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