module onnxrt.ops_cpu.op_concat_from_sequence#

Inheritance diagram of mlprodict.onnxrt.ops_cpu.op_concat_from_sequence

Short summary#

module mlprodict.onnxrt.ops_cpu.op_concat_from_sequence

Runtime operator.

source on GitHub

Classes#

class

truncated documentation

ConcatFromSequence

ConcatFromSequence ================== Concatenate a sequence of tensors into a single tensor. All input tensors must have …

Functions#

function

truncated documentation

_concat_from_sequence

Properties#

property

truncated documentation

args_default

Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …

args_default_modified

Returns the list of modified parameters.

args_mandatory

Returns the list of optional arguments.

args_optional

Returns the list of optional arguments.

atts_value

Returns all parameters in a dictionary.

Methods#

method

truncated documentation

__init__

_run

Documentation#

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_concat_from_sequence.ConcatFromSequence(onnx_node, desc=None, **options)#

Bases: OpRun

Concatenate a sequence of tensors into a single tensor. All input tensors must have the same shape, except for the dimension size of the axis to concatenate on. By default ‘new_axis’ is 0, the behavior is similar to numpy.concatenate. When ‘new_axis’ is 1, the behavior is similar to numpy.stack.

Attributes

  • axis (required): Which axis to concat on. Accepted range in [-r, r - 1], where r is the rank of input tensors. When new_axis is 1, accepted range is [-r - 1, r]. default value cannot be automatically retrieved (INT)

  • new_axis: Insert and concatenate on a new axis or not, default 0 means do not insert new axis. Default value is namenewaxisi0typeINT (INT)

Inputs

  • input_sequence (heterogeneous)S: Sequence of tensors for concatenation

Outputs

  • concat_result (heterogeneous)T: Concatenated tensor

Type Constraints

  • S seq(tensor(uint8)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(int8)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(float16)), seq(tensor(float)), seq(tensor(double)), seq(tensor(string)), seq(tensor(bool)), seq(tensor(complex64)), seq(tensor(complex128)): Constrain input types to any tensor type.

  • T tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(int8), tensor(int16), tensor(int32), tensor(int64), tensor(float16), tensor(float), tensor(double), tensor(string), tensor(bool), tensor(complex64), tensor(complex128): Constrain output types to any tensor type.

Version

Onnx name: ConcatFromSequence

This version of the operator has been available since version 11.

Runtime implementation: ConcatFromSequence

__init__(onnx_node, desc=None, **options)#
_run(seq, attributes=None, verbose=0, fLOG=None)#

Should be overwritten.

source on GitHub

mlprodict.onnxrt.ops_cpu.op_concat_from_sequence._concat_from_sequence(seq, axis, new_axis=0)#