Instructions to use replicate/layer_norm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use replicate/layer_norm with Kernels:
# !pip install kernels from kernels import get_kernel # a version (or an explicit revision) is required; see the "Files and versions" tab for the available ones kernel = get_kernel("replicate/layer_norm", version=1) - Notebooks
- Google Colab
- Kaggle
Download torch-ext/torch_binding.cpp from replicate/layer_norm: direct link, hf CLI and curl.
- Browser
- Download file 1.54 kB
-
https://huggingface.co/replicate/layer_norm/resolve/8b60ef7d13bf222002f7c033d4e1586baa185c07/torch-ext/torch_binding.cpp
- Command line
-
hf download hf://replicate/layer_norm@8b60ef7d13bf222002f7c033d4e1586baa185c07/torch-ext/torch_binding.cpp
-
curl -L -o torch_binding.cpp https://huggingface.co/replicate/layer_norm/resolve/8b60ef7d13bf222002f7c033d4e1586baa185c07/torch-ext/torch_binding.cpp
1.54 kB
| TORCH_LIBRARY_EXPAND(TORCH_EXTENSION_NAME, ops) { | |
| ops.def("dropout_add_ln_fwd(Tensor input, Tensor gamma, Tensor beta, Tensor rowscale, Tensor colscale, Tensor x0_subset, Tensor z_subset, float dropout_p, float epsilon, float rowscale_const, int64_t z_numrows, Generator gen, bool residual_in_fp32, bool is_rms_norm) -> Tensor"); | |
| ops.impl("dropout_add_ln_fwd", torch::kCUDA, &dropout_add_ln_fwd); | |
| ops.def("dropout_add_ln_bwd(Tensor dz, Tensor dx, Tensor x, Tensor mu, Tensor rsigma, Tensor gamma, Tensor rowscale, Tensor colscale, Tensor x0_subset, Tensor z_subset, float dropout_p, float rowscale_const, int64_t x0_numrows, bool has_residual, bool is_rms_norm) -> Tensor"); | |
| ops.impl("dropout_add_ln_bwd", torch::kCUDA, &dropout_add_ln_bwd); | |
| ops.def("dropout_add_ln_parallel_residual_fwd(Tensor input, Tensor gamma0, Tensor beta0, Tensor gamma1, Tensor beta1, float dropout_p, float epsilon, Generator gen, bool residual_in_fp32, bool is_rms_norm) -> Tensor"); | |
| ops.impl("dropout_add_ln_parallel_residual_fwd", torch::kCUDA, &dropout_add_ln_parallel_residual_fwd); | |
| ops.def("dropout_add_ln_parallel_residual_bwd(Tensor dz0, Tensor dz1, Tensor dx, Tensor x, Tensor mu, Tensor rsigma, Tensor gamma0, Tensor gamma1, float dropout_p, bool has_x1, bool has_residual, bool is_rms_norm) -> Tensor"); | |
| ops.impl("dropout_add_ln_parallel_residual_bwd", torch::kCUDA, &dropout_add_ln_parallel_residual_bwd); | |
| } | |
| REGISTER_EXTENSION(TORCH_EXTENSION_NAME) | |