update convert test to check result data

convert/convert_test.go

-//go:build slow
-
 package convert
 
 import (
+	"crypto/sha256"
+	"encoding/json"
+	"flag"
+	"fmt"
+	"io"
+	"log/slog"
+	"math"
 	"os"
 	"path/filepath"
+	"slices"
 	"testing"
 
 	"github.com/ollama/ollama/llm"
+	"golang.org/x/exp/maps"
 )
 
-func convertFull(t *testing.T, p string) (llm.KV, llm.Tensors) {
+func convertFull(t *testing.T, d string) (*os.File, llm.KV, llm.Tensors) {
 	t.Helper()
 
-	mf, err := GetModelFormat(p)
+	mf, err := GetModelFormat(d)
 	if err != nil {
 		t.Fatal(err)
 	}
 
-	params, err := mf.GetParams(p)
+	params, err := mf.GetParams(d)
 	if err != nil {
 		t.Fatal(err)
 	}
 
-	arch, err := mf.GetModelArch("", p, params)
+	arch, err := mf.GetModelArch("", d, params)
 	if err != nil {
 		t.Fatal(err)
 	}
@@ -50,53 +57,91 @@ func convertFull(t *testing.T, p string) (llm.KV, llm.Tensors) {
 	if err != nil {
 		t.Fatal(err)
 	}
-	defer r.Close()
+	t.Cleanup(func() { r.Close() })
 
-	m, _, err := llm.DecodeGGML(r)
+	m, _, err := llm.DecodeGGML(r, math.MaxInt)
 	if err != nil {
 		t.Fatal(err)
 	}
 
-	return m.KV(), m.Tensors()
+	if _, err := r.Seek(0, io.SeekStart); err != nil {
+		t.Fatal(err)
+	}
+
+	return r, m.KV(), m.Tensors()
+}
+
+func TestMain(m *testing.M) {
+	var level slog.Level
+	flag.TextVar(&level, "level", slog.LevelInfo, "log level")
+	flag.Parse()
+	slog.SetLogLoggerLevel(level)
+	os.Exit(m.Run())
 }
 
 func TestConvertFull(t *testing.T) {
-	cases := []struct {
-		path    string
-		arch    string
-		tensors int
-		layers  int
-	}{
-		{"Meta-Llama-3-8B-Instruct", "llama", 291, 35},
-		{"Mistral-7B-Instruct-v0.2", "llama", 291, 35},
-		{"Mixtral-8x7B-Instruct-v0.1", "llama", 291, 35},
-		{"gemma-2b-it", "gemma", 164, 20},
+	cases := []string{
+		"Meta-Llama-3-8B-Instruct",
+		"Mistral-7B-Instruct-v0.2",
+		"Mixtral-8x7B-Instruct-v0.1",
+		"gemma-2b-it",
 	}
 
-	for _, tt := range cases {
-		t.Run(tt.path, func(t *testing.T) {
-			p := filepath.Join("testdata", tt.path)
-			if _, err := os.Stat(p); err != nil {
+	for i := range cases {
+		tt := cases[i]
+		t.Run(tt, func(t *testing.T) {
+			t.Parallel()
+
+			p := filepath.Join("testdata", tt)
+			if testing.Short() {
+				t.Skip("skipping in short mode")
+			} else if _, err := os.Stat(p); err != nil {
 				t.Skipf("%s not found", p)
 			}
 
-			kv, tensors := convertFull(t, p)
+			f, kv, tensors := convertFull(t, p)
+			actual := make(map[string]string)
+			for k, v := range kv {
+				if s, ok := v.(json.Marshaler); !ok {
+					actual[k] = fmt.Sprintf("%v", v)
+				} else {
+					bts, err := json.Marshal(s)
+					if err != nil {
+						t.Fatal(err)
+					}
+
+					actual[k] = fmt.Sprintf("%x", sha256.Sum256(bts))
+				}
+			}
+
+			for _, tensor := range tensors.Items {
+				sha256sum := sha256.New()
+				sr := io.NewSectionReader(f, int64(tensors.Offset+tensor.Offset), int64(tensor.Size()))
+				if _, err := io.Copy(sha256sum, sr); err != nil {
+					t.Fatal(err)
+				}
 
-			if kv.Architecture() != tt.arch {
-				t.Fatalf("expected llama, got %s", kv.Architecture())
+				actual[tensor.Name] = fmt.Sprintf("%x", sha256sum.Sum(nil))
 			}
 
-			if kv.FileType().String() != "F16" {
-				t.Fatalf("expected F16, got %s", kv.FileType())
+			expectFile, err := os.Open(filepath.Join("testdata", fmt.Sprintf("%s.json", tt)))
+			if err != nil {
+				t.Fatal(err)
 			}
 
-			if len(tensors) != tt.tensors {
-				t.Fatalf("expected %d tensors, got %d", tt.tensors, len(tensors))
+			var expect map[string]string
+			if err := json.NewDecoder(expectFile).Decode(&expect); err != nil {
+				t.Fatal(err)
 			}
 
-			layers := tensors.Layers()
-			if len(layers) != tt.layers {
-				t.Fatalf("expected %d layers, got %d", tt.layers, len(layers))
+			keys := maps.Keys(expect)
+			slices.Sort(keys)
+			for _, k := range keys {
+				if v, ok := actual[k]; !ok {
+					t.Errorf("missing %s", k)
+				} else if v != expect[k] {
+					t.Errorf("unexpected %s: want %s, got %s", k, expect[k], v)
+				}
 			}
 		})
 	}

convert/testdata/Mixtral-8x7B-Instruct-v0.1.json

+{}

convert/testdata/gemma-2b-it.json

+{
+  "general.architecture": "gemma",
+  "general.file_type": "1",
+  "general.quantization_version": "2",
+  "gemma.block_count": "18",
+  "gemma.context_length": "8192",
+  "gemma.embedding_length": "2048",
+  "gemma.feed_forward_length": "16384",
+  "gemma.attention.head_count": "8",
+  "gemma.attention.head_count_kv": "1",
+  "gemma.attention.key_length": "256",
+  "gemma.attention.value_length": "256",
+  "gemma.attention.layer_norm_rms_epsilon": "1e-06",
+  "tokenizer.ggml.model": "llama",
+  "tokenizer.ggml.add_bos_token": "true",
+  "tokenizer.ggml.add_eos_token": "false",
+  "tokenizer.ggml.bos_token_id": "2",
+  "tokenizer.ggml.eos_token_id": "1",
+  "tokenizer.ggml.padding_token_id": "0",
+  "tokenizer.ggml.unknown_token_id": "3",
+  "tokenizer.ggml.scores": "0872465d173867d755d3ee728f882b9dc2057a0bfd596fe1e3d131522f1250d8",
+  "tokenizer.ggml.token_type": "485e40bf3d715a4764818fc097d6a2a41db872d82ee714bc500872a3437ff48d",
+  "tokenizer.ggml.tokens": "c6e66de1841f04de8b8d236d461ab720a4c9b9b5414dc293a09c6e10eab45fda",
+  "token_embd.weight": "17b87ab2c01c80657855a5413d0457b4a041afaeda0cc785080e44e2f04acf07",
+  "blk.0.attn_k.weight": "28ac0da05754ad2714ae95da28a5ad191192140b30b8fd22d108d4700c9d989f",
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+  "blk.10.ffn_up.weight": "bffbba605922e972dc47dda88a0b4659aa52236c76e5fe861a949e6d9a367492",
+  "blk.11.attn_k.weight": "9f31c63d66cd32c29b1eb8bb829d0c8525ce2ae936e0eefdaab6335a2d12a3df",
+  "blk.11.attn_norm.weight": "0bde1a266d8b2e8f202bb7e2e88b19147ca83021901f6d3cae77a4df5548c754",
+  "blk.11.attn_output.weight": "e10725c7cf746ed4a7e472cf7aea6cb564e5db6a1d5197adc980d650a387ccea",
+  "blk.11.attn_q.weight": "05ee758a7d065802630f8c65dca424364c1c8825e389aa33f9405c45e8a50cce",
+  "blk.11.attn_v.weight": "0c3ae7090f11775d24c51120db6e305db6aff706493e7ee123dcab74485ba789",
+  "blk.11.ffn_down.weight": "7ba40b8e12c09c5fb2006b77a771cb01ce894e88a3b3e1877f927a5b89c91709",
+  "blk.11.ffn_gate.weight": "db76388a023b98097972d354ba1c6a5e26efdeb1c596b9c28bf2cd8f6596975e",
+  "blk.11.ffn_norm.weight": "a38c3ae1b89a68ddc7b72c99c5b28be7fe3787c4fad9904d0c43d64eaf00c474",
+  "blk.11.ffn_up.weight": "13c8142f9cf1eddc658babf978daf3515c4ccc45f849f3e7e3930aa18a8480a0",
+  "blk.12.attn_k.weight": "f03241c36ac87cb57429a2ef22186b8d7d0b590a8b173beb01fa13d93772f3b1",
+  "blk.12.attn_norm.weight": "4568f654e6d65104d586e7c16ba960c83428698ce103022b7e0be15e2884e13b",
+  "blk.12.attn_output.weight": "04867603f82f91e41306e09b33ecda0104b3ee4834061f2c0bbdc8da33c72509",
+  "blk.12.attn_q.weight": "70fe04b9a8e08b6100cc8d6b58bf4cbbad15ca1de82d63baca5d352ba6c4cbae",
+  "blk.12.attn_v.weight": "15cb28db61a86c98687991d7e611bc92a1fcc6007f3432149cfb5fe518a4f65e",
+  "blk.12.ffn_down.weight": "6d10c790a4e3dc44c2dc36d96251ae97cdf30a4fa04d4c43e31bfbd038e6a7b7",
+  "blk.12.ffn_gate.weight": "3462a2d8f6b4743b25e24da51b90018ac2858d05ac7e582bcb69063cfdac1104",
+  "blk.12.ffn_norm.weight": "1f96392c1faa34e34ae5dea55a6a86c5aa4c79758952075d53d28de89dd88456",
+  "blk.12.ffn_up.weight": "d22eacc612a7411953d948483c5fb201e11722955ee0754da866e7bec578ac6d",
+  "blk.13.attn_k.weight": "5864977e6b733ea942647d6feed5c76156c48c200649c22e4e11b9e5860e57f3",
+  "blk.13.attn_norm.weight": "87e053535144723db4145aa5402acc54331b7696752d852bb9fc542ff33f0fb5",
+  "blk.13.attn_output.weight": "078145f5ad83f8b14f97a869346f7fd1583b24d1e3edadaa95d3da4242973f8f",
+  "blk.13.attn_q.weight": "3b8caf35504cbc4d1a7dd6e011a95760703b7f71e2218b030b1254f811362dd7",
+  "blk.13.attn_v.weight": "4fdf8365a603e043e5b40c4a21c84ac167f9be62794178f9d8a608dfe5653bf9",
+  "blk.13.ffn_down.weight": "a07d3abbfcacf48ba028df2cab895be32cc15022d23389a745286e79c1b1d1fd",
+  "blk.13.ffn_gate.weight": "1d2ab39666aa2909acc96787432a3ed13b19d25170f74665fadff9b17bbaffb1",
+  "blk.13.ffn_norm.weight": "4f2e809fda5f3eadf52578ee50e0ba36e53be91e55dce418c12dfe595f5f18e7",
+  "blk.13.ffn_up.weight": "8783d2720c2c37ca176a5801e0b3ef1f9cc9cf3ef1cd37af423aaf6b2a27e2bd",
+  "blk.14.attn_k.weight": "ce9428e2b55d43ae0c6690dbd56182f99adc427694ba8236b405cc8ea5035e86",
+  "blk.14.attn_norm.weight": "6abb35f9db8251d6ae954bda147c6ada2371b0574d11702e828f3c6ac99b7cc0",
+  "blk.14.attn_output.weight": "fe3880916d0ceb5bff672c88bbefb7060a545be609bf049beb2024b38221836d",
+  "blk.14.attn_q.weight": "7c8ad81be6f4a350931fd108b5f7c9e366e8c26ef62d1d85ffef5dca8fd893f8",
+  "blk.14.attn_v.weight": "e4bdedffacbebe38567a0734dfd67db90e911d9a9669fcde9a7c4ad8a0066c52",
+  "blk.14.ffn_down.weight": "ef6694dff1e05820aac0cd2b22f39ac7788b4967afc9250775575554c66aab2c",
+  "blk.14.ffn_gate.weight": "db63c4179e2db704bc505e2b4696e055b593e295a1b7c4c586fc793bdd5aab19",
+  "blk.14.ffn_norm.weight": "2796a62d832a9710148f95d533320492a33e712b2e5218659c548705bd11684d",
+  "blk.14.ffn_up.weight": "3f78c78d8c2d54df45f799d4ff902316628af296834afe4ceed63d4a324ff03e",
+  "blk.15.attn_k.weight": "6e810ee3859e07695645ee0c9a5efc7962668984a5f0a9325f47e462743b447c",
+  "blk.15.attn_norm.weight": "0956b576ae96db0b28cb09f761f801cfd9281432284664f0fe181c8d9c55d1ec",
+  "blk.15.attn_output.weight": "03a17f7e94208177aace5cc41b7f54670ba57873b7274ff6e23caf58cce110ca",
+  "blk.15.attn_q.weight": "b8edafe7d2216a6f8b4ae4905a906475490e6ea418f6e1d3cec563dbdc6fab91",
+  "blk.15.attn_v.weight": "f8ae8cae0f4cfa34a459824eba57350c3c248104ba5607e7d9dc7d7c39aaf4a6",
+  "blk.15.ffn_down.weight": "8d02eb439da852246d2ca67e9b7b6de0b090b80744355e64728a23e41926505b",
+  "blk.15.ffn_gate.weight": "ed5bf361c67db8731f186b775826f21c33bdb521111fd2d922539719a770239f",
+  "blk.15.ffn_norm.weight": "5942ca3c73209ac9a0c8bfd9b4aab7f7be7aee9aa12d9c35833493b44af76767",
+  "blk.15.ffn_up.weight": "f4bebf4ad99ec5f911327dec347be6c595814885309c7bc5647ce28c7f4d1cf5",
+  "blk.16.attn_k.weight": "756a534c19364448e0958b8948fe33891c6ccda0fbb4dfa2024e1f532a87804b",
+  "blk.16.attn_norm.weight": "386b7b9e4e6509f6af9c022d942b6c6c6cc136aeed8751ecb037c74d7c4bfb93",
+  "blk.16.attn_output.weight": "3ba1a766a25830b84d7c22178203635f9c5624caad290bc5e5d73da5d5e7a2ec",
+  "blk.16.attn_q.weight": "d39b0c91e1fda7685d50a0f7cc8d18c44b5bdc90a142c7fda0bc329cca1afa74",
+  "blk.16.attn_v.weight": "98b33fcb0ee3483cff1b06ecb44d7b7ffb4d34c268248e4d73dfdf82b2065b2f",
+  "blk.16.ffn_down.weight": "14006f5e4acb2f9416271ae562e299359cd2585739c7fc77ccbca54495563948",
+  "blk.16.ffn_gate.weight": "12f8abae2d301d8f88bedb6af98b1daecc7b0b8d05148594f931f30958d77aca",
+  "blk.16.ffn_norm.weight": "129a15a046ee96d06de288bd43c80f77a6b0fb3a159c7367154c6e4aaf362672",
+  "blk.16.ffn_up.weight": "b4a5911a45f3871ef1d4efb7dc7108645a564b70f818eccf45beebef2e844ee9",
+  "blk.17.attn_k.weight": "5e1bfcff0146ebdde3817b656952892eb671e14e75afc92fa53f84f8eecbec4c",
+  "blk.17.attn_norm.weight": "60bc988fab7c4b29ee9de599df41a8de00caa94fcd74677da011fac82f60f465",
+  "blk.17.attn_output.weight": "ba49b40d6a0b5685f749c24b0edbed3adc44dbe13b5d5e5fa1e56169fc746555",
+  "blk.17.attn_q.weight": "82bb415d24efcd14d03ace03f907bb70db6a204c76a0bdd1892e0fba165db87d",
+  "blk.17.attn_v.weight": "73dbe54beb91a899884e275ea81ffc5187a20cb7d5b68d5c299b783096999d94",
+  "blk.17.ffn_down.weight": "7c086166241e0664f8963fd1ca4ed74c737abfb2525ec20f8435821ff50158f3",
+  "blk.17.ffn_gate.weight": "51a32f78244d42a539f619c5ce661db9e6cf41636280a826d439b5444edcd28c",
+  "blk.17.ffn_norm.weight": "c4bb247fccd1ecc84875028af63dd20aaf5cbd17eb94a9bc36679c09285dccab",
+  "blk.17.ffn_up.weight": "b5886182790bc6fbadd63de9bc4ffee416f3b69a66280d197ab8c18edf769abf",
+  "output_norm.weight": "481f3097d0a20412e35b3a739b1b958487bcd41ff67744baa3c9acbddd2ee4d4"
+}

llm/ggla.go

@@ -36,6 +36,8 @@ type ggla struct {
 
 	kv      KV
 	tensors []*Tensor
+
+	tensorOffset uint64
 }
 
 func newGGLA(container *containerGGLA) *ggla {
@@ -50,7 +52,10 @@ func (llm *ggla) KV() KV {
 }
 
 func (llm *ggla) Tensors() Tensors {
-	return llm.tensors
+	return Tensors{
+		Items:  llm.tensors,
+		Offset: llm.tensorOffset,
+	}
 }
 
 func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
@@ -66,6 +71,13 @@ func (llm *ggla) decode(rs io.ReadSeeker) (retErr error) {
 	}
 	llm.kv["alpha"] = alpha
 
+	offset, err := rs.Seek(0, io.SeekCurrent)
+	if err != nil {
+		return err
+	}
+
+	llm.tensorOffset = uint64(offset)
+
 	for {
 		var dims uint32
 		if err := binary.Read(rs, binary.LittleEndian, &dims); err != nil {

llm/ggml.go

@@ -112,11 +112,14 @@ func (kv KV) ChatTemplate() string {
 	return s
 }
 
-type Tensors []*Tensor
+type Tensors struct {
+	Items  []*Tensor
+	Offset uint64
+}
 
 func (ts Tensors) Layers() map[string]Layer {
 	layers := make(map[string]Layer)
-	for _, t := range ts {
+	for _, t := range ts.Items {
 		parts := strings.Split(t.Name, ".")
 		if parts[0] == "blk" {
 			// join first and second part, e.g. blk.%d

llm/gguf.go

@@ -89,6 +89,7 @@ type gguf struct {
 	tensors []*Tensor
 
 	parameters uint64
+	tensorOffset uint64
 
 	scratch [16 << 10]byte
 }
@@ -109,7 +110,10 @@ func (llm *gguf) KV() KV {
 }
 
 func (llm *gguf) Tensors() Tensors {
-	return llm.tensors
+	return Tensors{
+		Items:  llm.tensors,
+		Offset: llm.tensorOffset,
+	}
 }
 
 func (llm *gguf) numTensor() uint64 {
@@ -236,6 +240,14 @@ func (llm *gguf) Decode(rs io.ReadSeeker) error {
 		alignment = 32
 	}
 
+	offset, err := rs.Seek(0, io.SeekCurrent)
+	if err != nil {
+		return err
+	}
+
+	padding := llm.padding(offset, int64(alignment))
+	llm.tensorOffset = uint64(offset + padding)
+
 	for _, tensor := range llm.tensors {
 		offset, err := rs.Seek(0, io.SeekCurrent)
 		if err != nil {