tf.fake_quant_with_min_max_vars

tf.fake_quant_with_min_max_vars

tf.fake_quant_with_min_max_vars

fake_quant_with_min_max_vars(
    inputs,
    min,
    max,
    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 of type float via global float scalars min

and max to 'outputs' tensor of same shape as inputs.

[min; max] is 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.

This operation has a gradient and thus allows for training min and max values.

Args:

• inputs: A Tensor of type float32.
• min: A Tensor of type float32.
• max: A Tensor of type float32.
• num_bits: An optional int. Defaults to 8.
• name: A name for the operation (optional).

Returns:

A Tensor of type float32.