Added the TensorInfo arg to the compressor so the shape and scale can be output correctly to the file in future.

Corrected some errors in the TensorIndex.

PiperOrigin-RevId: 705014619

compression/blob_store.h

@@ -104,6 +104,9 @@ class BlobWriter {
   // Stores all blobs to disk in the given order with padding for alignment.
   BlobError WriteAll(hwy::ThreadPool& pool, const Path& filename);
 
+  // Returns the number of blobs added.
+  size_t DebugNumBlobsAdded() const { return keys_.size(); }
+
  private:
   std::vector<hwy::uint128_t> keys_;
   std::vector<hwy::Span<const uint8_t>> blobs_;

compression/compress-inl.h

@@ -705,6 +705,9 @@ class Compressor {
     return err;
   }
 
+  // Returns the number of blobs added.
+  size_t DebugNumBlobsAdded() const { return writer_.DebugNumBlobsAdded(); }
+
  private:
   CompressWorkingSet work_;
   hwy::ThreadPool& pool_;

compression/compress.h

@@ -216,8 +216,9 @@ class MatPtrT : public MatPtr {
       : MatPtr(name, TypeEnum<MatT>(), sizeof(MatT), rows, cols) {}
   // Construction from TensorIndex entry to remove duplication of sizes.
   MatPtrT(const std::string& name, const TensorIndex& tensor_index)
+      : MatPtrT<MatT>(name, tensor_index.FindName(name)) {}
+  MatPtrT(const std::string& name, const TensorInfo* tensor)
       : MatPtr(name, TypeEnum<MatT>(), sizeof(MatT), 0, 0) {
-    const TensorInfo* tensor = tensor_index.FindName(name);
     HWY_ASSERT(tensor != nullptr);
     cols_ = tensor->shape.back();
     rows_ = 1;

compression/python/BUILD.bazel

@@ -15,6 +15,7 @@ cc_library(
     visibility = ["//visibility:private"],
     deps = [
         "@abseil-cpp//absl/types:span",
+        "//:common",
         "//compression:compress",
         "//compression:io",
         "@highway//:hwy",
@@ -28,6 +29,7 @@ pybind_extension(
     deps = [
         ":compression_clif_aux",
         "@abseil-cpp//absl/types:span",
+        "//:common",
         "//compression:sfp",
     ],
 )

compression/python/compression_clif_aux.cc

@@ -1,5 +1,7 @@
 #include "compression/python/compression_clif_aux.h"
 
+#include <cstddef>
+#include <cstdio>
 #include <string>
 #include <vector>
 
@@ -22,6 +24,7 @@
 
 #include "absl/types/span.h"
 #include "compression/io.h"
+#include "gemma/tensor_index.h"
 #include "hwy/base.h"
 #include "hwy/contrib/thread_pool/thread_pool.h"
 
@@ -32,7 +35,8 @@ class WriterInterface {
   virtual ~WriterInterface() = default;
 
   virtual void Insert(std::string name, absl::Span<const float> weights,
-                      Type type) = 0;
+                      Type type, const TensorInfo& tensor_info,
+                      float scale) = 0;
   virtual void InsertSfp(std::string name, absl::Span<const float> weights) = 0;
   virtual void InsertNUQ(std::string name, absl::Span<const float> weights) = 0;
   virtual void InsertBfloat16(std::string name,
@@ -41,6 +45,8 @@ class WriterInterface {
                            absl::Span<const float> weights) = 0;
   virtual void AddScales(const std::vector<float>& scales) = 0;
 
+  virtual size_t DebugNumBlobsAdded() const = 0;
+
   virtual int Write(std::string path) = 0;
 };
 
@@ -65,24 +71,39 @@ class SbsWriterImpl : public WriterInterface {
     std::string decorated_name = storage.CacheName();
     compressor_(&storage, decorated_name.c_str(), weights.data());
   }
+  template <typename Packed>
+  void AllocateWithShape(const std::string& name,
+                         absl::Span<const float> weights,
+                         const TensorInfo& tensor_info, float scale) {
+    MatPtrT<Packed> storage(name, &tensor_info);
+    storage.set_scale(scale);
+    storage.SetNumElements(CompressedArrayElements<Packed>(weights.size()));
+    model_memory_.push_back(storage);
+    if (mode_ == CompressorMode::kTEST_ONLY) return;
+    model_memory_.back().Allocate();
+    storage.SetPtr(model_memory_.back());
+    std::string decorated_name = storage.CacheName();
+    compressor_(&storage, decorated_name.c_str(), weights.data());
+  }
 
  public:
-  SbsWriterImpl() : pool_(0), compressor_(pool_) {}
+  explicit SbsWriterImpl(CompressorMode mode)
+      : pool_(0), compressor_(pool_), mode_(mode) {}
 
-  void Insert(std::string name, absl::Span<const float> weights,
-              Type type) override {
+  void Insert(std::string name, absl::Span<const float> weights, Type type,
+              const TensorInfo& tensor_info, float scale) override {
     switch (type) {
       case Type::kSFP:
-        AllocateAndCompress<SfpStream>(name, weights);
+        AllocateWithShape<SfpStream>(name, weights, tensor_info, scale);
         break;
       case Type::kNUQ:
-        AllocateAndCompress<NuqStream>(name, weights);
+        AllocateWithShape<NuqStream>(name, weights, tensor_info, scale);
         break;
       case Type::kBF16:
-        AllocateAndCompress<BF16>(name, weights);
+        AllocateWithShape<BF16>(name, weights, tensor_info, scale);
         break;
       case Type::kF32:
-        AllocateAndCompress<float>(name, weights);
+        AllocateWithShape<float>(name, weights, tensor_info, scale);
         break;
       default:
         HWY_ABORT("Unsupported type");
@@ -112,6 +133,12 @@ class SbsWriterImpl : public WriterInterface {
     compressor_.AddScales(scales_.data(), scales_.size());
   }
 
+  // Returns the number of blobs added.
+  size_t DebugNumBlobsAdded() const {
+    if (mode_ == CompressorMode::kTEST_ONLY) return model_memory_.size();
+    return compressor_.DebugNumBlobsAdded();
+  }
+
   int Write(std::string path) override {
     return compressor_.WriteAll(pool_, gcpp::Path(path));
   }
@@ -121,9 +148,12 @@ class SbsWriterImpl : public WriterInterface {
   CompressWorkingSet working_set_;
   std::vector<MatStorage> model_memory_;
   std::vector<float> scales_;
+  CompressorMode mode_;
 };
 
-WriterInterface* NewSbsWriter() { return new SbsWriterImpl(); }
+WriterInterface* NewSbsWriter(CompressorMode mode) {
+  return new SbsWriterImpl(mode);
+}
 
 }  // namespace HWY_NAMESPACE
 }  // namespace gcpp
@@ -134,12 +164,13 @@ namespace gcpp {
 
 HWY_EXPORT(NewSbsWriter);
 
-SbsWriter::SbsWriter() : impl_(HWY_DYNAMIC_DISPATCH(NewSbsWriter)()) {}
+SbsWriter::SbsWriter(CompressorMode mode)
+    : impl_(HWY_DYNAMIC_DISPATCH(NewSbsWriter)(mode)) {}
 SbsWriter::~SbsWriter() = default;
 
 void SbsWriter::Insert(std::string name, absl::Span<const float> weights,
-                       Type type) {
-  impl_->Insert(name, weights, type);
+                       Type type, const TensorInfo& tensor_info, float scale) {
+  impl_->Insert(name, weights, type, tensor_info, scale);
 }
 void SbsWriter::InsertSfp(std::string name, absl::Span<const float> weights) {
   impl_->InsertSfp(name, weights);
@@ -158,6 +189,11 @@ void SbsWriter::InsertFloat(std::string name, absl::Span<const float> weights) {
 void SbsWriter::AddScales(const std::vector<float>& scales) {
   impl_->AddScales(scales);
 }
+
+size_t SbsWriter::DebugNumBlobsAdded() const {
+  return impl_->DebugNumBlobsAdded();
+}
+
 int SbsWriter::Write(std::string path) { return impl_->Write(path); }
 
 }  // namespace gcpp

compression/python/compression_clif_aux.h

@@ -1,29 +1,44 @@
 #ifndef THIRD_PARTY_GEMMA_CPP_COMPRESSION_PYTHON_COMPRESSION_CLIF_AUX_H_
 #define THIRD_PARTY_GEMMA_CPP_COMPRESSION_PYTHON_COMPRESSION_CLIF_AUX_H_
 
+#include <cstddef>
 #include <memory>
 #include <string>
 #include <vector>
 
 #include "absl/types/span.h"
 #include "compression/shared.h"
+#include "gemma/tensor_index.h"
 
 namespace gcpp {
 
+// How to process the data.
+enum class CompressorMode {
+  // No compression, no write to file, just for testing.
+  kTEST_ONLY,
+  // Old-style compression, no table of contents.
+  kNO_TOC,
+  // New-style compression, with table of contents.
+  kWITH_TOC,
+};
+
 class WriterInterface;
 
 class SbsWriter {
  public:
-  SbsWriter();
+  explicit SbsWriter(CompressorMode mode);
   ~SbsWriter();
 
-  void Insert(std::string name, absl::Span<const float> weights, Type type);
+  void Insert(std::string name, absl::Span<const float> weights, Type type,
+              const TensorInfo& tensor_info, float scale);
   void InsertSfp(std::string name, absl::Span<const float> weights);
   void InsertNUQ(std::string name, absl::Span<const float> weights);
   void InsertBfloat16(std::string name, absl::Span<const float> weights);
   void InsertFloat(std::string name, absl::Span<const float> weights);
   void AddScales(const std::vector<float>& scales);
 
+  size_t DebugNumBlobsAdded() const;
+
   int Write(std::string path);
 
  private:

compression/python/compression_extension.cc

@@ -9,6 +9,7 @@
 #include "compression/python/compression_clif_aux.h"
 #include "compression/shared.h"
 
+using gcpp::CompressorMode;
 using gcpp::SbsWriter;
 
 namespace py = pybind11;
@@ -23,18 +24,24 @@ void wrap_span(SbsWriter& writer, std::string name, py::array_t<float> data) {
 }
 template <auto Func>
 void wrap_span_typed(SbsWriter& writer, std::string name,
-                     py::array_t<float> data, gcpp::Type type) {
+                     py::array_t<float> data, gcpp::Type type,
+                     gcpp::TensorInfo tensor_info, float scale) {
   if (data.ndim() != 1 || data.strides(0) != sizeof(float)) {
     throw std::domain_error("Input array must be 1D and densely packed.");
   }
   std::invoke(Func, writer, name, absl::MakeSpan(data.data(0), data.size()),
-              type);
+              type, tensor_info, scale);
 }
 }  // namespace
 
 PYBIND11_MODULE(compression, m) {
+  py::enum_<CompressorMode>(m, "CompressorMode")
+      .value("TEST_ONLY", CompressorMode::kTEST_ONLY)
+      .value("NO_TOC", CompressorMode::kNO_TOC)
+      .value("WITH_TOC", CompressorMode::kWITH_TOC);
+
   py::class_<SbsWriter>(m, "SbsWriter")
-      .def(py::init<>())
+      .def(py::init<CompressorMode>())
       // NOTE: Individual compression backends may impose constraints on the
       // array length, such as a minimum of (say) 32 elements.
       .def("insert", wrap_span_typed<&SbsWriter::Insert>)
@@ -43,5 +50,6 @@ PYBIND11_MODULE(compression, m) {
       .def("insert_bf16", wrap_span<&SbsWriter::InsertBfloat16>)
       .def("insert_float", wrap_span<&SbsWriter::InsertFloat>)
       .def("add_scales", &SbsWriter::AddScales)
+      .def("debug_num_blobs_added", &SbsWriter::DebugNumBlobsAdded)
       .def("write", &SbsWriter::Write);
 }

compression/python/compression_test.py

@@ -11,12 +11,18 @@ class CompressionTest(unittest.TestCase):
 
   def test_sbs_writer(self):
     temp_file = self.create_tempfile("test.sbs")
+    tensor_info = configs.TensorInfo()
+    tensor_info.name = "foo"
+    tensor_info.axes = [0]
+    tensor_info.shape = [192]
 
-    writer = compression.SbsWriter()
+    writer = compression.SbsWriter(compression.CompressorMode.NO_TOC)
     writer.insert(
         "foo",
         np.array([0.0012] * 128 + [0.001] * 64, dtype=np.float32),
         configs.Type.kSFP,
+        tensor_info,
+        1.0,
     )
     writer.insert_sfp(
         "bar", np.array([0.000375] * 128 + [0.00009] * 128, dtype=np.float32)
@@ -30,6 +36,7 @@ class CompressionTest(unittest.TestCase):
     writer.insert_float(
         "quux", np.array([0.000375] * 128 + [0.00006] * 128, dtype=np.float32)
     )
+    self.assertEqual(writer.debug_num_blobs_added(), 5)
     self.assertEqual(writer.write(temp_file.full_path), 0)
 
 

gemma/tensor_index.cc

@@ -138,8 +138,8 @@ std::vector<TensorInfo> ImageLayerTensors(const ModelConfig& config,
       TensorInfo{
           .name = "qkv_ein_w",
           .source_names = {"MultiHeadDotProductAttention_0/qkv/kernel"},
-          .axes = {2, 0, 3, 1},
-          .shape = {layer_config.heads, 3, layer_config.qkv_dim,
+          .axes = {1, 2, 0},
+          .shape = {layer_config.heads, 3 * layer_config.qkv_dim,
                     config.vit_model_dim},
           .min_size = Type::kBF16,
       },
@@ -156,7 +156,7 @@ std::vector<TensorInfo> ImageLayerTensors(const ModelConfig& config,
           .name = "k_ein_b",
           .source_names = {"MultiHeadDotProductAttention_0/key/bias"},
           .axes = {0, 1},
-          .shape = {layer_config.heads, layer_config.qkv_dim},
+          .shape = {layer_config.kv_heads, layer_config.qkv_dim},
           .concat_names = {""},
           .min_size = Type::kF32,
       },
@@ -164,15 +164,16 @@ std::vector<TensorInfo> ImageLayerTensors(const ModelConfig& config,
           .name = "v_ein_b",
           .source_names = {"MultiHeadDotProductAttention_0/value/bias"},
           .axes = {0, 1},
-          .shape = {layer_config.heads, layer_config.qkv_dim},
+          .shape = {layer_config.kv_heads, layer_config.qkv_dim},
           .concat_names = {""},
           .min_size = Type::kF32,
       },
       TensorInfo{
           .name = "qkv_ein_b",
           .source_names = {"MultiHeadDotProductAttention_0/qkv/bias"},
-          .axes = {1, 0, 2},
-          .shape = {layer_config.heads * 3, layer_config.qkv_dim},
+          .axes = {0, 1},
+          .shape = {layer_config.heads + layer_config.kv_heads * 2,
+                    layer_config.qkv_dim},
           .min_size = Type::kF32,
       },
       TensorInfo{
@@ -243,14 +244,15 @@ std::vector<TensorInfo> LLMLayerTensors(const ModelConfig& config,
           .name = "qkv1_w",
           .source_names = {"attn/q_einsum/w"},
           .axes = {0, 2, 1},
-          .shape = {layer_config.heads, layer_config.qkv_dim, config.model_dim},
+          .shape = {layer_config.heads * layer_config.qkv_dim,
+                    config.model_dim},
           .concat_names = {"qkv_ein", "qkv2_w"},
       },
       TensorInfo{
           .name = "qkv2_w",
           .source_names = {"attn/kv_einsum/w"},
           .axes = {1, 0, 3, 2},
-          .shape = {2 * layer_config.kv_heads, layer_config.qkv_dim,
+          .shape = {2 * layer_config.kv_heads * layer_config.qkv_dim,
                     config.model_dim},
           .concat_names = {""},
       },
@@ -279,8 +281,9 @@ std::vector<TensorInfo> LLMLayerTensors(const ModelConfig& config,
           .name = "qkv_ein",
           .source_names = {"attn/qkv_einsum/w"},
           .axes = {1, 0, 3, 2},
-          .shape = {(layer_config.heads + 2 * layer_config.kv_heads),
-                    layer_config.qkv_dim, config.model_dim},
+          .shape = {(layer_config.heads + 2 * layer_config.kv_heads) *
+                        layer_config.qkv_dim,
+                    config.model_dim},
       },
       TensorInfo{
           .name = "attn_ob",
@@ -535,7 +538,8 @@ TensorIndex::TensorIndex(const ModelConfig& config, int llm_layer_idx,
   }
 }
 
-TensorInfo TensorIndex::GetTensorInfo(const std::string& path) const {
+TensorInfo TensorIndex::TensorInfoFromSourcePath(
+    const std::string& path) const {
   for (const auto& tensor : tensors_) {
     for (const auto& source_name : tensor.source_names) {
       auto pos = path.rfind(source_name);

gemma/tensor_index.h

@@ -68,7 +68,17 @@ class TensorIndex {
   // or an empty TensorInfo if not found.
   // NOTE: that the returned TensorInfo is a copy, so that the source
   // TensorIndex can be destroyed without affecting the returned TensorInfo.
-  TensorInfo GetTensorInfo(const std::string& path) const;
+  TensorInfo TensorInfoFromSourcePath(const std::string& path) const;
+
+  // Returns the TensorInfo whose name matches the given name,
+  // or an empty TensorInfo if not found.
+  // NOTE: that the returned TensorInfo is a copy, so that the source
+  // TensorIndex can be destroyed without affecting the returned TensorInfo.
+  TensorInfo TensorInfoFromName(const std::string& name) const {
+    const TensorInfo* info = FindName(name);
+    if (info == nullptr) return TensorInfo();
+    return *info;
+  }
 
   // Returns the TensorInfo for the given tensor name, for concise construction
   // of ModelWeightsPtrs/LayerWeightsPtrs.