This document describes LiteRT's op versioning schema. Op versioning enables developers to add new functionalities and parameters into existing ops. In addition, it guarantees the following:
- Backward compatibility: New LiteRT implementation should handle an old model file.
- Forward compatibility: Old LiteRT implementation should handle a new model file produced by new version of converter, as long as no new features are used.
- Forward in-compatibility detection: If an old LiteRT implementation reads a new model that contains a new version of an op which isn't supported, it should report the error.
Example: Adding dilation into depthwise convolution
The remainder of this document explains op versioning in TFLite by showing how to add dilation parameters to the depthwise convolution operation.
Knowledge of dilation is not required to understand this document. Note that:
- 2 new integer parameters will be added:
dilation_width_factoranddilation_height_factor. - Old depthwise convolution kernels that don't support dilation are equivalent to setting the dilation factors to 1.
Change FlatBuffer schema
To add new parameters into an op, change the options table in lite/schema/schema.fbs
.
For example, the options table of depthwise convolution looks like this:
table
DepthwiseConv2DOptions
{
padding
:
Padding
;
stride_w
:
int
;
stride_h
:
int
;
depth_multiplier
:
int
;
fused_activation_function
:
ActivationFunctionType
;
}
When adding new parameters:
- Add comments indicating which parameters are supported by which version.
- When the new implementation gets the default values for newly added parameters, it should work exactly the same as the old implementation.
The table will be like this after the new parameters are added:
table
DepthwiseConv2DOptions
{
//
Parameters
for
DepthwiseConv
version
1
or
above.
padding
:
Padding
;
stride_w
:
int
;
stride_h
:
int
;
depth_multiplier
:
int
;
fused_activation_function
:
ActivationFunctionType
;
//
Parameters
for
DepthwiseConv
version
2
or
above.
dilation_w_factor
:
int
=
1
;
dilation_h_factor
:
int
=
1
;
}
The file lite/schema/schema_generated.h
should be re-generated for the new
schema.
Change C structures and kernel implementation
In LiteRT, the kernel implementation is decoupled from FlatBuffer definition.
The kernels read the parameter from C structures defined in lite/c/builtin_op_data.h
.
The original depthwise convolution parameter is as follows:
typedef
struct
{
TfLitePadding
padding
;
int
stride_width
;
int
stride_height
;
int
depth_multiplier
;
TfLiteFusedActivation
activation
;
}
TfLiteDepthwiseConvParams
;
As with the FlatBuffer schema, add comments indicating which parameters are supported starting from which version. The result is seen below:
typedef
struct
{
// Parameters for DepthwiseConv version 1 or above.
TfLitePadding
padding
;
int
stride_width
;
int
stride_height
;
int
depth_multiplier
;
TfLiteFusedActivation
activation
;
// Parameters for DepthwiseConv version 2 or above.
int
dilation_width_factor
;
int
dilation_height_factor
;
}
TfLiteDepthwiseConvParams
;
Please also change the kernel implementation to read the newly added parameters from the C structures. The details are omitted here.
Change the FlatBuffer reading code
The logic to read FlatBuffer and produce C structure is in lite/core/api/flatbuffer_conversions.cc
.
Update the file to handle the new parameters, as shown below:
TfLiteStatus
ParseDepthwiseConv2D
(
const
Operator
*
op
,
ErrorReporter
*
error_reporter
,
BuiltinDataAllocator
*
allocator
,
void
**
builtin_data
)
{
CheckParsePointerParams
(
op
,
error_reporter
,
allocator
,
builtin_data
);
SafeBuiltinDataAllocator
safe_allocator
(
allocator
);
std
::
unique_ptr<TfLiteDepthwiseConvParams
,
SafeBuiltinDataAllocator
::
BuiltinDataDeleter
>
params
=
safe_allocator
.
Allocate<TfLiteDepthwiseConvParams>
();
TF_LITE_ENSURE
(
error_reporter
,
params
!=
nullptr
);
const
DepthwiseConv2DOptions
*
schema_params
=
op
-
> builtin_options_as_DepthwiseConv2DOptions
();
if
(
schema_params
!=
nullptr
)
{
params
-
> padding
=
ConvertPadding
(
schema_params
-
> padding
());
params
-
> stride_width
=
schema_params
-
> stride_w
();
params
-
> stride_height
=
schema_params
-
> stride_h
();
params
-
> depth_multiplier
=
schema_params
-
> depth_multiplier
();
params
-
> activation
=
ConvertActivation
(
schema_params
-
> fused_activation_function
());
params
-
> dilation_width_factor
=
schema_params
-
> dilation_w_factor
();
params
-
> dilation_height_factor
=
schema_params
-
> dilation_h_factor
();
}
*
builtin_data
=
params
.
release
();
return
kTfLiteOk
;
}
It's not required to check the op version here. When the new implementation reads an old model file where dilation factors are missing, it will use 1 as the default value, and the new kernel will work consistently with the old kernel.
Change kernel registration
The MutableOpResolver (defined in lite/mutable_op_resolver.h
) provides a few
functions to register op kernels. The minimum and maximum version are 1 by
default:
void
AddBuiltin
(
tflite
::
BuiltinOperator
op
,
TfLiteRegistration
*
registration
,
int
min_version
=
1
,
int
max_version
=
1
);
void
AddCustom
(
const
char
*
name
,
TfLiteRegistration
*
registration
,
int
min_version
=
1
,
int
max_version
=
1
);
The built-in ops are registered in lite/kernels/register.cc
. In this example,
we implemented a new op kernel which can handle DepthwiseConv2D
version 1 and
2, so we need to change this line:
AddBuiltin(BuiltinOperator_DEPTHWISE_CONV_2D, Register_DEPTHWISE_CONV_2D());
to:
AddBuiltin(BuiltinOperator_DEPTHWISE_CONV_2D, Register_DEPTHWISE_CONV_2D(),
/* min_version = */ 1,
/*
max_version = */ 2);
Change TFLite op version
The next step is to make TFLite populate the minimum version that's required to execute the op. In this example, it means:
- Populate version=1 when dilation factors are all 1.
- Populate version=2 otherwise.
Modify GetBuiltinOperatorVersion
function for the operator in lite/tools/versioning/op_version.cc
by adding the new version to the case of DepthwiseConv2D
:
case
BuiltinOperator_DEPTHWISE_CONV_2D
:
auto
depthwise_conv_params
=
reinterpret_cast<TfLiteDepthwiseConvParams
*>(
op_sig
.
builtin_data
);
TFLITE_DCHECK
(
depthwise_conv_params
!=
nullptr
);
if
(
depthwise_conv_params->dilation_width_factor
!=
1
||
depthwise_conv_params->dilation_height_factor
!=
1
)
{
return
2
;
}
return
1
;
Update the operator version map
The last step is to add the new version info into the operator version map. This step is required because we need to generate the model's minimum required runtime version based on this version map.
To do this, you need to add a new map entry in lite/tools/versioning/runtime_version.cc
.
In this example, you need to add the following entry into op_version_map
:
{ {BuiltinOperator_DEPTHWISE_CONV_2D, 2}, %CURRENT_RUNTIME_VERSION%}
where %CURRENT_RUNTIME_VERSION%
corresponds to the current runtime version
defined in release_version.h
.
Delegation implementation
LiteRT provides a delegation API which enables delegating ops to hardware
backends. In the delegate's Prepare
function, check if the version is
supported for every node in Delegation code.
const
int
kMaxVersion
=
1
;
TfLiteNode
*
node
;
TfLiteRegistration
*
registration
=
nullptr
;
TF_LITE_ENSURE_STATUS
(
context
-
> GetNodeAndRegistration
(
context
,
node_index
,
& node
,
& registration
));
if
(
registration
-
> version
>
kMaxVersion
)
{
//
Reject
the
node
if
the
version
isn
't supported.
}
This is required even if the delegation only supports version 1 ops, so the delegation can detect incompatibility when getting a higher version op.
