[Frontend] Unified LSTM cell

[vvchernov]

LSTM cell was unified and transferred to common place for all frontends. Here it is simultaneously used by onnx and pytorch frontends of TVM. LSTM cell was analyzed and modified to remove excess memory and other manipulations which potentially can not be fixed by compiler on its side. Performance tests for different modification of LSTM before and after were carried out. The results are collected in the tables:

Table 1. Average time per run (microsec) for 10000 runs. The following parameters are used (small input size): with biases = True, batch first = True, feature size = 5, hidden size = 10, number of stacked layers = 2, sequence length = 3, batch size = 1, trials number = 100

Frontend name/LSTM type	uni	b	s	sb
Onnx	26.8	55.3	50.7	112.7
Onnx dev	20.1	40.5	37.7	81.7
Onnx tuned	5.1	5.8	7.1	11.1
Onnx dev tuned	4.7	6.0	6.2	10.2
Pytorch	12.1	19.9	20.5	37.2
Pytorch dev	8.9	14.1	14.9	27.5
Pytorch tuned	4.8	6.0	6.4	9.9
Pytorch dev tuned	4.7	6.1	6.4	9.8
Onnxruntime	16.0	21.1	24.8	36.7

There are several LSTM types: uni – unidirectional, b – bidirectional, s – stacked (2 layers are used in the tests), sb - stacked bidirectional. Suffix "dev" means implementation in this patch. We had strong difference for performance between implementation on onnx and pytorch without tuning (onnx one is slower). With tuning onnx implementation was slightly worse than pytorch. This patch fixed performance differences for LSTM with tuning and imporved results without tuning for both onnx and pytorch.

Table 2. Average time per run (ms) for 1000 runs. The following parameters are used (big input size): with biases = True, batch first = True, feature size = 40, hidden size = 256, number of stacked layers = 3, sequence length = 160, batch size = 1, trials number = 100

Frontend name/LSTM type	uni	b	s	sb
Onnx	47.3		205
Onnx dev	57.7
Onnx tuned	8.74		31.8
Onnx dev tuned	7.63
Pytorch	7.77		27.2
Pytorch dev	7.65
Pytorch tuned	7.71		27.3
Pytorch dev tuned	7.60
Onnxruntime	1.50		4.69

@masahi @jwfromm please review

[junrushao]

CC @masahi if you are interested

[masahi]

cc @mbrookhart

[masahi]

Thanks @vvchernov I only have minor comments left.

[masahi]

thanks @vvchernov