tflite

library2.18.0pypypi✓ verified 81d ago

A pure Python parser for TensorFlow Lite models (*.tflite) that extracts model metadata, operator codes, subgraphs, and tensors without requiring TensorFlow runtime. Current version 2.18.0 corresponds to TensorFlow 2.18.0 schema. Releases follow TensorFlow's major.minor versions, with occasional patches.

ai-ml data serialization

pip install tflite

github ↗package ↗homepage ↗

INSTALL

IMPORT

SIG · TFLITE

tflite

ai-mlpythonv2.18.0

Install

3.9s avg

Import

418ms

Disk

91MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v2.18.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.404s · 91.4MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 3.9s · import 0.432s · 88MB

91MB installed

● package 91MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Model

✓ from tflite import Model

✗ import tflite

Parses a TFLite file and prints each operator's name.

import tflite # Load a TFLite model file (must be a .tflite file) with open('/path/to/model.tflite', 'rb') as f: buf = f.read() # Parse the model model = tflite.Model.GetRootAsModel(buf, 0) # Access version print('Model version:', model.Version()) # Access operator codes for i in range(model.OperatorCodesLength()): opcode = model.OperatorCodes(i) code = opcode.BuiltinCode() print('Opcode', i, ':', tflite.BUILTIN_OPCODE2NAME.get(code, 'UNKNOWN'))

Debug

Known issues

gotchaThe package version must match the TensorFlow version that generated the model. Using tflite 2.10.0 to parse a model from TF 2.18.0 may fail due to schema changes (e.g., new operator codes).

fix

Align tflite version with the TensorFlow version used to create the model.

affects: all

gotchaThe model buffer must be read as bytes (binary mode). Passing a text string or reading as text will lead to parsing errors.

fix

Use 'rb' mode: open(path, 'rb').read()

affects: all

deprecatedOperatorCode.BuiltinCode() may be deprecated in future releases; check the README for compatibility handling. In TF 2.4.0+, the method exists but the schema may expose 'builtin_code' directly on the operator code object.

fix

Use tflite.OperatorCode.BuiltinCode() as documented, but watch for direct attribute access in newer flatbuffers.

affects: >=2.4.0

gotchaThe package does not validate that the input file is a valid TFLite model. If the buffer is malformed, the GetRootAsModel call may succeed but subsequent accesses can raise exceptions.

fix

Wrap usage in try/except blocks when dealing with untrusted files.

affects: all

Upgrade

Version history

2.18.0latest on PyPI · released Jan 28, 2025

Audit

Dependencies

flatbuffersrequiredRequired for deserializing TFLite FlatBuffer files

Agent activity

25 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/zhenhuaw-me/tflite ↗

packagehttps://pypi.org/project/tflite/ ↗

homepagehttps://zhenhuaw.me/tflite ↗