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2ab06b48
编写于
12月 10, 2018
作者:
A
A. Unique TensorFlower
提交者:
TensorFlower Gardener
12月 10, 2018
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@@ -95,11 +95,11 @@ tflite_convert \
...
@@ -95,11 +95,11 @@ tflite_convert \
The TensorFlow Lite Converter is compatible with fixed point quantization models
The TensorFlow Lite Converter is compatible with fixed point quantization models
described
described
[
here
](
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/q
[
here
](
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/q
uantize/README.md
)
.
uantize/README.md). These are float models with
`FakeQuant*`
ops inserted at the
These are float models with
`FakeQuant*`
ops inserted at the boundaries of fused
boundaries of fused layers to record min-max range information. This generates a
layers to record min-max range information. This generates a quantized inference
quantized inference workload that reproduces the quantization behavior that was
workload that reproduces the quantization behavior that was used during
used during
training.
training.
The following command generates a quantized TensorFlow Lite FlatBuffer from a
The following command generates a quantized TensorFlow Lite FlatBuffer from a
"quantized" TensorFlow GraphDef.
"quantized" TensorFlow GraphDef.
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