{{ env.wgsl.resourceDeclarations }}

const HIDDEN: u32 = {{ hiddenSize }}u;
const EPSILON: f32 = {{ epsilon }};
const WG: u32 = {{ workgroupSize }}u;

{% if scaleRank > 0 %}
const X_RANK: u32 = {{ xRank }}u;
const SCALE_RANK: u32 = {{ scaleRank }}u;
const X_SHAPE: array<u32, {{ xRank }}> = array<u32, {{ xRank }}>({% for d in xShape %}{{ d }}u{% if not loop.last %}, {% endif %}{% endfor %});
const SCALE_SHAPE: array<u32, {{ scaleRank }}> = array<u32, {{ scaleRank }}>({% for d in scaleShape %}{{ d }}u{% if not loop.last %}, {% endif %}{% endfor %});

fn x_stride(axis: u32) -> u32 {
  var stride = 1u;
  for (var i = axis + 1u; i < X_RANK; i += 1u) {
    stride *= X_SHAPE[i];
  }
  return stride;
}

fn scale_stride(axis: u32) -> u32 {
  var stride = 1u;
  for (var i = axis + 1u; i < SCALE_RANK; i += 1u) {
    stride *= SCALE_SHAPE[i];
  }
  return stride;
}

{% endif %}
fn scale_offset({% if scaleRank > 0 %}out_index: u32{% endif %}) -> u32 {
{% if scaleRank == 0 %}
  return 0u;
{% else %}
  var rem = out_index;
  var offset = 0u;
  for (var axis = 0u; axis < X_RANK; axis += 1u) {
    let stride = x_stride(axis);
    let coord = rem / stride;
    rem %= stride;
    let scale_axis = i32(axis) - i32(X_RANK - SCALE_RANK);
    if (scale_axis >= 0) {
      let s_axis = u32(scale_axis);
      if (SCALE_SHAPE[s_axis] != 1u) {
        offset += coord * scale_stride(s_axis);
      }
    }
  }
  return offset;
{% endif %}
}

var<workgroup> partial: array<f32, WG>;
{% macro wgsl_tree_fold_stmt(a, op, idx, svar) %}
{% if op == "max" or op == "min" %}
{{ a }}[{{ idx }}] = {{ op }}({{ a }}[{{ idx }}], {{ a }}[{{ idx }} + {{ svar }}]);{% else %}
{{ a }}[{{ idx }}] = {{ a }}[{{ idx }}] {{ "*" if op == "prod" else "+" }} {{ a }}[{{ idx }} + {{ svar }}];{% endif %}{% endmacro %}
{% macro wgsl_tree_fold(arrays, op="add", idx="lid", wg="WORKGROUP_SIZE", svar="stride", typed=false, form="tail", breakInline=false, bodyInline=false, barrierFirst=false, reuse=false) %}
  var {{ svar }}{{ ": u32 " if typed else " " }}= {{ wg }} / 2u;
  loop {
    if ({{ svar }} == 0u) {
      break;
    }
    if ({{ idx }} < {{ svar }}) {
{% for a in arrays %}
      {{ wgsl_tree_fold_stmt(a, op, idx, svar) }}
{% endfor %}
    }
    {{ svar }} = {{ svar }} / 2u;
    workgroupBarrier();
  }{% endmacro %}
// Reusing partial after this reduction requires a barrier between the read of
// partial[0] and the next write, or the next round can race the prior readers.
fn reduce_sum(value: f32, tid: u32) -> f32 {
  partial[tid] = value;
  workgroupBarrier();
{{ wgsl_tree_fold(["partial"], idx="tid", wg="WG", form="head") }}
  return partial[0];
}

@compute @workgroup_size(WG, 1, 1)
fn main(@builtin(workgroup_id) wg: vec3<u32>, @builtin(local_invocation_id) lid: vec3<u32>) {
  let row = wg.x + wg.y * params.rowStride;
  if (row >= params.rows) {
    return;
  }
  let tid = lid.x;
  let base = row * HIDDEN;

  var local_sq = 0.0;
  for (var d = tid; d < HIDDEN; d = d + WG) {
    let value = f32(x[base + d]);
    local_sq = local_sq + value * value;
  }
  let inv = inverseSqrt(reduce_sum(local_sq, tid) / f32(HIDDEN) + EPSILON);
{% if writeStats %}
  if (tid == 0u) {
    inv_std_out[row] = inv;
  }

{% endif %}
  for (var d = tid; d < HIDDEN; d = d + WG) {
    let index = base + d;
    let value = f32(x[index]) * inv * f32(scale[scale_offset({% if scaleRank > 0 %}index{% endif %})]);
    y[base + d] = {{ scalar }}(value);
  }
}