tf.fake_quant_with_min_max_args

Aliases:

  • tf.fake_quant_with_min_max_args
  • tf.quantization.fake_quant_with_min_max_args
tf.fake_quant_with_min_max_args(
    inputs,
    min=-6,
    max=6,
    num_bits=8,
    narrow_range=False,
    name=None
)

Defined in generated file: 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.

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.
  • narrow_range: An optional bool. Defaults to False.
  • name: A name for the operation (optional).

Returns:

A Tensor of type float32.