module `onnxrt.ops_cpu.op_shape`#

Short summary#

module mlprodict.onnxrt.ops_cpu.op_shape

Runtime operator.

Classes#

class	truncated documentation
`Shape`	Shape ===== Takes a tensor as input and outputs an 1D int64 tensor containing the shape of the input tensor. Optional …

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__`
`_infer_shapes`
`_infer_sizes`
`_infer_types`
`_run`

Documentation#

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_shape.Shape(onnx_node, desc=None, **options)#

Bases: mlprodict.onnxrt.ops_cpu._op.OpRun

Takes a tensor as input and outputs an 1D int64 tensor containing the shape of the input tensor. Optional attributes start and end can be used to compute a slice of the input tensor’s shape. If start axis is omitted, the slice starts from axis 0. The end axis, if specified, is exclusive (and the returned value will not include the size of that axis). If the end axis is omitted, the axes upto the last one will be included. Negative axes indicate counting back from the last axis. Note that axes will be clipped to the range [0, r-1], where r is the rank of the input tensor if they are out-of-range (after adding r in the case of negative axis). Thus, specifying any end value > r is equivalent to specifying an end value of r, and specifying any start value < -r is equivalent to specifying a start value of 0.

For example: Input tensor with shape: [2, 3, 4] No attributes specified. Output: [2, 3, 4]

Input tensor with shape: [2, 3, 4] start: -1 Output: [4]

Input tensor with shape: [2, 3, 4] end: -1 Output: [2, 3]

Input tensor with shape: [2, 3, 4] start: 1 end: 2 Output: [3]

Attributes

end: (Optional) Ending axis for slicing the shape. Negative value means counting dimensions from the back. If omitted, sizes of all axes upto (including) the last one will be included. default value cannot be automatically retrieved (INT)
start: (Optional) Starting axis for slicing the shape. Default value is 0.Negative value means counting dimensions from the back. Default value is namestarti0typeINT (INT)

Inputs

data (heterogeneous)T: An input tensor.

Outputs

shape (heterogeneous)T1: Shape of the input tensor

Type Constraints

T tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(int8), tensor(int16), tensor(int32), tensor(int64), tensor(bfloat16), tensor(float16), tensor(float), tensor(double), tensor(string), tensor(bool), tensor(complex64), tensor(complex128): Input tensor can be of arbitrary type.
T1 tensor(int64): Constrain output to int64 tensor.

Version

Onnx name: Shape

This version of the operator has been available since version 15.

Runtime implementation: Shape

Parameters