Windows.AI.MachineLearning.MachineLearningContract

Describes the common properties that all features have.

A description of what this feature is used for in the model.

If true, you must bind a value to this feature before calling LearningModelSession.Evaluate.

If true, you must bind a value to this feature before calling **LearningModelSession.Evaluate**.

The kind of feature—use this to know which derived class to use.

The name you use to bind values to this feature.

The instantiated value for a feature.

The data type of the feature.

Describes the properties of the image the model is expecting.

Specifies the expected alpha mode of the image.

The alpha mode of the image.

Specifies the expected pixel format (channel ordering, bit depth, and data type).

The pixel format of the image.

A description of what this feature is used for in the model.

The expected image height.

If true, you must bind a value to this feature before calling LearningModelSession.Evaluate.

True if you must bind a value to this feature before calling LearningModelSession.Evaluate, otherwise false.

The kind of feature—use this to know which derived class to use.

The kind of feature.

The name you use to bind values to this feature.

The expected image width.

Describes the properties of the image used to pass into a model.

Gets the video frame.

The video frame.

Creates an ImageFeatureValue using the given video frame.

The video frame to use to create the **ImageFeatureValue**. The **ImageFeatureValue** created from the given video frame.

Tensors are multi-dimensional values.

Returns the count and size of each dimension.

The count and size of each dimension of the tensor.

Returns the data type of the tensor.

The data type of the tensor.

Represents a trained machine learning model.

The name of the model author.

A description of the model.

The domain of the model.

A list of the model's input features.

The raw <string,string> metadata from the ONNX model.

The name of the model.

A list of the model's output features.

The version of the model.

Releases the in-memory ONNX model. After calling this, you cannot create any more LearningModelSession objects.

Loads an ONNX model from a file on disk.

The path to the ONNX model file on disk. An object representing the model.

Loads an ONNX model from a file on disk.

The path to the ONNX model file on disk. An object representing the model.

Loads an ONNX model from an IStorageFile asynchronously.

The location of the model file. A LearningModel based on the model file.

Loads an ONNX model from an IStorageFile asynchronously.

The location of the model file. A LearningModel based on the model file.

Loads an ONNX model from a stream.

The stream from which to load the model. An object representing the model file.

Loads an ONNX model from a stream.

The stream from which to load the model. An object representing the model file.

Loads an ONNX model from a stream asynchronously.

The stream from which to load the model. An object representing the model.

Loads an ONNX model from a stream asynchronously.

The stream from which to load the model. An object representing the model.

Used to bind values to named input and output features.

Creates a LearningModelBinding from the specified LearningModelSession.

The **LearningModelSession** from which to create the **LearningModelBinding**.

Gets the number of elements in the map.

The number of elements in the map.

Bind a value to the named feature.

The name of the feature. The value to bind.

Bind a value to the named feature using properties to control the binding.

The name of the feature to which to bind. The value to bind to the feature. The properties to control the binding.

Remove all bindings.

Returns an iterator that is initialized to the first element in the map view.

An iterator that is initialized to the first element in the map view.

Determines whether the map view contains the specified key.

The key to check if it is contained in the map view. True if the map view contains the specified key; otherwise, false.

Returns the item at the specified key in the map view.

The key in the map view to look up. The item at the specified key in the map view.

Splits the map view into two views.

One half of the original map. The second half of the original map.

The device used to evaluate the machine learning model.

Create a LearningModelDevice from the specified LearningModelDeviceKind.

The specified **LearningModelDeviceKind** to evaluate the model on.

Returns the unique identifier for the device.

The unique identifier for the device.

Returns the IDirect3DDevice for the device.

The **IDirect3DDevice** for the device.

Create a LearningModelDevice from the specified IDirect3DDevice.

The **IDirect3DDevice** from which to create a **LearningModelDevice**. A **LearningModelDevice** created from the specified **IDirect3DDevice**.

Defines the list of device kinds that can evaluate a machine learning model.

Use the CPU to evaluate the model.

Let the system decide which device to use.

Use a GPU or other DirectX device to evaluate the model.

Use the system policy-defined device for high performance.

Use the system policy-defined device for minimum power.

Get the results of the evaluation.

The optional string that was passed to LearningModelSession.Evaluate.

The optional string that was passed to **LearningModelSession.Evaluate**.

If the evaluation failed, returns an error code for what caused the failure.

The error code for what caused the failure.

Gets the output features of the model.

The output features of the model.

True if the evaluation completed successfully; otherwise, false.

Input and output feature kinds for a machine learning model.

The feature is an image, so use ImageFeatureDescriptor.

The feature is a map, so use MapFeatureDescriptor.

The feature is a sequence, so use SequenceFeatureDescriptor.

The feature is a tensor, so use TensorFeatureDescriptor.

Used to evaluate machine learning models.

Creates a session using the default device.

The trained machine learning model for this session.

Creates a session using the specified device.

The trained machine learning model for this session. The session's evaluation device.

Creates a session using the specified device and additional inference options.

The trained machine learning model for this session. The session's evaluation device. The options used to configure session creation and evaluation.

Returns the session's evaluation device.

The session's evaluation device.

Set of properties that control model evaluation.

Returns the trained machine learning model for this session.

The trained machine learning model for this session.

Evaluate the machine learning model using the feature values bound in *bindings*.

Holder for associations between model inputs and variable instances. Optional user-supplied string to connect the output results. The results of the evaluation.

Asynchronously evaluate the machine learning model using the feature values already bound in *bindings*.

The values bound to the named input and output features. Optional user-supplied string to connect the output results. A LearningModelEvaluationResult from the evaluation.

Evaluate the machine learning model using the feature values in *features*.

A map of features with which to evaluate the model. Optional user supplied string to connect the output results. The result of the evaluation.

Asynchronously evaluate the machine learning model using the feature values in *features*.

A map of features with which to evaluate the model. Optional user supplied string to connect the output results. The result of the evaluation.

Describes inference options that are used during the creation of LearningModelSession objects.

Creates options to configure the creation of a LearningModelSession.

A numeric value that specifies a constant batch size override value for the target model.

The constant batch size for model inputs feature values expected by calls to Bind. The default value for the **BatchSizeOverride** will be 1 indicating a static batch size of 1.

Specifies whether a LearningModelSession should close the associated learning model when it is created.

Indicates whether the model should be closed upon session creation.

A map is a collection of (key, value) pairs.

A description of what this feature is used for in the model.

If true, you must bind a value to this feature before calling LearningModelSession.Evaluate.

True if you must bind a value to this feature before calling **LearningModelSession.Evaluate**; otherwise, false.

Map keys can be tensor kinds.

The type of tensor this map key is.

The kind of feature; use this to know which derived class to use.

The kind of feature.

The name you use to bind values to this feature.

Map values can be feature kinds.

The feature for this map value.

A sequence is an array of elements.

A description of what this feature is used for in the model.

Sequence elements can be feature kinds.

The feature descriptor for this sequence element.

If true, you must bind a value to this feature before calling LearningModelSession.Evaluate.

True if you must bind a value to this feature before calling **LearningModelSession.Evaluate**; otherwise, false.

The kind of feature; use this to know which derived class to use.

The kind of feature.

The name you use to bind values to this feature.

A boolean tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

If there are no outstanding IMemoryBufferReference objects created from this object, **Close** will dispose of the object and destroy its associated resources. Otherwise, **Close** will detach itself from its associated resources and they will be destroyed when the last IMemoryBufferReference is closed.

Creates a boolean tensor object without allocating a buffer.

A boolean tensor object.

Creates a boolean tensor object and allocates a buffer of size *shape*.

The size of the buffer. A boolean tensor object with a buffer of the given size.

Creates a boolean tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A boolean tensor object with a buffer containing the given data.

Creates a boolean tensor object with the given *shape* and uses the underlying buffer in *data* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. A boolean tensor object backed by a buffer reference to the provided IBuffer *data*.

Creates a boolean tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A boolean tensor object with a buffer containing the given data.

Creates a boolean tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A boolean tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the boolean tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

A 64-bit float tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates a 64-bit float tensor object without allocating a buffer.

A 64-bit float tensor object.

Creates a 64-bit float tensor object and allocates a buffer of size *shape*.

The size of the buffer. A 64-bit float tensor object with a buffer of the given size.

Creates a 64-bit float tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 64-bit float tensor object with a buffer containing the given data.

Creates a double tensor object with the given *shape* and uses the underlying buffer in *data* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. A double tensor object backed by a buffer reference to the provided IBuffer *data*.

Creates a 64-bit float tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 64-bit float tensor object with a buffer containing the given data.

Creates a 64-bit float tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 64-bit float tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the double tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

Tensors are multi-dimensional arrays of values.

A description of what this feature is used for in the model.

If true, you must bind a value to this feature before calling LearningModelSession.Evaluate.

True if you must bind a value to this feature before calling **LearningModelSession.Evaluate**; otherwise, false.

The kind of feature; use this to know which derived class to use.

The kind of feature.

The name you use to bind values to this feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

A 32-bit float tensor object.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates a 32-bit float tensor object without allocating a buffer.

A 32-bit float tensor object.

Creates a 32-bit float tensor object and allocates a buffer of size *shape*.

The size of the buffer. A 32-bit float tensor object with a buffer of the given size.

Creates a 32-bit float tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 32-bit float tensor object with a buffer containing the given data.

Creates a float tensor object with the given *shape* and uses the underlying buffer in *data* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. A float tensor object backed by a buffer reference to the provided IBuffer *data*.

Creates a 32-bit float tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 32-bit float tensor object with a buffer containing the given data.

Creates a 32-bit float tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 32-bit float tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the 32-bit float tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

A 16-bit float tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates a 16-bit float tensor object without allocating a buffer.

A 16-bit float tensor object.

Creates a 16-bit float tensor object and allocates a buffer of size *shape*.

The size of the buffer. A 16-bit float tensor object with a buffer of the given size.

Creates a 16-bit float tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 16-bit float tensor object with a buffer containing the given data.

Creates a 16-bit float tensor object with the given *shape* and uses the underlying buffer in *data* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. A 16-bit float tensor object backed by a buffer reference to the provided IBuffer *data*.

Creates a 16-bit float tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 16-bit float tensor object with a buffer containing the given data.

Creates a 16-bit float tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 16-bit float tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the 16-bit float tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

A 16-bit signed integer tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates a 16-bit signed integer tensor object without allocating a buffer.

A 16-bit signed integer tensor object.

Creates a 16-bit signed integer tensor object and allocates a buffer of size *shape*.

The size of the buffer. A 16-bit signed integer tensor object with a buffer of the given size.

Creates a 16-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 16-bit signed integer tensor object with a buffer containing the given data.

Creates a 16-bit signed integer tensor object with the given *shape* and uses the underlying buffer in *buffer* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. A 16-bit signed integer tensor object backed by a buffer reference to the provided IBuffer *buffer*.

Creates a 16-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 16-bit signed integer tensor object with a buffer containing the given data.

Creates a 16-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 16-bit signed integer tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the 16-bit signed integer tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

A 32-bit signed integer tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates a 32-bit signed integer tensor object without allocating a buffer.

A 32-bit signed integer tensor object.

Creates a 32-bit signed integer tensor object and allocates a buffer of size *shape*.

The size of the buffer. A 32-bit signed integer tensor object with a buffer of the given size.

Creates a 32-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 32-bit signed integer tensor object with a buffer containing the given data.

Creates a 32-bit signed integer tensor object with the given *shape* and uses the underlying buffer in *buffer* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. A 32-bit signed integer tensor object backed by a buffer reference to the provided IBuffer *buffer*.

Creates a 32-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 32-bit signed integer tensor object with a buffer containing the given data.

Creates a 32-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 32-bit signed integer tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the 32-bit signed integer tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

A 64-bit signed integer tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates a 64-bit signed integer tensor object without allocating a buffer.

A 64-bit signed integer tensor object.

Creates a 64-bit signed integer tensor object and allocates a buffer of size *shape*.

The size of the buffer. A 64-bit signed integer tensor object with a buffer of the given size.

Creates a 64-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 64-bit signed integer tensor object with a buffer containing the given data.

Creates a 64-bit signed integer tensor object with the given *shape* and uses the underlying buffer in *buffer* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. A 64-bit signed integer tensor object backed by a buffer reference to the provided IBuffer *buffer*.

Creates a 64-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 64-bit signed integer tensor object with a buffer containing the given data.

Creates a 64-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 64-bit signed integer tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the 64-bit signed integer tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

An 8-bit signed integer tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates an 8-bit signed integer tensor object without allocating a buffer.

An 8-bit signed integer tensor object.

Creates an 8-bit signed integer tensor object and allocates a buffer of size *shape*.

The size of the buffer. An 8-bit signed integer tensor object with a buffer of the given size.

Creates an 8-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. An 8-bit signed integer tensor object with a buffer containing the given data.

Creates an 8-bit signed integer tensor object with the given *shape* and uses the underlying buffer in *buffer* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. An 8-bit signed integer tensor object backed by a buffer reference to the provided IBuffer *buffer*.

Creates an 8-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. An 8-bit signed integer tensor object with a buffer containing the given data.

Creates an 8-bit signed integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. An 8-bit signed integer tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the 8-bit signed integer tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

Defines the list of supported tensor data types.

The tensor type is **Boolean**.

Invalid type.

The tensor type is 64-bit floating point.

The tensor type is 32-bit floating point.

The tensor type is 16-bit floating point.

The tensor type is 16-bit signed integer.

The tensor type is 32-bit signed integer.

The tensor type is 64-bit signed integer.

The tensor type is 8-bit signed integer.

The tensor type is **String**.

The tensor type is 16-bit unsigned integer.

The tensor type is 32-bit unsigned integer.

The tensor type is 64-bit unsigned integer.

The tensor type is 8-bit unsigned integer.

Invalid type.

A string tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates a string tensor object without allocating a buffer.

A string tensor object.

Creates a string tensor object and allocates a buffer of size *shape*.

The size of the buffer. A string tensor object with a buffer of the given size.

Creates a string tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A string tensor object with a buffer containing the given data.

Creates a string tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A string tensor object with a buffer containing the given data.

Creates a string tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A string tensor object with a buffer containing the given data.

This method is disallowed on TensorString objects and should not be used.

The IMemoryBufferReference returned is always **null**.

Returns a read-only view of the data.

A read-only view of the data.

A 16-bit unsigned integer tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates a 16-bit unsigned integer tensor object without allocating a buffer.

A 16-bit unsigned integer tensor object.

Creates a 16-bit unsigned integer tensor object and allocates a buffer of size *shape*.

The size of the buffer. A 16-bit unsigned integer tensor object with a buffer of the given size.

Creates a 16-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 16-bit unsigned integer tensor object with a buffer containing the given data.

Creates a 16-bit unsigned integer tensor object with the given *shape* and uses the underlying buffer in *buffer* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. A 16-bit unsigned integer tensor object backed by a buffer reference to the provided IBuffer *buffer*.

Creates a 16-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 16-bit unsigned integer tensor object with a buffer containing the given data.

Creates a 16-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 16-bit unsigned integer tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the 16-bit unsigned integer tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

A 32-bit unsigned integer tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates a 32-bit unsigned integer tensor object without allocating a buffer.

A 32-bit unsigned integer tensor object.

Creates a 32-bit unsigned integer tensor object and allocates a buffer of size *shape*.

The size of the buffer. A 32-bit unsigned integer tensor object with a buffer of the given size.

Creates a 32-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 32-bit unsigned integer tensor object with a buffer containing the given data.

Creates a 32-bit unsigned integer tensor object with the given *shape* and uses the underlying buffer in *buffer* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. A 32-bit unsigned integer tensor object backed by a buffer reference to the provided IBuffer *buffer*.

Creates a 32-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 32-bit unsigned integer tensor object with a buffer containing the given data.

Creates a 32-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. A 32-bit unsigned integer tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the 32-bit unsigned integer tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

A 64-bit unsigned integer tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates a 64-bit unsigned integer tensor object without allocating a buffer.

A 64-bit unsigned integer tensor object.

Creates a 64-bit unsigned integer tensor object and allocates a buffer of size *shape*.

The size of the buffer. A 64-bit unsigned integer tensor object with a buffer of the given size.

Creates a 64-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to be copied into the buffer. A 64-bit unsigned integer tensor object with a buffer containing the given data.

Creates a 64-bit unsigned integer tensor object with the given *shape* and uses the underlying buffer in *buffer* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. A 64-bit unsigned integer tensor object backed by a buffer reference to the provided IBuffer *buffer*.

Creates a 64-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to be copied into the buffer. A 64-bit unsigned integer tensor object with a buffer containing the given data.

Creates a 64-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to be copied into the buffer. A 64-bit unsigned integer tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the 64-bit unsigned integer tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.

A 8-bit unsigned integer tensor object.

The kind of the feature.

Returns the count and size of each dimension.

The count and size of each dimension.

Returns the data type of the tensor.

The data type of the tensor.

Creates an 8-bit unsigned integer tensor object without allocating a buffer.

An 8-bit unsigned integer tensor object.

Creates an 8-bit unsigned integer tensor object and allocates a buffer of size *shape*.

The size of the buffer. An 8-bit unsigned integer tensor object with a buffer of the given size.

Creates an 8-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. An 8-bit unsigned integer tensor object with a buffer containing the given data.

Creates an 8-bit unsigned integer tensor object with the given *shape* and uses the underlying buffer in *buffer* for subsequent evaluation.

The size of the buffer. The buffer to use during evaluation. An 8-bit unsigned integer tensor object backed by a buffer reference to the provided IBuffer *buffer*.

Creates an 8-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. An 8-bit unsigned integer tensor object with a buffer containing the given data.

Creates an 8-bit unsigned integer tensor object, allocates a buffer of size *shape*, and copies all of *data* into it.

The size of the buffer. The data to copy into the buffer. An 8-bit unsigned integer tensor object with a buffer containing the given data.

Returns an IMemoryBufferReference representation of the buffer backing the 8-bit unsigned tensor object.

The IMemoryBufferReference representation of a tensor buffer.

Returns a read-only view of the data.

A read-only view of the data.