upsample
class torch.ao.nn.quantized.functional.upsample(input, size=None, scale_factor=None, mode='nearest', align_corners=None)
Upsamples the input to either the given "size" or the given
   "scale_factor"
Warning:
 This function is deprecated in favor of
 "torch.nn.quantized.functional.interpolate()". This is equivalent
 with "nn.quantized.functional.interpolate(...)".

See "torch.nn.functional.interpolate()" for implementation details.
The input dimensions are interpreted in the form: mini-batch x
   channels x [optional depth] x [optional height] x width.
Note:
 The input quantization parameters propagate to the output.

Note:
 Only 2D input is supported for quantized inputs

Note:
 Only the following modes are supported for the quantized inputs:

 * *bilinear*

 * *nearest*

Parameters:
      * input (Tensor) -- quantized input tensor
  * **size** (*int** or **Tuple**[**int**] or **Tuple**[**int**,
