tf.lite.OpsSet

TensorFlow 1 version

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Representative dataset to evaluate optimizations.

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tf.compat.v1.lite.RepresentativeDataset

tf.lite.RepresentativeDataset(
    input_gen
)

A representative dataset that can be used to evaluate optimizations by the converter. E.g. converter can use these examples to estimate (min, max) ranges by calibrating the model on inputs. This can allow converter to quantize a converted floating point model.

Args
`input_gen`	an input generator that can be used to generate input samples for the model. This must be a callable object that returns an object that supports the `iter()` protocol (e.g. a generator function). The elements generated must have same type and shape as inputs to the model.

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.lite / OpsSet

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Args