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onnxruntime_go.go
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onnxruntime_go.go
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// This library wraps the C "onnxruntime" library maintained at
// https://github.com/microsoft/onnxruntime. It seeks to provide as simple an
// interface as possible to load and run ONNX-format neural networks from
// Go code.
package onnxruntime_go
import (
"fmt"
"unsafe"
)
// #cgo CFLAGS: -O2 -g
//
// #include "onnxruntime_wrapper.h"
import "C"
// This string should be the path to onnxruntime.so, or onnxruntime.dll.
var onnxSharedLibraryPath string
// For simplicity, this library maintains a single ORT environment internally.
var ortEnv *C.OrtEnv
// We also keep a single OrtMemoryInfo value around, since we only support CPU
// allocations for now.
var ortMemoryInfo *C.OrtMemoryInfo
var NotInitializedError error = fmt.Errorf("InitializeRuntime() has either " +
"not yet been called, or did not return successfully")
var ZeroShapeLengthError error = fmt.Errorf("The shape has no dimensions")
var ShapeOverflowError error = fmt.Errorf("The shape's flattened size " +
"overflows an int64")
// This type of error is returned when we attempt to validate a tensor that has
// a negative or 0 dimension.
type BadShapeDimensionError struct {
DimensionIndex int
DimensionSize int64
}
func (e *BadShapeDimensionError) Error() string {
return fmt.Sprintf("Dimension %d of the shape has invalid value %d",
e.DimensionIndex, e.DimensionSize)
}
// GetVersion return version of the Onnxruntime library for logging.
func GetVersion() string {
return C.GoString(C.GetVersion())
}
// Does two things: converts the given OrtStatus to a Go error, and releases
// the status. If the status is nil, this does nothing and returns nil.
func statusToError(status *C.OrtStatus) error {
if status == nil {
return nil
}
msg := C.GetErrorMessage(status)
toReturn := C.GoString(msg)
C.ReleaseOrtStatus(status)
return fmt.Errorf("%s", toReturn)
}
// Use this function to set the path to the "onnxruntime.so" or
// "onnxruntime.dll" function. By default, it will be set to "onnxruntime.so"
// on non-Windows systems, and "onnxruntime.dll" on Windows. Users wishing to
// specify a particular location of this library must call this function prior
// to calling onnxruntime.InitializeEnvironment().
func SetSharedLibraryPath(path string) {
onnxSharedLibraryPath = path
}
// Returns false if the onnxruntime package is not initialized. Called
// internally by several functions, to avoid segfaulting if
// InitializeEnvironment hasn't been called yet.
func IsInitialized() bool {
return ortEnv != nil
}
// Call this function to initialize the internal onnxruntime environment. If
// this doesn't return an error, the caller will be responsible for calling
// DestroyEnvironment to free the onnxruntime state when no longer needed.
func InitializeEnvironment() error {
if IsInitialized() {
return fmt.Errorf("The onnxruntime has already been initialized")
}
// Do the windows- or linux- specific initialization first.
e := platformInitializeEnvironment()
if e != nil {
return fmt.Errorf("Platform-specific initialization failed: %w", e)
}
name := C.CString("Golang onnxruntime environment")
defer C.free(unsafe.Pointer(name))
status := C.CreateOrtEnv(name, &ortEnv)
if status != nil {
return fmt.Errorf("Error creating ORT environment: %w",
statusToError(status))
}
status = C.CreateOrtMemoryInfo(&ortMemoryInfo)
if status != nil {
DestroyEnvironment()
return fmt.Errorf("Error creating ORT memory info: %w",
statusToError(status))
}
return nil
}
// Call this function to cleanup the internal onnxruntime environment when it
// is no longer needed.
func DestroyEnvironment() error {
var e error
if !IsInitialized() {
return NotInitializedError
}
if ortMemoryInfo != nil {
C.ReleaseOrtMemoryInfo(ortMemoryInfo)
ortMemoryInfo = nil
}
if ortEnv != nil {
C.ReleaseOrtEnv(ortEnv)
ortEnv = nil
}
// platformCleanup primarily unloads the library, so we need to call it
// last, after any functions that make use of the ORT API.
e = platformCleanup()
if e != nil {
return fmt.Errorf("Platform-specific cleanup failed: %w", e)
}
return nil
}
// Disables telemetry events for the onnxruntime environment. Must be called
// after initializing the environment using InitializeEnvironment(). It is
// unclear from the onnxruntime docs whether this will cause an error or
// silently return if telemetry is already disabled.
func DisableTelemetry() error {
if !IsInitialized() {
return NotInitializedError
}
status := C.DisableTelemetry(ortEnv)
if status != nil {
return fmt.Errorf("Error disabling onnxruntime telemetry: %w",
statusToError(status))
}
return nil
}
// Enables telemetry events for the onnxruntime environment. Must be called
// after initializing the environment using InitializeEnvironment(). It is
// unclear from the onnxruntime docs whether this will cause an error or
// silently return if telemetry is already enabled.
func EnableTelemetry() error {
if !IsInitialized() {
return NotInitializedError
}
status := C.EnableTelemetry(ortEnv)
if status != nil {
return fmt.Errorf("Error enabling onnxruntime telemetry: %w",
statusToError(status))
}
return nil
}
// The Shape type holds the shape of the tensors used by the network input and
// outputs.
type Shape []int64
// Returns a Shape, with the given dimensions.
func NewShape(dimensions ...int64) Shape {
return Shape(dimensions)
}
// Returns the total number of elements in a tensor with the given shape. Note
// that this may be an invalid value due to overflow or negative dimensions. If
// a shape comes from an untrusted source, it may be a good practice to call
// Validate() prior to trusting the FlattenedSize.
func (s Shape) FlattenedSize() int64 {
if len(s) == 0 {
return 0
}
toReturn := int64(s[0])
for i := 1; i < len(s); i++ {
toReturn *= s[i]
}
return toReturn
}
// Returns a non-nil error if the shape has bad or zero dimensions. May return
// a ZeroShapeLengthError, a ShapeOverflowError, or a BadShapeDimensionError.
// In the future, this may return other types of errors if it others become
// necessary.
func (s Shape) Validate() error {
if len(s) == 0 {
return ZeroShapeLengthError
}
if s[0] <= 0 {
return &BadShapeDimensionError{
DimensionIndex: 0,
DimensionSize: s[0],
}
}
flattenedSize := int64(s[0])
for i := 1; i < len(s); i++ {
d := s[i]
if d <= 0 {
return &BadShapeDimensionError{
DimensionIndex: i,
DimensionSize: d,
}
}
tmp := flattenedSize * d
if tmp < flattenedSize {
return ShapeOverflowError
}
flattenedSize = tmp
}
return nil
}
// Makes and returns a deep copy of the Shape.
func (s Shape) Clone() Shape {
toReturn := make([]int64, len(s))
copy(toReturn, []int64(s))
return Shape(toReturn)
}
func (s Shape) String() string {
return fmt.Sprintf("%v", []int64(s))
}
// Returns true if both shapes match in every dimension.
func (s Shape) Equals(other Shape) bool {
if len(s) != len(other) {
return false
}
for i := 0; i < len(s); i++ {
if s[i] != other[i] {
return false
}
}
return true
}
// This wraps internal implementation details to avoid exposing them to users
// via the Value interface.
type ValueInternalData struct {
ortValue *C.OrtValue
}
// An interface for managing tensors or other onnxruntime values where we don't
// necessarily need to access the underlying data slice. All typed tensors will
// support this interface regardless of the underlying data type.
type Value interface {
DataType() C.ONNXTensorElementDataType
GetShape() Shape
Destroy() error
GetInternals() *ValueInternalData
ZeroContents()
GetONNXType() ONNXType
}
// Used to manage all input and output data for onnxruntime networks. A Tensor
// always has an associated type and refers to data contained in an underlying
// Go slice. New tensors should be created using the NewTensor or
// NewEmptyTensor functions, and must be destroyed using the Destroy function
// when no longer needed.
type Tensor[T TensorData] struct {
// The shape of the tensor
shape Shape
// The go slice containing the flattened data that backs the ONNX tensor.
data []T
// The number of bytes taken by the data slice.
dataSize uintptr
// The underlying ONNX value we use with the C API.
ortValue *C.OrtValue
}
// Cleans up and frees the memory associated with this tensor.
func (t *Tensor[_]) Destroy() error {
C.ReleaseOrtValue(t.ortValue)
t.ortValue = nil
t.data = nil
t.dataSize = 0
t.shape = nil
return nil
}
// Returns the slice containing the tensor's underlying data. The contents of
// the slice can be read or written to get or set the tensor's contents.
func (t *Tensor[T]) GetData() []T {
return t.data
}
// Returns the value from the ONNXTensorElementDataType C enum corresponding to
// the type of data held by this tensor.
//
// NOTE: This function was added prior to the introduction of the
// Go TensorElementDataType int wrapping the C enum, so it still returns the
// CGo type.
func (t *Tensor[T]) DataType() C.ONNXTensorElementDataType {
return GetTensorElementDataType[T]()
}
// Always returns ONNXTypeTensor for any Tensor[T] even if the underlying
// tensor is invalid for some reason.
func (t *Tensor[_]) GetONNXType() ONNXType {
return ONNXTypeTensor
}
// Returns the shape of the tensor. The returned shape is only a copy;
// modifying this does *not* change the shape of the underlying tensor.
// (Modifying the tensor's shape can only be accomplished by Destroying and
// recreating the tensor with the same data.)
func (t *Tensor[_]) GetShape() Shape {
return t.shape.Clone()
}
func (t *Tensor[_]) GetInternals() *ValueInternalData {
return &ValueInternalData{
ortValue: t.ortValue,
}
}
// Sets every element in the tensor's underlying data slice to 0.
func (t *Tensor[T]) ZeroContents() {
C.memset(unsafe.Pointer(&t.data[0]), 0, C.size_t(t.dataSize))
}
// Makes a deep copy of the tensor, including its ONNXRuntime value. The Tensor
// returned by this function must be destroyed when no longer needed. The
// returned tensor will also no longer refer to the same underlying data; use
// GetData() to obtain the new underlying slice.
func (t *Tensor[T]) Clone() (*Tensor[T], error) {
toReturn, e := NewEmptyTensor[T](t.shape)
if e != nil {
return nil, fmt.Errorf("Error allocating tensor clone: %w", e)
}
copy(toReturn.GetData(), t.data)
return toReturn, nil
}
// Creates a new empty tensor with the given shape. The shape provided to this
// function is copied, and is no longer needed after this function returns.
func NewEmptyTensor[T TensorData](s Shape) (*Tensor[T], error) {
e := s.Validate()
if e != nil {
return nil, fmt.Errorf("Invalid tensor shape: %w", e)
}
elementCount := s.FlattenedSize()
data := make([]T, elementCount)
return NewTensor(s, data)
}
// Creates a new tensor backed by an existing data slice. The shape provided to
// this function is copied, and is no longer needed after this function
// returns. If the data slice is longer than s.FlattenedSize(), then only the
// first portion of the data will be used.
func NewTensor[T TensorData](s Shape, data []T) (*Tensor[T], error) {
if !IsInitialized() {
return nil, NotInitializedError
}
e := s.Validate()
if e != nil {
return nil, fmt.Errorf("Invalid tensor shape: %w", e)
}
elementCount := s.FlattenedSize()
if elementCount > int64(len(data)) {
return nil, fmt.Errorf("The tensor's shape (%s) requires %d "+
"elements, but only %d were provided", s, elementCount,
len(data))
}
var ortValue *C.OrtValue
dataType := GetTensorElementDataType[T]()
dataSize := unsafe.Sizeof(data[0]) * uintptr(elementCount)
status := C.CreateOrtTensorWithShape(unsafe.Pointer(&data[0]),
C.size_t(dataSize), (*C.int64_t)(unsafe.Pointer(&s[0])),
C.int64_t(len(s)), ortMemoryInfo, dataType, &ortValue)
if status != nil {
return nil, fmt.Errorf("ORT API error creating tensor: %s",
statusToError(status))
}
toReturn := Tensor[T]{
data: data[0:elementCount],
dataSize: dataSize,
shape: s.Clone(),
ortValue: ortValue,
}
// TODO: Set a finalizer on new Tensors to hopefully prevent careless
// memory leaks.
// - Idea: use a "destroyable" interface?
return &toReturn, nil
}
// Wraps the ONNXTEnsorElementDataType enum in C.
type TensorElementDataType int
const (
TensorElementDataTypeUndefined = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED
TensorElementDataTypeFloat = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT
TensorElementDataTypeUint8 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8
TensorElementDataTypeInt8 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8
TensorElementDataTypeUint16 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16
TensorElementDataTypeInt16 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16
TensorElementDataTypeInt32 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32
TensorElementDataTypeInt64 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64
TensorElementDataTypeString = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING
TensorElementDataTypeBool = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL
TensorElementDataTypeFloat16 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16
TensorElementDataTypeDouble = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE
TensorElementDataTypeUint32 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32
TensorElementDataTypeUint64 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64
// Not supported by onnxruntime (as of onnxruntime version 1.20.0)
TensorElementDataTypeComplex64 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_COMPLEX64
// Not supported by onnxruntime (as of onnxruntime version 1.20.0)
TensorElementDataTypeComplex128 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_COMPLEX128
// Non-IEEE floating-point format based on IEEE754 single-precision
TensorElementDataTypeBFloat16 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16
// 8-bit float types, introduced in onnx 1.14. See
// https://onnx.ai/onnx/technical/float8.html
TensorElementDataTypeFloat8E4M3FN = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E4M3FN
TensorElementDataTypeFloat8E4M3FNUZ = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E4M3FNUZ
TensorElementDataTypeFloat8E5M2 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E5M2
TensorElementDataTypeFloat8E5M2FNUZ = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E5M2FNUZ
// Int4 types were introduced in ONNX 1.16. See
// https://onnx.ai/onnx/technical/int4.html
TensorElementDataTypeUint4 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT4
TensorElementDataTypeInt4 = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_INT4
)
func (t TensorElementDataType) String() string {
switch t {
case TensorElementDataTypeUndefined:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED"
case TensorElementDataTypeFloat:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT"
case TensorElementDataTypeUint8:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8"
case TensorElementDataTypeInt8:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8"
case TensorElementDataTypeUint16:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT16"
case TensorElementDataTypeInt16:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_INT16"
case TensorElementDataTypeInt32:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32"
case TensorElementDataTypeInt64:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64"
case TensorElementDataTypeString:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING"
case TensorElementDataTypeBool:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_BOOL"
case TensorElementDataTypeFloat16:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16"
case TensorElementDataTypeDouble:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE"
case TensorElementDataTypeUint32:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT32"
case TensorElementDataTypeUint64:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT64"
case TensorElementDataTypeComplex64:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_COMPLEX64"
case TensorElementDataTypeComplex128:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_COMPLEX128"
case TensorElementDataTypeBFloat16:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16"
case TensorElementDataTypeFloat8E4M3FN:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E4M3FN"
case TensorElementDataTypeFloat8E4M3FNUZ:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E4M3FNUZ"
case TensorElementDataTypeFloat8E5M2:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E5M2"
case TensorElementDataTypeFloat8E5M2FNUZ:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT8E5M2FNUZ"
case TensorElementDataTypeUint4:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT4"
case TensorElementDataTypeInt4:
return "ONNX_TENSOR_ELEMENT_DATA_TYPE_INT4"
}
return fmt.Sprintf("Unknown tensor element data type: %d", int(t))
}
// This wraps an ONNX_TYPE_SEQUENCE OrtValue. Satisfies the Value interface,
// though Tensor-related functions such as ZeroContents() may be no-ops.
type Sequence struct {
ortValue *C.OrtValue
// We'll stash the values in the sequence here, so we don't need to look
// them up, and so that users don't need to remember to free them.
contents []Value
}
// Returns the value at the given index in the sequence or map. (In a map,
// index 0 is for keys, and 1 is for values.) Used internally when initializing
// a go Sequence or Map object.
func getSequenceOrMapValue(sequenceOrMap *C.OrtValue,
index int64) (Value, error) {
var result *C.OrtValue
status := C.GetValue(sequenceOrMap, C.int(index), &result)
if status != nil {
return nil, fmt.Errorf("Error getting value of index %d: %s", index,
statusToError(status))
}
return createGoValueFromOrtValue(result)
}
// Creates a new ONNX sequence with the given contents. The returned Sequence
// must be Destroyed by the caller when no longer needed. Destroying the
// Sequence created by this function does _not_ destroy the Values it was
// created with, so the caller is still responsible for destroying them
// as well.
//
// The contents of a sequence are subject to additional constraints. I can't
// find mention of some of these in the C API docs, but they are enforced by
// the onnxruntime API. Notably: all elements of the sequence must have the
// same type, and all elements must be either maps or tensors. Finally, the
// sequence must contain at least one element, and none of the elements may be
// nil. There may be other constraints that I am unaware of, as well.
func NewSequence(contents []Value) (*Sequence, error) {
if !IsInitialized() {
return nil, NotInitializedError
}
length := int64(len(contents))
if length == 0 {
return nil, fmt.Errorf("Sequences must contain at least 1 element")
}
ortValues := make([]*C.OrtValue, length)
for i, v := range contents {
if v == nil {
return nil, fmt.Errorf("Sequences must not contain nil (index "+
"%d was nil)", i)
}
ortValues[i] = v.GetInternals().ortValue
}
var sequence *C.OrtValue
status := C.CreateOrtValue(&(ortValues[0]), C.size_t(length),
C.ONNX_TYPE_SEQUENCE, &sequence)
if status != nil {
return nil, fmt.Errorf("Error creating ORT sequence: %s",
statusToError(status))
}
// Finally, we want to get each OrtValue from the sequence itself, but we
// already have a function to do this in the case of onnxruntime-allocated
// sequences.
toReturn, e := createSequenceFromOrtValue(sequence)
if e != nil {
// createSequenceFromOrtValue destroys the sequence on error.
return nil, fmt.Errorf("Error creating go Sequence from sequence "+
"OrtValue: %w", e)
}
return toReturn, nil
}
// Returns the list of values in the sequence. Each of these values should
// _not_ be Destroy()'ed by the caller, they will be automatically destroyed
// upon calling Destroy() on the sequence. If this sequence was created via
// NewSequence, these are not the same Values that the sequence was created
// with, though if they are tensors they should still refer to the same
// underlying data.
func (s *Sequence) GetValues() ([]Value, error) {
return s.contents, nil
}
func (s *Sequence) Destroy() error {
C.ReleaseOrtValue(s.ortValue)
var e error
for _, v := range s.contents {
if v != nil {
// Just return the last error if any of these returns an error.
e2 := v.Destroy()
if e2 != nil {
e = e2
}
}
}
s.ortValue = nil
s.contents = nil
return e
}
// This returns a 1-dimensional Shape containing a single element: the number
// of elements the sequence. Typically, Sequence users should prefer calling
// len(s.GetValues()) over this function. This function only exists to maintain
// compatibility with the Value interface.
func (s *Sequence) GetShape() Shape {
return NewShape(int64(len(s.contents)))
}
// Always returns ONNXTypeSequence
func (s *Sequence) GetONNXType() ONNXType {
return ONNXTypeSequence
}
// This function is meaningless for a Sequence and shouldn't be used. The
// return value is always TENSOR_ELEMENT_DATA_TYPE_UNDEFINED for now, but this
// may change in the future. This function is only present for compatibility
// with the Value interface and should not be relied on for sequences.
func (s *Sequence) DataType() C.ONNXTensorElementDataType {
return C.ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED
}
// This function does nothing for a Sequence, and is only present for
// compatibility with the Value interface.
func (s *Sequence) ZeroContents() {
}
func (s *Sequence) GetInternals() *ValueInternalData {
return &ValueInternalData{
ortValue: s.ortValue,
}
}
// This wraps an ONNX_TYPE_MAP OrtValue. Satisfies the Value interface,
// though Tensor-related functions such as ZeroContents() may be no-ops.
type Map struct {
ortValue *C.OrtValue
// An onnxruntime map is really just two tensors, keys and values, that
// must be the same length. These Values will be cleaned up when calling
// Map.Destroy.
keys Value
values Value
}
// Creates a new ONNX map that maps the given keys tensor to the given values
// tensor. Destroying the Map created by this function does _not_ destroy these
// keys and values tensors; the caller is still responsible for destroying
// them.
//
// Internally, creating a Map requires two tensors of the same length, and
// with constraints on type. For example, keys are not allowed to be floats
// (at least currently). (At the time of writing, this has only been confirmed
// to work with int64 keys.) There may be many other constraints enforced by
// the underlying C API.
func NewMap(keys, values Value) (*Map, error) {
if !IsInitialized() {
return nil, NotInitializedError
}
newMapArgs := []*C.OrtValue{
keys.GetInternals().ortValue,
values.GetInternals().ortValue,
}
var result *C.OrtValue
status := C.CreateOrtValue(&(newMapArgs[0]), 2, C.ONNX_TYPE_MAP, &result)
if status != nil {
return nil, fmt.Errorf("Error creating ORT map: %s",
statusToError(status))
}
// We need to obtain internal references to the keys and values allocated
// by onnxruntime. createMapFromOrtValue does this for us.
toReturn, e := createMapFromOrtValue(result)
if e != nil {
// createMapFromOrtValue already destroys the OrtValue on error.
return nil, fmt.Errorf("Error creating Map instance from map "+
"OrtValue: %w", e)
}
return toReturn, nil
}
// Wraps the creation of an ONNX map from a Go map. K is the key type, and V is
// the value type. Be aware that constraints on these types exist based on
// what ONNX supports. See the comment on NewMap.
func NewMapFromGoMap[K, V TensorData](m map[K]V) (*Map, error) {
if !IsInitialized() {
return nil, NotInitializedError
}
keysSlice := make([]K, len(m))
valuesSlice := make([]V, len(m))
i := 0
for k, v := range m {
keysSlice[i] = k
valuesSlice[i] = v
i++
}
tensorShape := NewShape(int64(len(m)))
keysTensor, e := NewTensor(tensorShape, keysSlice)
if e != nil {
return nil, fmt.Errorf("Error creating keys tensor for map: %w", e)
}
defer keysTensor.Destroy()
valuesTensor, e := NewTensor(tensorShape, valuesSlice)
if e != nil {
return nil, fmt.Errorf("Error creating values tensor for map: %w", e)
}
defer valuesTensor.Destroy()
toReturn, e := NewMap(keysTensor, valuesTensor)
if e != nil {
return nil, fmt.Errorf("Error creating map from key and value "+
"tensors: %w", e)
}
return toReturn, nil
}
// Returns two Tensors containing the keys and values, respectively. These
// tensors should _not_ be Destroyed by users; they will be automatically
// cleaned up when m.Destroy() is called. These are _not_ the same Value
// instances that were passed to NewMap, and these should not be modified by
// users.
func (m *Map) GetKeysAndValues() (Value, Value, error) {
return m.keys, m.values, nil
}
func (m *Map) Destroy() error {
C.ReleaseOrtValue(m.ortValue)
// Just return the last error if either of these returns an error.
var e error
e2 := m.keys.Destroy()
if e2 != nil {
e = e2
}
e2 = m.values.Destroy()
if e2 != nil {
e = e2
}
m.ortValue = nil
m.keys = nil
m.values = nil
return e
}
// Always returns ONNXTypeMap
func (m *Map) GetONNXType() ONNXType {
return ONNXTypeMap
}
// Returns the shape of the map's keys Tensor. Essentially, this can be used
// to determine the number of key/value pairs in the map.
func (m *Map) GetShape() Shape {
return m.keys.GetShape()
}
func (m *Map) GetInternals() *ValueInternalData {
return &ValueInternalData{
ortValue: m.ortValue,
}
}
// As with Sequence.ZeroContents(), this is a no-op (at least for now), and is
// only present for compatibility with the Value interface.
func (m *Map) ZeroContents() {
}
// As with a Sequence, this always returns the undefined data type and is only
// present for compatibility with the Value interface.
func (m *Map) DataType() C.ONNXTensorElementDataType {
return C.ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED
}
// Wraps the ONNXType enum in C.
type ONNXType int
const (
ONNXTypeUnknown = C.ONNX_TYPE_UNKNOWN
ONNXTypeTensor = C.ONNX_TYPE_TENSOR
ONNXTypeSequence = C.ONNX_TYPE_SEQUENCE
ONNXTypeMap = C.ONNX_TYPE_MAP
ONNXTypeOpaque = C.ONNX_TYPE_OPAQUE
ONNXTypeSparseTensor = C.ONNX_TYPE_SPARSETENSOR
ONNXTypeOptional = C.ONNX_TYPE_OPTIONAL
)
func (t ONNXType) String() string {
switch t {
case ONNXTypeUnknown:
return "ONNX_TYPE_UNKNOWN"
case ONNXTypeTensor:
return "ONNX_TYPE_TENSOR"
case ONNXTypeSequence:
return "ONNX_TYPE_SEQUENCE"
case ONNXTypeMap:
return "ONNX_TYPE_MAP"
case ONNXTypeOpaque:
return "ONNX_TYPE_OPAQUE"
case ONNXTypeSparseTensor:
return "ONNX_TYPE_SPARSE_TENSOR"
case ONNXTypeOptional:
return "ONNX_TYPE_OPTIONAL"
}
return fmt.Sprintf("Unknown ONNX type: %d", int(t))
}
// This satisfies the Value interface, but is intended to allow users to
// provide tensors of types that may not be supported by the generic typed
// Tensor[T] struct. Instead, CustomDataTensors are backed by a slice of bytes,
// using a user-provided shape and type from the ONNXTensorElementDataType
// enum.
type CustomDataTensor struct {
data []byte
dataType C.ONNXTensorElementDataType
shape Shape
ortValue *C.OrtValue
}
// Creates and returns a new CustomDataTensor using the given bytes as the
// underlying data slice. Apart from ensuring that the provided data slice is
// non-empty, this function mostly delegates validation of the provided data to
// the C onnxruntime library. For example, it is the caller's responsibility to
// ensure that the provided dataType and data slice are valid and correctly
// sized for the specified shape. If this returns successfully, the caller must
// call the returned tensor's Destroy() function to free it when no longer in
// use.
func NewCustomDataTensor(s Shape, data []byte,
dataType TensorElementDataType) (*CustomDataTensor, error) {
if !IsInitialized() {
return nil, NotInitializedError
}
e := s.Validate()
if e != nil {
return nil, fmt.Errorf("Invalid tensor shape: %w", e)
}
if len(data) == 0 {
return nil, fmt.Errorf("A CustomDataTensor requires at least one " +
"byte of data")
}
dt := C.ONNXTensorElementDataType(dataType)
var ortValue *C.OrtValue
status := C.CreateOrtTensorWithShape(unsafe.Pointer(&data[0]),
C.size_t(len(data)), (*C.int64_t)(unsafe.Pointer(&s[0])),
C.int64_t(len(s)), ortMemoryInfo, dt, &ortValue)
if status != nil {
return nil, fmt.Errorf("ORT API error creating tensor: %s",
statusToError(status))
}
toReturn := CustomDataTensor{
data: data,
dataType: dt,
shape: s.Clone(),
ortValue: ortValue,
}
return &toReturn, nil
}
func (t *CustomDataTensor) Destroy() error {
C.ReleaseOrtValue(t.ortValue)
t.ortValue = nil
t.data = nil
t.shape = nil
t.dataType = C.ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED
return nil
}
func (t *CustomDataTensor) DataType() C.ONNXTensorElementDataType {
return t.dataType
}
func (t *CustomDataTensor) GetShape() Shape {
return t.shape.Clone()
}
func (t *CustomDataTensor) GetInternals() *ValueInternalData {
return &ValueInternalData{
ortValue: t.ortValue,
}
}
// Always returns ONNXTypeTensor, even if the CustomDataTensor is invalid for
// some reason.
func (t *CustomDataTensor) GetONNXType() ONNXType {
return ONNXTypeTensor
}
// Sets all bytes in the data slice to 0.
func (t *CustomDataTensor) ZeroContents() {
C.memset(unsafe.Pointer(&t.data[0]), 0, C.size_t(len(t.data)))
}
// Returns the same slice that was passed to NewCustomDataTensor.
func (t *CustomDataTensor) GetData() []byte {
return t.data
}
// Scalar is like a tensor but the underlying go slice is of length 1 and it
// has no dimension. It was introduced for use with the training API, but
// remains supported since it may be useful apart from the training API.
type Scalar[T TensorData] struct {
data []T
dataSize uintptr
ortValue *C.OrtValue
}
// Always returns nil for Scalars.
func (s *Scalar[T]) GetShape() Shape {
return nil
}
func (s *Scalar[T]) ZeroContents() {
C.memset(unsafe.Pointer(&s.data[0]), 0, C.size_t(s.dataSize))
}
func (s *Scalar[T]) Destroy() error {
C.ReleaseOrtValue(s.ortValue)
s.ortValue = nil
s.data = nil
s.dataSize = 0
return nil
}
// GetData returns the undelying data for the scalar. If you want to set the
// scalar's data, use Set.
func (t *Scalar[T]) GetData() T {
return t.data[0]
}
// Changes the underlying value of the scalar to the new value.
func (t *Scalar[T]) Set(value T) {
t.data = []T{value}
}
func (t *Scalar[T]) DataType() C.ONNXTensorElementDataType {
return GetTensorElementDataType[T]()
}
func (t *Scalar[_]) GetInternals() *ValueInternalData {
return &ValueInternalData{
ortValue: t.ortValue,
}
}
func (t *Scalar[_]) GetONNXType() ONNXType {
return ONNXTypeTensor
}
// NewEmptyScalar creates a new scalar of type T.
func NewEmptyScalar[T TensorData]() (*Scalar[T], error) {
var data T
return NewScalar(data)
}
// NewScalar creates a new scalar of type T backed by a value of type T.
// Note that, differently from tensors, this is not a []T but just a value T.
func NewScalar[T TensorData](data T) (*Scalar[T], error) {
if !IsInitialized() {
return nil, NotInitializedError
}
dataSlice := []T{data}
var ortValue *C.OrtValue
dataType := GetTensorElementDataType[T]()
dataSize := unsafe.Sizeof(dataSlice[0]) * uintptr(1)
status := C.CreateOrtTensorWithShape(unsafe.Pointer(&dataSlice[0]),
C.size_t(dataSize), nil, C.int64_t(0), ortMemoryInfo, dataType, &ortValue)
if status != nil {
return nil, statusToError(status)
}
toReturn := Scalar[T]{
data: dataSlice,
dataSize: dataSize,
ortValue: ortValue,
}
return &toReturn, nil
}
// Holds options required when enabling the CUDA backend for a session. This
// struct wraps C onnxruntime types; users must create instances of this using
// the NewCUDAProviderOptions() function. So, to enable CUDA for a session,
// follow these steps:
//
// 1. Call NewSessionOptions() to create a SessionOptions struct.
// 2. Call NewCUDAProviderOptions() to obtain a CUDAProviderOptions struct.
// 3. Call the CUDAProviderOptions struct's Update(...) function to pass a
// list of settings to CUDA. (See the comment on the Update() function.)
// 4. Pass the CUDA options struct pointer to the
// SessionOptions.AppendExecutionProviderCUDA(...) function.
// 5. Call the Destroy() function on the CUDA provider options.
// 6. Call NewAdvancedSession(...), passing the SessionOptions struct to it.
// 7. Call the Destroy() function on the SessionOptions struct.
//
// Admittedly, this is a bit of a mess, but that's how it's handled by the C
// API internally. (The onnxruntime python API hides a bunch of this complexity
// using getter and setter functions, for which Go does not have a terse
// equivalent.)
type CUDAProviderOptions struct {
o *C.OrtCUDAProviderOptionsV2
}
// Used when setting key-value pair options with certain obnoxious C APIs.
// The entries in each of the returned slices must be freed when they're
// no longer needed.
func mapToCStrings(options map[string]string) ([]*C.char, []*C.char) {
keys := make([]*C.char, 0, len(options))
values := make([]*C.char, 0, len(options))
for k, v := range options {
keys = append(keys, C.CString(k))
values = append(values, C.CString(v))
}
return keys, values
}