tf.fake_quant_with_min_max_args
tf.fake_quant_with_min_max_args
tf.fake_quant_with_min_max_args
fake_quant_with_min_max_args( inputs, min=None, max=None, num_bits=None, 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. Op divides this range into 255 steps (total of 256 values), then replaces each 'inputs' value with the closest of the quantized step values. 'num_bits' is the bitwidth of the quantization; between 2 and 8, inclusive.
Quantization is called fake since the output is still in floating point.
Args:
-
inputs
: ATensor
of typefloat32
. -
min
: An optionalfloat
. Defaults to-6
. -
max
: An optionalfloat
. Defaults to6
. -
num_bits
: An optionalint
. Defaults to8
. -
name
: A name for the operation (optional).
Returns:
A Tensor
of type float32
.
© 2017 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