Det#

Det - 11#

Version

  • name: Det (GitHub)

  • domain: main

  • since_version: 11

  • function: False

  • support_level: SupportType.COMMON

  • shape inference: True

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

Summary

Det calculates determinant of a square matrix or batches of square matrices. Det takes one input tensor of shape [*, M, M], where * is zero or more batch dimensions, and the inner-most 2 dimensions form square matrices. The output is a tensor of shape [*], containing the determinants of all input submatrices. e.g., When the input is 2-D, the output is a scalar(shape is empty: []).

Inputs

  • X (heterogeneous) - T: Input tensor

Outputs

  • Y (heterogeneous) - T: Output tensor

Type Constraints

  • T in ( tensor(double), tensor(float), tensor(float16) ): Constrain input and output types to floating-point tensors.

Examples

_2d

node = onnx.helper.make_node(
    'Det',
    inputs=['x'],
    outputs=['y'],
)

x = np.arange(4).reshape(2, 2).astype(np.float32)
y = np.linalg.det(x)  # expect -2
expect(node, inputs=[x], outputs=[y],
       name='test_det_2d')

_nd

node = onnx.helper.make_node(
    'Det',
    inputs=['x'],
    outputs=['y'],
)

x = np.array([[[1, 2], [3, 4]], [[1, 2], [2, 1]], [[1, 3], [3, 1]]]).astype(np.float32)
y = np.linalg.det(x)  # expect array([-2., -3., -8.])
expect(node, inputs=[x], outputs=[y],
       name='test_det_nd')