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get_physical_cpu_count api family #4302

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merged 12 commits into from Oct 31, 2022
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@nihui nihui commented Oct 23, 2022

  • test on linux
  • test on android
  • test on ios
  • test on macos
  • test on windows
  • test on big.little cpu
  • test on smp cpu (eg most x86)
  • test on smp + big.little cpu (eg intel 12th/13th)
  • test on 3-cluster cpu (eg qcom 8gen1)
  • resolve interaction with thread affinity
  • set for option default
  • set for benchncnn default

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codecov-commenter commented Oct 23, 2022

Codecov Report

Merging #4302 (4356346) into master (9c6f110) will decrease coverage by 0.01%.
The diff coverage is 49.18%.

@@            Coverage Diff             @@
##           master    #4302      +/-   ##
==========================================
- Coverage   91.52%   91.51%   -0.02%     
==========================================
  Files         783      783              
  Lines      183445   183505      +60     
==========================================
+ Hits       167903   167938      +35     
- Misses      15542    15567      +25     
Impacted Files Coverage Δ
src/cpu.cpp 61.64% <48.33%> (-0.47%) ⬇️
src/option.cpp 100.00% <100.00%> (ø)

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kagurazakakotori commented Oct 24, 2022

Tested on i9-12900K (E-cores and HT enabled) with Ubuntu 22.10 + kernel 5.19, num_threads is 8 by default in benchncnn. On my setup, it does not run on E-cores.

$ ./benchncnn 
loop_count = 4
num_threads = 8
powersave = 2
gpu_device = -1
cooling_down = 1
          squeezenet  min =    1.94  max =    1.94  avg =    1.94
     squeezenet_int8  min =    3.37  max =    3.38  avg =    3.38
           mobilenet  min =    2.41  max =    2.49  avg =    2.44
      mobilenet_int8  min =    3.69  max =    3.80  avg =    3.75
        mobilenet_v2  min =    2.39  max =    2.85  avg =    2.57
        mobilenet_v3  min =    1.56  max =    1.65  avg =    1.60
          shufflenet  min =    2.04  max =    2.09  avg =    2.06
       shufflenet_v2  min =    2.01  max =    2.15  avg =    2.06
             mnasnet  min =    1.74  max =    1.78  avg =    1.76
     proxylessnasnet  min =    2.80  max =    3.15  avg =    2.98
     efficientnet_b0  min =    3.87  max =    3.98  avg =    3.94
   efficientnetv2_b0  min =    4.20  max =    4.61  avg =    4.31
        regnety_400m  min =    4.86  max =    4.96  avg =    4.90
           blazeface  min =    0.70  max =    0.72  avg =    0.71
           googlenet  min =    6.47  max =    6.58  avg =    6.52
      googlenet_int8  min =    8.18  max =    8.25  avg =    8.22
            resnet18  min =    5.19  max =    5.41  avg =    5.33
       resnet18_int8  min =    6.85  max =    6.97  avg =    6.90
             alexnet  min =    4.24  max =    4.59  avg =    4.35
               vgg16  min =   22.17  max =   23.28  avg =   22.94
          vgg16_int8  min =   19.29  max =   20.24  avg =   19.91
            resnet50  min =   10.80  max =   12.17  avg =   11.47
       resnet50_int8  min =   11.71  max =   19.37  avg =   15.53
      squeezenet_ssd  min =    7.87  max =    8.12  avg =    8.01
 squeezenet_ssd_int8  min =    5.40  max =    5.64  avg =    5.57
       mobilenet_ssd  min =    4.34  max =    4.72  avg =    4.48
  mobilenet_ssd_int8  min =    4.57  max =    4.70  avg =    4.64
      mobilenet_yolo  min =   19.91  max =   20.95  avg =   20.30
  mobilenetv2_yolov3  min =    7.23  max =    7.80  avg =    7.61
         yolov4-tiny  min =   11.43  max =   12.44  avg =   12.16
           nanodet_m  min =    4.48  max =    4.57  avg =    4.52
    yolo-fastest-1.1  min =    2.53  max =    2.55  avg =    2.54
      yolo-fastestv2  min =    2.52  max =    2.54  avg =    2.53
  vision_transformer  min =  205.26  max =  212.66  avg =  208.73
          FastestDet  min =    2.66  max =    2.80  avg =    2.73

Without this PR it's 24 by default.

loop_count = 4
num_threads = 24
powersave = 0
gpu_device = -1
cooling_down = 1
          squeezenet  min =    2.41  max =    4.56  avg =    3.22
     squeezenet_int8  min =    3.40  max =    3.51  avg =    3.43
           mobilenet  min =    2.87  max =    4.48  avg =    3.45
      mobilenet_int8  min =    3.70  max =    4.16  avg =    3.86
        mobilenet_v2  min =    3.25  max =    5.36  avg =    3.80
        mobilenet_v3  min =    2.40  max =    8.69  avg =    4.12
          shufflenet  min =    3.34  max =    3.35  avg =    3.34
       shufflenet_v2  min =    3.24  max =    3.30  avg =    3.26
             mnasnet  min =    2.89  max =    4.28  avg =    3.32
     proxylessnasnet  min =    3.21  max =   16.49  avg =    8.53
     efficientnet_b0  min =    4.43  max =    4.57  avg =    4.47
   efficientnetv2_b0  min =    6.16  max =   42.60  avg =   21.47
        regnety_400m  min =    9.73  max =   11.94  avg =   10.37
           blazeface  min =    1.17  max =    1.18  avg =    1.17
           googlenet  min =    7.08  max =    7.19  avg =    7.14
      googlenet_int8  min =   10.02  max =   10.30  avg =   10.17
            resnet18  min =    6.72  max =   16.32  avg =   10.69
       resnet18_int8  min =    8.16  max =    8.24  avg =    8.20
             alexnet  min =    4.71  max =    7.42  avg =    5.41
               vgg16  min =   23.82  max =   33.07  avg =   26.71
          vgg16_int8  min =   21.11  max =   30.79  avg =   24.42
            resnet50  min =   11.59  max =   15.28  avg =   12.69
       resnet50_int8  min =   15.11  max =   25.67  avg =   18.08
      squeezenet_ssd  min =    9.06  max =   18.40  avg =   12.14
 squeezenet_ssd_int8  min =    7.10  max =    7.33  avg =    7.19
       mobilenet_ssd  min =    5.14  max =    5.23  avg =    5.17
  mobilenet_ssd_int8  min =    6.92  max =    9.76  avg =    7.75
      mobilenet_yolo  min =   21.21  max =   37.19  avg =   25.40
  mobilenetv2_yolov3  min =    7.64  max =    7.72  avg =    7.68
         yolov4-tiny  min =   14.61  max =   22.32  avg =   17.40
           nanodet_m  min =    7.02  max =    7.12  avg =    7.07
    yolo-fastest-1.1  min =    4.36  max =    6.55  avg =    4.99
      yolo-fastestv2  min =    4.65  max =    4.73  avg =    4.68
  vision_transformer  min =  157.35  max =  691.71  avg =  406.97
          FastestDet  min =    3.11  max =    3.14  avg =    3.13

src/cpu.cpp Outdated Show resolved Hide resolved
@nihui
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nihui commented Oct 30, 2022

#include <stdio.h>
#include <stdlib.h>

#include <vector>

#define WIN32_LEAN_AND_MEAN
#include <windows.h>
#include <powerbase.h>

#pragma comment(lib, "PowrProf.lib")
// Helper function to count set bits in the processor mask.
DWORD CountSetBits(ULONG_PTR bitMask)
{
    DWORD LSHIFT = sizeof(ULONG_PTR) * 8 - 1;
    DWORD bitSetCount = 0;
    ULONG_PTR bitTest = (ULONG_PTR)1 << LSHIFT;
    DWORD i;

    for (i = 0; i <= LSHIFT; ++i)
    {
        bitSetCount += ((bitMask & bitTest) ? 1 : 0);
        bitTest /= 2;
    }

    return bitSetCount;
}
static int get_physical_cpucount()
{
    int count = 0;
    typedef BOOL(WINAPI* LPFN_GLPI)(PSYSTEM_LOGICAL_PROCESSOR_INFORMATION, PDWORD);
    LPFN_GLPI glpi = (LPFN_GLPI)GetProcAddress(GetModuleHandle(TEXT("kernel32")), "GetLogicalProcessorInformation");
    if (glpi == NULL)
    {
        printf("GetLogicalProcessorInformation is not supported\n");
        return -1;
    }

    DWORD return_length = 0;
    glpi(NULL, &return_length);

    PSYSTEM_LOGICAL_PROCESSOR_INFORMATION buffer = (PSYSTEM_LOGICAL_PROCESSOR_INFORMATION)malloc(return_length);
    glpi(buffer, &return_length);

    PSYSTEM_LOGICAL_PROCESSOR_INFORMATION ptr = buffer;
    DWORD byte_offset = 0;
    while (byte_offset + sizeof(SYSTEM_LOGICAL_PROCESSOR_INFORMATION) <= return_length)
    {
        if (ptr->Relationship == RelationProcessorCore)
        {
            count++;

            int cc = CountSetBits(ptr->ProcessorMask);
            printf("smt count = %d   %x\n", cc, ptr->ProcessorMask);
        }

        byte_offset += sizeof(SYSTEM_LOGICAL_PROCESSOR_INFORMATION);
        ptr++;
    }

    free(buffer);

    return count;
}

static int get_cpu_count()
{
    SYSTEM_INFO system_info;
    GetSystemInfo(&system_info);
    return system_info.dwNumberOfProcessors;
}

static std::vector<int> get_cpu_max_mhz()
{
    typedef struct _PROCESSOR_POWER_INFORMATION {
        ULONG Number;
        ULONG MaxMhz;
        ULONG CurrentMhz;
        ULONG MhzLimit;
        ULONG MaxIdleState;
        ULONG CurrentIdleState;
    } PROCESSOR_POWER_INFORMATION, * PPROCESSOR_POWER_INFORMATION;

    int count = get_cpu_count();

    DWORD return_length = sizeof(PROCESSOR_POWER_INFORMATION) * count;
    PPROCESSOR_POWER_INFORMATION buffer = (PPROCESSOR_POWER_INFORMATION)malloc(return_length);

    CallNtPowerInformation(ProcessorInformation, NULL, 0, buffer, return_length);

    std::vector<int> ret;
    for (int i = 0; i < count; i++)
    {
        ULONG max_mhz = buffer[i].MaxMhz;
        printf("%d max_mhz = %d\n", i, max_mhz);

        ret.push_back(max_mhz);
    }

    free(buffer);
    return ret;
}

int main()
{
    printf("get_cpu_count = %d\n", get_cpu_count());
    printf("------------------------------------\n");
    printf("get_physical_cpucount = %d\n", get_physical_cpucount());
    printf("------------------------------------\n");
    get_cpu_max_mhz();
    return 0;
}

@MouriNaruto
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@nihui

Here are results.

i7-11800H

get_cpu_count = 16
------------------------------------
smt count = 2   3
smt count = 2   c
smt count = 2   30
smt count = 2   c0
smt count = 2   300
smt count = 2   c00
smt count = 2   3000
smt count = 2   c000
get_physical_cpucount = 8
------------------------------------
0 max_mhz = 2304
1 max_mhz = 2304
2 max_mhz = 2304
3 max_mhz = 2304
4 max_mhz = 2304
5 max_mhz = 2304
6 max_mhz = 2304
7 max_mhz = 2304
8 max_mhz = 2304
9 max_mhz = 2304
10 max_mhz = 2304
11 max_mhz = 2304
12 max_mhz = 2304
13 max_mhz = 2304
14 max_mhz = 2304
15 max_mhz = 2304

Snapdragon 8cx Gen 3

get_cpu_count = 8
------------------------------------
smt count = 1   1
smt count = 1   2
smt count = 1   4
smt count = 1   8
smt count = 1   10
smt count = 1   20
smt count = 1   40
smt count = 1   80
get_physical_cpucount = 8
------------------------------------
0 max_mhz = 2438
1 max_mhz = 2438
2 max_mhz = 2438
3 max_mhz = 2438
4 max_mhz = 2995
5 max_mhz = 2995
6 max_mhz = 2995
7 max_mhz = 2995

Kenji Mouri

@nihui nihui changed the title [WIP] get_physical_cpu_count api family get_physical_cpu_count api family Oct 30, 2022
@nihui nihui merged commit b853b3d into Tencent:master Oct 31, 2022
csukuangfj added a commit to csukuangfj/ncnn that referenced this pull request Dec 1, 2022
* remove duplicated newline (Tencent#4187)

* remove duplicated newline (Tencent#4188)

* optmize softmax arm neon (Tencent#4171)

* [docs] Fix typo (Tencent#4201)

* [Prelu x86] Finish intrinsic with elempack merged (Tencent#4177)

* changed size of images for pretty formatting of page (Tencent#4193)

* [Gelu x86] Finish intrinsic with elempack merged(fast version) (Tencent#4144)

* Finish the gelu x86 intrinsics
* Finish the fast tanh x86 simd impl

* Ignore .xmake directory (Tencent#4212)

* Bump pypa/cibuildwheel from 2.9.0 to 2.10.1 (Tencent#4207)

Bumps [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel) from 2.9.0 to 2.10.1.
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](pypa/cibuildwheel@v2.9.0...v2.10.1)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* style: space alignment (Tencent#4217)

* Ignore CMakeSettings.json, the Visual Studio CMake schema file (Tencent#4228)

* RVV: use new interface for segment load/store & change word_type to size_t&add clang ci (part Tencent#4100) (Tencent#4118)

* RVV: use size_t for vl

* RVV: replace vsseg.v tuple type by using regex

-----

search:
vsseg([1-9])e(8|16|32)_v_(f|i|u)\2m(1|2|4|8)x\1\(([ -~]+), vcreate_\3\2m\4x\1\(([ -~]+)\), vl\);

substitute by:
vsseg$1e$2_v_$3$2m$4($5, $6, vl);

* RVV: replace vssseg.v tuple types by using regex

---

search:
vssseg([1-9])e(8|16|32)_v_f\2m1x\1\(([ -~]+), vcreate_f\2m1x\1\(([ -~]+)\), vl\);

substitute by:
vssseg$1e$2_v_f$2m1($3, $4, vl);

* RVV: replace vlseg.v tuple types in load/store

* RVV: replace vloxseg2ei32.v tuple types

* RVV: add a wrapper for old compilers

* RVV: add segment load/store wrapper in pakcing

* RVV: fix cmake test

* RVV: make clang happy by dropping VLAs in sgemm

* RVV: add clang cmake toolchain configure

* RVV: add clang ci, riscv64-unknown-linux-gnu

Co-authored-by: thelastlin <thelastlin@users.noreply.github.com>
Co-authored-by: nihui <shuizhuyuanluo@126.com>

* Bump pypa/cibuildwheel from 2.10.1 to 2.10.2 (Tencent#4220)

Bumps [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel) from 2.10.1 to 2.10.2.
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](pypa/cibuildwheel@v2.10.1...v2.10.2)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* add c906 build ci (Tencent#4232)

* Add benchmark result of T-Head TH1520 (Tencent#4240)

`cpuinfo`: 

```
isa             : rv64imafdcvsu
mmu             : sv39
cpu-freq                : 1.848Ghz
cpu-icache              : 64KB
cpu-dcache              : 64KB
cpu-l2cache             : 1MB
cpu-tlb         : 1024 4-ways
cpu-cacheline           : 64Bytes
cpu-vector              : 0.7.1
```

Compiled with `-DCMAKE_TOOLCHAIN_FILE=../toolchains/c910-v240.toolchain.cmake -DCMAKE_BUILD_TYPE=release -DNCNN_OPENMP=OFF -DNCNN_THREADS=OFF -DNCNN_RUNTIME_CPU=OFF -DNCNN_RVV=ON -DNCNN_SIMPLEOCV=ON -DNCNN_BUILD_EXAMPLES=ON` 

Seems much worse than expected 🤔

* fix param parsing issue when layer/blob name exceeds 255 (Tencent#4236)

* fix param parsing issue when layer/blob name exceeds 255

* apply code-format changes

Co-authored-by: ZhangGe6 <ZhangGe6@users.noreply.github.com>

* Memory Pool Improvement For Variadic Sized Inputs (Tencent#4190)

* Simple miss count for better space efficiency

* Simple double ended greedy;

* Add size drop threshold setter;

* set workspace allocator cr to zero as we had some sort of recylcing capability :P

Co-authored-by: LinHeLurking <LinHeLurking@users.noreply.github.com>
Co-authored-by: nihuini <nihuini@tencent.com>

* docs: disable fp16 when wrong results encountered caused by overflow (Tencent#4248)

* pnnx math operation (Tencent#4251)

* more stricter armv7 fp16 and armv84 bf16 compiler check, fix Tencent#4147 fix Tencent#4222 (Tencent#4247)

* modified the param axes of expanddims in modelwriter (Tencent#4259)

* Add TH1520 (4*C910V) toolchain support.  (Tencent#4267)

* implement lstm proj_size (Tencent#4263)

* Optimize x86 DeformableConv2D (Tencent#4128)

* fix compile warning with gcc 9.1.0 including simplestl.h file (Tencent#4274)

* fix compile warning with gcc 9.1.0 including simplestl.h file

* apply code-format changes

Co-authored-by: veahow <veahow@users.noreply.github.com>

* add benchmark for rk3588 on rock5b (Tencent#4275)

* linux-x64-cpu-gcc on tencent ci

* implement layer feature disabled bit (Tencent#4278)

* add elu vulkan operator (Tencent#4280)

* fix tencent ci (Tencent#4277)

* implement GLU and pnnx conversion (Tencent#4283)

* Bump pypa/cibuildwheel from 2.10.2 to 2.11.1 (Tencent#4271)

Bumps [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel) from 2.10.2 to 2.11.1.
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](pypa/cibuildwheel@v2.10.2...v2.11.1)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* fix pnnx softmax/normalize/slice negative axis conversion to ncnn (Tencent#4284)

* pnnx glu batchindex aware conversion (Tencent#4285)

* 1. Fix typo in readme (Tencent#4287)

* x86 sse2/avx2 optimization for convolution sgemm/winograd int8 family (Tencent#4286)

* pnnx skip dynamic size evaluation (Tencent#4291)

* Fix linux build error(Tencent#4265) (Tencent#4294)

Co-authored-by: wangyu <786794414@qq.com>

* general cpu feature detection on macos/ios, enable bf16 and i8mm on a15 a16 and m2 (Tencent#4300)

* x86 unified fc fp32/fp16s (Tencent#4303)

* more fma
* more transpose utility function

* Bump pypa/cibuildwheel from 2.11.1 to 2.11.2 (Tencent#4308)

Bumps [pypa/cibuildwheel](https://github.com/pypa/cibuildwheel) from 2.11.1 to 2.11.2.
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
- [Changelog](https://github.com/pypa/cibuildwheel/blob/main/docs/changelog.md)
- [Commits](pypa/cibuildwheel@v2.11.1...v2.11.2)

---
updated-dependencies:
- dependency-name: pypa/cibuildwheel
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* pnnx pytorch 1.13 (Tencent#4314)

* fix Tencent#4315 (Tencent#4316)

* get_physical_cpu_count api family (Tencent#4302)

* get_physical_cpu_count api family

* set default to physical big cpu

* always treat smt core as big core

* is_smt_cpu

* get max freq mhz on windows

* windows thread affinity

* groupnorm 1d/2d/4d (Tencent#4312)

* fix slice end index, fix fp16 model weight alignment (Tencent#4317)

* tencent ci test-coverage pnnx (Tencent#4305)

* RVV: BatchNorm with fp16s(a) support (Tencent#4075)

* RVV: InstanceNorm with fp16s(a) support (Tencent#4078)

* fix ci pnnx build

* fold new_full and full_like (Tencent#4323)

* pnnx convert nn.Softmax2d (Tencent#4324)

* pnnx convert fold unfold (Tencent#4325)

* support yolov5 6.2 (Tencent#4328)

* implement ncnn fold and unfold (Tencent#4326)

* pnnx load gpu torchscript and reset device (Tencent#4330)

* fix:pnnx-softmax (Tencent#4333)

* pnnx save onnx zero (Tencent#4077)

* save foldable constants in file for reducing memory usage (Tencent#4337)

* match inplace slice copy pattern, rewrite copy uses (Tencent#4338)

* add vector optimization for loongarch64 (Tencent#4242)

* ci loongarch64 lsx (Tencent#4344)

* gridsample op support (Tencent#4288)



Co-authored-by: LRY89757 <LRY89757@users.noreply.github.com>
Co-authored-by: nihuini <nihuini@tencent.com>
Co-authored-by: nihui <shuizhuyuanluo@126.com>

* squeeze and expanddims 4d (Tencent#4346)

* implement MultiheadAttention kdim vdim (Tencent#4347)

* pnnx convert torch bitwise left_shift right_shift (Tencent#4349)

* pnnx fp16 option for ncnn and onnx weight type (Tencent#4350)

* pnnx fuse more function to module (Tencent#4351)

* pnnx fuse more function to module

* rename some pass name

* fuse adjacent reshape, fuse pad conv2d

* fuse pad conv1d

* split tests (Tencent#4354)

* Support mat.numpy() in Python (Tencent#4356)

* Fix typo in stb_image.h (Tencent#4358)

exitting -> exiting

* Fix windows-arm64 build for non-neon case (Tencent#4227)

* update release ci (Tencent#4359)

* update release ci

* find modern glslang

* parallel jobs on windows

* Fix c api allocator (Tencent#4360)

* add some c_api interfaces related to allocator setup.

* fix errors in allocator parameters in c_api.

* test c api allocator

Co-authored-by: zhangtongshe <yuyuyezi@vip.qq.com>

* update glslang (Tencent#4361)

* disable out-of-line atomics since ndk23+ for resolving linking issue with old ndk (Tencent#4362)

* I added one more project to the list of examples. (Tencent#4205)

* Dedicated to coloring black and white photographs.

* add example project link (Tencent#4365)

* fix(pybind11): build error (Tencent#4368)

* fix openmp affinity abort when cpu goes offline (Tencent#4370)

* Update release-python.yml

* small fixes

* unpack list input

* Remove LSTM2

* fix LSTM

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4 participants