MQL5 ReferenceONNX modelsAutomatic data type conversion

Autoconvert input and output values when running ONNX models

The current ONNX version in MQL5 supports only tensors for input/output values. Tensors are data arrays with the elements of the following data types:

ONNX type	Corresponds to MQL5 type
ONNX_DATA_TYPE_BOOL	bool
ONNX_DATA_TYPE_FLOAT	float
ONNX_DATA_TYPE_UINT8	uchar
ONNX_DATA_TYPE_INT8	char
ONNX_DATA_TYPE_UINT16	ushort
ONNX_DATA_TYPE_INT16	short
ONNX_DATA_TYPE_INT32	int
ONNX_DATA_TYPE_INT64	long
ONNX_DATA_TYPE_FLOAT16	—
ONNX_DATA_TYPE_DOUBLE	double
ONNX_DATA_TYPE_UINT32	uint
ONNX_DATA_TYPE_UINT64	ulong
ONNX_DATA_TYPE_COMPLEX64	—
ONNX_DATA_TYPE_COMPLEX128	complex
ONNX_DATA_TYPE_BFLOAT16	—
ONNX_DATA_TYPE_STRING	—

Only arrays, vectors and matrices (we will refer to them as the Data) can be fed into ONNX models as input/output values.

If the parameter types does not match the ONNX model's parameter type, and the OnnxRun is called without the ONNX_NO_CONVERSION flag specified, automatic data conversion will be applied. Autoconversion implies that before running an ONNX model, user Data will be copied into ONNX tensors with the relevant conversion.

When an ONNX model is run without the autoconversion, the model will be calculated using the Data without any additional copying.

IMPORTANT! Autoconversion does not control overflow (truncate), therefore you should carefully monitor the data and the data types input into the ONNX model.

Autoconversion supports the following ONNX types:

ONNX_DATA_TYPE_BOOL
ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_UINT8
ONNX_DATA_TYPE_INT8
ONNX_DATA_TYPE_UINT16
ONNX_DATA_TYPE_INT16
ONNX_DATA_TYPE_INT32
ONNX_DATA_TYPE_INT64
ONNX_DATA_TYPE_FLOAT16
ONNX_DATA_TYPE_DOUBLE
ONNX_DATA_TYPE_UINT32
ONNX_DATA_TYPE_UINT64
ONNX_DATA_TYPE_COMPLEX64
ONNX_DATA_TYPE_COMPLEX128

Unsupported types:

ONNX_DATA_TYPE_BFLOAT16
ONNX_DATA_TYPE_STRING

Autoconversion Rules by Tensor Types

If the MQL5 type is not included into the list of types supported by the model, running the ONNX model will return the ERR_ONNX_NOT_SUPPORTED error (error code 5802).

Note: During autoconversion, the color type is processed as uint, while datetime is processed as long.

Autoconversion of input values

ONNX type (tensor item type)	MQL5 type supported by autoconversion
ONNX_DATA_TYPE_BOOL	bool, char, uchar, short, ushort, int, color, uint, datetime, long, folat, double, complex During conversion, Data elements are checked by a simple comparison against 0
ONNX_DATA_TYPE_FLOAT16	float, double
ONNX_DATA_TYPE_FLOAT	char, uchar, short, ushort, int, color, uint, datetime, long, ulong, float, double
ONNX_DATA_TYPE_UINT8	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_INT8	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_UINT16	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_INT16	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_INT32	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_INT64	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_DOUBLE	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_UINT32	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_UINT64	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_COMPLEX64	complex
ONNX_DATA_TYPE_COMPLEX128	complex

Autoconversion of output values

ONNX type (tensor item type)	MQL5 type supported by autoconversion
ONNX_DATA_TYPE_BOOL	bool, char, uchar, short, ushort, int, color, uint, datetime, long, folat, double, complex If the tensor element is zero, then the Data element is set to 0; otherwise, the value is 1
ONNX_DATA_TYPE_FLOAT16	float, double
ONNX_DATA_TYPE_FLOAT	char, uchar, short, ushort, int, color, uint, datetime, long, ulong, float, double
ONNX_DATA_TYPE_UINT8	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_INT8	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_UINT16	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_INT16	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_INT32	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_INT64	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_DOUBLE	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_UINT32	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_UINT64	See ONNX_DATA_TYPE_FLOAT
ONNX_DATA_TYPE_COMPLEX64	complex
ONNX_DATA_TYPE_COMPLEX128	complex