module onnxrt.ops_cpu.op_flatten#

Inheritance diagram of mlprodict.onnxrt.ops_cpu.op_flatten

Short summary#

module mlprodict.onnxrt.ops_cpu.op_flatten

Runtime operator.

source on GitHub

Classes#

class

truncated documentation

Flatten

Flatten ======= Flattens the input tensor into a 2D matrix. If input tensor has shape (d_0, d_1, .

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

to_python

Documentation#

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_flatten.Flatten(onnx_node, desc=None, **options)#

Bases: OpRunUnary

Flattens the input tensor into a 2D matrix. If input tensor has shape (d_0, d_1, … d_n) then the output will have shape (d_0 X d_1 … d_(axis-1), d_axis X d_(axis+1) … X dn).

Attributes

  • axis: Indicate up to which input dimensions (exclusive) should be flattened to the outer dimension of the output. The value for axis must be in the range [-r, r], where r is the rank of the input tensor. Negative value means counting dimensions from the back. When axis = 0, the shape of the output tensor is (1, (d_0 X d_1 … d_n), where the shape of the input tensor is (d_0, d_1, … d_n). Default value is nameaxisi1typeINT (INT)

Inputs

  • input (heterogeneous)T: A tensor of rank >= axis.

Outputs

  • output (heterogeneous)T: A 2D tensor with the contents of the input tensor, with input dimensions up to axis flattened to the outer dimension of the output and remaining input dimensions flattened into the inner dimension of the output.

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): Constrain input and output to all tensor types.

Version

Onnx name: Flatten

This version of the operator has been available since version 13.

Runtime implementation: Flatten

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

Should be overwritten.

source on GitHub

to_python(inputs)#

Returns a python code equivalent to this operator.

Parameters:

inputs – inputs name

Returns:

imports, python code, both as strings

source on GitHub