ShaSpec
The official code repository of ShaSpec model from CVPR 2023 [paper](https://arxiv.org/pdf/2307.14126) "Multi-modal Learning with Missing Modality via Shared-Specific Feature Modelling"
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Download Latest Version (.zip)- __init__.py
- functional_overrides.py
- tensor_overrides.py
- torch_overrides.py
- __init__.py
- __version__.py
- _amp_state.py
- _initialize.py
- _process_optimizer.py
- amp.py
- compat.py
- frontend.py
- handle.py
- opt.py
- README.md
- rnn_compat.py
- scaler.py
- utils.py
- wrap.py
- __init__.py
- bottleneck.py
- test.py
- bottleneck.cpp
- gemm.h
- gmem_tile.h
- kernel_traits.h
- mask.h
- smem_tile.h
- softmax.h
- utils.h
- fmha.h
- fmha_dgrad_fp16_128_64_kernel.sm80.cu
- fmha_dgrad_fp16_256_64_kernel.sm80.cu
- fmha_dgrad_fp16_384_64_kernel.sm80.cu
- fmha_dgrad_fp16_512_64_kernel.sm80.cu
- fmha_dgrad_kernel_1xN_reload.h
- fmha_fprop_fp16_128_64_kernel.sm80.cu
- fmha_fprop_fp16_256_64_kernel.sm80.cu
- fmha_fprop_fp16_384_64_kernel.sm80.cu
- fmha_fprop_fp16_512_64_kernel.sm80.cu
- fmha_fprop_kernel_1xN.h
- fmha_fprop_kernel_1xN_reload_v.h
- fmha_kernel.h
- fmha_utils.h
- fmha_api.cpp
- batch_norm.cu
- batch_norm.h
- batch_norm_add_relu.cu
- batch_norm_add_relu.h
- cuda_utils.h
- interface.cpp
- ipc.cu
- nhwc_batch_norm_kernel.h
- ln_api.cpp
- ln_bwd_semi_cuda_kernel.cu
- ln_fwd_cuda_kernel.cu
- ln_kernel_traits.h
- utils.cuh
- additive_masked_softmax_dropout.cpp
- additive_masked_softmax_dropout_cuda.cu
- dropout.h
- encdec_multihead_attn.cpp
- encdec_multihead_attn_cuda.cu
- encdec_multihead_attn_norm_add.cpp
- encdec_multihead_attn_norm_add_cuda.cu
- layer_norm.h
- masked_softmax_dropout.cpp
- masked_softmax_dropout_cuda.cu
- philox.h
- self_multihead_attn.cpp
- self_multihead_attn_bias.cpp
- self_multihead_attn_bias_additive_mask.cpp
- self_multihead_attn_bias_additive_mask_cuda.cu
- self_multihead_attn_bias_cuda.cu
- self_multihead_attn_cuda.cu
- self_multihead_attn_norm_add.cpp
- self_multihead_attn_norm_add_cuda.cu
- softmax.h
- strided_batched_gemm.h
- fused_adam_cuda.cpp
- fused_adam_cuda_kernel.cu
- fused_lamb_cuda.cpp
- fused_lamb_cuda_kernel.cu
- multi_tensor_distopt_adam.cpp
- multi_tensor_distopt_adam_kernel.cu
- multi_tensor_distopt_lamb.cpp
- multi_tensor_distopt_lamb_kernel.cu
- transducer_joint.cpp
- transducer_joint_kernel.cu
- transducer_loss.cpp
- transducer_loss_kernel.cu
- interface.cpp
- xentropy_kernel.cu
- func_test_multihead_attn.py
- perf_test_multihead_attn.py
- __init__.py
- fmha.py
- __init__.py
- batch_norm.py
- __init__.py
- layer_norm.py
- __init__.py
- encdec_multihead_attn.py
- encdec_multihead_attn_func.py
- fast_encdec_multihead_attn_func.py
- fast_encdec_multihead_attn_norm_add_func.py
- fast_self_multihead_attn_func.py
- fast_self_multihead_attn_norm_add_func.py
- mask_softmax_dropout_func.py
- MHA_bwd.png
- MHA_fwd.png
- README.md
- self_multihead_attn.py
- self_multihead_attn_func.py
- __init__.py
- distributed_fused_adam.py
- distributed_fused_adam_v2.py
- distributed_fused_adam_v3.py
- distributed_fused_lamb.py
- fp16_optimizer.py
- fused_adam.py
- fused_lamb.py
- fused_sgd.py
- checkpointing_test_part1.py
- checkpointing_test_part2.py
- checkpointing_test_reference.py
- toy_problem.py
- __init__.py
- asp.py
- README.md
- sparse_masklib.py
- test_fmha.py
- test_fast_layer_norm.py
- test_encdec_multihead_attn.py
- test_encdec_multihead_attn_norm_add.py
- test_fast_self_multihead_attn_bias.py
- test_mha_fused_softmax.py
- test_self_multihead_attn.py
- test_self_multihead_attn_norm_add.py
- test_transducer_joint.py
- test_transducer_loss.py
- transducer_ref.py
- test_label_smoothing.py
- __init__.py
- transducer.py
- __init__.py
- softmax_xentropy.py
- __init__.py
- __init__.py
- fp16_optimizer.py
- fp16util.py
- loss_scaler.py
- README.md
- __init__.py
- mlp.py
- __init__.py
- multi_tensor_apply.py
- __init__.py
- fused_layer_norm.py
- __init__.py
- fused_adagrad.py
- fused_adam.py
- fused_lamb.py
- fused_novograd.py
- fused_sgd.py
- __init__.py
- distributed.py
- LARC.py
- multiproc.py
- optimized_sync_batchnorm.py
- optimized_sync_batchnorm_kernel.py
- README.md
- sync_batchnorm.py
- sync_batchnorm_kernel.py
- fused_adam.py
- fused_layer_norm.py
- README.md
- test.sh
- custom_function.py
- custom_module.py
- README.md
- test.sh
- imagenet.py
- test.sh
- jit_script_function.py
- jit_script_method.py
- jit_trace_function.py
- jit_trace_method.py
- README.md
- test.sh
- README.md
- resnet.py
- test.sh
- .gitignore
- lenet.py
- operators.py
- simple.py
- __init__.py
- nvmarker.py
- __init__.py
- __main__.py
- db.py
- kernel.py
- nvvp.py
- parse.py
- __init__.py
- __main__.py
- activation.py
- base.py
- blas.py
- conv.py
- convert.py
- data.py
- dropout.py
- embedding.py
- index_slice_join_mutate.py
- linear.py
- loss.py
- misc.py
- normalization.py
- optim.py
- output.py
- pointwise.py
- pooling.py
- prof.py
- randomSample.py
- recurrentCell.py
- reduction.py
- softmax.py
- usage.py
- utility.py
- __init__.py
- FAQs.md
- README.md
- __init__.py
- README.md
- reparameterization.py
- weight_norm.py
- __init__.py
- cells.py
- models.py
- README.md
- RNNBackend.py
- __init__.py
- BraTS18_test.csv
- BraTS18_train.csv
- BraTS18_train_all.csv
- BraTS18_val.csv
- __init__.py
- custom_transforms.py
- functional_instancenorm_noverifydim.py
- HausdorffD.py
- logger.py
- ParaFlop.py
- pyt_utils.py
- utils.py
- __init__.py
- BraTSDataSet.py
- dsn.py
- DualNet_SS.py
- engine.py
- environment.yml
- eval.py
- eval.sh
- loss_Dual.py
- postprocess.py
- README.md
- requirements.txt
- Res50.py
- run.sh
- train_SS.py
# Installation Guide
1. Get the code
git clone https://github.com/billhhh/ShaSpec
Downloads the entire project code from GitHub to your computer.
cd ShaSpec
Moves into the project folder you just downloaded.
2. Python
Easy RecommendedPrerequisites
pip install -r requirements.txt
Installs the Python libraries listed in requirements.txt (or similar).
If it runs without errors and prints output in the terminal, it worked.
Pulled directly from this repo's README.
// repository documentation
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