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The MLX runner is the only Go inference runner left and is no longer experimental, so its packages leave x/. The bindings become a top-level mlx package beside the carried patches in mlx/compat, mirroring how llama/ holds the llama.cpp integration, and the runner becomes mlxrunner with the architectures nested under the package they implement. Subpackages move with their parent unless listed. x/mlxrunner/mlx mlx x/internal/mlxthread mlx/mlxthread x/internal/mlxthreadtest mlx/mlxthread/mlxthreadtest x/internal/mlxtest mlx/mlxtest x/quant mlx/quant mlx/compat/*.patch mlx/compat/mlx-c (MLX patches go in mlx/compat/mlx) x/mlxrunner mlxrunner x/models/nn mlxrunner/nn x/models/<arch> mlxrunner/model/<arch> x/mlxrunner/imports.go mlxrunner/model/architectures (new package) x/create create x/safetensors fs/safetensors x/tokenizer mlxrunner/tokenizer Every package keeps its name, so the Go changes are the import path rewrites the moves force, and the CMake, Dockerfile, CI cache keys, drift check and Darwin payload script follow the new paths. Four edits are not paths: the runner's blank architecture imports become the package mlxrunner/model/architectures, so the list to extend for a new model sits beside the architecture directories; a depguard rule keeps the two test harnesses out of non-test code, as the x/internal placement used to; the CI change filter's two entries for the long-deleted x/imagegen/mlx now name the bindings' CMake project and the carried patches, so a change to either builds the payload; and the tokenizer parity test reads its fixtures from its own testdata instead of walking out of x/. x/server and x/imagegen/manifest stay for the next two commits.
241 lines
8.6 KiB
Go
241 lines
8.6 KiB
Go
package mlx
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import (
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"fmt"
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"math"
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"testing"
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"github.com/ollama/ollama/mlx/mlxthread/mlxthreadtest"
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)
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type gatedDeltaTestGeometry struct {
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Hk, Dk, Hv, Dv int
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}
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func (g gatedDeltaTestGeometry) packedDim() int { return 2*g.Hk*g.Dk + g.Hv*g.Dv }
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type gatedDeltaTestInputs struct {
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packed, ba, dtBias, aExp, state *Array
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}
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func gatedDeltaTestInputs36(g gatedDeltaTestGeometry, T int) gatedDeltaTestInputs {
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return gatedDeltaTestInputs{
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packed: patternArray(DTypeBFloat16, []int{1, T, g.packedDim()}, 0.01, 0.003, 37, 257),
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ba: patternArray(DTypeBFloat16, []int{1, T, 2 * g.Hv}, 0, 0.4, 13, 37),
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dtBias: patternArray(DTypeBFloat16, []int{g.Hv}, -2.5, 0.08, 5, 29),
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aExp: patternArray(DTypeFloat32, []int{g.Hv}, 0.12, 0.002, 3, 19),
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state: patternArray(DTypeFloat32, []int{1, g.Hv, g.Dv, g.Dk}, 0, 0.0001, 17, 101),
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}
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}
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// gatedDeltaReference runs the graph implementation the fused kernels fall
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// back to; the test pins the kernels against it bit-for-bit.
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func gatedDeltaReference(in gatedDeltaTestInputs, captureAll bool) (y, nextState *Array, interior []*Array) {
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return gatedDeltaGraph(in.packed, in.ba, in.dtBias, in.aExp, in.state, captureAll)
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}
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// Exactness is per compiler pair: the metallib and the runtime JIT round
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// metal::exp a float ulp apart, which after bf16 rounding leaves rare
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// differing inputs (beta sigmoid at -6.84375); the lattice here avoids them.
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func TestGatedDeltaMatchesGraph(t *testing.T) {
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withMLXThread(t, func(t *mlxthreadtest.T) {
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testGatedDeltaMatchesGraph(t)
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})
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}
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func testGatedDeltaMatchesGraph(t *mlxthreadtest.T) {
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geometries := []gatedDeltaTestGeometry{
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{Hk: 16, Dk: 128, Hv: 32, Dv: 128},
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{Hk: 4, Dk: 64, Hv: 8, Dv: 32},
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}
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for _, g := range geometries {
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for T := 1; T <= gatedDeltaMaxTokens; T++ {
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for _, B := range []int{1, 3} {
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for _, captureAll := range []bool{false, true} {
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name := fmt.Sprintf("hk%d_dk%d_T%d_B%d_all%v", g.Hk, g.Dk, T, B, captureAll)
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in := batchGatedDeltaRows(gatedDeltaTestInputs36(g, T), B)
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refY, refState, refInterior := gatedDeltaReference(in, captureAll)
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y, state, interior := GatedDelta(in.packed, in.ba, in.dtBias, in.aExp, in.state, nil, captureAll)
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if err := requireExact("y", y, refY); err != nil {
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t.Fatalf("%s: %v", name, err)
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}
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if err := requireExact("state", state, refState); err != nil {
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t.Fatalf("%s: %v", name, err)
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}
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if captureAll && len(interior) != len(refInterior) {
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t.Fatalf("%s: interior count = %d, want %d", name, len(interior), len(refInterior))
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}
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for i := range interior {
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if err := requireExact(fmt.Sprintf("interior[%d]", i), interior[i], refInterior[i]); err != nil {
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t.Fatalf("%s: %v", name, err)
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}
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}
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}
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}
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}
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}
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}
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func TestGatedDeltaGraphRouting(t *testing.T) {
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withMLXThread(t, func(t *mlxthreadtest.T) {
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testGatedDeltaGraphRouting(t)
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})
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}
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// Contract misses — T beyond the kernel cap and a float32 packed input —
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// run the same step as graph ops.
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func testGatedDeltaGraphRouting(t *mlxthreadtest.T) {
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g := gatedDeltaTestGeometry{Hk: 4, Dk: 64, Hv: 8, Dv: 32}
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check := func(name string, in gatedDeltaTestInputs, captureAll bool) {
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y, end, interior := GatedDelta(in.packed, in.ba, in.dtBias, in.aExp, in.state, nil, captureAll)
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refY, refEnd, refInterior := gatedDeltaReference(in, captureAll)
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if err := requireExact("y", y, refY); err != nil {
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t.Fatalf("%s: %v", name, err)
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}
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if err := requireExact("state", end, refEnd); err != nil {
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t.Fatalf("%s: %v", name, err)
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}
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if len(interior) != len(refInterior) {
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t.Fatalf("%s: interior count = %d, want %d", name, len(interior), len(refInterior))
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}
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}
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check("tooLong", gatedDeltaTestInputs36(g, gatedDeltaMaxTokens+1), true)
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f32 := gatedDeltaTestInputs36(g, 2)
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f32.packed = f32.packed.AsType(DTypeFloat32)
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check("float32", f32, false)
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}
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// batchGatedDeltaRows widens a single-row input to B rows with distinct
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// per-row contents.
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func batchGatedDeltaRows(row gatedDeltaTestInputs, B int) gatedDeltaTestInputs {
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if B == 1 {
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return row
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}
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packed := make([]*Array, B)
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ba := make([]*Array, B)
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state := make([]*Array, B)
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for i := range B {
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r := row
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if i > 0 {
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r = scaledGatedDeltaRow(row, 1-0.3*float32(i))
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}
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packed[i], ba[i], state[i] = r.packed, r.ba, r.state
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}
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return gatedDeltaTestInputs{
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packed: Concatenate(packed, 0),
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ba: Concatenate(ba, 0),
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dtBias: row.dtBias,
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aExp: row.aExp,
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state: Concatenate(state, 0),
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}
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}
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func scaledGatedDeltaRow(base gatedDeltaTestInputs, scale float32) gatedDeltaTestInputs {
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return gatedDeltaTestInputs{
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packed: MulScalar(base.packed, scale),
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ba: MulScalar(base.ba, -scale),
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dtBias: base.dtBias,
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aExp: base.aExp,
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state: MulScalar(base.state, scale),
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}
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}
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func TestGatedDeltaBatchedRows(t *testing.T) {
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withMLXThread(t, func(t *mlxthreadtest.T) {
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testGatedDeltaBatchedRows(t)
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})
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}
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// Each batched row must match its own single-row launch bit-for-bit.
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func testGatedDeltaBatchedRows(t *mlxthreadtest.T) {
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g := gatedDeltaTestGeometry{Hk: 4, Dk: 64, Hv: 8, Dv: 32}
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for _, T := range []int{1, 5, 11} {
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rows := []gatedDeltaTestInputs{gatedDeltaTestInputs36(g, T)}
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rows = append(rows, scaledGatedDeltaRow(rows[0], 0.7), scaledGatedDeltaRow(rows[0], 0.4))
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packed := Concatenate([]*Array{rows[0].packed, rows[1].packed, rows[2].packed}, 0)
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ba := Concatenate([]*Array{rows[0].ba, rows[1].ba, rows[2].ba}, 0)
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state := Concatenate([]*Array{rows[0].state, rows[1].state, rows[2].state}, 0)
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y, end, _ := GatedDelta(packed, ba, rows[0].dtBias, rows[0].aExp, state, nil, false)
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for i, row := range rows {
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refY, refEnd, _ := GatedDelta(row.packed, row.ba, row.dtBias, row.aExp, row.state, nil, false)
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gotY := SliceStartStop(y,
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[]int32{int32(i), 0, 0, 0},
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[]int32{int32(i) + 1, int32(T), int32(g.Hv), int32(g.Dv)})
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gotEnd := SliceStartStop(end,
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[]int32{int32(i), 0, 0, 0},
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[]int32{int32(i) + 1, int32(g.Hv), int32(g.Dv), int32(g.Dk)})
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if err := requireExact("y", gotY, refY); err != nil {
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t.Fatalf("T=%d row %d: %v", T, i, err)
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}
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if err := requireExact("state", gotEnd, refEnd); err != nil {
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t.Fatalf("T=%d row %d: %v", T, i, err)
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}
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}
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}
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}
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func TestGatedDeltaRaggedRows(t *testing.T) {
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withMLXThread(t, func(t *mlxthreadtest.T) {
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testGatedDeltaRaggedRows(t)
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})
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}
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// A padded row neutralized the way the nn seam does it — zeroed conv rows,
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// ba tail poisoned to -inf — runs identity steps with zero output there: its
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// full output and final state must match a launch of only its real tokens
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// with zeros appended, while the full-length row is unaffected.
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func testGatedDeltaRaggedRows(t *mlxthreadtest.T) {
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g := gatedDeltaTestGeometry{Hk: 4, Dk: 64, Hv: 8, Dv: 32}
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const T, realLen = 6, 4
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row0 := gatedDeltaTestInputs36(g, T)
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row1 := scaledGatedDeltaRow(row0, 0.7)
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pad := make([]float32, (T-realLen)*2*g.Hv)
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negInf := float32(math.Inf(-1))
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for i := range pad {
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pad[i] = negInf
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}
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row1BA := Concatenate([]*Array{
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SliceStartStop(row1.ba, []int32{0, 0, 0}, []int32{1, realLen, int32(2 * g.Hv)}),
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FromValues(pad, 1, T-realLen, 2*g.Hv).AsType(DTypeBFloat16),
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}, 1)
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row1Packed := Concatenate([]*Array{
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SliceStartStop(row1.packed, []int32{0, 0, 0}, []int32{1, realLen, int32(g.packedDim())}),
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Zeros(DTypeBFloat16, 1, T-realLen, g.packedDim()),
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}, 1)
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packed := Concatenate([]*Array{row0.packed, row1Packed}, 0)
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ba := Concatenate([]*Array{row0.ba, row1BA}, 0)
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state := Concatenate([]*Array{row0.state, row1.state}, 0)
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y, end, _ := GatedDelta(packed, ba, row0.dtBias, row0.aExp, state, nil, false)
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ref0Y, ref0End, _ := GatedDelta(row0.packed, row0.ba, row0.dtBias, row0.aExp, row0.state, nil, false)
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got0Y := SliceStartStop(y, []int32{0, 0, 0, 0}, []int32{1, T, int32(g.Hv), int32(g.Dv)})
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got0End := SliceStartStop(end, []int32{0, 0, 0, 0}, []int32{1, int32(g.Hv), int32(g.Dv), int32(g.Dk)})
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if err := requireExact("row0 y", got0Y, ref0Y); err != nil {
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t.Fatal(err)
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}
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if err := requireExact("row0 state", got0End, ref0End); err != nil {
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t.Fatal(err)
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}
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prefixPacked := SliceStartStop(row1.packed, []int32{0, 0, 0}, []int32{1, realLen, int32(g.packedDim())})
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prefixBA := SliceStartStop(row1.ba, []int32{0, 0, 0}, []int32{1, realLen, int32(2 * g.Hv)})
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ref1Y, ref1End, _ := GatedDelta(prefixPacked, prefixBA, row1.dtBias, row1.aExp, row1.state, nil, false)
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want1Y := Concatenate([]*Array{ref1Y, Zeros(DTypeBFloat16, 1, T-realLen, g.Hv, g.Dv)}, 1)
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got1Y := SliceStartStop(y, []int32{1, 0, 0, 0}, []int32{2, T, int32(g.Hv), int32(g.Dv)})
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got1End := SliceStartStop(end, []int32{1, 0, 0, 0}, []int32{2, int32(g.Hv), int32(g.Dv), int32(g.Dk)})
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if err := requireExact("row1 y", got1Y, want1Y); err != nil {
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t.Fatal(err)
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}
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if err := requireExact("row1 state", got1End, ref1End); err != nil {
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t.Fatal(err)
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}
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}
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