tf.raw_ops.FakeQuantWithMinMaxArgs
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Fake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same shape and type.
tf.raw_ops.FakeQuantWithMinMaxArgs(
inputs, min=-6, max=6, num_bits=8, narrow_range=False, name=None
)
Quantization is called fake since the output is still in floating point.
The API converts inputs into values within the range [min and max] and returns
as output.
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.
Before quantization, min and max values are adjusted with the following
logic.
It is suggested to have min <= 0 <= max. If 0 is not in the range of values,
the behavior can be unexpected:
- If
0 < min < max: min_adj = 0 and max_adj = max - min.
- If
min < max < 0: min_adj = min - max and max_adj = 0.
- If
min <= 0 <= max: scale = (max - min) / (2^num_bits - 1),
min_adj = scale * round(min / scale) and max_adj = max + min_adj - min.
Examples
inp = tf.constant ([10.03, -10.23, 3])
out = tf.quantization.fake_quant_with_min_max_args(inp, min=-5, max=5,
num_bits=16)
print(out)
# Output:
# tf.Tensor([ 4.9999237 -5.0000763 3.0000763], shape=(3,), dtype=float32)
Raises |
|---|
- InvalidArgumentError:
- If num_bits are outside of range [2, 16].
- If min >= max.
- ValueError: If
inputs are of any other type than float32.
|
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.
|
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Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.raw_ops.FakeQuantWithMinMaxArgs\n\n\u003cbr /\u003e\n\nFake-quantize the 'inputs' tensor, type float to 'outputs' tensor of same shape and type.\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.raw_ops.FakeQuantWithMinMaxArgs`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/FakeQuantWithMinMaxArgs)\n\n\u003cbr /\u003e\n\n tf.raw_ops.FakeQuantWithMinMaxArgs(\n inputs, min=-6, max=6, num_bits=8, narrow_range=False, name=None\n )\n\nQuantization is called fake since the output is still in floating point.\nThe API converts inputs into values within the range \\[min and max\\] and returns\nas output.\n\nAttributes\n\n- `[min; max]` define the clamping range for the `inputs` data.\n- `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.\n- `num_bits` is the bitwidth of the quantization; between 2 and 16, inclusive.\n\nBefore quantization, `min` and `max` values are adjusted with the following\nlogic.\nIt is suggested to have `min \u003c= 0 \u003c= max`. If `0` is not in the range of values,\nthe behavior can be unexpected:\n\n- If `0 \u003c min \u003c max`: `min_adj = 0` and `max_adj = max - min`.\n- If `min \u003c max \u003c 0`: `min_adj = min - max` and `max_adj = 0`.\n- If `min \u003c= 0 \u003c= max`: `scale = (max - min) / (2^num_bits - 1)`, `min_adj = scale * round(min / scale)` and `max_adj = max + min_adj - min`.\n\nExamples \n\n\n inp = tf.constant ([10.03, -10.23, 3])\n out = tf.quantization.fake_quant_with_min_max_args(inp, min=-5, max=5,\n num_bits=16)\n print(out)\n\n # Output:\n # tf.Tensor([ 4.9999237 -5.0000763 3.0000763], shape=(3,), dtype=float32)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|---|---|\n| \u003cbr /\u003e - InvalidArgumentError: - If num_bits are outside of range \\[2, 16\\]. - If min \\\u003e= max. - ValueError: If `inputs` are of any other type than float32. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------------|------------------------------------------|\n| `inputs` | A `Tensor` of type `float32`. |\n| `min` | An optional `float`. Defaults to `-6`. |\n| `max` | An optional `float`. Defaults to `6`. |\n| `num_bits` | An optional `int`. Defaults to `8`. |\n| `narrow_range` | An optional `bool`. Defaults to `False`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` of type `float32`. ||\n\n\u003cbr /\u003e"]]
