triton.language.randn
- triton.language.randn = <function randn>
Given a
seedscalar and anoffsetblock, returns a block of randomfloat32in \(\mathcal{N}(0, 1)\).- 参数:
seed -- The seed for generating random numbers.
offsets -- The offsets to generate random numbers for.
Example
import triton import triton.language as tl import torch import math @triton.jit def kernel_randn(x_ptr, n_rounds: tl.constexpr, N: tl.constexpr, XBLOCK: tl.constexpr): block_offset = tl.program_id(0) * XBLOCK offsets = block_offset + tl.arange(0, XBLOCK) # Block-level offset tensor mask = offsets < N rand_vals = tl.randn(5, 10 + offsets, n_rounds) # Generate a block of random numbers at once tl.store(x_ptr + offsets, rand_vals, mask=mask) def test_randn(): shape = (1, 3) y_calf = torch.zeros(shape, dtype=eval('torch.float32')).npu() numel = y_calf.numel() ncore = 1 if numel < 32 else 32 xblock = math.ceil(numel / ncore) kernel_randn[ncore, 1, 1](y_calf, 10, numel, xblock) if __name__ == "__main__": test_randn()