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mypy error: Argument 4 to "AugmentationSequential" has incompatible type "RandomTransplantation"; expected "_AugmentationBase | ImageSequential" #2918

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robmarkcole opened this issue May 21, 2024 · 0 comments
Open

mypy error: Argument 4 to "AugmentationSequential" has incompatible type "RandomTransplantation"; expected "_AugmentationBase | ImageSequential" #2918

robmarkcole opened this issue May 21, 2024 · 0 comments
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help wanted Extra attention is needed

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@robmarkcole
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Describe the bug

It appears RandomTransplantation is incompatible type for AugmentationSequential, although the use is documented in the Note here.

Reviewing the chain:
RandomTransplantation(MixAugmentationBaseV2) > MixAugmentationBaseV2(_BasicAugmentationBase) > _BasicAugmentationBase(Module) where from kornia.core import Module, Tensor, tensor, zeros

Reproduction steps

import kornia.augmentation as Ka
from kornia.augmentation.container import AugmentationSequential

...
        self.train_aug = AugmentationSequential(
            Ka.Normalize(mean=self.mean, std=self.std, keepdim=True),
            Ka.RandomHorizontalFlip(p=0.5, keepdim=True),
            Ka.RandomVerticalFlip(p=0.5, keepdim=True),
            Ka.RandomTransplantation(p=1.0, excluded_labels=[0]),
            data_keys=None,
        )

Run mypy on this file results in:

error: Argument 4 to "AugmentationSequential" has incompatible type "RandomTransplantation"; expected "_AugmentationBase | ImageSequential"  [arg-type]



### Expected behavior

No mypy error

### Environment

```shell
⚡ ~ wget https://raw.githubusercontent.com/pytorch/pytorch/main/torch/utils/collect_env.py
--2024-05-21 10:53:39--  https://raw.githubusercontent.com/pytorch/pytorch/main/torch/utils/collect_env.py
Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.111.133, 185.199.108.133, 185.199.109.133, ...
Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 22068 (22K) [text/plain]
Saving to: ‘collect_env.py.1’

collect_env.py.1                                 100%[========================================================================================================>]  21.55K  --.-KB/s    in 0s      

2024-05-21 10:53:39 (51.9 MB/s) - ‘collect_env.py.1’ saved [22068/22068]

⚡ ~ python collect_env.py
Collecting environment information...
PyTorch version: 2.1.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
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: version 3.16.3
Libc version: glibc-2.31

Python version: 3.10.10 (main, Mar 21 2023, 18:45:11) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-1058-aws-x86_64-with-glibc2.31
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
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, 48 bits virtual
CPU(s):                             4
On-line CPU(s) list:                0-3
Thread(s) per core:                 2
Core(s) per socket:                 2
Socket(s):                          1
NUMA node(s):                       1
Vendor ID:                          GenuineIntel
CPU family:                         6
Model:                              85
Model name:                         Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz
Stepping:                           7
CPU MHz:                            2499.994
BogoMIPS:                           4999.98
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          64 KiB
L1i cache:                          64 KiB
L2 cache:                           2 MiB
L3 cache:                           35.8 MiB
NUMA node0 CPU(s):                  0-3
Vulnerability Gather data sampling: Unknown: Dependent on hypervisor status
Vulnerability Itlb multihit:        KVM: Mitigation: VMX unsupported
Vulnerability L1tf:                 Mitigation; PTE Inversion
Vulnerability Mds:                  Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Meltdown:             Mitigation; PTI
Vulnerability Mmio stale data:      Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Retbleed:             Vulnerable
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Vulnerable
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Retpolines, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
⚡ ~ python collect_env.py
Collecting environment information...
PyTorch version: 2.1.1+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
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: version 3.16.3
Libc version: glibc-2.31

Python version: 3.10.10 (main, Mar 21 2023, 18:45:11) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-1058-aws-x86_64-with-glibc2.31
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
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, 48 bits virtual
CPU(s):                             4
On-line CPU(s) list:                0-3
Thread(s) per core:                 2
Core(s) per socket:                 2
Socket(s):                          1
NUMA node(s):                       1
Vendor ID:                          GenuineIntel
CPU family:                         6
Model:                              85
Model name:                         Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz
Stepping:                           7
CPU MHz:                            2499.994
BogoMIPS:                           4999.98
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          64 KiB
L1i cache:                          64 KiB
L2 cache:                           2 MiB
L3 cache:                           35.8 MiB
NUMA node0 CPU(s):                  0-3
Vulnerability Gather data sampling: Unknown: Dependent on hypervisor status
Vulnerability Itlb multihit:        KVM: Mitigation: VMX unsupported
Vulnerability L1tf:                 Mitigation; PTE Inversion
Vulnerability Mds:                  Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Meltdown:             Mitigation; PTI
Vulnerability Mmio stale data:      Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Retbleed:             Vulnerable
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass:    Vulnerable
Vulnerability Spectre v1:           Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:           Mitigation; Retpolines, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves ida arat pku ospke

Versions of relevant libraries:
[pip3] efficientnet-pytorch==0.7.1
[pip3] mypy==1.10.0
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.2
[pip3] pytorch-lightning==2.1.2
[pip3] segmentation-models-pytorch==0.3.3
[pip3] torch==2.1.1+cu121
[pip3] torchaudio==2.1.1+cu121
[pip3] torchgeo==0.6.0.dev0
[pip3] torchmetrics==1.2.0
[pip3] torchvision==0.16.1+cu121
[pip3] triton==2.1.0
[conda] efficientnet-pytorch      0.7.1                    pypi_0    pypi
[conda] numpy                     1.26.2                   pypi_0    pypi
[conda] pytorch-lightning         2.1.2                    pypi_0    pypi
[conda] segmentation-models-pytorch 0.3.3                    pypi_0    pypi
[conda] torch                     2.1.1+cu121              pypi_0    pypi
[conda] torchaudio                2.1.1+cu121              pypi_0    pypi
[conda] torchgeo                  0.6.0.dev0               pypi_0    pypi
[conda] torchmetrics              1.2.0                    pypi_0    pypi
[conda] torchvision               0.16.1+cu121             pypi_0    pypi
[conda] triton                    2.1.0                    pypi_0    pypi

Additional context

No response
@robmarkcole robmarkcole added the help wanted Extra attention is needed label May 21, 2024
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