### Description
Release OrtEnv before main function returns. Before this change, OrtEnv
is deleted when C/C++ runtime destructs all global variables in ONNX
Runtime's core framework.
The callstack is like this:
```
  * frame #0: 0x00007fffee39f5a6 libonnxruntime.so.1.16.0`onnxruntime::Environment::~Environment(this=0x00007fffee39fbf2) at environment.h:20:7
    frame #1: 0x00007fffee39f614 libonnxruntime.so.1.16.0`std::default_delete<onnxruntime::Environment>::operator()(this=0x00007ffff4c30e50, __ptr=0x0000000005404b00) const at unique_ptr.h:85:2
    frame #2: 0x00007fffee39edca libonnxruntime.so.1.16.0`std::unique_ptr<onnxruntime::Environment, std::default_delete<onnxruntime::Environment>>::~unique_ptr(this=0x5404b00) at unique_ptr.h:361:17
    frame #3: 0x00007fffee39e2ab libonnxruntime.so.1.16.0`OrtEnv::~OrtEnv(this=0x00007ffff4c30e50) at ort_env.cc:43:1
    frame #4: 0x00007fffee39fa96 libonnxruntime.so.1.16.0`std::default_delete<OrtEnv>::operator()(this=0x00007fffefff8f78, __ptr=0x00007ffff4c30e50) const at unique_ptr.h:85:2
    frame #5: 0x00007fffee39f394 libonnxruntime.so.1.16.0`std::unique_ptr<OrtEnv, std::default_delete<OrtEnv>>::~unique_ptr(this=0x7ffff4c30e50) at unique_ptr.h:361:17
    frame #6: 0x00007ffff78574b5 libc.so.6`__run_exit_handlers + 261
    frame #7: 0x00007ffff7857630 libc.so.6`exit + 32
    frame #8: 0x00007ffff783feb7 libc.so.6`__libc_start_call_main + 135
    frame #9: 0x00007ffff783ff60 libc.so.6`__libc_start_main@@GLIBC_2.34 + 128
    frame #10: 0x0000000000abbdee node`_start + 46
```
After this change, OrtEnv will be deleted before the main function
returns and nodejs is still alive.

### Description
Security fuzz test with address sanitizer found several bugs

### Description
Add [Lean Attention](https://arxiv.org/abs/2405.10480) and the
integration with MultiHeadAttention operator for LLM in GPU.

LeanAttention speeds up self-attention for the token-generation phase
(decode-phase) of decoder-only transformer models, especially on long
context lengths.

- [x] Initial implementation of Lean Attention (by Srikant Bharadwaj)
- [x] Integration with MultiHeadAttention operator
- [x] Add parity tests
- [x] Add benchmark

#### Implementation Details

(1) Lean Attention is enabled in build for Linux, and disabled for
Windows
(2) Lean Attention is disabled by default. Need enable it through cuda
provider option sdpa_kernel, or use environment variable
`ORT_ENABLE_LEAN_ATTENTION=1`
(3) It only works for token-generation (sequence_length==1,
past_sequence_length > 0).
(4) Like flash attention, it only works in Ampere or newer GPU.

We can revisit #1 and #2 after comparing with
DecoderMaskedMultiHeadAttention and XQA kernels.

#### Benchmark

```
cd onnxruntime/test/python/transformers 
/bin/bash benchmark_mha.sh lean
```

Example outputs in H100:

Note that past and present does not share buffer for MHA for now, so we
can see low tflops. The relative ratio will change after buffer sharing
is enabled. But we expect that the order (kernel A is faster than B)
will remain the same after buffer sharing is enabled.

Note that common settings `sequence_length=1;
causal=True;attn_bias=None;cuda_graph=False` are not shown in the below
table.

batch_size | past_sequence_length | num_heads | head_size |
average_latency | tflops | kernel
-- | -- | -- | -- | -- | -- | --
1 | 512 | 16 | 64 | 0.000059 | 0.0178 | ort:flash
1 | 512 | 16 | 64 | 0.000068 | 0.0155 | ort:efficient
1 | 512 | 16 | 64 | 0.000065 | 0.0161 | ort:math
1 | 512 | 16 | 64 | 0.000060 | 0.0176 | ort:lean
1 | 512 | 32 | 128 | 0.000062 | 0.0674 | ort:flash
1 | 512 | 32 | 128 | 0.000064 | 0.0661 | ort:efficient
1 | 512 | 32 | 128 | 0.000067 | 0.0625 | ort:math
1 | 512 | 32 | 128 | 0.000062 | 0.0678 | ort:lean
1 | 1024 | 16 | 64 | 0.000061 | 0.0345 | ort:flash
1 | 1024 | 16 | 64 | 0.000086 | 0.0244 | ort:efficient
1 | 1024 | 16 | 64 | 0.000065 | 0.0322 | ort:math
1 | 1024 | 16 | 64 | 0.000063 | 0.0332 | ort:lean
1 | 1024 | 32 | 128 | 0.000075 | 0.1125 | ort:flash
1 | 1024 | 32 | 128 | 0.000088 | 0.0951 | ort:efficient
1 | 1024 | 32 | 128 | 0.000079 | 0.1068 | ort:math
1 | 1024 | 32 | 128 | 0.000072 | 0.1171 | ort:lean
1 | 2048 | 16 | 64 | 0.000069 | 0.0606 | ort:flash
1 | 2048 | 16 | 64 | 0.000125 | 0.0336 | ort:efficient
1 | 2048 | 16 | 64 | 0.000064 | 0.0655 | ort:lean
1 | 2048 | 32 | 128 | 0.000098 | 0.1720 | ort:flash
1 | 2048 | 32 | 128 | 0.000132 | 0.1270 | ort:efficient
1 | 2048 | 32 | 128 | 0.000092 | 0.1828 | ort:lean
1 | 4096 | 16 | 64 | 0.000076 | 0.1097 | ort:flash
1 | 4096 | 16 | 64 | 0.000207 | 0.0406 | ort:efficient
1 | 4096 | 16 | 64 | 0.000069 | 0.1209 | ort:lean
1 | 4096 | 32 | 128 | 0.000140 | 0.2394 | ort:flash
1 | 4096 | 32 | 128 | 0.000213 | 0.1575 | ort:efficient
1 | 4096 | 32 | 128 | 0.000139 | 0.2419 | ort:lean
1 | 8192 | 16 | 64 | 0.000104 | 0.1609 | ort:flash
1 | 8192 | 16 | 64 | 0.000392 | 0.0428 | ort:efficient
1 | 8192 | 16 | 64 | 0.000093 | 0.1809 | ort:lean
1 | 8192 | 32 | 128 | 0.000212 | 0.3160 | ort:flash
1 | 8192 | 32 | 128 | 0.000360 | 0.1866 | ort:efficient
1 | 8192 | 32 | 128 | 0.000212 | 0.3162 | ort:lean
1 | 16384 | 16 | 64 | 0.000139 | 0.2410 | ort:flash
1 | 16384 | 16 | 64 | 0.000731 | 0.0459 | ort:efficient
1 | 16384 | 16 | 64 | 0.000136 | 0.2465 | ort:lean
1 | 16384 | 32 | 128 | 0.000361 | 0.3722 | ort:flash
1 | 16384 | 32 | 128 | 0.000667 | 0.2014 | ort:efficient
1 | 16384 | 32 | 128 | 0.000357 | 0.3765 | ort:lean
1 | 32768 | 16 | 64 | 0.000210 | 0.3194 | ort:flash
1 | 32768 | 16 | 64 | 0.001428 | 0.0470 | ort:efficient
1 | 32768 | 16 | 64 | 0.000209 | 0.3211 | ort:lean
1 | 32768 | 32 | 128 | 0.000659 | 0.4074 | ort:flash
1 | 32768 | 32 | 128 | 0.001270 | 0.2114 | ort:efficient
1 | 32768 | 32 | 128 | 0.000651 | 0.4123 | ort:lean
1 | 65536 | 16 | 64 | 0.000355 | 0.3785 | ort:flash
1 | 65536 | 16 | 64 | 0.002736 | 0.0491 | ort:efficient
1 | 65536 | 16 | 64 | 0.000349 | 0.3845 | ort:lean
1 | 65536 | 32 | 128 | 0.001251 | 0.4290 | ort:flash
1 | 65536 | 32 | 128 | 0.002480 | 0.2165 | ort:efficient
1 | 65536 | 32 | 128 | 0.001239 | 0.4333 | ort:lean
4 | 512 | 16 | 64 | 0.000063 | 0.0665 | ort:flash
4 | 512 | 16 | 64 | 0.000069 | 0.0607 | ort:efficient
4 | 512 | 16 | 64 | 0.000066 | 0.0634 | ort:math
4 | 512 | 16 | 64 | 0.000062 | 0.0674 | ort:lean
4 | 512 | 32 | 128 | 0.000100 | 0.1677 | ort:flash
4 | 512 | 32 | 128 | 0.000099 | 0.1703 | ort:efficient
4 | 512 | 32 | 128 | 0.000108 | 0.1557 | ort:math
4 | 512 | 32 | 128 | 0.000092 | 0.1818 | ort:lean
4 | 1024 | 16 | 64 | 0.000077 | 0.1094 | ort:flash
4 | 1024 | 16 | 64 | 0.000099 | 0.0850 | ort:efficient
4 | 1024 | 16 | 64 | 0.000081 | 0.1038 | ort:math
4 | 1024 | 16 | 64 | 0.000072 | 0.1161 | ort:lean
4 | 1024 | 32 | 128 | 0.000143 | 0.2343 | ort:flash
4 | 1024 | 32 | 128 | 0.000137 | 0.2447 | ort:efficient
4 | 1024 | 32 | 128 | 0.000150 | 0.2245 | ort:math
4 | 1024 | 32 | 128 | 0.000135 | 0.2496 | ort:lean
4 | 2048 | 16 | 64 | 0.000096 | 0.1757 | ort:flash
4 | 2048 | 16 | 64 | 0.000156 | 0.1078 | ort:efficient
4 | 2048 | 16 | 64 | 0.000089 | 0.1892 | ort:lean
4 | 2048 | 32 | 128 | 0.000223 | 0.3010 | ort:flash
4 | 2048 | 32 | 128 | 0.000217 | 0.3101 | ort:efficient
4 | 2048 | 32 | 128 | 0.000209 | 0.3209 | ort:lean
4 | 4096 | 16 | 64 | 0.000137 | 0.2448 | ort:flash
4 | 4096 | 16 | 64 | 0.000256 | 0.1312 | ort:efficient
4 | 4096 | 16 | 64 | 0.000133 | 0.2530 | ort:lean
4 | 4096 | 32 | 128 | 0.000389 | 0.3450 | ort:flash
4 | 4096 | 32 | 128 | 0.000376 | 0.3574 | ort:efficient
4 | 4096 | 32 | 128 | 0.000354 | 0.3794 | ort:lean
4 | 8192 | 16 | 64 | 0.000210 | 0.3198 | ort:flash
4 | 8192 | 16 | 64 | 0.000453 | 0.1480 | ort:efficient
4 | 8192 | 16 | 64 | 0.000206 | 0.3260 | ort:lean
4 | 8192 | 32 | 128 | 0.000725 | 0.3705 | ort:flash
4 | 8192 | 32 | 128 | 0.000693 | 0.3874 | ort:efficient
4 | 8192 | 32 | 128 | 0.000653 | 0.4114 | ort:lean
4 | 16384 | 16 | 64 | 0.000355 | 0.3782 | ort:flash
4 | 16384 | 16 | 64 | 0.000849 | 0.1581 | ort:efficient
4 | 16384 | 16 | 64 | 0.000346 | 0.3874 | ort:lean
4 | 16384 | 32 | 128 | 0.001395 | 0.3848 | ort:flash
4 | 16384 | 32 | 128 | 0.001337 | 0.4017 | ort:efficient
4 | 16384 | 32 | 128 | 0.001252 | 0.4288 | ort:lean
4 | 32768 | 16 | 64 | 0.000647 | 0.4146 | ort:flash
4 | 32768 | 16 | 64 | 0.001649 | 0.1628 | ort:efficient
4 | 32768 | 16 | 64 | 0.000639 | 0.4204 | ort:lean
4 | 32768 | 32 | 128 | 0.002721 | 0.3947 | ort:flash
4 | 32768 | 32 | 128 | 0.002601 | 0.4128 | ort:efficient
4 | 32768 | 32 | 128 | 0.002434 | 0.4411 | ort:lean
4 | 65536 | 16 | 64 | 0.001231 | 0.4361 | ort:flash
4 | 65536 | 16 | 64 | 0.003238 | 0.1658 | ort:efficient
4 | 65536 | 16 | 64 | 0.001217 | 0.4412 | ort:lean
4 | 65536 | 32 | 128 | 0.005357 | 0.4009 | ort:flash
4 | 65536 | 32 | 128 | 0.005118 | 0.4196 | ort:efficient
4 | 65536 | 32 | 128 | 0.004781 | 0.4492 | ort:lean
16 | 512 | 16 | 64 | 0.000098 | 0.1724 | ort:flash
16 | 512 | 16 | 64 | 0.000104 | 0.1616 | ort:efficient
16 | 512 | 16 | 64 | 0.000118 | 0.1420 | ort:math
16 | 512 | 16 | 64 | 0.000087 | 0.1926 | ort:lean
16 | 512 | 32 | 128 | 0.000220 | 0.3062 | ort:flash
16 | 512 | 32 | 128 | 0.000208 | 0.3237 | ort:efficient
16 | 512 | 32 | 128 | 0.000237 | 0.2838 | ort:math
16 | 512 | 32 | 128 | 0.000209 | 0.3216 | ort:lean
16 | 1024 | 16 | 64 | 0.000136 | 0.2465 | ort:flash
16 | 1024 | 16 | 64 | 0.000150 | 0.2235 | ort:efficient
16 | 1024 | 16 | 64 | 0.000148 | 0.2266 | ort:math
16 | 1024 | 16 | 64 | 0.000129 | 0.2611 | ort:lean
16 | 1024 | 32 | 128 | 0.000367 | 0.3663 | ort:flash
16 | 1024 | 32 | 128 | 0.000351 | 0.3829 | ort:efficient
16 | 1024 | 32 | 128 | 0.000400 | 0.3357 | ort:math
16 | 1024 | 32 | 128 | 0.000349 | 0.3853 | ort:lean
16 | 2048 | 16 | 64 | 0.000209 | 0.3206 | ort:flash
16 | 2048 | 16 | 64 | 0.000243 | 0.2762 | ort:efficient
16 | 2048 | 16 | 64 | 0.000201 | 0.3338 | ort:lean
16 | 2048 | 32 | 128 | 0.000671 | 0.4002 | ort:flash
16 | 2048 | 32 | 128 | 0.000645 | 0.4163 | ort:efficient
16 | 2048 | 32 | 128 | 0.000642 | 0.4185 | ort:lean
16 | 4096 | 16 | 64 | 0.000360 | 0.3732 | ort:flash
16 | 4096 | 16 | 64 | 0.000425 | 0.3162 | ort:efficient
16 | 4096 | 16 | 64 | 0.000341 | 0.3933 | ort:lean
16 | 4096 | 32 | 128 | 0.001292 | 0.4156 | ort:flash
16 | 4096 | 32 | 128 | 0.001251 | 0.4291 | ort:efficient
16 | 4096 | 32 | 128 | 0.001241 | 0.4327 | ort:lean
16 | 8192 | 16 | 64 | 0.000666 | 0.4030 | ort:flash
16 | 8192 | 16 | 64 | 0.000804 | 0.3339 | ort:efficient
16 | 8192 | 16 | 64 | 0.000627 | 0.4283 | ort:lean
16 | 8192 | 32 | 128 | 0.002541 | 0.4226 | ort:flash
16 | 8192 | 32 | 128 | 0.002454 | 0.4376 | ort:efficient
16 | 8192 | 32 | 128 | 0.002438 | 0.4405 | ort:lean
16 | 16384 | 16 | 64 | 0.001292 | 0.4156 | ort:flash
16 | 16384 | 16 | 64 | 0.001571 | 0.3417 | ort:efficient
16 | 16384 | 16 | 64 | 0.001217 | 0.4411 | ort:lean
16 | 16384 | 32 | 128 | 0.005042 | 0.4260 | ort:flash
16 | 16384 | 32 | 128 | 0.004859 | 0.4420 | ort:efficient
16 | 16384 | 32 | 128 | 0.004827 | 0.4449 | ort:lean
16 | 32768 | 16 | 64 | 0.002537 | 0.4233 | ort:flash
16 | 32768 | 16 | 64 | 0.003103 | 0.3461 | ort:efficient
16 | 32768 | 16 | 64 | 0.002385 | 0.4501 | ort:lean
16 | 32768 | 32 | 128 | 0.009961 | 0.4312 | ort:flash
16 | 32768 | 32 | 128 | 0.009605 | 0.4472 | ort:efficient
16 | 32768 | 32 | 128 | 0.009524 | 0.4510 | ort:lean
16 | 65536 | 16 | 64 | 0.005019 | 0.4279 | ort:flash
16 | 65536 | 16 | 64 | 0.006133 | 0.3502 | ort:efficient
16 | 65536 | 16 | 64 | 0.004703 | 0.4566 | ort:lean
16 | 65536 | 32 | 128 | 0.019746 | 0.4350 | ort:flash
16 | 65536 | 32 | 128 | 0.019027 | 0.4515 | ort:efficient
16 | 65536 | 32 | 128 | 0.018864 | 0.4554 | ort:lean

### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->