tf.quantization.quantize_and_dequantize
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Quantizes then dequantizes a tensor.
tf.quantization.quantize_and_dequantize(
input, input_min, input_max, signed_input=True, num_bits=8, range_given=False,
round_mode='HALF_TO_EVEN', name=None, narrow_range=False
)
Args |
input
|
A Tensor to quantize and dequantize.
|
input_min
|
If range_given=True, the minimum input value that needs to be
represented in the quantized representation.
|
input_max
|
If range_given=True, the maximum input value that needs to be
represented in the quantized representation.
|
signed_input
|
True if the quantization is signed or unsigned.
|
num_bits
|
The bitwidth of the quantization.
|
range_given
|
If true use input_min and input_max for the range of the
input, otherwise determine min and max from the input Tensor .
|
round_mode
|
Rounding mode when rounding from float values to quantized ones.
|
name
|
Optional name for the operation.
|
narrow_range
|
If true, then the absolute value of the quantized minimum
value is the same as the quantized maximum value, instead of 1 greater.
i.e. for 8 bit quantization, the minimum value is -127 instead of -128.
|
Returns |
A Tensor . Each element is the result of quantizing and dequantizing the
corresponding element of input .
|
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.quantization.quantize_and_dequantize\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/quantization/quantize_and_dequantize) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/ops/array_ops.py#L4433-L4474) |\n\nQuantizes then dequantizes a tensor.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.quantization.quantize_and_dequantize`](/api_docs/python/tf/quantization/quantize_and_dequantize)\n\n\u003cbr /\u003e\n\n tf.quantization.quantize_and_dequantize(\n input, input_min, input_max, signed_input=True, num_bits=8, range_given=False,\n round_mode='HALF_TO_EVEN', name=None, narrow_range=False\n )\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `input` | A `Tensor` to quantize and dequantize. |\n| `input_min` | If range_given=True, the minimum input value that needs to be represented in the quantized representation. |\n| `input_max` | If range_given=True, the maximum input value that needs to be represented in the quantized representation. |\n| `signed_input` | True if the quantization is signed or unsigned. |\n| `num_bits` | The bitwidth of the quantization. |\n| `range_given` | If true use `input_min` and `input_max` for the range of the input, otherwise determine min and max from the input `Tensor`. |\n| `round_mode` | Rounding mode when rounding from float values to quantized ones. |\n| `name` | Optional name for the operation. |\n| `narrow_range` | If true, then the absolute value of the quantized minimum value is the same as the quantized maximum value, instead of 1 greater. i.e. for 8 bit quantization, the minimum value is -127 instead of -128. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor`. Each element is the result of quantizing and dequantizing the corresponding element of `input`. ||\n\n\u003cbr /\u003e"]]