Add the 3d upsample quantized op for video model (#34594)
Summary:
as title, we are currently missing this 3d op, which is required for video related model.
Performance benchmark:
```
import torch, time
for dtype in [torch.qint8, torch.quint8, torch.qint32]:
print('****', str(dtype), '*****')
x = torch.rand(1, 56, 64, 56, 256)
q_x = torch.quantize_per_tensor(x, 0.5, 1, dtype)
q_x = q_x.permute([0, 4, 1, 2, 3])
x = x.permute([0, 4, 1, 2, 3])
NITER = 100
s = time.time()
for i in range(NITER):
float_out = torch.nn.functional.interpolate(x, size=30, scale_factor=None, mode="nearest", align_corners=None)
time_per_iter_float = (time.time() - s) / NITER
s = time.time()
for i in range(NITER):
quant_out = torch.nn.functional.interpolate(q_x, size=30, scale_factor=None, mode="nearest", align_corners=None)
time_per_iter_quant = (time.time() - s) / NITER
ref_quantized = torch.quantize_per_tensor(float_out, 0.5, 1, dtype)
torch.testing.assert_allclose(ref_quantized.dequantize(), quant_out.dequantize())
print('time/iter ms (float)', 'time/iter ms (quant)', 'quant/float', sep='\t')
print(time_per_iter_float * 1000, time_per_iter_quant * 1000, time_per_iter_quant / time_per_iter_float, sep='\t')
bytes_float = (x.numel() + float_out.numel()) * x.element_size()
bytes_quant = (q_x.numel() + quant_out.numel()) * q_x.element_size()
float_bw_gbps = bytes_float / time_per_iter_float / 1e9
quant_bw_gbps = bytes_quant / time_per_iter_quant / 1e9
print('GB/s float', 'GB/s quant', sep='\t')
print(float_bw_gbps, quant_bw_gbps, sep='\t')
```
```
**** torch.qint8 *****
time/iter ms (float) time/iter ms (quant) quant/float
1136.8209528923035 1.294245719909668 0.0011384780660638283
GB/s float GB/s quant
0.20510608588517917 45.03953391792442
**** torch.quint8 *****
time/iter ms (float) time/iter ms (quant) quant/float
827.9890131950378 1.11464262008667 0.0013462046021426
GB/s float GB/s quant
0.28160868355034036 52.29678369508914
**** torch.qint32 *****
time/iter ms (float) time/iter ms (quant) quant/float
834.6958303451538 7.481417655944824 0.008963046638020456
GB/s float GB/s quant
0.2793459455806586 31.16640544920269
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34594
Differential Revision: D20389106
Pulled By: lly-zero-one
fbshipit-source-id: d3a8c2cac58087d8b29e9cae64822f5b2d4c03ba
