposition (SVD) algorithm.
|
||||
</summary>
|
||||
<param name="catalog">The anomaly detection catalog trainer object.</param>
|
||||
<param name="featureColumnName">The name of the feature column. The column data must be a known-sized vector of <see cref="T:System.Single"/>.</param>
|
||||
<param name="exampleWeightColumnName">The name of the example weight column (optional). To use the weight column, the column data
|
||||
must be of type <see cref="T:System.Single"/>.</param>
|
||||
<param name="rank">The number of components in the PCA.</param>
|
||||
<param name="oversampling">Oversampling parameter for randomized PCA training.</param>
|
||||
<param name="ensureZeroMean">If enabled, data is centered to be zero mean.</param>
|
||||
<param name="seed">The seed for random number generation.</param>
|
||||
<remarks>
|
||||
By default the threshold used to determine the label of a data point based on the predicted score is 0.5. Scores range from 0 to 1. A data point with predicted
|
||||
score higher than 0.5 is considered an outlier. Use <see cref="M:Microsoft.ML.AnomalyDetectionCatalog.ChangeModelThreshold``1(Microsoft.ML.Data.AnomalyPredictionTransformer{``0},System.Single)"/> to change this threshold.
|
||||
</remarks>
|
||||
<example>
|
||||
<format type="text/markdown">
|
||||
<]
|
||||
]]></format>
|
||||
</example>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.PcaCatalog.RandomizedPca(Microsoft.ML.AnomalyDetectionCatalog.AnomalyDetectionTrainers,Microsoft.ML.Trainers.RandomizedPcaTrainer.Options)">
|
||||
<summary>
|
||||
Create <see cref="T:Microsoft.ML.Trainers.RandomizedPcaTrainer"/> with advanced options, which trains an approximate principal component analysis (PCA) model using randomized singular value decomposition (SVD) algorithm.
|
||||
</summary>
|
||||
<param name="catalog">The anomaly detection catalog trainer object.</param>
|
||||
<param name="options">Advanced options to the algorithm.</param>
|
||||
<remarks>
|
||||
By default the threshold used to determine the label of a data point based on the predicted score is 0.5. Scores range from 0 to 1. A data point with predicted
|
||||
score higher than 0.5 is considered an outlier. Use <see cref="M:Microsoft.ML.AnomalyDetectionCatalog.ChangeModelThreshold``1(Microsoft.ML.Data.AnomalyPredictionTransformer{``0},System.Single)"/> to change this threshold.
|
||||
</remarks>
|
||||
<example>
|
||||
<format type="text/markdown">
|
||||
<]
|
||||
]]></format>
|
||||
</example>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Trainers.RandomizedPcaTrainer">
|
||||
<summary>
|
||||
The <see cref="T:Microsoft.ML.IEstimator`1"/> for training an approximate PCA using Randomized SVD algorithm.
|
||||
</summary>
|
||||
<remarks>
|
||||
<format type="text/markdown"><)
|
||||
or [RandomizedPca(Options)](xref:Microsoft.ML.PcaCatalog.RandomizedPca(Microsoft.ML.AnomalyDetectionCatalog.AnomalyDetectionTrainers,Microsoft.ML.Trainers.RandomizedPcaTrainer.Options)).
|
||||
|
||||
[!include[io](~/../docs/samples/docs/api-reference/io-columns-anomaly-detection.md)]
|
||||
|
||||
### Trainer Characteristics
|
||||
| | |
|
||||
| -- | -- |
|
||||
| Machine learning task | Anomaly Detection |
|
||||
| Is normalization required? | Yes |
|
||||
| Is caching required? | No |
|
||||
| Required NuGet in addition to Microsoft.ML | None |
|
||||
| Exportable to ONNX | No |
|
||||
|
||||
### Training Algorithm Details
|
||||
This trainer uses the top eigenvectors to approximate the subspace containing the normal class.
|
||||
For each new instance, it computes the norm difference between the raw feature vector and the projected feature on that subspace.
|
||||
If the error is close to 0, the instance is considered normal (non-anomaly).
|
||||
|
||||
More specifically, this trainer trains an approximate PCA using a randomized method for computing the singular value decomposition (SVD) of
|
||||
the matrix whose rows are the input vectors.
|
||||
The model generated by this trainer contains three parameters:
|
||||
- A projection matrix $U$
|
||||
- The mean vector in the original feature space $m$
|
||||
- The mean vector in the projected feature space $p$
|
||||
|
||||
For an input feature vector $x$, the anomaly score is computed by comparing the $L_2$
|
||||
norm of the original input vector, and the $L_2$ norm of the projected vector:
|
||||
$\sqrt{\left(\|x-m\|_2^2 - \|Ux-p\|_2^2\right)\|x-m\|_2^2}$.
|
||||
|
||||
The method is described [here](https://web.stanford.edu/group/mmds/slides2010/Martinsson.pdf).
|
||||
|
||||
Note that the algorithm can be made into Kernel PCA by applying the <xref:Microsoft.ML.Transforms.ApproximatedKernelTransformer>
|
||||
to the data before passing it to the trainer.
|
||||
|
||||
Check the See Also section for links to usage examples.
|
||||
]]>
|
||||
</format>
|
||||
</remarks>
|
||||
<seealso cref="M:Microsoft.ML.PcaCatalog.RandomizedPca(Microsoft.ML.AnomalyDetectionCatalog.AnomalyDetectionTrainers,System.String,System.String,System.Int32,System.Int32,System.Boolean,System.Nullable{System.Int32})"/>
|
||||
<seealso cref="M:Microsoft.ML.PcaCatalog.RandomizedPca(Microsoft.ML.AnomalyDetectionCatalog.AnomalyDetectionTrainers,Microsoft.ML.Trainers.RandomizedPcaTrainer.Options)"/>
|
||||
<seealso cref="T:Microsoft.ML.Trainers.RandomizedPcaTrainer.Options"/>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Trainers.RandomizedPcaTrainer.Options">
|
||||
<summary>
|
||||
Options for the <see cref="T:Microsoft.ML.Trainers.RandomizedPcaTrainer"/> as used in
|
||||
[RandomizedPca(Options)](xref:Microsoft.ML.PcaCatalog.RandomizedPca(Microsoft.ML.AnomalyDetectionCatalog.AnomalyDetectionTrainers,Microsoft.ML.Trainers.RandomizedPcaTrainer.Options)).
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.RandomizedPcaTrainer.#ctor(Microsoft.ML.Runtime.IHostEnvironment,System.String,System.String,System.Int32,System.Int32,System.Boolean,System.Nullable{System.Int32})">
|
||||
<summary>
|
||||
Initializes a new instance of <see cref="T:Microsoft.ML.Trainers.RandomizedPcaTrainer"/>.
|
||||
</summary>
|
||||
<param name="env">The local instance of the <see cref="T:Microsoft.ML.Runtime.IHostEnvironment"/>.</param>
|
||||
<param name="featureColumnName">The name of the feature column.</param>
|
||||
<param name="exampleWeightColumnName">The name of the weight column.</param>
|
||||
<param name="rank">The number of components in the PCA.</param>
|
||||
<param name="oversampling">Oversampling parameter for randomized PCA training.</param>
|
||||
<param name="ensureZeroMean">If enabled, data is centered to be zero mean.</param>
|
||||
<param name="seed">The seed for random number generation.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.RandomizedPcaTrainer.PostProcess(System.Single[][],System.Single[],System.Single[],System.Int32,System.Int32)">
|
||||
<summary>
|
||||
Modifies <paramref name="y"/> in place so it becomes <paramref name="y"/> * eigenvectors / eigenvalues.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Trainers.PcaModelParameters">
|
||||
<summary>
|
||||
Model parameters for <see cref="T:Microsoft.ML.Trainers.RandomizedPcaTrainer"/>.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.PcaModelParameters.#ctor(Microsoft.ML.Runtime.IHostEnvironment,System.Int32,System.Single[][],Microsoft.ML.Data.VBuffer{System.Single}@)">
|
||||
<summary>
|
||||
Instantiate new model parameters from trained model.
|
||||
</summary>
|
||||
<param name="env">The host environment.</param>
|
||||
<param name="rank">The rank of the PCA approximation of the covariance matrix. This is the number of eigenvectors in the model.</param>
|
||||
<param name="eigenVectors">Array of eigenvectors.</param>
|
||||
<param name="mean">The mean vector of the training data.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.PcaModelParameters.GetEigenVectors(Microsoft.ML.Data.VBuffer{System.Single}[]@,System.Int32@)">
|
||||
<summary>
|
||||
Copies the top eigenvectors of the covariance matrix of the training data
|
||||
into a set of buffers.
|
||||
</summary>
|
||||
<param name="vectors">A possibly reusable set of vectors, which will
|
||||
be expanded as necessary to accommodate the data.</param>
|
||||
<param name="rank">Set to the rank, which is also the logical length
|
||||
of <paramref name="vectors"/>.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Trainers.PcaModelParameters.GetMean(Microsoft.ML.Data.VBuffer{System.Single}@)">
|
||||
<summary>
|
||||
Copies the mean vector of the training data.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Transforms.PrincipalComponentAnalysisTransformer">
|
||||
<summary>
|
||||
PCA is a dimensionality-reduction transform which computes the projection of the feature vector onto a low-rank subspace.
|
||||
</summary><remarks>
|
||||
<a href="https://en.wikipedia.org/wiki/Principal_component_analysis">Principle Component Analysis (PCA)</a> is a dimensionality-reduction algorithm which computes the projection of the feature vector to onto a low-rank subspace.
|
||||
Its training is done using the technique described in the paper: <a href="https://arxiv.org/pdf/1310.6304v2.pdf">Combining Structured and Unstructured Randomness in Large Scale PCA</a>,
|
||||
and the paper <a href="https://arxiv.org/pdf/0909.4061v2.pdf">Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions</a>
|
||||
<para>For more information, see also:</para>
|
||||
<list type="bullet">
|
||||
<item><description>
|
||||
<a href="https://web.stanford.edu/group/mmds/slides2010/Martinsson.pdf">Randomized Methods for Computing the Singular Value Decomposition (SVD) of very large matrices</a>
|
||||
</description></item>
|
||||
<item><description>
|
||||
<a href="https://arxiv.org/abs/0809.2274">A randomized algorithm for principal component analysis</a>
|
||||
</description></item>
|
||||
<item><description>
|
||||
<a href="http://users.cms.caltech.edu/~jtropp/papers/HMT11-Finding-Structure-SIREV.pdf">Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions</a>
|
||||
</description></item>
|
||||
</list>
|
||||
</remarks>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Transforms.PrincipalComponentAnalyzer">
|
||||
<summary>
|
||||
PCA is a dimensionality-reduction transform which computes the projection of the feature vector onto a low-rank subspace.
|
||||
</summary><remarks>
|
||||
<a href="https://en.wikipedia.org/wiki/Principal_component_analysis">Principle Component Analysis (PCA)</a> is a dimensionality-reduction algorithm which computes the projection of the feature vector to onto a low-rank subspace.
|
||||
Its training is done using the technique described in the paper: <a href="https://arxiv.org/pdf/1310.6304v2.pdf">Combining Structured and Unstructured Randomness in Large Scale PCA</a>,
|
||||
and the paper <a href="https://arxiv.org/pdf/0909.4061v2.pdf">Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions</a>
|
||||
<para>For more information, see also:</para>
|
||||
<list type="bullet">
|
||||
<item><description>
|
||||
<a href="https://web.stanford.edu/group/mmds/slides2010/Martinsson.pdf">Randomized Methods for Computing the Singular Value Decomposition (SVD) of very large matrices</a>
|
||||
</description></item>
|
||||
<item><description>
|
||||
<a href="https://arxiv.org/abs/0809.2274">A randomized algorithm for principal component analysis</a>
|
||||
</description></item>
|
||||
<item><description>
|
||||
<a href="http://users.cms.caltech.edu/~jtropp/papers/HMT11-Finding-Structure-SIREV.pdf">Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions</a>
|
||||
</description></item>
|
||||
</list>
|
||||
</remarks>
|
||||
</member>
|
||||
<member name="T:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions">
|
||||
<summary>
|
||||
Describes how the transformer handles one column pair.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions.Name">
|
||||
<summary>
|
||||
Name of the column resulting from the transformation of <see cref="F:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions.InputColumnName"/>.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions.InputColumnName">
|
||||
<summary>
|
||||
Name of column to transform.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions.WeightColumn">
|
||||
<summary>
|
||||
The name of the weight column.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions.Rank">
|
||||
<summary>
|
||||
The number of components in the PCA.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions.Oversampling">
|
||||
<summary>
|
||||
Oversampling parameter for randomized PCA training.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions.EnsureZeroMean">
|
||||
<summary>
|
||||
If enabled, data is centered to be zero mean.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="F:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions.Seed">
|
||||
<summary>
|
||||
The seed for random number generation.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions.#ctor(System.String,System.String,System.String,System.Int32,System.Int32,System.Boolean,System.Nullable{System.Int32})">
|
||||
<summary>
|
||||
Describes how the transformer handles one column pair.
|
||||
</summary>
|
||||
<param name="name">Name of the column resulting from the transformation of <paramref name="inputColumnName"/>.</param>
|
||||
<param name="inputColumnName">Name of column to transform.
|
||||
If set to <see langword="null"/>, the value of the <paramref name="name"/> will be used as source.</param>
|
||||
<param name="weightColumn">The name of the weight column.</param>
|
||||
<param name="rank">The number of components in the PCA.</param>
|
||||
<param name="overSampling">Oversampling parameter for randomized PCA training.</param>
|
||||
<param name="ensureZeroMean">If enabled, data is centered to be zero mean.</param>
|
||||
<param name="seed">The random seed. If unspecified random state will be instead derived from the <see cref="T:Microsoft.ML.MLContext"/>.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.#ctor(Microsoft.ML.Runtime.IHostEnvironment,System.String,System.String,System.String,System.Int32,System.Int32,System.Boolean,System.Nullable{System.Int32})">
|
||||
<summary>
|
||||
PCA is a dimensionality-reduction transform which computes the projection of the feature vector onto a low-rank subspace.
|
||||
</summary><remarks>
|
||||
<a href="https://en.wikipedia.org/wiki/Principal_component_analysis">Principle Component Analysis (PCA)</a> is a dimensionality-reduction algorithm which computes the projection of the feature vector to onto a low-rank subspace.
|
||||
Its training is done using the technique described in the paper: <a href="https://arxiv.org/pdf/1310.6304v2.pdf">Combining Structured and Unstructured Randomness in Large Scale PCA</a>,
|
||||
and the paper <a href="https://arxiv.org/pdf/0909.4061v2.pdf">Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions</a>
|
||||
<para>For more information, see also:</para>
|
||||
<list type="bullet">
|
||||
<item><description>
|
||||
<a href="https://web.stanford.edu/group/mmds/slides2010/Martinsson.pdf">Randomized Methods for Computing the Singular Value Decomposition (SVD) of very large matrices</a>
|
||||
</description></item>
|
||||
<item><description>
|
||||
<a href="https://arxiv.org/abs/0809.2274">A randomized algorithm for principal component analysis</a>
|
||||
</description></item>
|
||||
<item><description>
|
||||
<a href="http://users.cms.caltech.edu/~jtropp/papers/HMT11-Finding-Structure-SIREV.pdf">Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions</a>
|
||||
</description></item>
|
||||
</list>
|
||||
</remarks>
|
||||
<param name="env">The environment to use.</param>
|
||||
<param name="outputColumnName">Name of the column resulting from the transformation of <paramref name="inputColumnName" />.</param>
|
||||
<param name="inputColumnName">Name of the column to transform.
|
||||
If set to <see langword="null" />, the value of the <paramref name="outputColumnName" /> will be used as source.</param>
|
||||
<param name="weightColumn">The name of the weight column.</param>
|
||||
<param name="rank">The number of components in the PCA.</param>
|
||||
<param name="overSampling">Oversampling parameter for randomized PCA training.</param>
|
||||
<param name="ensureZeroMean">If enabled, data is centered to be zero mean.</param>
|
||||
<param name="seed">The seed for random number generation.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.#ctor(Microsoft.ML.Runtime.IHostEnvironment,Microsoft.ML.Transforms.PrincipalComponentAnalyzer.ColumnOptions[])">
|
||||
<summary>
|
||||
PCA is a dimensionality-reduction transform which computes the projection of the feature vector onto a low-rank subspace.
|
||||
</summary><remarks>
|
||||
<a href="https://en.wikipedia.org/wiki/Principal_component_analysis">Principle Component Analysis (PCA)</a> is a dimensionality-reduction algorithm which computes the projection of the feature vector to onto a low-rank subspace.
|
||||
Its training is done using the technique described in the paper: <a href="https://arxiv.org/pdf/1310.6304v2.pdf">Combining Structured and Unstructured Randomness in Large Scale PCA</a>,
|
||||
and the paper <a href="https://arxiv.org/pdf/0909.4061v2.pdf">Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions</a>
|
||||
<para>For more information, see also:</para>
|
||||
<list type="bullet">
|
||||
<item><description>
|
||||
<a href="https://web.stanford.edu/group/mmds/slides2010/Martinsson.pdf">Randomized Methods for Computing the Singular Value Decomposition (SVD) of very large matrices</a>
|
||||
</description></item>
|
||||
<item><description>
|
||||
<a href="https://arxiv.org/abs/0809.2274">A randomized algorithm for principal component analysis</a>
|
||||
</description></item>
|
||||
<item><description>
|
||||
<a href="http://users.cms.caltech.edu/~jtropp/papers/HMT11-Finding-Structure-SIREV.pdf">Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions</a>
|
||||
</description></item>
|
||||
</list>
|
||||
</remarks>
|
||||
<param name="env">The environment to use.</param>
|
||||
<param name="columns">The dataset columns to use, and their specific settings.</param>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.Fit(Microsoft.ML.IDataView)">
|
||||
<summary>
|
||||
Trains and returns a <see cref="T:Microsoft.ML.Transforms.PrincipalComponentAnalysisTransformer"/>.
|
||||
</summary>
|
||||
</member>
|
||||
<member name="M:Microsoft.ML.Transforms.PrincipalComponentAnalyzer.GetOutputSchema(Microsoft.ML.SchemaShape)">
|
||||
<summary>
|
||||
Returns the <see cref="T:Microsoft.ML.SchemaShape"/> of the schema which will be produced by the transformer.
|
||||
Used for schema propagation and verification in a pipeline.
|
||||
</summary>
|
||||
</member>
|
||||
</members>
|
||||
</doc>
|
||||
BIN
W/Debug_Folder/Microsoft.ML.StandardTrainers.dll
Normal file
BIN
W/Debug_Folder/Microsoft.ML.StandardTrainers.dll
Normal file
Binary file not shown.
4565
W/Debug_Folder/Microsoft.ML.StandardTrainers.xml
Normal file
4565
W/Debug_Folder/Microsoft.ML.StandardTrainers.xml
Normal file
File diff suppressed because it is too large
Load diff
BIN
W/Debug_Folder/Microsoft.ML.Transforms.dll
Normal file
BIN
W/Debug_Folder/Microsoft.ML.Transforms.dll
Normal file
Binary file not shown.
7777
W/Debug_Folder/Microsoft.ML.Transforms.xml
Normal file
7777
W/Debug_Folder/Microsoft.ML.Transforms.xml
Normal file
File diff suppressed because it is too large
Load diff
BIN
W/Debug_Folder/Microsoft.ML.dll
Normal file
BIN
W/Debug_Folder/Microsoft.ML.dll
Normal file
Binary file not shown.
8
W/Debug_Folder/Microsoft.ML.xml
Normal file
8
W/Debug_Folder/Microsoft.ML.xml
Normal file
|
|
@ -0,0 +1,8 @@
|
|||
<?xml version="1.0"?>
|
||||
<doc>
|
||||
<assembly>
|
||||
<name>Microsoft.ML</name>
|
||||
</assembly>
|
||||
<members>
|
||||
</members>
|
||||
</doc>
|
||||
BIN
W/Debug_Folder/Newtonsoft.Json.dll
Normal file
BIN
W/Debug_Folder/Newtonsoft.Json.dll
Normal file
Binary file not shown.
11305
W/Debug_Folder/Newtonsoft.Json.xml
Normal file
11305
W/Debug_Folder/Newtonsoft.Json.xml
Normal file
File diff suppressed because it is too large
Load diff
BIN
W/Debug_Folder/System.Buffers.dll
Normal file
BIN
W/Debug_Folder/System.Buffers.dll
Normal file
Binary file not shown.
39
W/Debug_Folder/System.Buffers.xml
Normal file
39
W/Debug_Folder/System.Buffers.xml
Normal file
|
|
@ -0,0 +1,39 @@
|
|||
<?xml version="1.0" encoding="utf-8"?><span>
|
||||
<doc>
|
||||
<assembly>
|
||||
<name>System.Buffers</name>
|
||||
</assembly>
|
||||
<members>
|
||||
<member name="T:System.Buffers.ArrayPool`1">
|
||||
<summary>Provides a resource pool that enables reusing instances of type <see cref="T[]"></see>.</summary>
|
||||
<typeparam name="T">The type of the objects that are in the resource pool.</typeparam>
|
||||
</member>
|
||||
<member name="M:System.Buffers.ArrayPool`1.#ctor">
|
||||
<summary>Initializes a new instance of the <see cref="ArrayPool{T}"></see> class.</summary>
|
||||
</member>
|
||||
<member name="M:System.Buffers.ArrayPool`1.Create">
|
||||
<summary>Creates a new instance of the <see cref="ArrayPool{T}"></see> class.</summary>
|
||||
<returns>A new instance of the <see cref="ArrayPool{T}"></see> class.</returns>
|
||||
</member>
|
||||
<member name="M:System.Buffers.ArrayPool`1.Create(System.Int32,System.Int32)">
|
||||
<summary>Creates a new instance of the <see cref="ArrayPool{T}"></see> class using the specifed configuration.</summary>
|
||||
<param name="maxArrayLength">The maximum length of an array instance that may be stored in the pool.</param>
|
||||
<param name="maxArraysPerBucket">The maximum number of array instances that may be stored in each bucket in the pool. The pool groups arrays of similar lengths into buckets for faster access.</param>
|
||||
<returns>A new instance of the <see cref="ArrayPool{T}"></see> class with the specified configuration.</returns>
|
||||
</member>
|
||||
<member name="M:System.Buffers.ArrayPool`1.Rent(System.Int32)">
|
||||
<summary>Retrieves a buffer that is at least the requested length.</summary>
|
||||
<param name="minimumLength">The minimum length of the array.</param>
|
||||
<returns>An array of type <see cref="T[]"></see> that is at least <paramref name="minimumLength">minimumLength</paramref> in length.</returns>
|
||||
</member>
|
||||
<member name="M:System.Buffers.ArrayPool`1.Return(`0[],System.Boolean)">
|
||||
<summary>Returns an array to the pool that was previously obtained using the <see cref="Rent"></see> method on the same <see cref="ArrayPool{T}"></see> instance.</summary>
|
||||
<param name="array">A buffer to return to the pool that was previously obtained using the <see cref="Rent"></see> method.</param>
|
||||
<param name="clearArray">Indicates whether the contents of the buffer should be cleared before reuse. If <paramref name="bufferLength">bufferLength</paramref> is set to true, and if the pool will store the buffer to enable subsequent reuse, the <see cref="Return"></see> method will clear the <paramref name="array">array</paramref> of its contents so that a subsequent caller using the <see cref="Rent"></see> method will not see the content of the previous caller. If <paramref name="bufferLength">bufferLength</paramref> is set to false or if the pool will release the buffer, the array's contents are left unchanged.</param>
|
||||
</member>
|
||||
<member name="P:System.Buffers.ArrayPool`1.Shared">
|
||||
<summary>Gets a shared <see cref="ArrayPool{T}"></see> instance.</summary>
|
||||
<returns>A shared <see cref="ArrayPool{T}"></see> instance.</returns>
|
||||
</member>
|
||||
</members>
|
||||
</doc></span>
|
||||
BIN
W/Debug_Folder/System.CodeDom.dll
Normal file
BIN
W/Debug_Folder/System.CodeDom.dll
Normal file
Binary file not shown.
BIN
W/Debug_Folder/System.Collections.Immutable.dll
Normal file
BIN
W/Debug_Folder/System.Collections.Immutable.dll
Normal file
Binary file not shown.
4908
W/Debug_Folder/System.Collections.Immutable.xml
Normal file
4908
W/Debug_Folder/System.Collections.Immutable.xml
Normal file
File diff suppressed because it is too large
Load diff
BIN
W/Debug_Folder/System.Memory.dll
Normal file
BIN
W/Debug_Folder/System.Memory.dll
Normal file
Binary file not shown.
355
W/Debug_Folder/System.Memory.xml
Normal file
355
W/Debug_Folder/System.Memory.xml
Normal file
|
|
@ -0,0 +1,355 @@
|
|||
<?xml version="1.0" encoding="utf-8"?><doc>
|
||||
<assembly>
|
||||
<name>System.Memory</name>
|
||||
</assembly>
|
||||
<members>
|
||||
<member name="T:System.Span`1">
|
||||
<typeparam name="T"></typeparam>
|
||||
</member>
|
||||
<member name="M:System.Span`1.#ctor(`0[])">
|
||||
<param name="array"></param>
|
||||
</member>
|
||||
<member name="M:System.Span`1.#ctor(System.Void*,System.Int32)">
|
||||
<param name="pointer"></param>
|
||||
<param name="length"></param>
|
||||
</member>
|
||||
<member name="M:System.Span`1.#ctor(`0[],System.Int32)">
|
||||
<param name="array"></param>
|
||||
<param name="start"></param>
|
||||
</member>
|
||||
<member name="M:System.Span`1.#ctor(`0[],System.Int32,System.Int32)">
|
||||
<param name="array"></param>
|
||||
<param name="start"></param>
|
||||
<param name="length"></param>
|
||||
</member>
|
||||
<member name="M:System.Span`1.Clear">
|
||||
|
||||
</member>
|
||||
<member name="M:System.Span`1.CopyTo(System.Span{`0})">
|
||||
<param name="destination"></param>
|
||||
</member>
|
||||
<member name="M:System.Span`1.DangerousCreate(System.Object,`0@,System.Int32)">
|
||||
<param name="obj"></param>
|
||||
<param name="objectData"></param>
|
||||
<param name="length"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.DangerousGetPinnableReference">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="P:System.Span`1.Empty">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.Equals(System.Object)">
|
||||
<param name="obj"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.Fill(`0)">
|
||||
<param name="value"></param>
|
||||
</member>
|
||||
<member name="M:System.Span`1.GetHashCode">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="P:System.Span`1.IsEmpty">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="P:System.Span`1.Item(System.Int32)">
|
||||
<param name="index"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="P:System.Span`1.Length">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.op_Equality(System.Span{`0},System.Span{`0})">
|
||||
<param name="left"></param>
|
||||
<param name="right"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.op_Implicit(System.ArraySegment{T})~System.Span{T}">
|
||||
<param name="arraySegment"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.op_Implicit(System.Span{T})~System.ReadOnlySpan{T}">
|
||||
<param name="span"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.op_Implicit(T[])~System.Span{T}">
|
||||
<param name="array"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.op_Inequality(System.Span{`0},System.Span{`0})">
|
||||
<param name="left"></param>
|
||||
<param name="right"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.Slice(System.Int32)">
|
||||
<param name="start"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.Slice(System.Int32,System.Int32)">
|
||||
<param name="start"></param>
|
||||
<param name="length"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.ToArray">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Span`1.TryCopyTo(System.Span{`0})">
|
||||
<param name="destination"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="T:System.SpanExtensions">
|
||||
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.AsBytes``1(System.ReadOnlySpan{``0})">
|
||||
<param name="source"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.AsBytes``1(System.Span{``0})">
|
||||
<param name="source"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.AsSpan(System.String)">
|
||||
<param name="text"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.AsSpan``1(System.ArraySegment{``0})">
|
||||
<param name="arraySegment"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.AsSpan``1(``0[])">
|
||||
<param name="array"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.CopyTo``1(``0[],System.Span{``0})">
|
||||
<param name="array"></param>
|
||||
<param name="destination"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOf(System.Span{System.Byte},System.ReadOnlySpan{System.Byte})">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOf(System.Span{System.Byte},System.Byte)">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOf(System.ReadOnlySpan{System.Byte},System.Byte)">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOf(System.ReadOnlySpan{System.Byte},System.ReadOnlySpan{System.Byte})">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOf``1(System.ReadOnlySpan{``0},System.ReadOnlySpan{``0})">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOf``1(System.ReadOnlySpan{``0},``0)">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOf``1(System.Span{``0},System.ReadOnlySpan{``0})">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOf``1(System.Span{``0},``0)">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOfAny(System.ReadOnlySpan{System.Byte},System.Byte,System.Byte,System.Byte)">
|
||||
<param name="span"></param>
|
||||
<param name="value0"></param>
|
||||
<param name="value1"></param>
|
||||
<param name="value2"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOfAny(System.Span{System.Byte},System.Byte,System.Byte,System.Byte)">
|
||||
<param name="span"></param>
|
||||
<param name="value0"></param>
|
||||
<param name="value1"></param>
|
||||
<param name="value2"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOfAny(System.Span{System.Byte},System.Byte,System.Byte)">
|
||||
<param name="span"></param>
|
||||
<param name="value0"></param>
|
||||
<param name="value1"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOfAny(System.ReadOnlySpan{System.Byte},System.ReadOnlySpan{System.Byte})">
|
||||
<param name="span"></param>
|
||||
<param name="values"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOfAny(System.Span{System.Byte},System.ReadOnlySpan{System.Byte})">
|
||||
<param name="span"></param>
|
||||
<param name="values"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.IndexOfAny(System.ReadOnlySpan{System.Byte},System.Byte,System.Byte)">
|
||||
<param name="span"></param>
|
||||
<param name="value0"></param>
|
||||
<param name="value1"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.NonPortableCast``2(System.ReadOnlySpan{``0})">
|
||||
<param name="source"></param>
|
||||
<typeparam name="TFrom"></typeparam>
|
||||
<typeparam name="TTo"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.NonPortableCast``2(System.Span{``0})">
|
||||
<param name="source"></param>
|
||||
<typeparam name="TFrom"></typeparam>
|
||||
<typeparam name="TTo"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.SequenceEqual(System.ReadOnlySpan{System.Byte},System.ReadOnlySpan{System.Byte})">
|
||||
<param name="first"></param>
|
||||
<param name="second"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.SequenceEqual(System.Span{System.Byte},System.ReadOnlySpan{System.Byte})">
|
||||
<param name="first"></param>
|
||||
<param name="second"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.SequenceEqual``1(System.ReadOnlySpan{``0},System.ReadOnlySpan{``0})">
|
||||
<param name="first"></param>
|
||||
<param name="second"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.SequenceEqual``1(System.Span{``0},System.ReadOnlySpan{``0})">
|
||||
<param name="first"></param>
|
||||
<param name="second"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.StartsWith(System.ReadOnlySpan{System.Byte},System.ReadOnlySpan{System.Byte})">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.StartsWith(System.Span{System.Byte},System.ReadOnlySpan{System.Byte})">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.StartsWith``1(System.ReadOnlySpan{``0},System.ReadOnlySpan{``0})">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.SpanExtensions.StartsWith``1(System.Span{``0},System.ReadOnlySpan{``0})">
|
||||
<param name="span"></param>
|
||||
<param name="value"></param>
|
||||
<typeparam name="T"></typeparam>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="T:System.ReadOnlySpan`1">
|
||||
<typeparam name="T"></typeparam>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.#ctor(`0[])">
|
||||
<param name="array"></param>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.#ctor(System.Void*,System.Int32)">
|
||||
<param name="pointer"></param>
|
||||
<param name="length"></param>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.#ctor(`0[],System.Int32)">
|
||||
<param name="array"></param>
|
||||
<param name="start"></param>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.#ctor(`0[],System.Int32,System.Int32)">
|
||||
<param name="array"></param>
|
||||
<param name="start"></param>
|
||||
<param name="length"></param>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.CopyTo(System.Span{`0})">
|
||||
<param name="destination"></param>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.DangerousCreate(System.Object,`0@,System.Int32)">
|
||||
<param name="obj"></param>
|
||||
<param name="objectData"></param>
|
||||
<param name="length"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.DangerousGetPinnableReference">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="P:System.ReadOnlySpan`1.Empty">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.Equals(System.Object)">
|
||||
<param name="obj"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.GetHashCode">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="P:System.ReadOnlySpan`1.IsEmpty">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="P:System.ReadOnlySpan`1.Item(System.Int32)">
|
||||
<param name="index"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="P:System.ReadOnlySpan`1.Length">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.op_Equality(System.ReadOnlySpan{`0},System.ReadOnlySpan{`0})">
|
||||
<param name="left"></param>
|
||||
<param name="right"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.op_Implicit(System.ArraySegment{T})~System.ReadOnlySpan{T}">
|
||||
<param name="arraySegment"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.op_Implicit(T[])~System.ReadOnlySpan{T}">
|
||||
<param name="array"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.op_Inequality(System.ReadOnlySpan{`0},System.ReadOnlySpan{`0})">
|
||||
<param name="left"></param>
|
||||
<param name="right"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.Slice(System.Int32)">
|
||||
<param name="start"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.Slice(System.Int32,System.Int32)">
|
||||
<param name="start"></param>
|
||||
<param name="length"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.ToArray">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.ReadOnlySpan`1.TryCopyTo(System.Span{`0})">
|
||||
<param name="destination"></param>
|
||||
<returns></returns>
|
||||
</member>
|
||||
</members>
|
||||
</doc>
|
||||
BIN
W/Debug_Folder/System.Numerics.Vectors.dll
Normal file
BIN
W/Debug_Folder/System.Numerics.Vectors.dll
Normal file
Binary file not shown.
2597
W/Debug_Folder/System.Numerics.Vectors.xml
Normal file
2597
W/Debug_Folder/System.Numerics.Vectors.xml
Normal file
File diff suppressed because it is too large
Load diff
BIN
W/Debug_Folder/System.Runtime.CompilerServices.Unsafe.dll
Normal file
BIN
W/Debug_Folder/System.Runtime.CompilerServices.Unsafe.dll
Normal file
Binary file not shown.
200
W/Debug_Folder/System.Runtime.CompilerServices.Unsafe.xml
Normal file
200
W/Debug_Folder/System.Runtime.CompilerServices.Unsafe.xml
Normal file
|
|
@ -0,0 +1,200 @@
|
|||
<?xml version="1.0" encoding="utf-8"?><doc>
|
||||
<assembly>
|
||||
<name>System.Runtime.CompilerServices.Unsafe</name>
|
||||
</assembly>
|
||||
<members>
|
||||
<member name="T:System.Runtime.CompilerServices.Unsafe">
|
||||
<summary>Contains generic, low-level functionality for manipulating pointers.</summary>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.Add``1(``0@,System.Int32)">
|
||||
<summary>Adds an element offset to the given reference.</summary>
|
||||
<param name="source">The reference to add the offset to.</param>
|
||||
<param name="elementOffset">The offset to add.</param>
|
||||
<typeparam name="T">The type of reference.</typeparam>
|
||||
<returns>A new reference that reflects the addition of offset to pointer.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.Add``1(``0@,System.IntPtr)">
|
||||
<summary>Adds an element offset to the given reference.</summary>
|
||||
<param name="source">The reference to add the offset to.</param>
|
||||
<param name="elementOffset">The offset to add.</param>
|
||||
<typeparam name="T">The type of reference.</typeparam>
|
||||
<returns>A new reference that reflects the addition of offset to pointer.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.AddByteOffset``1(``0@,System.IntPtr)">
|
||||
<summary>Adds a byte offset to the given reference.</summary>
|
||||
<param name="source">The reference to add the offset to.</param>
|
||||
<param name="byteOffset">The offset to add.</param>
|
||||
<typeparam name="T">The type of reference.</typeparam>
|
||||
<returns>A new reference that reflects the addition of byte offset to pointer.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.AreSame``1(``0@,``0@)">
|
||||
<summary>Determines whether the specified references point to the same location.</summary>
|
||||
<param name="left">The first reference to compare.</param>
|
||||
<param name="right">The second reference to compare.</param>
|
||||
<typeparam name="T">The type of reference.</typeparam>
|
||||
<returns>true if <paramref name="left">left</paramref> and <paramref name="right">right</paramref> point to the same location; otherwise, false.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.As``1(System.Object)">
|
||||
<summary>Casts the given object to the specified type.</summary>
|
||||
<param name="o">The object to cast.</param>
|
||||
<typeparam name="T">The type which the object will be cast to.</typeparam>
|
||||
<returns>The original object, casted to the given type.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.As``2(``0@)">
|
||||
<summary>Reinterprets the given reference as a reference to a value of type <typeparamref name="TTo">TTo</typeparamref>.</summary>
|
||||
<param name="source">The reference to reinterpret.</param>
|
||||
<typeparam name="TFrom">The type of reference to reinterpret..</typeparam>
|
||||
<typeparam name="TTo">The desired type of the reference.</typeparam>
|
||||
<returns>A reference to a value of type <typeparamref name="TTo">TTo</typeparamref>.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.AsPointer``1(``0@)">
|
||||
<summary>Returns a pointer to the given by-ref parameter.</summary>
|
||||
<param name="value">The object whose pointer is obtained.</param>
|
||||
<typeparam name="T">The type of object.</typeparam>
|
||||
<returns>A pointer to the given value.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.AsRef``1(System.Void*)">
|
||||
<summary>Reinterprets the given location as a reference to a value of type <typeparamref name="T">T</typeparamref>.</summary>
|
||||
<param name="source">The location of the value to reference.</param>
|
||||
<typeparam name="T">The type of the interpreted location.</typeparam>
|
||||
<returns>A reference to a value of type <typeparamref name="T">T</typeparamref>.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.ByteOffset``1(``0@,``0@)">
|
||||
<summary>Determines the byte offset from origin to target from the given references.</summary>
|
||||
<param name="origin">The reference to origin.</param>
|
||||
<param name="target">The reference to target.</param>
|
||||
<typeparam name="T">The type of reference.</typeparam>
|
||||
<returns>Byte offset from origin to target i.e. <paramref name="target">target</paramref> - <paramref name="origin">origin</paramref>.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.Copy``1(System.Void*,``0@)">
|
||||
<summary>Copies a value of type <typeparamref name="T">T</typeparamref> to the given location.</summary>
|
||||
<param name="destination">The location to copy to.</param>
|
||||
<param name="source">A reference to the value to copy.</param>
|
||||
<typeparam name="T">The type of value to copy.</typeparam>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.Copy``1(``0@,System.Void*)">
|
||||
<summary>Copies a value of type <typeparamref name="T">T</typeparamref> to the given location.</summary>
|
||||
<param name="destination">The location to copy to.</param>
|
||||
<param name="source">A pointer to the value to copy.</param>
|
||||
<typeparam name="T">The type of value to copy.</typeparam>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.CopyBlock(System.Byte@,System.Byte@,System.UInt32)">
|
||||
<summary>Copies bytes from the source address to the destination address.</summary>
|
||||
<param name="destination">The destination address to copy to.</param>
|
||||
<param name="source">The source address to copy from.</param>
|
||||
<param name="byteCount">The number of bytes to copy.</param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.CopyBlock(System.Void*,System.Void*,System.UInt32)">
|
||||
<summary>Copies bytes from the source address to the destination address.</summary>
|
||||
<param name="destination">The destination address to copy to.</param>
|
||||
<param name="source">The source address to copy from.</param>
|
||||
<param name="byteCount">The number of bytes to copy.</param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.CopyBlockUnaligned(System.Void*,System.Void*,System.UInt32)">
|
||||
<summary>Copies bytes from the source address to the destination address
|
||||
without assuming architecture dependent alignment of the addresses.</summary>
|
||||
<param name="destination">The destination address to copy to.</param>
|
||||
<param name="source">The source address to copy from.</param>
|
||||
<param name="byteCount">The number of bytes to copy.</param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.CopyBlockUnaligned(System.Byte@,System.Byte@,System.UInt32)">
|
||||
<summary>Copies bytes from the source address to the destination address
|
||||
without assuming architecture dependent alignment of the addresses.</summary>
|
||||
<param name="destination">The destination address to copy to.</param>
|
||||
<param name="source">The source address to copy from.</param>
|
||||
<param name="byteCount">The number of bytes to copy.</param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.InitBlock(System.Byte@,System.Byte,System.UInt32)">
|
||||
<summary>Initializes a block of memory at the given location with a given initial value.</summary>
|
||||
<param name="startAddress">The address of the start of the memory block to initialize.</param>
|
||||
<param name="value">The value to initialize the block to.</param>
|
||||
<param name="byteCount">The number of bytes to initialize.</param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.InitBlock(System.Void*,System.Byte,System.UInt32)">
|
||||
<summary>Initializes a block of memory at the given location with a given initial value.</summary>
|
||||
<param name="startAddress">The address of the start of the memory block to initialize.</param>
|
||||
<param name="value">The value to initialize the block to.</param>
|
||||
<param name="byteCount">The number of bytes to initialize.</param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.InitBlockUnaligned(System.Byte@,System.Byte,System.UInt32)">
|
||||
<summary>Initializes a block of memory at the given location with a given initial value
|
||||
without assuming architecture dependent alignment of the address.</summary>
|
||||
<param name="startAddress">The address of the start of the memory block to initialize.</param>
|
||||
<param name="value">The value to initialize the block to.</param>
|
||||
<param name="byteCount">The number of bytes to initialize.</param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.InitBlockUnaligned(System.Void*,System.Byte,System.UInt32)">
|
||||
<summary>Initializes a block of memory at the given location with a given initial value
|
||||
without assuming architecture dependent alignment of the address.</summary>
|
||||
<param name="startAddress">The address of the start of the memory block to initialize.</param>
|
||||
<param name="value">The value to initialize the block to.</param>
|
||||
<param name="byteCount">The number of bytes to initialize.</param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.Read``1(System.Void*)">
|
||||
<summary>Reads a value of type <typeparamref name="T">T</typeparamref> from the given location.</summary>
|
||||
<param name="source">The location to read from.</param>
|
||||
<typeparam name="T">The type to read.</typeparam>
|
||||
<returns>An object of type <typeparamref name="T">T</typeparamref> read from the given location.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.ReadUnaligned``1(System.Byte@)">
|
||||
<summary>Reads a value of type <typeparamref name="T">T</typeparamref> from the given location
|
||||
without assuming architecture dependent alignment of the addresses.</summary>
|
||||
<param name="source">The location to read from.</param>
|
||||
<typeparam name="T">The type to read.</typeparam>
|
||||
<returns>An object of type <typeparamref name="T">T</typeparamref> read from the given location.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.ReadUnaligned``1(System.Void*)">
|
||||
<summary>Reads a value of type <typeparamref name="T">T</typeparamref> from the given location
|
||||
without assuming architecture dependent alignment of the addresses.</summary>
|
||||
<param name="source">The location to read from.</param>
|
||||
<typeparam name="T">The type to read.</typeparam>
|
||||
<returns>An object of type <typeparamref name="T">T</typeparamref> read from the given location.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.SizeOf``1">
|
||||
<summary>Returns the size of an object of the given type parameter.</summary>
|
||||
<typeparam name="T">The type of object whose size is retrieved.</typeparam>
|
||||
<returns>The size of an object of type <typeparamref name="T">T</typeparamref>.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.Subtract``1(``0@,System.Int32)">
|
||||
<summary>Subtracts an element offset from the given reference.</summary>
|
||||
<param name="source">The reference to subtract the offset from.</param>
|
||||
<param name="elementOffset">The offset to subtract.</param>
|
||||
<typeparam name="T">The type of reference.</typeparam>
|
||||
<returns>A new reference that reflects the subraction of offset from pointer.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.Subtract``1(``0@,System.IntPtr)">
|
||||
<summary>Subtracts an element offset from the given reference.</summary>
|
||||
<param name="source">The reference to subtract the offset from.</param>
|
||||
<param name="elementOffset">The offset to subtract.</param>
|
||||
<typeparam name="T">The type of reference.</typeparam>
|
||||
<returns>A new reference that reflects the subraction of offset from pointer.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.SubtractByteOffset``1(``0@,System.IntPtr)">
|
||||
<summary>Subtracts a byte offset from the given reference.</summary>
|
||||
<param name="source">The reference to subtract the offset from.</param>
|
||||
<param name="byteOffset"></param>
|
||||
<typeparam name="T">The type of reference.</typeparam>
|
||||
<returns>A new reference that reflects the subraction of byte offset from pointer.</returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.Write``1(System.Void*,``0)">
|
||||
<summary>Writes a value of type <typeparamref name="T">T</typeparamref> to the given location.</summary>
|
||||
<param name="destination">The location to write to.</param>
|
||||
<param name="value">The value to write.</param>
|
||||
<typeparam name="T">The type of value to write.</typeparam>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.WriteUnaligned``1(System.Byte@,``0)">
|
||||
<summary>Writes a value of type <typeparamref name="T">T</typeparamref> to the given location
|
||||
without assuming architecture dependent alignment of the addresses.</summary>
|
||||
<param name="destination">The location to write to.</param>
|
||||
<param name="value">The value to write.</param>
|
||||
<typeparam name="T">The type of value to write.</typeparam>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.Unsafe.WriteUnaligned``1(System.Void*,``0)">
|
||||
<summary>Writes a value of type <typeparamref name="T">T</typeparamref> to the given location
|
||||
without assuming architecture dependent alignment of the addresses.</summary>
|
||||
<param name="destination">The location to write to.</param>
|
||||
<param name="value">The value to write.</param>
|
||||
<typeparam name="T">The type of value to write.</typeparam>
|
||||
</member>
|
||||
</members>
|
||||
</doc>
|
||||
BIN
W/Debug_Folder/System.Threading.Channels.dll
Normal file
BIN
W/Debug_Folder/System.Threading.Channels.dll
Normal file
Binary file not shown.
217
W/Debug_Folder/System.Threading.Channels.xml
Normal file
217
W/Debug_Folder/System.Threading.Channels.xml
Normal file
|
|
@ -0,0 +1,217 @@
|
|||
<?xml version="1.0" encoding="utf-8"?>
|
||||
<doc>
|
||||
<assembly>
|
||||
<name>System.Threading.Channels</name>
|
||||
</assembly>
|
||||
<members>
|
||||
<member name="T:System.Threading.Channels.BoundedChannelFullMode">
|
||||
<summary>Specifies the behavior to use when writing to a bounded channel that is already full.</summary>
|
||||
</member>
|
||||
<member name="F:System.Threading.Channels.BoundedChannelFullMode.DropNewest">
|
||||
<summary>Removes and ignores the newest item in the channel in order to make room for the item being written.</summary>
|
||||
</member>
|
||||
<member name="F:System.Threading.Channels.BoundedChannelFullMode.DropOldest">
|
||||
<summary>Removes and ignores the oldest item in the channel in order to make room for the item being written.</summary>
|
||||
</member>
|
||||
<member name="F:System.Threading.Channels.BoundedChannelFullMode.DropWrite">
|
||||
<summary>Drops the item being written.</summary>
|
||||
</member>
|
||||
<member name="F:System.Threading.Channels.BoundedChannelFullMode.Wait">
|
||||
<summary>Waits for space to be available in order to complete the write operation.</summary>
|
||||
</member>
|
||||
<member name="T:System.Threading.Channels.BoundedChannelOptions">
|
||||
<summary>Provides options that control the behavior of bounded <see cref="T:System.Threading.Channels.Channel`1" /> instances.</summary>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.BoundedChannelOptions.#ctor(System.Int32)">
|
||||
<summary>Initializes the options.</summary>
|
||||
<param name="capacity">The maximum number of items the bounded channel may store.</param>
|
||||
</member>
|
||||
<member name="P:System.Threading.Channels.BoundedChannelOptions.Capacity">
|
||||
<summary>Gets or sets the maximum number of items the bounded channel may store.</summary>
|
||||
</member>
|
||||
<member name="P:System.Threading.Channels.BoundedChannelOptions.FullMode">
|
||||
<summary>Gets or sets the behavior incurred by write operations when the channel is full.</summary>
|
||||
</member>
|
||||
<member name="T:System.Threading.Channels.Channel">
|
||||
<summary>Provides static methods for creating channels.</summary>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.Channel.CreateBounded``1(System.Int32)">
|
||||
<summary>Creates a channel with the specified maximum capacity.</summary>
|
||||
<param name="capacity">The maximum number of items the channel may store.</param>
|
||||
<typeparam name="T">Specifies the type of data in the channel.</typeparam>
|
||||
<returns>The created channel.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.Channel.CreateBounded``1(System.Threading.Channels.BoundedChannelOptions)">
|
||||
<summary>Creates a channel with the specified maximum capacity.</summary>
|
||||
<param name="options">Options that guide the behavior of the channel.</param>
|
||||
<typeparam name="T">Specifies the type of data in the channel.</typeparam>
|
||||
<returns>The created channel.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.Channel.CreateUnbounded``1">
|
||||
<summary>Creates an unbounded channel usable by any number of readers and writers concurrently.</summary>
|
||||
<typeparam name="T">The type of data in the channel.</typeparam>
|
||||
<returns>The created channel.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.Channel.CreateUnbounded``1(System.Threading.Channels.UnboundedChannelOptions)">
|
||||
<summary>Creates an unbounded channel subject to the provided options.</summary>
|
||||
<param name="options">Options that guide the behavior of the channel.</param>
|
||||
<typeparam name="T">Specifies the type of data in the channel.</typeparam>
|
||||
<returns>The created channel.</returns>
|
||||
</member>
|
||||
<member name="T:System.Threading.Channels.Channel`1">
|
||||
<summary>Provides a base class for channels that support reading and writing elements of type <typeparamref name="T" />.</summary>
|
||||
<typeparam name="T">Specifies the type of data readable and writable in the channel.</typeparam>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.Channel`1.#ctor">
|
||||
<summary>Initializes an instance of the <see cref="T:System.Threading.Channels.Channel`1" /> class.</summary>
|
||||
</member>
|
||||
<member name="T:System.Threading.Channels.Channel`2">
|
||||
<summary>Provides a base class for channels that support reading elements of type <typeparamref name="TRead" /> and writing elements of type <typeparamref name="TWrite" />.</summary>
|
||||
<typeparam name="TWrite">Specifies the type of data that may be written to the channel.</typeparam>
|
||||
<typeparam name="TRead">Specifies the type of data that may be read from the channel.</typeparam>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.Channel`2.#ctor">
|
||||
<summary>Initializes an instance of the <see cref="T:System.Threading.Channels.Channel`2" /> class.</summary>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.Channel`2.op_Implicit(System.Threading.Channels.Channel{`0,`1})~System.Threading.Channels.ChannelReader{`1}">
|
||||
<summary>Implicit cast from a <see cref="T:System.Threading.Channels.Channel`2" /> to its readable half.</summary>
|
||||
<param name="channel">The <see cref="T:System.Threading.Channels.Channel`2" /> being cast.</param>
|
||||
<returns>The readable half.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.Channel`2.op_Implicit(System.Threading.Channels.Channel{`0,`1})~System.Threading.Channels.ChannelWriter{`0}">
|
||||
<summary>Implicit cast from a <see cref="T:System.Threading.Channels.Channel`2" /> to its writable half.</summary>
|
||||
<param name="channel">The <see cref="T:System.Threading.Channels.Channel`2" /> being cast.</param>
|
||||
<returns>The writable half.</returns>
|
||||
</member>
|
||||
<member name="P:System.Threading.Channels.Channel`2.Reader">
|
||||
<summary>Gets the readable half of this channel.</summary>
|
||||
</member>
|
||||
<member name="P:System.Threading.Channels.Channel`2.Writer">
|
||||
<summary>Gets the writable half of this channel.</summary>
|
||||
</member>
|
||||
<member name="T:System.Threading.Channels.ChannelClosedException">
|
||||
<summary>Exception thrown when a channel is used after it's been closed.</summary>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelClosedException.#ctor">
|
||||
<summary>Initializes a new instance of the <see cref="T:System.Threading.Channels.ChannelClosedException" /> class.</summary>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelClosedException.#ctor(System.Exception)">
|
||||
<summary>Initializes a new instance of the <see cref="T:System.Threading.Channels.ChannelClosedException" /> class.</summary>
|
||||
<param name="innerException">The exception that is the cause of this exception.</param>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelClosedException.#ctor(System.Runtime.Serialization.SerializationInfo,System.Runtime.Serialization.StreamingContext)">
|
||||
<summary>Initializes a new instance of the <see cref="T:System.Threading.Channels.ChannelClosedException" /> class with serialized data.</summary>
|
||||
<param name="info">The object that holds the serialized object data.</param>
|
||||
<param name="context">The contextual information about the source or destination.</param>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelClosedException.#ctor(System.String)">
|
||||
<summary>Initializes a new instance of the <see cref="T:System.Threading.Channels.ChannelClosedException" /> class.</summary>
|
||||
<param name="message">The message that describes the error.</param>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelClosedException.#ctor(System.String,System.Exception)">
|
||||
<summary>Initializes a new instance of the <see cref="T:System.Threading.Channels.ChannelClosedException" /> class.</summary>
|
||||
<param name="message">The message that describes the error.</param>
|
||||
<param name="innerException">The exception that is the cause of this exception.</param>
|
||||
</member>
|
||||
<member name="T:System.Threading.Channels.ChannelOptions">
|
||||
<summary>Provides options that control the behavior of channel instances.</summary>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelOptions.#ctor">
|
||||
<summary>Initializes an instance of the <see cref="T:System.Threading.Channels.ChannelOptions" /> class.</summary>
|
||||
</member>
|
||||
<member name="P:System.Threading.Channels.ChannelOptions.AllowSynchronousContinuations">
|
||||
<summary>
|
||||
<see langword="true" /> if operations performed on a channel may synchronously invoke continuations subscribed to
|
||||
notifications of pending async operations; <see langword="false" /> if all continuations should be invoked asynchronously.</summary>
|
||||
</member>
|
||||
<member name="P:System.Threading.Channels.ChannelOptions.SingleReader">
|
||||
<summary>
|
||||
<see langword="true" /> readers from the channel guarantee that there will only ever be at most one read operation at a time;
|
||||
<see langword="false" /> if no such constraint is guaranteed.</summary>
|
||||
</member>
|
||||
<member name="P:System.Threading.Channels.ChannelOptions.SingleWriter">
|
||||
<summary>
|
||||
<see langword="true" /> if writers to the channel guarantee that there will only ever be at most one write operation
|
||||
at a time; <see langword="false" /> if no such constraint is guaranteed.</summary>
|
||||
</member>
|
||||
<member name="T:System.Threading.Channels.ChannelReader`1">
|
||||
<summary>Provides a base class for reading from a channel.</summary>
|
||||
<typeparam name="T">Specifies the type of data that may be read from the channel.</typeparam>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelReader`1.#ctor">
|
||||
<summary>Initializes an instance of the <see cref="T:System.Threading.Channels.ChannelReader`1" /> class.</summary>
|
||||
</member>
|
||||
<member name="P:System.Threading.Channels.ChannelReader`1.Completion">
|
||||
<summary>Gets a <see cref="T:System.Threading.Tasks.Task" /> that completes when no more data will ever
|
||||
be available to be read from this channel.</summary>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelReader`1.ReadAllAsync(System.Threading.CancellationToken)">
|
||||
<summary>Creates an <see cref="T:System.Collections.Generic.IAsyncEnumerable`1" /> that enables reading all of the data from the channel.</summary>
|
||||
<param name="cancellationToken">The cancellation token to use to cancel the enumeration.</param>
|
||||
<returns>The created async enumerable.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelReader`1.ReadAsync(System.Threading.CancellationToken)">
|
||||
<summary>Asynchronously reads an item from the channel.</summary>
|
||||
<param name="cancellationToken">A <see cref="T:System.Threading.CancellationToken" /> used to cancel the read operation.</param>
|
||||
<returns>A <see cref="T:System.Threading.Tasks.ValueTask`1" /> that represents the asynchronous read operation.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelReader`1.TryRead(`0@)">
|
||||
<summary>Attempts to read an item from the channel.</summary>
|
||||
<param name="item">The read item, or a default value if no item could be read.</param>
|
||||
<returns>
|
||||
<see langword="true" /> if an item was read; otherwise, <see langword="false" />.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelReader`1.WaitToReadAsync(System.Threading.CancellationToken)">
|
||||
<summary>Returns a <see cref="T:System.Threading.Tasks.ValueTask`1" /> that will complete when data is available to read.</summary>
|
||||
<param name="cancellationToken">A <see cref="T:System.Threading.CancellationToken" /> used to cancel the wait operation.</param>
|
||||
<returns>A <see cref="T:System.Threading.Tasks.ValueTask`1" /> that will complete with a <see langword="true" /> result when data is available to read
|
||||
or with a <see langword="false" /> result when no further data will ever be available to be read due to the channel completing successfully.
|
||||
If the channel completes with an exception, the task will also complete with an exception.
|
||||
.</returns>
|
||||
</member>
|
||||
<member name="T:System.Threading.Channels.ChannelWriter`1">
|
||||
<summary>Provides a base class for writing to a channel.</summary>
|
||||
<typeparam name="T">Specifies the type of data that may be written to the channel.</typeparam>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelWriter`1.#ctor">
|
||||
<summary>Initializes an instance of the <see cref="T:System.Threading.Channels.ChannelWriter`1" /> class.</summary>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelWriter`1.Complete(System.Exception)">
|
||||
<summary>Mark the channel as being complete, meaning no more items will be written to it.</summary>
|
||||
<param name="error">Optional Exception indicating a failure that's causing the channel to complete.</param>
|
||||
<exception cref="T:System.InvalidOperationException">The channel has already been marked as complete.</exception>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelWriter`1.TryComplete(System.Exception)">
|
||||
<summary>Attempts to mark the channel as being completed, meaning no more data will be written to it.</summary>
|
||||
<param name="error">An <see cref="T:System.Exception" /> indicating the failure causing no more data to be written, or null for success.</param>
|
||||
<returns>
|
||||
<see langword="true" /> if this operation successfully completes the channel; otherwise, <see langword="false" /> if the channel could not be marked for completion,
|
||||
for example due to having already been marked as such, or due to not supporting completion.
|
||||
.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelWriter`1.TryWrite(`0)">
|
||||
<summary>Attempts to write the specified item to the channel.</summary>
|
||||
<param name="item">The item to write.</param>
|
||||
<returns>
|
||||
<see langword="true" /> if the item was written; otherwise, <see langword="false" />.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelWriter`1.WaitToWriteAsync(System.Threading.CancellationToken)">
|
||||
<summary>Returns a <see cref="T:System.Threading.Tasks.ValueTask`1" /> that will complete when space is available to write an item.</summary>
|
||||
<param name="cancellationToken">A <see cref="T:System.Threading.CancellationToken" /> used to cancel the wait operation.</param>
|
||||
<returns>A <see cref="T:System.Threading.Tasks.ValueTask`1" /> that will complete with a <see langword="true" /> result when space is available to write an item
|
||||
or with a <see langword="false" /> result when no further writing will be permitted.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.ChannelWriter`1.WriteAsync(`0,System.Threading.CancellationToken)">
|
||||
<summary>Asynchronously writes an item to the channel.</summary>
|
||||
<param name="item">The value to write to the channel.</param>
|
||||
<param name="cancellationToken">A <see cref="T:System.Threading.CancellationToken" /> used to cancel the write operation.</param>
|
||||
<returns>A <see cref="T:System.Threading.Tasks.ValueTask" /> that represents the asynchronous write operation.</returns>
|
||||
</member>
|
||||
<member name="T:System.Threading.Channels.UnboundedChannelOptions">
|
||||
<summary>Provides options that control the behavior of unbounded <see cref="T:System.Threading.Channels.Channel`1" /> instances.</summary>
|
||||
</member>
|
||||
<member name="M:System.Threading.Channels.UnboundedChannelOptions.#ctor">
|
||||
<summary>Initializes a new instance of the <see cref="T:System.Threading.Channels.UnboundedChannelOptions" /> class.</summary>
|
||||
</member>
|
||||
</members>
|
||||
</doc>
|
||||
BIN
W/Debug_Folder/System.Threading.Tasks.Extensions.dll
Normal file
BIN
W/Debug_Folder/System.Threading.Tasks.Extensions.dll
Normal file
Binary file not shown.
166
W/Debug_Folder/System.Threading.Tasks.Extensions.xml
Normal file
166
W/Debug_Folder/System.Threading.Tasks.Extensions.xml
Normal file
|
|
@ -0,0 +1,166 @@
|
|||
<?xml version="1.0" encoding="utf-8"?><doc>
|
||||
<assembly>
|
||||
<name>System.Threading.Tasks.Extensions</name>
|
||||
</assembly>
|
||||
<members>
|
||||
<member name="T:System.Runtime.CompilerServices.ValueTaskAwaiter`1">
|
||||
<typeparam name="TResult"></typeparam>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.ValueTaskAwaiter`1.GetResult">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="P:System.Runtime.CompilerServices.ValueTaskAwaiter`1.IsCompleted">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.ValueTaskAwaiter`1.OnCompleted(System.Action)">
|
||||
<param name="continuation"></param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.ValueTaskAwaiter`1.UnsafeOnCompleted(System.Action)">
|
||||
<param name="continuation"></param>
|
||||
</member>
|
||||
<member name="T:System.Threading.Tasks.ValueTask`1">
|
||||
<summary>Provides a value type that wraps a <see cref="Task{TResult}"></see> and a <typeparamref name="TResult">TResult</typeparamref>, only one of which is used.</summary>
|
||||
<typeparam name="TResult">The result.</typeparam>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.#ctor(System.Threading.Tasks.Task{`0})">
|
||||
<summary>Initializes a new instance of the <see cref="ValueTask{TResult}"></see> class using the supplied task that represents the operation.</summary>
|
||||
<param name="task">The task.</param>
|
||||
<exception cref="T:System.ArgumentNullException">The <paramref name="task">task</paramref> argument is null.</exception>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.#ctor(`0)">
|
||||
<summary>Initializes a new instance of the <see cref="ValueTask{TResult}"></see> class using the supplied result of a successful operation.</summary>
|
||||
<param name="result">The result.</param>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.AsTask">
|
||||
<summary>Retrieves a <see cref="Task{TResult}"></see> object that represents this <see cref="ValueTask{TResult}"></see>.</summary>
|
||||
<returns>The <see cref="Task{TResult}"></see> object that is wrapped in this <see cref="ValueTask{TResult}"></see> if one exists, or a new <see cref="Task{TResult}"></see> object that represents the result.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.ConfigureAwait(System.Boolean)">
|
||||
<summary>Configures an awaiter for this value.</summary>
|
||||
<param name="continueOnCapturedContext">true to attempt to marshal the continuation back to the captured context; otherwise, false.</param>
|
||||
<returns>The configured awaiter.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.CreateAsyncMethodBuilder">
|
||||
<summary>Creates a method builder for use with an async method.</summary>
|
||||
<returns>The created builder.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.Equals(System.Object)">
|
||||
<summary>Determines whether the specified object is equal to the current object.</summary>
|
||||
<param name="obj">The object to compare with the current object.</param>
|
||||
<returns>true if the specified object is equal to the current object; otherwise, false.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.Equals(System.Threading.Tasks.ValueTask{`0})">
|
||||
<summary>Determines whether the specified <see cref="ValueTask{TResult}"></see> object is equal to the current <see cref="ValueTask{TResult}"></see> object.</summary>
|
||||
<param name="other">The object to compare with the current object.</param>
|
||||
<returns>true if the specified object is equal to the current object; otherwise, false.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.GetAwaiter">
|
||||
<summary>Creates an awaiter for this value.</summary>
|
||||
<returns>The awaiter.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.GetHashCode">
|
||||
<summary>Returns the hash code for this instance.</summary>
|
||||
<returns>The hash code for the current object.</returns>
|
||||
</member>
|
||||
<member name="P:System.Threading.Tasks.ValueTask`1.IsCanceled">
|
||||
<summary>Gets a value that indicates whether this object represents a canceled operation.</summary>
|
||||
<returns>true if this object represents a canceled operation; otherwise, false.</returns>
|
||||
</member>
|
||||
<member name="P:System.Threading.Tasks.ValueTask`1.IsCompleted">
|
||||
<summary>Gets a value that indicates whether this object represents a completed operation.</summary>
|
||||
<returns>true if this object represents a completed operation; otherwise, false.</returns>
|
||||
</member>
|
||||
<member name="P:System.Threading.Tasks.ValueTask`1.IsCompletedSuccessfully">
|
||||
<summary>Gets a value that indicates whether this object represents a successfully completed operation.</summary>
|
||||
<returns>true if this object represents a successfully completed operation; otherwise, false.</returns>
|
||||
</member>
|
||||
<member name="P:System.Threading.Tasks.ValueTask`1.IsFaulted">
|
||||
<summary>Gets a value that indicates whether this object represents a failed operation.</summary>
|
||||
<returns>true if this object represents a failed operation; otherwise, false.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.op_Equality(System.Threading.Tasks.ValueTask{`0},System.Threading.Tasks.ValueTask{`0})">
|
||||
<summary>Compares two values for equality.</summary>
|
||||
<param name="left">The first value to compare.</param>
|
||||
<param name="right">The second value to compare.</param>
|
||||
<returns>true if the two <see cref="ValueTask{TResult}"></see> values are equal; otherwise, false.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.op_Inequality(System.Threading.Tasks.ValueTask{`0},System.Threading.Tasks.ValueTask{`0})">
|
||||
<summary>Determines whether two <see cref="ValueTask{TResult}"></see> values are unequal.</summary>
|
||||
<param name="left">The first value to compare.</param>
|
||||
<param name="right">The seconed value to compare.</param>
|
||||
<returns>true if the two <see cref="ValueTask{TResult}"></see> values are not equal; otherwise, false.</returns>
|
||||
</member>
|
||||
<member name="P:System.Threading.Tasks.ValueTask`1.Result">
|
||||
<summary>Gets the result.</summary>
|
||||
<returns>The result.</returns>
|
||||
</member>
|
||||
<member name="M:System.Threading.Tasks.ValueTask`1.ToString">
|
||||
<summary>Returns a string that represents the current object.</summary>
|
||||
<returns>A string that represents the current object.</returns>
|
||||
</member>
|
||||
<member name="T:System.Runtime.CompilerServices.AsyncMethodBuilderAttribute">
|
||||
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.AsyncMethodBuilderAttribute.#ctor(System.Type)">
|
||||
<param name="builderType"></param>
|
||||
</member>
|
||||
<member name="P:System.Runtime.CompilerServices.AsyncMethodBuilderAttribute.BuilderType">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="T:System.Runtime.CompilerServices.AsyncValueTaskMethodBuilder`1">
|
||||
<typeparam name="TResult"></typeparam>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.AsyncValueTaskMethodBuilder`1.AwaitOnCompleted``2(``0@,``1@)">
|
||||
<param name="awaiter"></param>
|
||||
<param name="stateMachine"></param>
|
||||
<typeparam name="TAwaiter"></typeparam>
|
||||
<typeparam name="TStateMachine"></typeparam>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.AsyncValueTaskMethodBuilder`1.AwaitUnsafeOnCompleted``2(``0@,``1@)">
|
||||
<param name="awaiter"></param>
|
||||
<param name="stateMachine"></param>
|
||||
<typeparam name="TAwaiter"></typeparam>
|
||||
<typeparam name="TStateMachine"></typeparam>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.AsyncValueTaskMethodBuilder`1.Create">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.AsyncValueTaskMethodBuilder`1.SetException(System.Exception)">
|
||||
<param name="exception"></param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.AsyncValueTaskMethodBuilder`1.SetResult(`0)">
|
||||
<param name="result"></param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.AsyncValueTaskMethodBuilder`1.SetStateMachine(System.Runtime.CompilerServices.IAsyncStateMachine)">
|
||||
<param name="stateMachine"></param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.AsyncValueTaskMethodBuilder`1.Start``1(``0@)">
|
||||
<param name="stateMachine"></param>
|
||||
<typeparam name="TStateMachine"></typeparam>
|
||||
</member>
|
||||
<member name="P:System.Runtime.CompilerServices.AsyncValueTaskMethodBuilder`1.Task">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="T:System.Runtime.CompilerServices.ConfiguredValueTaskAwaitable`1.ConfiguredValueTaskAwaiter">
|
||||
<typeparam name="TResult"></typeparam>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.ConfiguredValueTaskAwaitable`1.ConfiguredValueTaskAwaiter.GetResult">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="P:System.Runtime.CompilerServices.ConfiguredValueTaskAwaitable`1.ConfiguredValueTaskAwaiter.IsCompleted">
|
||||
<returns></returns>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.ConfiguredValueTaskAwaitable`1.ConfiguredValueTaskAwaiter.OnCompleted(System.Action)">
|
||||
<param name="continuation"></param>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.ConfiguredValueTaskAwaitable`1.ConfiguredValueTaskAwaiter.UnsafeOnCompleted(System.Action)">
|
||||
<param name="continuation"></param>
|
||||
</member>
|
||||
<member name="T:System.Runtime.CompilerServices.ConfiguredValueTaskAwaitable`1">
|
||||
<typeparam name="TResult"></typeparam>
|
||||
</member>
|
||||
<member name="M:System.Runtime.CompilerServices.ConfiguredValueTaskAwaitable`1.GetAwaiter">
|
||||
<returns></returns>
|
||||
</member>
|
||||
</members>
|
||||
</doc>
|
||||
39
W/Debug_Folder/a.pas
Normal file
39
W/Debug_Folder/a.pas
Normal file
|
|
@ -0,0 +1,39 @@
|
|||
{$reference Microsoft.ML.Core.dll}
|
||||
{$reference Microsoft.ML.Data.dll}
|
||||
{$reference Microsoft.ML.KMeansClustering.dll}
|
||||
|
||||
uses Microsoft.ML;
|
||||
uses Microsoft.ML.Data;
|
||||
uses Microsoft.ML.Trainers;
|
||||
uses Microsoft.ML.Transforms;
|
||||
|
||||
begin
|
||||
var Context := new MLContext();
|
||||
{var loader := Context.Data.CreateTextLoader(
|
||||
Arr(
|
||||
new TextLoader.Column('SentimentText', DataKind.String, 1),
|
||||
new TextLoader.Column('Label', DataKind.Boolean, 0)
|
||||
));}
|
||||
var fullData := Context.Data.LoadFromTextFile('iris-full.txt',
|
||||
Arr(
|
||||
new TextLoader.Column('Label', DataKind.Single, 0),
|
||||
new TextLoader.Column('SepalLength', DataKind.Single, 1),
|
||||
new TextLoader.Column('SepalWidth', DataKind.Single, 2),
|
||||
new TextLoader.Column('PetalLength', DataKind.Single, 3),
|
||||
new TextLoader.Column('PetalWidth', DataKind.Single, 4)
|
||||
),
|
||||
#9, True
|
||||
);
|
||||
var trainTestData := Context.Data.TrainTestSplit(fullData, 0.2);
|
||||
var trainingDataView := trainTestData.TrainSet;
|
||||
var testingDataView := trainTestData.TestSet;
|
||||
var dataProcessPipeline := Context.Transforms.Concatenate('Features',
|
||||
'SepalLength', 'SepalWidth', 'PetalLength', 'PetalWidth');
|
||||
|
||||
//var trainer: KMeansTrainer := Context.Clustering.Trainers.KMeans('Features', nil, 3);
|
||||
var trainer: IEstimator<ClusteringPredictionTransformer<KMeansModelParameters>>;
|
||||
//trainer := Context.Clustering.Trainers.KMeans('Features', nil, 3);
|
||||
//dataProcessPipeline.Append(new KMeansTrainer);
|
||||
//var trainingPipeline := dataProcessPipeline.Append(trainer);
|
||||
//var trainedModel := trainingPipeline.Fit(trainingDataView);
|
||||
end.
|
||||
11
W/Debug_Folder/a1.pas
Normal file
11
W/Debug_Folder/a1.pas
Normal file
|
|
@ -0,0 +1,11 @@
|
|||
{$reference Microsoft.ML.Core.dll}
|
||||
{$reference Microsoft.ML.Data.dll}
|
||||
{$reference Microsoft.ML.KMeansClustering.dll}
|
||||
|
||||
uses Microsoft.ML;
|
||||
uses Microsoft.ML.Data;
|
||||
uses Microsoft.ML.Trainers;
|
||||
|
||||
begin
|
||||
var trainer: IEstimator<ClusteringPredictionTransformer<KMeansModelParameters>>;
|
||||
end.
|
||||
152
W/Debug_Folder/iris-full.txt
Normal file
152
W/Debug_Folder/iris-full.txt
Normal file
|
|
@ -0,0 +1,152 @@
|
|||
#Label Sepal length Sepal width Petal length Petal width
|
||||
0 5.1 3.5 1.4 0.2
|
||||
0 4.9 3.0 1.4 0.2
|
||||
0 4.7 3.2 1.3 0.2
|
||||
0 4.6 3.1 1.5 0.2
|
||||
0 5.0 3.6 1.4 0.2
|
||||
0 5.4 3.9 1.7 0.4
|
||||
0 4.6 3.4 1.4 0.3
|
||||
0 5.0 3.4 1.5 0.2
|
||||
0 4.4 2.9 1.4 0.2
|
||||
0 4.9 3.1 1.5 0.1
|
||||
0 5.4 3.7 1.5 0.2
|
||||
0 4.8 3.4 1.6 0.2
|
||||
0 4.8 3.0 1.4 0.1
|
||||
0 4.3 3.0 1.1 0.1
|
||||
0 5.8 4.0 1.2 0.2
|
||||
0 5.7 4.4 1.5 0.4
|
||||
0 5.4 3.9 1.3 0.4
|
||||
0 5.1 3.5 1.4 0.3
|
||||
0 5.7 3.8 1.7 0.3
|
||||
0 5.1 3.8 1.5 0.3
|
||||
0 5.4 3.4 1.7 0.2
|
||||
0 5.1 3.7 1.5 0.4
|
||||
0 4.6 3.6 1.0 0.2
|
||||
0 5.1 3.3 1.7 0.5
|
||||
0 4.8 3.4 1.9 0.2
|
||||
0 5.0 3.0 1.6 0.2
|
||||
0 5.0 3.4 1.6 0.4
|
||||
0 5.2 3.5 1.5 0.2
|
||||
0 5.2 3.4 1.4 0.2
|
||||
0 4.7 3.2 1.6 0.2
|
||||
0 4.8 3.1 1.6 0.2
|
||||
0 5.4 3.4 1.5 0.4
|
||||
0 5.2 4.1 1.5 0.1
|
||||
0 5.5 4.2 1.4 0.2
|
||||
0 4.9 3.1 1.5 0.1
|
||||
0 5.0 3.2 1.2 0.2
|
||||
0 5.5 3.5 1.3 0.2
|
||||
0 4.9 3.1 1.5 0.1
|
||||
0 4.4 3.0 1.3 0.2
|
||||
0 5.1 3.4 1.5 0.2
|
||||
0 5.0 3.5 1.3 0.3
|
||||
0 4.5 2.3 1.3 0.3
|
||||
0 4.4 3.2 1.3 0.2
|
||||
0 5.0 3.5 1.6 0.6
|
||||
0 5.1 3.8 1.9 0.4
|
||||
0 4.8 3.0 1.4 0.3
|
||||
0 5.1 3.8 1.6 0.2
|
||||
0 4.6 3.2 1.4 0.2
|
||||
0 5.3 3.7 1.5 0.2
|
||||
0 5.0 3.3 1.4 0.2
|
||||
1 7.0 3.2 4.7 1.4
|
||||
1 6.4 3.2 4.5 1.5
|
||||
1 6.9 3.1 4.9 1.5
|
||||
1 5.5 2.3 4.0 1.3
|
||||
1 6.5 2.8 4.6 1.5
|
||||
1 5.7 2.8 4.5 1.3
|
||||
1 6.3 3.3 4.7 1.6
|
||||
1 4.9 2.4 3.3 1.0
|
||||
1 6.6 2.9 4.6 1.3
|
||||
1 5.2 2.7 3.9 1.4
|
||||
1 5.0 2.0 3.5 1.0
|
||||
1 5.9 3.0 4.2 1.5
|
||||
1 6.0 2.2 4.0 1.0
|
||||
1 6.1 2.9 4.7 1.4
|
||||
1 5.6 2.9 3.6 1.3
|
||||
1 6.7 3.1 4.4 1.4
|
||||
1 5.6 3.0 4.5 1.5
|
||||
1 5.8 2.7 4.1 1.0
|
||||
1 6.2 2.2 4.5 1.5
|
||||
1 5.6 2.5 3.9 1.1
|
||||
1 5.9 3.2 4.8 1.8
|
||||
1 6.1 2.8 4.0 1.3
|
||||
1 6.3 2.5 4.9 1.5
|
||||
1 6.1 2.8 4.7 1.2
|
||||
1 6.4 2.9 4.3 1.3
|
||||
1 6.6 3.0 4.4 1.4
|
||||
1 6.8 2.8 4.8 1.4
|
||||
1 6.7 3.0 5.0 1.7
|
||||
1 6.0 2.9 4.5 1.5
|
||||
1 5.7 2.6 3.5 1.0
|
||||
1 5.5 2.4 3.8 1.1
|
||||
1 5.5 2.4 3.7 1.0
|
||||
1 5.8 2.7 3.9 1.2
|
||||
1 6.0 2.7 5.1 1.6
|
||||
1 5.4 3.0 4.5 1.5
|
||||
1 6.0 3.4 4.5 1.6
|
||||
1 6.7 3.1 4.7 1.5
|
||||
1 6.3 2.3 4.4 1.3
|
||||
1 5.6 3.0 4.1 1.3
|
||||
1 5.5 2.5 4.0 1.3
|
||||
1 5.5 2.6 4.4 1.2
|
||||
1 6.1 3.0 4.6 1.4
|
||||
1 5.8 2.6 4.0 1.2
|
||||
1 5.0 2.3 3.3 1.0
|
||||
1 5.6 2.7 4.2 1.3
|
||||
1 5.7 3.0 4.2 1.2
|
||||
1 5.7 2.9 4.2 1.3
|
||||
1 6.2 2.9 4.3 1.3
|
||||
1 5.1 2.5 3.0 1.1
|
||||
1 5.7 2.8 4.1 1.3
|
||||
2 6.3 3.3 6.0 2.5
|
||||
2 5.8 2.7 5.1 1.9
|
||||
2 7.1 3.0 5.9 2.1
|
||||
2 6.3 2.9 5.6 1.8
|
||||
2 6.5 3.0 5.8 2.2
|
||||
2 7.6 3.0 6.6 2.1
|
||||
2 4.9 2.5 4.5 1.7
|
||||
2 7.3 2.9 6.3 1.8
|
||||
2 6.7 2.5 5.8 1.8
|
||||
2 7.2 3.6 6.1 2.5
|
||||
2 6.5 3.2 5.1 2.0
|
||||
2 6.4 2.7 5.3 1.9
|
||||
2 6.8 3.0 5.5 2.1
|
||||
2 5.7 2.5 5.0 2.0
|
||||
2 5.8 2.8 5.1 2.4
|
||||
2 6.4 3.2 5.3 2.3
|
||||
2 6.5 3.0 5.5 1.8
|
||||
2 7.7 3.8 6.7 2.2
|
||||
2 7.7 2.6 6.9 2.3
|
||||
2 6.0 2.2 5.0 1.5
|
||||
2 6.9 3.2 5.7 2.3
|
||||
2 5.6 2.8 4.9 2.0
|
||||
2 7.7 2.8 6.7 2.0
|
||||
2 6.3 2.7 4.9 1.8
|
||||
2 6.7 3.3 5.7 2.1
|
||||
2 7.2 3.2 6.0 1.8
|
||||
2 6.2 2.8 4.8 1.8
|
||||
2 6.1 3.0 4.9 1.8
|
||||
2 6.4 2.8 5.6 2.1
|
||||
2 7.2 3.0 5.8 1.6
|
||||
2 7.4 2.8 6.1 1.9
|
||||
2 7.9 3.8 6.4 2.0
|
||||
2 6.4 2.8 5.6 2.2
|
||||
2 6.3 2.8 5.1 1.5
|
||||
2 6.1 2.6 5.6 1.4
|
||||
2 7.7 3.0 6.1 2.3
|
||||
2 6.3 3.4 5.6 2.4
|
||||
2 6.4 3.1 5.5 1.8
|
||||
2 6.0 3.0 4.8 1.8
|
||||
2 6.9 3.1 5.4 2.1
|
||||
2 6.7 3.1 5.6 2.4
|
||||
2 6.9 3.1 5.1 2.3
|
||||
2 5.8 2.7 5.1 1.9
|
||||
2 6.8 3.2 5.9 2.3
|
||||
2 6.7 3.3 5.7 2.5
|
||||
2 6.7 3.0 5.2 2.3
|
||||
2 6.3 2.5 5.0 1.9
|
||||
2 6.5 3.0 5.2 2.0
|
||||
2 6.2 3.4 5.4 2.3
|
||||
2 5.9 3.0 5.1 1.8
|
||||
|
||||
Loading…
Reference in a new issue