Identity - version 14#
This page documents version 14 of operator Identity. See Identity for the latest version (since version 25).
Domain:
ai.onnxSince version: 14
Identity operator
Inputs
input (V): Input tensor
Outputs
output (V): Tensor to copy input into.
Type Constraints
V: Constrain input and output types to all tensor and sequence types. Allowed types: seq(tensor(bool)), seq(tensor(complex128)), seq(tensor(complex64)), seq(tensor(double)), seq(tensor(float)), seq(tensor(float16)), seq(tensor(int16)), seq(tensor(int32)), seq(tensor(int64)), seq(tensor(int8)), seq(tensor(string)), seq(tensor(uint16)), seq(tensor(uint32)), seq(tensor(uint64)), seq(tensor(uint8)), tensor(bfloat16), tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8).
Examples#
test_cc_identity_sequence
Node:
Identity(seq) -> (seq_out)
Inputs:
seq: shape=(1, 2, 2), dtype=float32
[[[1., 2.],
[3., 4.]]]
input_1: shape=(1, 2, 2), dtype=float32
[[[2., 3.],
[1., 5.]]]
Outputs:
seq_out: shape=(2, 1, 2, 2), dtype=float32
[[[[1., 2.],
[3., 4.]]],
[[[2., 3.],
[1., 5.]]]]
Differences with previous version (13)#
SchemaDiff: Identity (domain 'ai.onnx')
old version: 13
new version: 14
breaking: yes
Breaking reasons:
input ‘input’ (changed): type_str changed ‘T’ -> ‘V’
output ‘output’ (changed): type_str changed ‘T’ -> ‘V’
type constraint ‘T’ (removed): entire constraint removed
Inputs:
[BREAKING] changed ‘input’: type_str changed ‘T’ -> ‘V’
Outputs:
[BREAKING] changed ‘output’: type_str changed ‘T’ -> ‘V’
Type constraints:
[BREAKING] removed ‘T’: entire constraint removed
added ‘V’: added types: [‘seq(tensor(bool))’, ‘seq(tensor(complex128))’, ‘seq(tensor(complex64))’, ‘seq(tensor(double))’, ‘seq(tensor(float))’, ‘seq(tensor(float16))’, ‘seq(tensor(int16))’, ‘seq(tensor(int32))’, ‘seq(tensor(int64))’, ‘seq(tensor(int8))’, ‘seq(tensor(string))’, ‘seq(tensor(uint16))’, ‘seq(tensor(uint32))’, ‘seq(tensor(uint64))’, ‘seq(tensor(uint8))’, ‘tensor(bfloat16)’, ‘tensor(bool)’, ‘tensor(complex128)’, ‘tensor(complex64)’, ‘tensor(double)’, ‘tensor(float)’, ‘tensor(float16)’, ‘tensor(int16)’, ‘tensor(int32)’, ‘tensor(int64)’, ‘tensor(int8)’, ‘tensor(string)’, ‘tensor(uint16)’, ‘tensor(uint32)’, ‘tensor(uint64)’, ‘tensor(uint8)’]