[OV JS] Add methods descriptions for Model, Tensor & InferRequest (#24768)
### Details: - Add methods descriptions for Model, Tensor & InferRequest --------- Co-authored-by: Maciej Smyk <maciejx.smyk@intel.com> Co-authored-by: Michal Lukaszewski <michal.lukaszewski@intel.com>
This commit is contained in:
Alicja Miloszewska
GitHub
parent
dd0846b8d5
commit
cf22524dcb
|
|
@ -188,17 +188,80 @@ interface CoreConstructor {
|
|||
new(): Core;
|
||||
}
|
||||
|
||||
/**
|
||||
* A user-defined model read by {@link Core.readModel}.
|
||||
*/
|
||||
interface Model {
|
||||
outputs: Output[];
|
||||
inputs: Output[];
|
||||
output(nameOrId?: string | number): Output;
|
||||
input(nameOrId?: string | number): Output;
|
||||
getName(): string;
|
||||
isDynamic(): boolean;
|
||||
getOutputSize(): number;
|
||||
setFriendlyName(name: string): void;
|
||||
/**
|
||||
* It gets the friendly name for a model. If a friendly name is not set
|
||||
* via {@link Model.setFriendlyName}, a unique model name is returned.
|
||||
* @returns A string with a friendly name of the model.
|
||||
*/
|
||||
getFriendlyName(): string;
|
||||
getOutputShape(): number[];
|
||||
/**
|
||||
* It gets the unique name of the model.
|
||||
* @returns A string with the name of the model.
|
||||
*/
|
||||
getName(): string;
|
||||
/**
|
||||
* It returns the shape of the element at the specified index.
|
||||
* @param index The index of the element.
|
||||
*/
|
||||
getOutputShape(index: number): number[];
|
||||
/**
|
||||
* It returns the number of the model outputs.
|
||||
*/
|
||||
getOutputSize(): number;
|
||||
/**
|
||||
* It gets the input of the model.
|
||||
* If a model has more than one input, this method throws an exception.
|
||||
*/
|
||||
input(): Output;
|
||||
/**
|
||||
* It gets the input of the model identified by the tensor name.
|
||||
* @param name The tensor name.
|
||||
*/
|
||||
input(name: string): Output;
|
||||
/**
|
||||
* It gets the input of the model identified by the index.
|
||||
* @param index The index of the input.
|
||||
*/
|
||||
input(index: number): Output;
|
||||
/**
|
||||
* It returns true if any of the op’s defined in the model contains a partial
|
||||
* shape.
|
||||
*/
|
||||
isDynamic(): boolean;
|
||||
/**
|
||||
* It gets the output of the model.
|
||||
* If a model has more than one output, this method throws an exception.
|
||||
*/
|
||||
output(): Output;
|
||||
/**
|
||||
* It gets the output of the model identified by the tensor name.
|
||||
* @param name The tensor name.
|
||||
*/
|
||||
output(name: string): Output;
|
||||
/**
|
||||
* It gets the output of the model identified by the index.
|
||||
* @param index The index of the input.
|
||||
*/
|
||||
output(index: number): Output;
|
||||
/**
|
||||
* Sets a friendly name for the model. This does not overwrite the unique
|
||||
* model name and is retrieved via {@link Model.getFriendlyName}.
|
||||
* Mainly used for debugging.
|
||||
* @param name The string to set as the friendly name.
|
||||
*/
|
||||
setFriendlyName(name: string): void;
|
||||
/**
|
||||
* It gets all the model inputs as an array.
|
||||
*/
|
||||
inputs: Output[];
|
||||
/**
|
||||
* It gets all the model outputs as an array
|
||||
*/
|
||||
outputs: Output[];
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
@ -262,31 +325,189 @@ interface CompiledModel {
|
|||
|
||||
}
|
||||
|
||||
/**
|
||||
* The {@link Tensor} is a lightweight class that represents data used for
|
||||
* inference. There are different ways to create a tensor. You can find them
|
||||
* in {@link TensorConstructor} section.
|
||||
*/
|
||||
interface Tensor {
|
||||
/**
|
||||
* This property provides access to the tensor's data.
|
||||
*
|
||||
* Its getter returns a subclass of TypedArray that corresponds to the
|
||||
* tensor element type, e.g. Float32Array corresponds to float32. The
|
||||
* content of the TypedArray subclass is a copy of the tensor underlaying
|
||||
* memory.
|
||||
*
|
||||
* Its setter fills the underlaying tensor memory by copying the binary data
|
||||
* buffer from the TypedArray subclass. An exception will be thrown if the size
|
||||
* or type of array does not match the tensor.
|
||||
*/
|
||||
data: SupportedTypedArray;
|
||||
/**
|
||||
* It gets the tensor element type.
|
||||
*/
|
||||
getElementType(): element;
|
||||
/**
|
||||
* It gets tensor data.
|
||||
* @returns A subclass of TypedArray corresponding to the tensor
|
||||
* element type, e.g. Float32Array corresponds to float32.
|
||||
*/
|
||||
getData(): SupportedTypedArray;
|
||||
/**
|
||||
* It gets the tensor shape.
|
||||
*/
|
||||
getShape(): number[];
|
||||
getData(): number[];
|
||||
/**
|
||||
* It gets the tensor size as a total number of elements.
|
||||
*/
|
||||
getSize(): number;
|
||||
}
|
||||
|
||||
/**
|
||||
* This interface contains constructors of the {@link Tensor} class.
|
||||
*
|
||||
* @remarks
|
||||
* The tensor memory is shared with the TypedArray. That is,
|
||||
* the responsibility for maintaining the reference to the TypedArray lies with
|
||||
* the user. Any action performed on the TypedArray will be reflected in this
|
||||
* tensor memory.
|
||||
*/
|
||||
interface TensorConstructor {
|
||||
new(type: element | elementTypeString,
|
||||
shape: number[],
|
||||
tensorData?: number[] | SupportedTypedArray): Tensor;
|
||||
/**
|
||||
* It constructs a tensor using the element type and shape. The new tensor data
|
||||
* will be allocated by default.
|
||||
* @param type The element type of the new tensor.
|
||||
* @param shape The shape of the new tensor.
|
||||
*/
|
||||
new(type: element | elementTypeString, shape: number[]): Tensor;
|
||||
/**
|
||||
* It constructs a tensor using the element type and shape. The new tensor wraps
|
||||
* allocated host memory.
|
||||
* @param type The element type of the new tensor.
|
||||
* @param shape The shape of the new tensor.
|
||||
* @param tensorData A subclass of TypedArray that will be wrapped
|
||||
* by a {@link Tensor}.
|
||||
*/
|
||||
new(type: element | elementTypeString, shape: number[],
|
||||
tensorData: SupportedTypedArray): Tensor;
|
||||
}
|
||||
|
||||
/**
|
||||
* The {@link InferRequest} object is created using
|
||||
* {@link CompiledModel.createInferRequest} method and is specific for a given
|
||||
* deployed model. It is used to make predictions and can be run in
|
||||
* asynchronous or synchronous manners.
|
||||
*/
|
||||
interface InferRequest {
|
||||
setTensor(name: string, tensor: Tensor): void;
|
||||
setInputTensor(idxOrTensor: number | Tensor, tensor?: Tensor): void;
|
||||
setOutputTensor(idxOrTensor: number | Tensor, tensor?: Tensor): void;
|
||||
getTensor(nameOrOutput: string | Output): Tensor;
|
||||
getInputTensor(idx?: number): Tensor;
|
||||
getOutputTensor(idx?: number): Tensor;
|
||||
infer(inputData?: { [inputName: string]: Tensor | SupportedTypedArray}
|
||||
| Tensor[] | SupportedTypedArray[]): { [outputName: string] : Tensor};
|
||||
/**
|
||||
* It infers specified input(s) in the synchronous mode.
|
||||
* @remarks
|
||||
* Inputs have to be specified earlier using {@link InferRequest.setTensor}
|
||||
* or {@link InferRequest.setInputTensor}
|
||||
*/
|
||||
infer(): { [outputName: string] : Tensor};
|
||||
/**
|
||||
* It infers specified input(s) in the synchronous mode.
|
||||
* @param inputData An object with the key-value pairs where the key is the
|
||||
* input name and value can be either a tensor or a TypedArray. TypedArray
|
||||
* will be wrapped into Tensor underneath using the input shape and element type
|
||||
* of the deployed model.
|
||||
*/
|
||||
infer(inputData: { [inputName: string]: Tensor | SupportedTypedArray})
|
||||
: { [outputName: string] : Tensor};
|
||||
/**
|
||||
* It infers specified input(s) in the synchronous mode.
|
||||
* @param inputData An array with tensors or TypedArrays. TypedArrays will be
|
||||
* wrapped into Tensors underneath using the input shape and element type
|
||||
* of the deployed model. If the model has multiple inputs, the Tensors
|
||||
* and TypedArrays must be passed in the correct order.
|
||||
*/
|
||||
infer(inputData: Tensor[] | SupportedTypedArray[])
|
||||
: { [outputName: string] : Tensor};
|
||||
/**
|
||||
* It infers specified input(s) in the asynchronous mode.
|
||||
* @param inputData An object with the key-value pairs where the key is the
|
||||
* input name and value is a tensor or an array with tensors. If the model has
|
||||
* multiple inputs, the Tensors must be passed in the correct order.
|
||||
*/
|
||||
inferAsync(inputData: { [inputName: string]: Tensor}
|
||||
| Tensor[] ): Promise<{ [outputName: string] : Tensor}>;
|
||||
/**
|
||||
* It gets the compiled model used by the InferRequest object.
|
||||
*/
|
||||
getCompiledModel(): CompiledModel;
|
||||
/**
|
||||
* It gets the input tensor for inference.
|
||||
* @returns The input tensor for the model. If the model has several inputs,
|
||||
* an exception is thrown.
|
||||
*/
|
||||
getInputTensor(): Tensor;
|
||||
/**
|
||||
* It gets the input tensor for inference.
|
||||
* @param idx An index of the tensor to get.
|
||||
* @returns A tensor at the specified index. If the tensor with the specified
|
||||
* idx is not found, an exception is thrown.
|
||||
*/
|
||||
getInputTensor(idx: number): Tensor;
|
||||
/**
|
||||
* It gets the output tensor for inference.
|
||||
* @returns The output tensor for the model. If the model has several outputs,
|
||||
* an exception is thrown.
|
||||
*/
|
||||
getOutputTensor(): Tensor;
|
||||
/**
|
||||
* It gets the output tensor for inference.
|
||||
* @param idx An index of the tensor to get.
|
||||
* @returns A tensor at the specified index. If the tensor with the specified
|
||||
* idx is not found, an exception is thrown.
|
||||
*/
|
||||
getOutputTensor(idx?: number): Tensor;
|
||||
/**
|
||||
* It gets an input/output tensor for inference.
|
||||
*
|
||||
* @remarks
|
||||
* If a tensor with the specified name or port is not found, an exception
|
||||
* is thrown.
|
||||
* @param nameOrOutput The name of the tensor or output object.
|
||||
*/
|
||||
getTensor(nameOrOutput: string | Output): Tensor;
|
||||
/**
|
||||
* It sets the input tensor to infer models with a single input.
|
||||
* @param tensor The input tensor. The element type and shape of the tensor
|
||||
* must match the type and size of the model's input element. If the model has several
|
||||
* inputs, an exception is thrown.
|
||||
*/
|
||||
setInputTensor(tensor: Tensor): void;
|
||||
/**
|
||||
* It sets the input tensor to infer.
|
||||
* @param idx The input tensor index. If idx is greater than the number of
|
||||
* model inputs, an exception is thrown.
|
||||
* @param tensor The input tensor. The element type and shape of the tensor
|
||||
* must match the input element type and size of the model.
|
||||
*/
|
||||
setInputTensor(idx: number, tensor: Tensor): void;
|
||||
/**
|
||||
* It sets the output tensor to infer models with a single output.
|
||||
* @param tensor The output tensor. The element type and shape of the tensor
|
||||
* must match the output element type and size of the model. If the model has several
|
||||
* outputs, an exception is thrown.
|
||||
*/
|
||||
setOutputTensor(tensor: Tensor): void;
|
||||
/**
|
||||
* It sets the output tensor to infer.
|
||||
* @param idx The output tensor index.
|
||||
* @param tensor The output tensor. The element type and shape of the tensor
|
||||
* must match the output element type and size of the model.
|
||||
*/
|
||||
setOutputTensor(idx: number, tensor: Tensor): void;
|
||||
/**
|
||||
* It sets the input/output tensor to infer.
|
||||
* @param name The input or output tensor name.
|
||||
* @param tensor The tensor. The element type and shape of the tensor
|
||||
* must match the input/output element type and size of the model.
|
||||
*/
|
||||
setTensor(name: string, tensor: Tensor): void;
|
||||
}
|
||||
|
||||
type Dimension = number | [number, number];
|
||||
|
|
|
|||
Loading…
Reference in New Issue