Instructions to use replicate/mra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use replicate/mra 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/mra", version=1) - Notebooks
- Google Colab
- Kaggle
File size: 703 Bytes
55ce07b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | #include <torch/torch.h>
#include <ATen/ATen.h>
#include <vector>
#define min(a, b) ((a)<(b)?(a):(b))
#define max(a, b) ((a)>(b)?(a):(b))
std::vector<at::Tensor> index_max_kernel(
at::Tensor index_vals,
at::Tensor indices,
int A_num_block,
int B_num_block
);
at::Tensor mm_to_sparse_kernel(
at::Tensor dense_A,
at::Tensor dense_B,
at::Tensor indices
);
at::Tensor sparse_dense_mm_kernel(
at::Tensor sparse_A,
at::Tensor indices,
at::Tensor dense_B,
int A_num_block
);
at::Tensor reduce_sum_kernel(
at::Tensor sparse_A,
at::Tensor indices,
int A_num_block,
int B_num_block
);
at::Tensor scatter_kernel(
at::Tensor dense_A,
at::Tensor indices,
int B_num_block
);
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