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

Tensor

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)