Datasets:
| [ | |
| { | |
| "id": "basic_reduce", | |
| "description": "Given array x, compute mean of each row.", | |
| "input": "data/x.npy", | |
| "output": "basic_reduce.npy" | |
| }, | |
| { | |
| "id": "map_square", | |
| "description": "Apply square function to each element using vectorization.", | |
| "input": "data/x.npy", | |
| "output": "map_square.npy" | |
| }, | |
| { | |
| "id": "grad_logistic", | |
| "description": "Compute gradient of logistic loss.", | |
| "input": "data/logistic.npz", | |
| "output": "grad_logistic.npy" | |
| }, | |
| { | |
| "id": "scan_rnn", | |
| "description": "Implement RNN forward pass using scan.", | |
| "input": "data/seq.npz", | |
| "output": "scan_rnn.npy" | |
| }, | |
| { | |
| "id": "jit_mlp", | |
| "description": "Implement and JIT compile a 2-layer MLP.", | |
| "input": "data/mlp.npz", | |
| "output": "jit_mlp.npy" | |
| } | |
| ] | |