[{"data":1,"prerenderedAt":48},["ShallowReactive",2],{"chapter:kernels\u002Freference\u002Fporting.json":3},{"project":4,"route":5,"title":6,"titleHtml":6,"navTitle":6,"part":7,"sourcePath":8,"editUrl":9,"html":10,"toc":11,"hasMermaid":43,"prev":44,"next":47},"kernels","\u002Fkernels\u002Freference\u002Fporting","Appendix: Porting a Python Triton Kernel","Reference","reference\u002Fporting.md","https:\u002F\u002Fgithub.com\u002Fteenygrad\u002Fteenygrad\u002Fedit\u002Fmain\u002Fbooks\u002Fkernels\u002Fsrc\u002Freference\u002Fporting.md","\u003Cp>A worked port, start to finish. The example is a fused softmax — the same\noperation as Chapter 10, approached from the other direction, because it is the\nkernel most people have already written in Python.\u003C\u002Fp>\n\u003Ch2 id=\"the-python-original\">The Python original\u003C\u002Fh2>\n\u003Cp>Here is the shape of a typical hand-written Triton softmax. One program per row,\nthe whole row loaded at once, masked because rows are rarely a power of two:\u003C\u002Fp>\n\u003Cpre data-lang=\"python\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">import\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> triton\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">import\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> triton\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">language\u003C\u002Fspan>\u003Cspan style=\"color:#FF5F9E\"> as\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#8A9088\">@\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">triton\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">jit\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">def\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> softmax_kernel\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">x_ptr\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> y_ptr\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> n_cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> BLOCK_SIZE\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">constexpr\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">):\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    row \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">program_id\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    row_start \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> row \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">*\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> n_cols\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    cols \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">arange\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> BLOCK_SIZE\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    mask \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> cols \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> n_cols\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    x \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">load\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">x_ptr \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">+\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> row_start \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">+\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> mask\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">mask\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> other\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=-\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">float\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">\"\u003C\u002Fspan>\u003Cspan style=\"color:#D8A76B\">inf\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">\"\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">))\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    x \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> x \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">-\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">max\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">x\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> axis\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    num \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">exp\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">x\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    y \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> num \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">\u002F\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">sum\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">num\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> axis\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">store\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">y_ptr \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">+\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> row_start \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">+\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> y\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> mask\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">mask\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Ch2 id=\"step-1--the-signature\">Step 1 — The signature\u003C\u002Fh2>\n\u003Cp>Python’s \u003Ccode>tl.constexpr\u003C\u002Fcode> marks a compile-time constant. In Rust that is a const\ngeneric, and you also need the two type parameters Python does not have: the\nGPU, and the dtype.\u003C\u002Fp>\n\u003Cpre data-lang=\"rust\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">pub\u003C\u002Fspan>\u003Cspan style=\"color:#FF5F9E\"> fn\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> softmax_forward\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> Triton\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> D\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> Float\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#FF5F9E\"> const\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> BLOCK_SIZE\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> i32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">>(\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    x_ptr\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">Pointer\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">D\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">>,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    y_ptr\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">Pointer\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">D\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">>,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    n_cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> i32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>\u003Ccode>D: Float\u003C\u002Fcode> rather than \u003Ccode>Num\u003C\u002Fcode>, because \u003Ccode>exp\u003C\u002Fcode> is only defined for floats. Python\nwould have discovered that at run time, on a GPU, if at all.\u003C\u002Fp>\n\u003Cp>Then the three \u003Ccode>where\u003C\u002Fcode> clauses. They are the same in every kernel:\u003C\u002Fp>\n\u003Cpre data-lang=\"rust\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">where\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">I32Tensor\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> types\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">Tensor\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">i32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> 1\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">>,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">I32Tensor\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> Comparison\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">i32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> BoolTensor\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> =\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">BoolTensor\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">>,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">Pointer\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">D\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">>:\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> AddOffsets\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">i32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> 1\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">I32Tensor\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> Output\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> =\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">Tensor\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">Pointer\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">D\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">>>>,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Ch2 id=\"step-2--indices\">Step 2 — Indices\u003C\u002Fh2>\n\u003Cpre data-lang=\"python\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">row \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">program_id\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">row_start \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> row \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">*\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> n_cols\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">cols \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">arange\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> BLOCK_SIZE\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">mask \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> cols \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> n_cols\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cpre data-lang=\"rust\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> row \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">program_id\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">Axis\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">X\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">);\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> row_start \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> row \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">*\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> n_cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">;\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> cols \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">arange\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> BLOCK_SIZE\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">);\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> mask \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">lt\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">n_cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">);\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>Nearly identical. \u003Ccode>0\u003C\u002Fcode> becomes \u003Ccode>Axis::X\u003C\u002Fcode>, and \u003Ccode><\u003C\u002Fcode> becomes \u003Ccode>.lt(...)\u003C\u002Fcode> because Rust\ncannot overload comparison operators to return something other than \u003Ccode>bool\u003C\u002Fcode>.\u003C\u002Fp>\n\u003Ch2 id=\"step-3--the-load\">Step 3 — The load\u003C\u002Fh2>\n\u003Cp>This is where the two languages diverge most.\u003C\u002Fp>\n\u003Cpre data-lang=\"python\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">x \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">load\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">x_ptr \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">+\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> row_start \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">+\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> mask\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">mask\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> other\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=-\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">float\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">\"\u003C\u002Fspan>\u003Cspan style=\"color:#D8A76B\">inf\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">\"\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">))\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cpre data-lang=\"rust\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> neg_inf \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">full\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(&[\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">BLOCK_SIZE\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">],\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> D\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">from_f64\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">f64\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">NEG_INFINITY\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">));\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> x \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">load\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    x_ptr\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">add_offsets\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">cols \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">+\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> row_start\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">),\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    Some\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">mask\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">),\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    Some\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">neg_inf\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">),\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#8A9088\">    &[],\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    None\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    None\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    None\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#B79AD4\">    false\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#8A9088\">);\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>Three differences:\u003C\u002Fp>\n\u003Cul>\n\u003Cli>\u003Cstrong>\u003Ccode>+\u003C\u002Fcode> becomes \u003Ccode>add_offsets\u003C\u002Fcode>.\u003C\u002Fstrong> Python overloads \u003Ccode>+\u003C\u002Fcode> on pointers; Rust uses a\nnamed method from the \u003Ccode>AddOffsets\u003C\u002Fcode> trait.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>The fill value is a tensor.\u003C\u002Fstrong> Python broadcasts a scalar; Rust wants a tensor\nof the right dtype, built with \u003Ccode>T::full\u003C\u002Fcode>.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Every optional argument is spelled out.\u003C\u002Fstrong> Six \u003Ccode>None\u003C\u002Fcode>s and a \u003Ccode>false\u003C\u002Fcode>. There is\nno way around it today, and it is the first item in \u003Ccode>API-FRICTION.md\u003C\u002Fcode>.\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>Note the fill value itself: negative infinity, because these lanes feed a\nmaximum. Chapter 10 has the table.\u003C\u002Fp>\n\u003Ch2 id=\"step-4--the-arithmetic\">Step 4 — The arithmetic\u003C\u002Fh2>\n\u003Cpre data-lang=\"python\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">x \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> x \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">-\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">max\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">x\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> axis\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">num \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">exp\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">x\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">y \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> num \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">\u002F\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">sum\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">num\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> axis\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cpre data-lang=\"rust\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> row_max \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">max\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">x\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> Some\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">),\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> true\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">);\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> shifted \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> x \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">-\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> row_max\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">;\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> num \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">exp\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">shifted\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">);\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> denom \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">sum\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">num\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> Some\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">0\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">),\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> true\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">);\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> y \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> num \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">\u002F\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> denom\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">;\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>Two differences worth care:\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Ccode>axis=0\u003C\u002Fcode> becomes \u003Ccode>Some(0)\u003C\u002Fcode>.\u003C\u002Fstrong> \u003Ccode>None\u003C\u002Fcode> means “reduce everything”, which Python\nspells by omitting the argument.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>\u003Ccode>keep_dims\u003C\u002Fcode> is explicit, and you want \u003Ccode>true\u003C\u002Fcode>.\u003C\u002Fstrong> Python’s default keeps the\nresult broadcastable against the input. Rust makes you say so, and \u003Ccode>false\u003C\u002Fcode> gives\na shape that will not line up with \u003Ccode>x\u003C\u002Fcode>. This is the most common porting mistake.\u003C\u002Fp>\n\u003Cp>\u003Cstrong>No reassignment.\u003C\u002Fstrong> Python rebinds \u003Ccode>x\u003C\u002Fcode>; the Rust version uses new names because\nthe tensors are \u003Ccode>Copy\u003C\u002Fcode> values, not mutable buffers.\u003C\u002Fp>\n\u003Ch2 id=\"step-5--the-store\">Step 5 — The store\u003C\u002Fh2>\n\u003Cpre data-lang=\"python\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">tl\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">store\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">y_ptr \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">+\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> row_start \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">+\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> y\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> mask\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">mask\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cpre data-lang=\"rust\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">T\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">store\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    y_ptr\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">add_offsets\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">cols \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">+\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> row_start\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">),\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    y\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    Some\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">mask\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">),\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#8A9088\">    &[],\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    None\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#6FBF98\">    None\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#8A9088\">);\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Ch2 id=\"step-6--the-launch\">Step 6 — The launch\u003C\u002Fh2>\n\u003Cp>Python launches with a grid expression and passes the constant as a keyword:\u003C\u002Fp>\n\u003Cpre data-lang=\"python\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">softmax_kernel\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">[(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">n_rows\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,)](\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">x\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> y\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\"> n_cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> BLOCK_SIZE\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">triton\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">next_power_of_2\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">n_cols\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">))\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>Rust splits this into building, compiling and launching — Chapter 5:\u003C\u002Fp>\n\u003Cpre data-lang=\"rust\" class=\"shiki teeny-datasheet\" style=\"background-color:#16181a;color:#e6e8e3\" tabindex=\"0\">\u003Ccode>\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> kernel \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> SoftmaxForward\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::<\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">f32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">>::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">new\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">BLOCK_SIZE\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">);\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> ptx \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> std\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">fs\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">read\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">compile_kernel\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(&\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">kernel\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> &\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">Target\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">new\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">capability\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">),\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> false\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)?)?;\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> program \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> testing\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">load_program_from_ptx\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">::<\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">SoftmaxForward\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"><\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\">f32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">>>(&\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">ptx\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">)?;\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#FF5F9E\">let\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> cfg \u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">=\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> CudaLaunchConfig\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> {\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> grid\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> [\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">n_rows \u003C\u002Fspan>\u003Cspan style=\"color:#FF5F9E\">as\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> u32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> 1\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> 1\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">],\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> block\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> [\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">BLOCK_SIZE\u003C\u002Fspan>\u003Cspan style=\"color:#FF5F9E\"> as\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> u32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> 1\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> 1\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">],\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\"> cluster\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">:\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> [\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\">1\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> 1\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#B79AD4\"> 1\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">]\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> };\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">device\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">launch\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">(&\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">program\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> &\u003C\u002Fspan>\u003Cspan style=\"color:#E6E8E3\">cfg\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> (\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    x_buf\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">as_device_ptr\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">()\u003C\u002Fspan>\u003Cspan style=\"color:#FF5F9E\"> as\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> *\u003C\u002Fspan>\u003Cspan style=\"color:#FF5F9E\">mut\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> f32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    y_buf\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">.\u003C\u002Fspan>\u003Cspan style=\"color:#7FB6D9\">as_device_ptr\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">()\u003C\u002Fspan>\u003Cspan style=\"color:#FF5F9E\"> as\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\"> *\u003C\u002Fspan>\u003Cspan style=\"color:#FF5F9E\">mut\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> f32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#E6E8E3\">    n_cols \u003C\u002Fspan>\u003Cspan style=\"color:#FF5F9E\">as\u003C\u002Fspan>\u003Cspan style=\"color:#6FBF98\"> i32\u003C\u002Fspan>\u003Cspan style=\"color:#8A9088\">,\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003Cspan style=\"color:#8A9088\">))?;\u003C\u002Fspan>\u003C\u002Fspan>\n\u003Cspan class=\"line\">\u003C\u002Fspan>\u003C\u002Fcode>\u003C\u002Fpre>\n\u003Cp>More ceremony, and one thing to be careful of: \u003Cstrong>the argument tuple is\npositional and unchecked.\u003C\u002Fstrong> Python matches by name at the call site; Rust does\nnot. Chapter 21.\u003C\u002Fp>\n\u003Cp>\u003Ccode>BLOCK_SIZE\u003C\u002Fcode> is a Rust constant now, so \u003Ccode>next_power_of_2\u003C\u002Fcode> happens on the host\nbefore you pick which pre-built kernel to use — you cannot compute it per launch\nwithout compiling a new kernel.\u003C\u002Fp>\n\u003Ch2 id=\"what-the-port-gained\">What the port gained\u003C\u002Fh2>\n\u003Cp>Four errors that Python would have found at run time, or not at all:\u003C\u002Fp>\n\u003Ctable>\n\u003Cthead>\n\u003Ctr>\n\u003Cth>Mistake\u003C\u002Fth>\n\u003Cth>Python\u003C\u002Fth>\n\u003Cth>Rust\u003C\u002Fth>\n\u003C\u002Ftr>\n\u003C\u002Fthead>\n\u003Ctbody>\n\u003Ctr>\n\u003Ctd>\u003Ccode>x\u003C\u002Fcode> is an integer tensor, \u003Ccode>exp\u003C\u002Fcode> undefined\u003C\u002Ftd>\n\u003Ctd>Runtime error on a GPU\u003C\u002Ftd>\n\u003Ctd>\u003Ccode>D: Float\u003C\u002Fcode> fails to compile\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>Mask built from the wrong tensor\u003C\u002Ftd>\n\u003Ctd>Wrong numbers\u003C\u002Ftd>\n\u003Ctd>Type error: not a \u003Ccode>BoolTensor\u003C\u002Fcode>\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>Storing \u003Ccode>f32\u003C\u002Fcode> into an \u003Ccode>f16\u003C\u002Fcode> buffer\u003C\u002Ftd>\n\u003Ctd>Silent\u003C\u002Ftd>\n\u003Ctd>Type error\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd>Forgetting \u003Ccode>other=\u003C\u002Fcode> before a max\u003C\u002Ftd>\n\u003Ctd>Wrong numbers, non-deterministic\u003C\u002Ftd>\n\u003Ctd>Still silent. Chapter 10\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003C\u002Ftbody>\n\u003C\u002Ftable>\n\u003Cp>Three out of four. The last is a real limitation: nothing knows that a load\nfeeding a reduction needs an identity fill.\u003C\u002Fp>\n\u003Ch2 id=\"what-it-cost\">What it cost\u003C\u002Fh2>\n\u003Cul>\n\u003Cli>\u003Cstrong>Three \u003Ccode>where\u003C\u002Fcode> clauses\u003C\u002Fstrong>, in every kernel, identical.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>Six \u003Ccode>None\u003C\u002Fcode>s per load\u003C\u002Fstrong>, four per store.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>A compile step you now manage\u003C\u002Fstrong> rather than a decorator.\u003C\u002Fli>\n\u003Cli>\u003Cstrong>No autotuner.\u003C\u002Fstrong> Python would have swept block sizes for you. Chapter 15.\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Ch2 id=\"a-checklist\">A checklist\u003C\u002Fh2>\n\u003Cp>For your own ports:\u003C\u002Fp>\n\u003Col>\n\u003Cli>\u003Ccode>tl.constexpr\u003C\u002Fcode> → const generic. Everything else → a normal argument.\u003C\u002Fli>\n\u003Cli>Pick the tightest dtype bound: \u003Ccode>Float\u003C\u002Fcode> if you use \u003Ccode>exp\u003C\u002Fcode>\u002F\u003Ccode>log\u003C\u002Fcode>\u002F\u003Ccode>sqrt\u003C\u002Fcode>, \u003Ccode>Int\u003C\u002Fcode>\nfor bitwise, \u003Ccode>Num\u003C\u002Fcode> otherwise.\u003C\u002Fli>\n\u003Cli>Copy the three \u003Ccode>where\u003C\u002Fcode> clauses.\u003C\u002Fli>\n\u003Cli>\u003Ccode>ptr + offsets\u003C\u002Fcode> → \u003Ccode>ptr.add_offsets(offsets)\u003C\u002Fcode>.\u003C\u002Fli>\n\u003Cli>\u003Ccode><\u003C\u002Fcode> → \u003Ccode>.lt()\u003C\u002Fcode>, and friends.\u003C\u002Fli>\n\u003Cli>\u003Ccode>mask=\u003C\u002Fcode>\u002F\u003Ccode>other=\u003C\u002Fcode> → the second and third arguments; pad the rest with \u003Ccode>None\u003C\u002Fcode>\nand \u003Ccode>false\u003C\u002Fcode>.\u003C\u002Fli>\n\u003Cli>\u003Ccode>axis=n\u003C\u002Fcode> → \u003Ccode>Some(n)\u003C\u002Fcode>; keep \u003Ccode>keep_dims: true\u003C\u002Fcode> unless you know otherwise.\u003C\u002Fli>\n\u003Cli>Fill masked lanes with the reduction’s identity.\u003C\u002Fli>\n\u003Cli>Check the launch tuple against the signature, by eye, twice.\u003C\u002Fli>\n\u003Cli>Compile it and read the MLIR. Chapter 9.\u003C\u002Fli>\n\u003C\u002Fol>\n",[12,16,19,22,25,28,31,34,37,40],{"id":13,"text":14,"level":15},"the-python-original","The Python original",2,{"id":17,"text":18,"level":15},"step-1--the-signature","Step 1 — The signature",{"id":20,"text":21,"level":15},"step-2--indices","Step 2 — Indices",{"id":23,"text":24,"level":15},"step-3--the-load","Step 3 — The load",{"id":26,"text":27,"level":15},"step-4--the-arithmetic","Step 4 — The arithmetic",{"id":29,"text":30,"level":15},"step-5--the-store","Step 5 — The store",{"id":32,"text":33,"level":15},"step-6--the-launch","Step 6 — The launch",{"id":35,"text":36,"level":15},"what-the-port-gained","What the port gained",{"id":38,"text":39,"level":15},"what-it-cost","What it cost",{"id":41,"text":42,"level":15},"a-checklist","A checklist",false,{"title":45,"titleHtml":45,"route":46},"Glossary","\u002Fkernels\u002Freference\u002Fglossary",null,1786271830297]