tf.fake_quant_with_min_max_args(inputs, min=None, max=None, name=None)

tf.fake_quant_with_min_max_args(inputs, min=None, max=None, name=None)

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.

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.
• name: A name for the operation (optional).

Returns:

A Tensor of type float32.

Defined in tensorflow/python/ops/gen_array_ops.py.