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: 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.
  • 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

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