Introducing LiteRT : Google's high-performance runtime for on-device AI, formerly known as TensorFlow Lite.
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tflite_support.metadata.MetadataDisplayer
Displays metadata and associated file info in human-readable format.
tflite_support . metadata . MetadataDisplayer (
model_buffer , metadata_buffer , associated_file_list
)
Args
model_buffer
valid buffer of the model file.
metadata_buffer
valid buffer of the metadata file.
associated_file_list
list of associate files in the model file.
Methods
get_associated_file_buffer
View source
get_associated_file_buffer (
filename
)
Get the specified associated file content in bytearray.
Args
filename
name of the file to be extracted.
Returns
The file content in bytearray.
Raises
ValueError
if the file does not exist in the model.
View source
get_metadata_buffer ()
Get the metadata buffer in bytearray out from the model.
View source
get_metadata_json ()
Converts the metadata into a json string.
get_packed_associated_file_list
View source
get_packed_associated_file_list ()
Returns a list of associated files that are packed in the model.
Returns
A name list of associated files.
with_model_buffer
View source
@classmethod
with_model_buffer (
model_buffer
)
Creates a MetadataDisplayer object for a file buffer.
Args
model_buffer
TensorFlow Lite model buffer in bytearray.
Returns
MetadataDisplayer object.
with_model_file
View source
@classmethod
with_model_file (
model_file
)
Creates a MetadataDisplayer object for the model file.
Args
model_file
valid path to a TensorFlow Lite model file.
Returns
MetadataDisplayer object.
Raises
IOError
File not found.
ValueError
The model does not have metadata.
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Last updated 2024-05-08 UTC.
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