Args:
input (Tensor): the input value(s), in ``torch.float32``.
- scale (double): quantization scale
- zero_point (int64): quantization zero_point
+ scale (double or Tensor): quantization scale
+ zero_point (int64 or Tensor): quantization zero_point
quant_min (int64): lower bound of the quantized domain
quant_max (int64): upper bound of the quantized domain
tensor([ 0.0552, 0.9730, 0.3973, -1.0780])
>>> torch.fake_quantize_per_tensor_affine(x, 0.1, 0, 0, 255)
tensor([0.1000, 1.0000, 0.4000, 0.0000])
+ >>> torch.fake_quantize_per_tensor_affine(x, torch.tensor(0.1), torch.tensor(0), 0, 255)
+ tensor([0.6000, 0.4000, 0.0000, 0.0000])
""")
add_docstr(torch.fake_quantize_per_channel_affine,