mltk.core.TfliteModelParameters¶

class TfliteModelParameters[source]¶

.tflite Model Parameters

Model parameters are effectively a dictionary of key/value pairs where:

key - Name of parameter as a string
value - Value of parameter as a specific scalar data type

The model parameters are serialized using a Flatbuffer schema.

The serialized parameters are inserted into a .tflite model’s “metadata” section: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/schema/schema.fbs#L1235

The basic flow is:

User Python script populates a TfliteModelParameters object
Use add_to_tflite_file() to serialize parameters and add to .tflite model metadata
At a later time, use load_from_tflite_file() to load parameters from .tflite model metadata
Another user Python script accesses parameters in TfliteModelParameters

Note

The TfliteModelParameters object inherits FlatbufferDictionary which inherits the standard Python ‘dict’ class.

Methods

`__init__`
`add_to_tflite_file`	Add the model parameters to the given .tflite model file
`add_to_tflite_flatbuffer`	Add the model parameters to the given .tflite flatbuffer and return the updated flatbuffer
`add_to_tflite_model`	Add the model parameters to the given TfliteModel object
`clear`
`copy`
`deserialize`	Instantiate a FlatbufferDictionary object with the given serialized flatbuffer binary data
`fromkeys`	Create a new dictionary with keys from iterable and values set to value.
`get`	Return the value for key if key is in the dictionary, else default.
`items`
`keys`
`load_from_tflite_file`	Load the TfliteModelParameters from the given .tflite model file's metadata
`load_from_tflite_flatbuffer`	Load the TfliteModelParameters from the given .tflite model flatbuffer bytes
`load_from_tflite_model`	Load the TfliteModelParameters from the given TfliteModel object
`pop`	If the key is not found, return the default if given; otherwise, raise a KeyError.
`popitem`	Remove and return a (key, value) pair as a 2-tuple.
`put`	Put an entry into the dictionary
`serialize`	Serialize the current dictionary entries into a flatbuffer
`setdefault`	Insert key with a value of default if key is not in the dictionary.
`summary`	Generate a summary of the dictionary
`update`	If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
`values`

static load_from_tflite_file(tflite_path, tag=None)[source]¶

Load the TfliteModelParameters from the given .tflite model file’s metadata

Parameters:

tflite_path (str) –
tag (str) –

static load_from_tflite_flatbuffer(tflite_flatbuffer, tag=None)[source]¶

Load the TfliteModelParameters from the given .tflite model flatbuffer bytes

Parameters:

tflite_flatbuffer (bytes) –
tag (str) –

static load_from_tflite_model(tflite_model, tag=None)[source]¶

Load the TfliteModelParameters from the given TfliteModel object

Parameters:

tflite_model (TfliteModel) –
tag (str) –

add_to_tflite_file(tflite_path, output=None, tag=None)[source]¶

Add the model parameters to the given .tflite model file

This adds the current parameters to the given .tflite model file’s metadata. If output argument is given, then overwrite the given .tflite model file.

Parameters:

tflite_path (str) – Path to .tflite model file
output (str) – Optional, path to output .tflite model file
tag (str) –

add_to_tflite_flatbuffer(tflite_flatbuffer, tag=None)[source]¶

Add the model parameters to the given .tflite flatbuffer and return the updated flatbuffer

Parameters:

tflite_flatbuffer (bytes) – .tflite model flatbuffer to update with the model parameters
tag (str) –

Return type:

bytes

Returns:

The update .tflite model flatbuffer

add_to_tflite_model(tflite_model, tag=None)[source]¶

Add the model parameters to the given TfliteModel object

Parameters:

tflite_model (TfliteModel) – TfliteModel model object
tag (str) –

__init__(*args, **kwargs)¶

__new__(*args, **kwargs)¶

clear() → None. Remove all items from D.¶

copy() → a shallow copy of D¶

static deserialize(serialized_data)¶

Instantiate a FlatbufferDictionary object with the given serialized flatbuffer binary data

Parameters:: serialized_data (bytes) –

fromkeys(iterable, value=None, /)¶: Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)¶: Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items¶

keys() → a set-like object providing a view on D's keys¶

pop(key, default=<unrepresentable>, /)¶: If the key is not found, return the default if given; otherwise, raise a KeyError.

popitem(/)¶

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

put(key, value, dtype=None)¶

Put an entry into the dictionary

This API allows for specifying the value’s datatype. Alternatively, you can use the standard Python dictionary syntax, e.g.:

my_params.set(‘foo’, 42, ‘int32’) OR my_params[‘foo’] = 42

Parameters:

key (str) – The dictionary key to insert or overwrite
value (Union[str, int, float, bool, List[str], bytes]) – The value of the entry. Must have a type of: str,int,float,bool,List[str], or bytes
dtype (str) – Optional. Force the value to have a specific data type. Must be a string and one of: bool,int8,int16,int32,int64,uint8,uint16,uint32,uint64,float,double,str,str_list,bin

serialize()¶

Serialize the current dictionary entries into a flatbuffer

Return type:: bytes
Returns:: Serialized dictionary flatbuffer bytes

setdefault(key, default=None, /)¶

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

summary()¶

Generate a summary of the dictionary

Return type:: str

update([E, ]**F) → None. Update D from dict/iterable E and F.¶: If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values() → an object providing a view on D's values¶