tf.fake_quant_with_min_max_args( inputs, min=-6, max=6, num_bits=8, narrow_range=False, name=None )
Defined in tensorflow/python/ops/gen_array_ops.py
.
See the guide: Tensor Transformations > Fake quantization
Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same type.
Attributes [min; max]
define the clamping range for the inputs
data. inputs
values are quantized into the quantization range ([0; 2^num_bits - 1]
when narrow_range
is false and [1; 2^num_bits - 1]
when it is true) and then de-quantized and output as floats in [min; max]
interval. num_bits
is the bitwidth of the quantization; between 2 and 16, inclusive.
Quantization is called fake since the output is still in floating point.
inputs
: A Tensor
of type float32
.min
: An optional float
. Defaults to -6
.max
: An optional float
. Defaults to 6
.num_bits
: An optional int
. Defaults to 8
.narrow_range
: An optional bool
. Defaults to False
.name
: A name for the operation (optional).A Tensor
of type float32
.
© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/fake_quant_with_min_max_args