torch / torch
torch.quantize_per_tensor¶
-
torch.
quantize_per_tensor
(input, scale, zero_point, dtype) → Tensor¶ Converts a float tensor to a quantized tensor with given scale and zero point.
- Parameters
input (Tensor) – float tensor to quantize
scale (float) – scale to apply in quantization formula
zero_point (int) – offset in integer value that maps to float zero
dtype (
torch.dtype
) – the desired data type of returned tensor. Has to be one of the quantized dtypes:torch.quint8
,torch.qint8
,torch.qint32
- Returns
A newly quantized tensor
- Return type
Example:
>>> torch.quantize_per_tensor(torch.tensor([-1.0, 0.0, 1.0, 2.0]), 0.1, 10, torch.quint8) tensor([-1., 0., 1., 2.], size=(4,), dtype=torch.quint8, quantization_scheme=torch.per_tensor_affine, scale=0.1, zero_point=10) >>> torch.quantize_per_tensor(torch.tensor([-1.0, 0.0, 1.0, 2.0]), 0.1, 10, torch.quint8).int_repr() tensor([ 0, 10, 20, 30], dtype=torch.uint8)
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