Repository: pytorch
Issue: FlexAttention gives me an INTERNAL_ASSERT_FAILED during mask_mod
Labels: needs reproduction,triaged,bug,oncall: pt2,module: higher order operators,module: pt2-dispatcher,module: flex attention,module: sdpa

### 🐛 Describe the bug

I am running some small, batch size 1 evaluations at inference, and get the following error with Flex Attention:
```Python
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/nn/attention/flex_attention.py", line 873, in create_block_mask
    mask_tensor = create_mask(mask_mod, B, H, Q_LEN, KV_LEN, device)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/nn/attention/flex_attention.py", line 804, in create_mask
    mask = mask_mod(b, h, m, n)
           ^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/apis.py", line 203, in wrapped
    return vmap_impl(
           ^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/vmap.py", line 331, in vmap_impl
    return _flat_vmap(
           ^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/vmap.py", line 479, in _flat_vmap
    batched_outputs = func(*batched_inputs, **kwargs)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/apis.py", line 203, in wrapped
    return vmap_impl(
           ^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/vmap.py", line 331, in vmap_impl
    return _flat_vmap(
           ^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/vmap.py", line 479, in _flat_vmap
    batched_outputs = func(*batched_inputs, **kwargs)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/apis.py", line 203, in wrapped
    return vmap_impl(
           ^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/vmap.py", line 331, in vmap_impl
    return _flat_vmap(
           ^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/vmap.py", line 479, in _flat_vmap
    batched_outputs = func(*batched_inputs, **kwargs)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/apis.py", line 203, in wrapped
    return vmap_impl(
           ^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/vmap.py", line 331, in vmap_impl
    return _flat_vmap(
           ^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/vmap.py", line 479, in _flat_vmap
    batched_outputs = func(*batched_inputs, **kwargs)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/inference/echo/models/models.py", line 82, in mask_mod
    kv_masked = kv_idx < source_lengths[b]
                         ~~~~~~~~~~~~~~^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_dynamo/_trace_wrapped_higher_order_op.py", line 141, in __torch_function__
    return mod_index(args[0], index_args)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/autograd/function.py", line 585, in apply
    return custom_function_call(cls, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 49, in __call__
    return super().__call__(autograd_function, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 440, in __call__
    return wrapper()
           ^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 721, in _fn
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 436, in wrapper
    return self.dispatch(
           ^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 305, in dispatch
    return dispatch_functorch(self, args, kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/pyfunctorch.py", line 294, in dispatch_functorch
    return interpreter.process(op, args, kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/pyfunctorch.py", line 130, in process
    return kernel(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 300, in custom_function_call_vmap
    return custom_function_call_vmap_generate_rule(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 376, in custom_function_call_vmap_generate_rule
    output = custom_function_call(vmapped_function, *unwrapped_operands)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 49, in __call__
    return super().__call__(autograd_function, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 440, in __call__
    return wrapper()
           ^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 721, in _fn
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 436, in wrapper
    return self.dispatch(
           ^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 305, in dispatch
    return dispatch_functorch(self, args, kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/pyfunctorch.py", line 294, in dispatch_functorch
    return interpreter.process(op, args, kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/pyfunctorch.py", line 130, in process
    return kernel(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 300, in custom_function_call_vmap
    return custom_function_call_vmap_generate_rule(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 376, in custom_function_call_vmap_generate_rule
    output = custom_function_call(vmapped_function, *unwrapped_operands)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 49, in __call__
    return super().__call__(autograd_function, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 440, in __call__
    return wrapper()
           ^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 721, in _fn
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 436, in wrapper
    return self.dispatch(
           ^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 305, in dispatch
    return dispatch_functorch(self, args, kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/pyfunctorch.py", line 294, in dispatch_functorch
    return interpreter.process(op, args, kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/pyfunctorch.py", line 130, in process
    return kernel(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 300, in custom_function_call_vmap
    return custom_function_call_vmap_generate_rule(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 376, in custom_function_call_vmap_generate_rule
    output = custom_function_call(vmapped_function, *unwrapped_operands)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 49, in __call__
    return super().__call__(autograd_function, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 440, in __call__
    return wrapper()
           ^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_dynamo/eval_frame.py", line 721, in _fn
    return fn(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 436, in wrapper
    return self.dispatch(
           ^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_ops.py", line 305, in dispatch
    return dispatch_functorch(self, args, kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/pyfunctorch.py", line 294, in dispatch_functorch
    return interpreter.process(op, args, kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/pyfunctorch.py", line 130, in process
    return kernel(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 300, in custom_function_call_vmap
    return custom_function_call_vmap_generate_rule(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/autograd_function.py", line 375, in custom_function_call_vmap_generate_rule
    with interpreter.lower():
  File "/opt/conda/envs/main-env/lib/python3.11/contextlib.py", line 158, in __exit__
    self.gen.throw(typ, value, traceback)
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/pyfunctorch.py", line 89, in temporarily_pop_interpreter_stack
    push_dynamic_layer_stack(saved)
RuntimeError: layerId == dynamic_layer.layerId() INTERNAL ASSERT FAILED at "../aten/src/ATen/functorch/DynamicLayer.cpp":236, please report a bug to PyTorch.
Exception ignored in: <generator object vmap_increment_nesting at 0x7239bcba9fc0>
Traceback (most recent call last):
  File "/opt/conda/envs/main-env/lib/python3.11/site-packages/torch/_functorch/vmap.py", line 469, in vmap_increment_nesting
    _vmap_decrement_nesting()
RuntimeError: !dynamicLayerStack.empty() INTERNAL ASSERT FAILED at "../aten/src/ATen/functorch/DynamicLayer.cpp":217, please report a bug to PyTorch.
```

### Versions

```
Collecting environment information...
PyTorch version: 2.6.0.dev20241106+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.31

Python version: 3.11.10 | packaged by conda-forge | (main, Sep 30 2024, 18:08:57) [GCC 13.3.0] (64-bit runtime)
Python platform: Linux-6.8.0-47-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 12.6.77
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA H100 PCIe
Nvidia driver version: 550.90.12
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Byte Order:                           Little Endian
Address sizes:                        46 bits physical, 57 bits virtual
CPU(s):                               26
On-line CPU(s) list:                  0-25
Thread(s) per core:                   1
Core(s) per socket:                   1
Socket(s):                            26
NUMA node(s):                         1
Vendor ID:                            GenuineIntel
CPU family:                           6
Model:                                143
Model name:                           Intel(R) Xeon(R) Platinum 8480+
Stepping:                             8
CPU MHz:                              2000.000
BogoMIPS:                             4000.00
Virtualization:                       VT-x
Hypervisor vendor:                    KVM
Virtualization type:                  full
L1d cache:                            832 KiB
L1i cache:                            832 KiB
L2 cache:                             104 MiB
L3 cache:                             416 MiB
NUMA node0 CPU(s):                    0-25
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Unknown: No mitigations
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Mitigation; TSX disabled
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq vmx ssse3 fma cx16 pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault ssbd ibrs ibpb sti
bp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx_vnni avx512_bf16 wbnoinvd arat vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdir
i movdir64b fsrm md_clear serialize tsxldtrk avx512_fp16 arch_capabilities

Versions of relevant libraries:
[pip3] flake8==5.0.4
[pip3] mypy==1.9.0
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-cusparselt-cu12==0.6.2
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] onnx==1.17.0
[pip3] optree==0.13.0
[pip3] pytest-flake8==1.2.2
[pip3] pytorch-metric-learning==2.6.0
[pip3] pytorch-triton==3.1.0+cf34004b8a
[pip3] torch==2.6.0.dev20241106+cu124
[pip3] torch-audiomentations==0.11.1
[pip3] torchdyn==1.0.6
[pip3] torcheval==0.0.7
[pip3] torchmetrics==1.4.2
[pip3] torchsde==0.2.6
[pip3] torchvision==0.20.0.dev20241106+cu124
[pip3] triton==3.1.0
[conda] blas                      1.0                         mkl    conda-forge
[conda] cuda-cudart               12.1.105                      0    nvidia
[conda] cuda-cupti                12.1.105                      0    nvidia
[conda] cuda-libraries            12.1.0                        0    nvidia
[conda] cuda-nvrtc                12.1.105                      0    nvidia
[conda] cuda-nvtx                 12.1.105                      0    nvidia
[conda] cuda-opencl               12.6.77                       0    nvidia
[conda] cuda-runtime              12.1.0                        0    nvidia
[conda] ignite                    0.5.0.post2                py_0    pytorch
[conda] libblas                   3.9.0            16_linux64_mkl    conda-forge
[conda] libcblas                  3.9.0            16_linux64_mkl    conda-forge
[conda] libcublas                 12.1.0.26                     0    nvidia
[conda] libcufft                  11.0.2.4                      0    nvidia
[conda] libcurand                 10.3.7.77                     0    nvidia
[conda] libcusolver               11.4.4.55                     0    nvidia
[conda] libcusparse               12.0.2.55                     0    nvidia
[conda] liblapack                 3.9.0            16_linux64_mkl    conda-forge
[conda] libnvjitlink              12.1.105                      0    nvidia
[conda] libopenvino-pytorch-frontend 2024.3.0             he02047a_0    conda-forge
[conda] mkl                       2022.1.0           hc2b9512_224
[conda] numpy                     1.26.4          py311h64a7726_0    conda-forge
[conda] nvidia-cublas-cu12        12.4.5.8                 pypi_0    pypi
[conda] nvidia-cuda-cupti-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-nvrtc-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-runtime-cu12  12.4.127                 pypi_0    pypi
[conda] nvidia-cudnn-cu12         9.1.0.70                 pypi_0    pypi
[conda] nvidia-cufft-cu12         11.2.1.3                 pypi_0    pypi
[conda] nvidia-curand-cu12        10.3.5.147               pypi_0    pypi
[conda] nvidia-cusolver-cu12      11.6.1.9                 pypi_0    pypi
[conda] nvidia-cusparse-cu12      12.3.1.170               pypi_0    pypi
[conda] nvidia-cusparselt-cu12    0.6.2                    pypi_0    pypi
[conda] nvidia-nccl-cu12          2.21.5                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.4.127                 pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.4.127                 pypi_0    pypi
[conda] optree                    0.13.0                   pypi_0    pypi
[conda] pytorch-cuda              12.1                 ha16c6d3_5    pytorch
[conda] pytorch-lightning         2.4.0              pyhd8ed1ab_0    conda-forge
[conda] pytorch-metric-learning   2.6.0                    pypi_0    pypi
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] pytorch-triton            3.1.0+cf34004b8a          pypi_0    pypi
[conda] torch                     2.6.0.dev20241106+cu124          pypi_0    pypi
[conda] torch-audiomentations     0.11.1                   pypi_0    pypi
[conda] torch-pitch-shift         1.2.5                    pypi_0    pypi
[conda] torch-stoi                0.2.3                    pypi_0    pypi
[conda] torchaudio                2.5.0.dev20241106+cu124          pypi_0    pypi
[conda] torchcde                  0.2.5                    pypi_0    pypi
[conda] torchcfm                  1.0.6                    pypi_0    pypi
[conda] torchdiffeq               0.2.2              pyhd8ed1ab_0    conda-forge
[conda] torchdyn                  1.0.6                    pypi_0    pypi
[conda] torcheval                 0.0.7                    pypi_0    pypi
[conda] torchmetrics              1.4.2              pyhd8ed1ab_0    conda-forge
[conda] torchsde                  0.2.6                    pypi_0    pypi
[conda] torchvision               0.20.0.dev20241106+cu124          pypi_0    pypi
[conda] triton                    3.1.0                    pypi_0    pypi
```

cc @jbschlosser @bhosmer @cpuhrsch @erichan1 @drisspg @mikaylagawarecki @ezyang @chauhang @penguinwu @zou3519 @ydwu4 @bdhirsh @yf225 @Chillee @yanboliang @BoyuanFeng