From c5276ac44874eb453485e73a7dca9ed3328d88c2 Mon Sep 17 00:00:00 2001
From: Dmitri Smirnov <yuslepukhin@users.noreply.github.com>
Date: Mon, 11 Nov 2024 09:59:05 -0800
Subject: [PATCH 1/4] Revert "enable serialize prepacked weights into data file
 (#22256)" (#22788)

This reverts commit c5b6be045ff58b706390bd7504e7d865e451a689.

### Description
Revert

### Motivation and Context
This needs simpler and more robust approach
---
 .../onnxruntime/core/framework/op_kernel.h    |  22 ---
 include/onnxruntime/core/graph/graph.h        |  29 +--
 .../onnxruntime_session_options_config_keys.h |   6 -
 onnxruntime/contrib_ops/cpu/bert/attention.cc |   2 -
 .../cpu/quantization/attention_quant.cc       |   2 -
 .../cpu/quantization/dynamic_quantize_lstm.cc |   3 +-
 .../cpu/quantization/matmul_nbits.cc          |  56 ------
 .../contrib_ops/cpu/skip_layer_norm.cc        |   1 -
 onnxruntime/contrib_ops/cpu/skip_layer_norm.h |   2 +-
 .../contrib_ops/cuda/diffusion/group_norm.cc  |   1 -
 .../contrib_ops/cuda/diffusion/group_norm.h   |   1 -
 .../qordered_ops/qordered_attention.cc        |   1 -
 .../qordered_ops/qordered_attention.h         |   1 -
 .../qordered_ops/qordered_matmul.cc           |   1 -
 .../qordered_ops/qordered_matmul.h            |   1 -
 onnxruntime/core/framework/session_options.h  |   6 -
 onnxruntime/core/framework/session_state.cc   |  85 ++-------
 onnxruntime/core/framework/session_state.h    |  33 +---
 .../core/framework/session_state_utils.cc     |  13 +-
 .../core/framework/session_state_utils.h      |   4 +-
 .../framework/tensor_external_data_info.cc    |   2 -
 .../framework/tensor_external_data_info.h     |   3 -
 .../core/framework/tensorprotoutils.cc        |  29 +--
 onnxruntime/core/framework/tensorprotoutils.h |  12 +-
 onnxruntime/core/framework/utils.cc           |   6 -
 onnxruntime/core/framework/utils.h            |   2 -
 onnxruntime/core/graph/graph.cc               | 175 ++++++------------
 onnxruntime/core/graph/model.cc               |  29 +--
 onnxruntime/core/graph/model.h                |  24 +--
 .../core/providers/cpu/fp16/fp16_conv.cc      |   2 -
 onnxruntime/core/providers/cpu/math/gemm.cc   |   3 +-
 onnxruntime/core/providers/cpu/math/gemm.h    |   1 -
 onnxruntime/core/providers/cpu/math/matmul.cc |   1 -
 onnxruntime/core/providers/cpu/math/matmul.h  |   1 -
 .../core/providers/cpu/nn/conv_transpose.cc   |   2 -
 .../core/providers/cpu/nn/conv_transpose.h    |   1 -
 .../core/providers/cpu/nn/layer_norm_impl.cc  |   1 -
 .../core/providers/cpu/nn/layer_norm_impl.h   |   2 +-
 .../cpu/quantization/matmul_integer_base.h    |   1 -
 .../providers/cpu/quantization/qlinearconv.cc |   2 -
 .../core/providers/cpu/rnn/deep_cpu_gru.cc    |   1 -
 .../core/providers/cpu/rnn/deep_cpu_gru.h     |   3 +-
 .../core/providers/cpu/rnn/deep_cpu_lstm.cc   |   4 +-
 .../core/providers/cpu/rnn/deep_cpu_lstm.h    |   1 -
 onnxruntime/core/providers/cuda/nn/conv.cc    |   1 -
 onnxruntime/core/providers/cuda/nn/conv.h     |   1 -
 .../core/providers/cuda/nn/conv_transpose.cc  |   3 +-
 .../core/providers/cuda/nn/conv_transpose.h   |   1 -
 .../core/providers/js/operators/conv.h        |   1 -
 .../providers/js/operators/conv_transpose.h   |   2 -
 .../core/providers/xnnpack/math/gemm.cc       |   1 -
 .../core/providers/xnnpack/math/gemm.h        |   1 -
 .../core/providers/xnnpack/math/matmul.cc     |   1 -
 .../core/providers/xnnpack/math/matmul.h      |   1 -
 onnxruntime/core/providers/xnnpack/nn/conv.cc |   1 -
 onnxruntime/core/providers/xnnpack/nn/conv.h  |   1 -
 .../providers/xnnpack/nn/conv_transpose.cc    |   1 -
 .../providers/xnnpack/nn/conv_transpose.h     |   1 -
 onnxruntime/core/session/inference_session.cc |  40 +---
 .../test/framework/inference_session_test.cc  |  54 ------
 .../save_model_with_external_initializers.cc  |  59 +-----
 .../test/framework/session_state_test.cc      |  66 +------
 onnxruntime/test/shared_lib/test_inference.cc |  83 ---------
 .../model_with_external_initializers.onnx     |   9 +-
 .../model_with_external_initializers.py       |   3 +-
 .../testdata/model_with_orig_ext_data.onnx    |   9 +-
 .../test/testdata/prepack/MatMul.Weight.bin   | Bin 8 -> 0 bytes
 ...xternal_initializers_and_prepack_kernel.py |  88 ---------
 .../prepack/model_with_matmul_nbits.onnx      | Bin 333 -> 0 bytes
 orttraining/orttraining/models/bert/main.cc   |   1 -
 .../orttraining/models/pipeline_poc/main.cc   |   1 -
 .../models/runner/training_runner.cc          |   1 -
 72 files changed, 137 insertions(+), 872 deletions(-)
 delete mode 100644 onnxruntime/test/testdata/prepack/MatMul.Weight.bin
 delete mode 100644 onnxruntime/test/testdata/prepack/model_with_external_initializers_and_prepack_kernel.py
 delete mode 100644 onnxruntime/test/testdata/prepack/model_with_matmul_nbits.onnx

diff --git a/include/onnxruntime/core/framework/op_kernel.h b/include/onnxruntime/core/framework/op_kernel.h
index a17da2a19bb99..07625c38d8474 100644
--- a/include/onnxruntime/core/framework/op_kernel.h
+++ b/include/onnxruntime/core/framework/op_kernel.h
@@ -79,7 +79,6 @@ class OpKernel {
   //               the allocator tied to the session if the kernel owns the pre-packed buffer or an
   //               allocator shared between sessions if the pre-packed buffer is to be shared across sessions
   //               (i.e.) the kernel does not own the buffer.
-  // @param save_prepacked_initializers: Set it to true if intend to save prepacked initializers to external data file.
   // @param is_packed: Set it to true if the kernel packed the tensor or to false
   //                   The kernel is responsible for keeping the packed data and related metadata if is_packed is true,
   //                   and the original initialized constant tensor will be released and not accessible anymore in
@@ -89,7 +88,6 @@ class OpKernel {
 
   virtual Status
   PrePack(const Tensor& /*tensor*/, int /*input_idx*/, AllocatorPtr /*alloc*/,
-          bool, /*save_prepacked_initializers*/
           /*out*/ bool& is_packed, /*out*/ PrePackedWeights* /*prepacked_weights*/) {
     is_packed = false;
     return Status::OK();
@@ -131,26 +129,6 @@ class OpKernel {
     return Status::OK();
   }
 
-  // Override this function to get pre-packed tensors from this kernel.
-  // Only useful for models run on PC with CPU so ORT could load prepacked weights directly from
-  // ONNX data file with mmap and no need to do prepacking on fly to save a lot of heap memory.
-  // @param input_idx : The index of input we prepacked before and intend to get packed tensor back.
-  // Please refer to matmul_nbits kernel for a complete example.
-  virtual std::optional<Tensor> GetPrePackTensor(int /*input_idx*/) {
-    return std::nullopt;
-  }
-
-  // Override this function to set pre-packed tensors to this kernel and restore prepacked weight buffer.
-  // Only useful for models run on PC with CPU so ORT could load prepacked weights directly from
-  // ONNX data file with mmap and no need to do prepacking on fly to save a lot of heap memory.
-  // Please refer to matmul_nbits kernel for a complete example.
-  // @param input_idx : The input index of the tensor in this kernel.
-  // @param pre_packed_tensor: The prepacked tensor read from onnx data file and use the prepacked tensor
-  // to restore prepacked weight buffer.
-  virtual Status SetPrePackTensor(int /*input_idx*/, const Tensor& /*pre_packed_tensor*/) {
-    return Status::OK();
-  }
-
   const OrtDevice GetDevice(OrtMemType mem_type) const;
   const OpKernelInfo& Info() const {
     return *op_kernel_info_;
diff --git a/include/onnxruntime/core/graph/graph.h b/include/onnxruntime/core/graph/graph.h
index 69af3c93d7a07..eb9581e8018d1 100644
--- a/include/onnxruntime/core/graph/graph.h
+++ b/include/onnxruntime/core/graph/graph.h
@@ -1148,11 +1148,6 @@ class Graph {  // NOLINT(clang-analyzer-optin.performance.Padding): preserve exi
   void FinalizeFuseSubGraph(const IndexedSubGraph& sub_graph, Node& fused_node);
 #endif
 
-  // Since one constant initializer could be used by different kernels
-  // and prepacked differently, use an unordered_map to store prepacked
-  // initializer in format of <[initializer_name], <[node_name], [prepacked_initializer]>>
-  typedef std::unordered_map<std::string, std::unordered_map<std::string, ONNX_NAMESPACE::TensorProto>> PrePackedTensorProtoToSave;
-
 #if !defined(ORT_MINIMAL_BUILD)
   /** Gets the GraphProto representation of this Graph. */
   const ONNX_NAMESPACE::GraphProto& ToGraphProto();
@@ -1187,26 +1182,18 @@ class Graph {  // NOLINT(clang-analyzer-optin.performance.Padding): preserve exi
   @param initializer_size_threshold initializers larger or equal to this threshold (in bytes) are saved
   in the external file. Initializer smaller than this threshold are included in the onnx file.
   @param align_info offset alignment info.
-  @param save_prepacked_constant_initializers whether to save prepacked initializer into external data file.
-         If set false to this boolean, prepacked initializer will not be saved into onnxruntime data file,
-         we keep constant initializer as it is.
-  @param pre_packed_initializers struct used to store all the prepacked initializers.
   @returns GraphProto serialization of the graph.
   */
   ONNX_NAMESPACE::GraphProto ToGraphProtoWithExternalInitializers(const std::filesystem::path& external_file_path,
                                                                   const std::filesystem::path& model_file_path,
                                                                   size_t initializer_size_threshold,
-                                                                  const OffsetAlignmentInfo& align_info,
-                                                                  bool save_prepacked_constant_initializers,
-                                                                  PrePackedTensorProtoToSave& pre_packed_initializers) const;
+                                                                  const OffsetAlignmentInfo& align_info) const;
 
   ONNX_NAMESPACE::GraphProto ToGraphProtoWithExternalInitializers(const std::filesystem::path& external_file_path,
                                                                   const std::filesystem::path& model_file_path,
                                                                   size_t initializer_size_threshold) const {
     OffsetAlignmentInfo default_options;
-    PrePackedTensorProtoToSave pre_packed_initializers;
-    return ToGraphProtoWithExternalInitializers(external_file_path, model_file_path, initializer_size_threshold, default_options,
-                                                false, pre_packed_initializers);
+    return ToGraphProtoWithExternalInitializers(external_file_path, model_file_path, initializer_size_threshold, default_options);
   }
 
   /** Gets the ISchemaRegistry instances being used with this Graph. */
@@ -1521,18 +1508,6 @@ class Graph {  // NOLINT(clang-analyzer-optin.performance.Padding): preserve exi
  private:
   void InitializeStateFromModelFileGraphProto();
 
-  // Private method used to setup external initializer properly during model save,
-  // this external initializer could be oroginal initializer or prepacked initializer.
-  static void SetUpExternalInitializer(const Graph::OffsetAlignmentInfo& align_info,
-                                       size_t tensor_bytes_size,
-                                       int64_t& external_offset,
-                                       std::ofstream& external_stream,
-                                       gsl::span<const uint8_t> raw_data,
-                                       ONNX_NAMESPACE::TensorProto& output_proto,
-                                       const std::filesystem::path& external_file_path,
-                                       const ONNX_NAMESPACE::TensorProto& initializer,
-                                       bool is_prepacked);
-
   // Add node with specified <node_proto>.
   Node& AddNode(const ONNX_NAMESPACE::NodeProto& node_proto,
                 const ArgNameToTypeMap& name_to_type);
diff --git a/include/onnxruntime/core/session/onnxruntime_session_options_config_keys.h b/include/onnxruntime/core/session/onnxruntime_session_options_config_keys.h
index 086919913cbea..6a01602e634f8 100644
--- a/include/onnxruntime/core/session/onnxruntime_session_options_config_keys.h
+++ b/include/onnxruntime/core/session/onnxruntime_session_options_config_keys.h
@@ -246,12 +246,6 @@ static const char* const kOrtSessionOptionsDisableCPUEPFallback = "session.disab
 static const char* const kOrtSessionOptionsOptimizedModelExternalInitializersFileName =
     "session.optimized_model_external_initializers_file_name";
 
-// Use this config when save prepacked constant initializers to onnx external data file.
-// Default is not save prepacked initializers to onnx data file.
-// Sample usage: sess_options.add_session_config_entry('session.save_prepacked_constant_initializers',  "1")
-static const char* const kOrtSessionOptionsSavePrePackedConstantInitializers =
-    "session.save_prepacked_constant_initializers";
-
 // Use this config to control the minimum size of the initializer when externalizing it during serialization
 static const char* const kOrtSessionOptionsOptimizedModelExternalInitializersMinSizeInBytes =
     "session.optimized_model_external_initializers_min_size_in_bytes";
diff --git a/onnxruntime/contrib_ops/cpu/bert/attention.cc b/onnxruntime/contrib_ops/cpu/bert/attention.cc
index b15e865aa423c..ad14fb8258656 100644
--- a/onnxruntime/contrib_ops/cpu/bert/attention.cc
+++ b/onnxruntime/contrib_ops/cpu/bert/attention.cc
@@ -30,7 +30,6 @@ class Attention : public OpKernel, public AttentionCPUBase {
   Status Compute(OpKernelContext* context) const override;
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
@@ -102,7 +101,6 @@ bool Attention<T>::IsPackWeightsSuccessful(int qkv_index,
 
 template <typename T>
 Status Attention<T>::PrePack(const Tensor& weights, int input_idx, AllocatorPtr alloc,
-                             bool /*save_prepacked_initializers*/,
                              /*out*/ bool& is_packed,
                              /*out*/ PrePackedWeights* prepacked_weights) {
   /* The PrePack() massages the weights to speed up Compute(), there is an option to
diff --git a/onnxruntime/contrib_ops/cpu/quantization/attention_quant.cc b/onnxruntime/contrib_ops/cpu/quantization/attention_quant.cc
index 71a66ea368943..2c897f183164f 100644
--- a/onnxruntime/contrib_ops/cpu/quantization/attention_quant.cc
+++ b/onnxruntime/contrib_ops/cpu/quantization/attention_quant.cc
@@ -24,7 +24,6 @@ class QAttention : public OpKernel, public AttentionCPUBase {
   Status Compute(OpKernelContext* context) const override;
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  bool& /*out*/ is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
@@ -59,7 +58,6 @@ QAttention<T>::QAttention(const OpKernelInfo& info) : OpKernel(info), AttentionC
 
 template <typename T>
 Status QAttention<T>::PrePack(const Tensor& weights, int input_idx, AllocatorPtr alloc,
-                              bool /*save_prepacked_initializers*/,
                               /*out*/ bool& is_packed,
                               /*out*/ PrePackedWeights* prepacked_weights) {
   if (1 != input_idx) {
diff --git a/onnxruntime/contrib_ops/cpu/quantization/dynamic_quantize_lstm.cc b/onnxruntime/contrib_ops/cpu/quantization/dynamic_quantize_lstm.cc
index 4148aae4b9a35..aa47f365c0005 100644
--- a/onnxruntime/contrib_ops/cpu/quantization/dynamic_quantize_lstm.cc
+++ b/onnxruntime/contrib_ops/cpu/quantization/dynamic_quantize_lstm.cc
@@ -13,7 +13,7 @@ class DynamicQuantizeLSTM : public OpKernel, public LSTMBase {
   DynamicQuantizeLSTM(const OpKernelInfo& info) : OpKernel(info), LSTMBase(info) {}
 
   Status PrePack(const Tensor& tensor, int input_idx,
-                 AllocatorPtr alloc, bool save_prepacked_initializers, /*out*/ bool& is_packed,
+                 AllocatorPtr alloc, /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
   Status UseSharedPrePackedBuffers(std::vector<BufferUniquePtr>& prepacked_buffers,
@@ -91,7 +91,6 @@ static void UseSharedPrePackedBuffersImpl(std::vector<BufferUniquePtr>& prepacke
 }
 
 Status DynamicQuantizeLSTM::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                                    bool /*save_prepacked_initializers*/,
                                     /*out*/ bool& is_packed,
                                     /*out*/ PrePackedWeights* prepacked_weights) {
   is_packed = false;
diff --git a/onnxruntime/contrib_ops/cpu/quantization/matmul_nbits.cc b/onnxruntime/contrib_ops/cpu/quantization/matmul_nbits.cc
index cee3dfc6b3f28..89e96543c4729 100644
--- a/onnxruntime/contrib_ops/cpu/quantization/matmul_nbits.cc
+++ b/onnxruntime/contrib_ops/cpu/quantization/matmul_nbits.cc
@@ -98,19 +98,12 @@ class MatMulNBits final : public OpKernel {
   Status Compute(OpKernelContext* context) const override;
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
-  void ConvertPrepackWeightIntoTensor(const onnxruntime::Tensor& tensor, int input_idx);
-
   Status UseSharedPrePackedBuffers(std::vector<BufferUniquePtr>& prepacked_buffers, int input_idx,
                                    /*out*/ bool& used_shared_buffers) override;
 
-  std::optional<Tensor> GetPrePackTensor(int /*input_idx*/) override;
-
-  Status SetPrePackTensor(int input_idx, const Tensor& pre_packed_tensor) override;
-
  private:
   const size_t K_;
   const size_t N_;
@@ -126,8 +119,6 @@ class MatMulNBits final : public OpKernel {
   size_t packed_b_size_{0};
   IAllocatorUniquePtr<float> scales_fp32_{};
   IAllocatorUniquePtr<float> bias_fp32_{};
-  std::optional<Tensor> packed_tensor_{std::nullopt};
-  MLDataType prepack_tensor_data_type_;
 
   bool has_zp_input_{false};
 
@@ -157,22 +148,8 @@ class MatMulNBits final : public OpKernel {
   }
 };
 
-template <typename T1>
-void MatMulNBits<T1>::ConvertPrepackWeightIntoTensor(const onnxruntime::Tensor& tensor, int input_idx) {
-  if (input_idx == InputIndex::B) {
-    prepack_tensor_data_type_ = tensor.DataType();
-  }
-
-  TensorShapeVector weights_dims = {static_cast<int64_t>((packed_b_size_ - 1) / prepack_tensor_data_type_->Size()) + 1};
-  packed_tensor_ = Tensor(prepack_tensor_data_type_,
-                          TensorShape(weights_dims),
-                          packed_b_.get(),
-                          OrtMemoryInfo(CPU, OrtAllocatorType::OrtDeviceAllocator));
-}
-
 template <typename T1>
 Status MatMulNBits<T1>::PrePack(const Tensor& tensor, int input_idx, /*out*/ AllocatorPtr alloc,
-                                bool save_prepacked_initializers,
                                 /*out*/ bool& is_packed,
                                 /*out*/ PrePackedWeights* prepacked_weights) {
   ORT_UNUSED_PARAMETER(prepacked_weights);
@@ -208,16 +185,11 @@ Status MatMulNBits<T1>::PrePack(const Tensor& tensor, int input_idx, /*out*/ All
 #endif  // MLAS_TARGET_AMD64_IX86
   }
 
-  if (save_prepacked_initializers) {
-    ConvertPrepackWeightIntoTensor(tensor, input_idx);
-  }
-
   return Status::OK();
 }
 
 template <>
 Status MatMulNBits<MLFloat16>::PrePack(const Tensor& tensor, int input_idx, /*out*/ AllocatorPtr alloc,
-                                       bool save_prepacked_initializers,
                                        /*out*/ bool& is_packed,
                                        /*out*/ PrePackedWeights* prepacked_weights) {
   ORT_UNUSED_PARAMETER(prepacked_weights);
@@ -267,34 +239,6 @@ Status MatMulNBits<MLFloat16>::PrePack(const Tensor& tensor, int input_idx, /*ou
 #endif  // MLAS_TARGET_AMD64_IX86
   }
 
-  if (save_prepacked_initializers) {
-    ConvertPrepackWeightIntoTensor(tensor, input_idx);
-  }
-
-  return Status::OK();
-}
-
-template <typename T1>
-std::optional<Tensor> MatMulNBits<T1>::GetPrePackTensor(int input_idx) {
-  // For this kernel, prepack is performed on input_B, and possibly scales, zeros_points.
-  // During compute process, scales and zeros_points will keep as it is and only use prepacked
-  // buffer to replace input_B.
-  // Inorder to cope with this logic, we need to return latest prepacked buffer and only serialize
-  // the latest one. So, we need to always return packed_tensor_ here not only for input_B.
-  ORT_UNUSED_PARAMETER(input_idx);
-  return std::move(packed_tensor_);
-}
-
-template <typename T1>
-Status MatMulNBits<T1>::SetPrePackTensor(int input_idx, const Tensor& pre_packed_tensor) {
-  if (input_idx == 1) {
-    // pre_packed_tensor is constant initialized tensor and its lifecycle is managed by session_state,
-    // session_state will release memory from pre_packed_tensor. packed_b_ will not release memory so
-    // pass empty/default buffer deleter here.
-    // const_cast here is temporary, will fix in follow up PR.
-    packed_b_ = BufferUniquePtr(const_cast<void*>(pre_packed_tensor.DataRaw()), BufferDeleter());
-  }
-
   return Status::OK();
 }
 
diff --git a/onnxruntime/contrib_ops/cpu/skip_layer_norm.cc b/onnxruntime/contrib_ops/cpu/skip_layer_norm.cc
index c9ee9e2cb760d..67b4950af73bf 100644
--- a/onnxruntime/contrib_ops/cpu/skip_layer_norm.cc
+++ b/onnxruntime/contrib_ops/cpu/skip_layer_norm.cc
@@ -278,7 +278,6 @@ Status SkipLayerNorm<T, simplified>::Compute(OpKernelContext* p_ctx) const {
 
 template <typename T, bool simplified>
 Status SkipLayerNorm<T, simplified>::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                                             bool /*save_prepacked_initializers*/,
                                              bool& is_packed, PrePackedWeights* prepacked_weights) {
   ORT_UNUSED_PARAMETER(prepacked_weights);
 
diff --git a/onnxruntime/contrib_ops/cpu/skip_layer_norm.h b/onnxruntime/contrib_ops/cpu/skip_layer_norm.h
index d904c14857437..08e2276c3d9d5 100644
--- a/onnxruntime/contrib_ops/cpu/skip_layer_norm.h
+++ b/onnxruntime/contrib_ops/cpu/skip_layer_norm.h
@@ -16,7 +16,7 @@ class SkipLayerNorm final : public OpKernel {
   SkipLayerNorm(const OpKernelInfo& op_kernel_info);
   Status Compute(OpKernelContext* p_op_kernel_context) const override;
 
-  Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc, bool save_prepacked_initializers,
+  Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
                  bool& is_packed, PrePackedWeights* prepacked_weights) override;
 
  private:
diff --git a/onnxruntime/contrib_ops/cuda/diffusion/group_norm.cc b/onnxruntime/contrib_ops/cuda/diffusion/group_norm.cc
index d190ed389f3e9..dea5391c7629b 100644
--- a/onnxruntime/contrib_ops/cuda/diffusion/group_norm.cc
+++ b/onnxruntime/contrib_ops/cuda/diffusion/group_norm.cc
@@ -95,7 +95,6 @@ GroupNorm::GroupNorm(const OpKernelInfo& op_info) : CudaKernel(op_info) {
 }
 
 Status GroupNorm::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr /*alloc*/,
-                          bool /*save_prepacked_initializers*/,
                           bool& is_packed, PrePackedWeights* /*prepacked_weights*/) {
   is_packed = false;
 
diff --git a/onnxruntime/contrib_ops/cuda/diffusion/group_norm.h b/onnxruntime/contrib_ops/cuda/diffusion/group_norm.h
index 4505c066baedb..b408b3c1ee79b 100644
--- a/onnxruntime/contrib_ops/cuda/diffusion/group_norm.h
+++ b/onnxruntime/contrib_ops/cuda/diffusion/group_norm.h
@@ -17,7 +17,6 @@ class GroupNorm final : public CudaKernel {
   Status ComputeInternal(OpKernelContext* context) const override;
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  bool& is_packed, PrePackedWeights* prepacked_weights) override;
 
  private:
diff --git a/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_attention.cc b/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_attention.cc
index aa2c8755f6536..3e93a527877c5 100644
--- a/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_attention.cc
+++ b/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_attention.cc
@@ -99,7 +99,6 @@ Status QOrderedAttention::PutIntoMergedBias(const Tensor& tensor, AllocatorPtr a
 }
 
 Status QOrderedAttention::PrePack(const Tensor& tensor, int input_idx, /*out*/ AllocatorPtr alloc,
-                                  bool /*save_prepacked_initializers*/,
                                   /*out*/ bool& is_packed,
                                   /*out*/ PrePackedWeights* /*prepacked_weights*/) {
   is_packed = false;
diff --git a/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_attention.h b/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_attention.h
index 529fd00307d66..9d4e563c1feab 100644
--- a/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_attention.h
+++ b/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_attention.h
@@ -20,7 +20,6 @@ class QOrderedAttention final : public CudaKernel, public AttentionBase {
 
  public:
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
diff --git a/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_matmul.cc b/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_matmul.cc
index 351e36b884540..a64f628f245e6 100644
--- a/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_matmul.cc
+++ b/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_matmul.cc
@@ -51,7 +51,6 @@ QOrderedMatMul::QOrderedMatMul(const OpKernelInfo& info) : CudaKernel(info) {
 }
 
 Status QOrderedMatMul::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                               bool /*save_prepacked_initializers*/,
                                /*out*/ bool& is_packed,
                                /*out*/ PrePackedWeights* /* prepacked_weights */) {
   is_packed = false;
diff --git a/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_matmul.h b/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_matmul.h
index d1cef99779e09..dcb6cc6374be1 100644
--- a/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_matmul.h
+++ b/onnxruntime/contrib_ops/cuda/quantization/qordered_ops/qordered_matmul.h
@@ -18,7 +18,6 @@ class QOrderedMatMul final : public CudaKernel {
   Status ComputeInternal(OpKernelContext* context) const override;
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
diff --git a/onnxruntime/core/framework/session_options.h b/onnxruntime/core/framework/session_options.h
index 18405231750ba..8d4db36106f28 100644
--- a/onnxruntime/core/framework/session_options.h
+++ b/onnxruntime/core/framework/session_options.h
@@ -83,11 +83,6 @@ struct SessionOptions {
   // enable profiling for this session.
   bool enable_profiling = false;
 
-  // save pre-packed constant external initializers instead of original initializers to onnxruntime data file.
-  // Only useful for models run on PC with CPU so ORT could load prepacked weights directly from
-  // ONNX data file with mmap and no need to do prepacking on fly to save a lot of heap memory.
-  bool save_prepacked_constant_initializers = false;
-
   // Non empty filepath enables serialization of the transformed optimized model to the specified filepath.
   //
   // Set session config value for ORT_SESSION_OPTIONS_CONFIG_SAVE_MODEL_FORMAT to 'ORT' or 'ONNX' to explicitly
@@ -196,7 +191,6 @@ inline std::ostream& operator<<(std::ostream& os, const SessionOptions& session_
      << " execution_mode:" << session_options.execution_mode
      << " execution_order:" << session_options.execution_order
      << " enable_profiling:" << session_options.enable_profiling
-     << " save_prepacked_constant_initializers:" << session_options.save_prepacked_constant_initializers
      << " optimized_model_filepath:" << ORT_TSTR_CONVERT_TO_PRINTABLE_STRING(session_options.optimized_model_filepath)
      << " enable_mem_pattern:" << session_options.enable_mem_pattern
      << " enable_mem_reuse:" << session_options.enable_mem_reuse
diff --git a/onnxruntime/core/framework/session_state.cc b/onnxruntime/core/framework/session_state.cc
index 943db091b341f..0d0b22ff61e01 100644
--- a/onnxruntime/core/framework/session_state.cc
+++ b/onnxruntime/core/framework/session_state.cc
@@ -14,7 +14,6 @@
 #include "core/framework/op_kernel.h"
 #include "core/framework/ort_value_pattern_planner.h"
 #include "core/framework/session_state_utils.h"
-#include "core/framework/tensorprotoutils.h"
 #include "core/framework/utils.h"
 #include "core/providers/cpu/controlflow/utils.h"
 #include "core/session/onnxruntime_session_options_config_keys.h"
@@ -398,18 +397,12 @@ static std::string GenerateKeyForPrepackedWeightsMap(const std::string& op_type,
 }
 
 Status SessionState::PrepackConstantInitializedTensors(InlinedHashMap<std::string, size_t>& constant_initializers_use_count,
-                                                       const std::unordered_map<std::string, const OrtValue*>& initializers_to_share_map,
-                                                       bool save_prepacked_constant_initializers,
-                                                       PrePackInitializers& pre_packed_initializers) {
-  auto prepacked_constant_weights = [this, &constant_initializers_use_count, &initializers_to_share_map,
-                                     save_prepacked_constant_initializers, &pre_packed_initializers](
+                                                       const std::unordered_map<std::string, const OrtValue*>& initializers_to_share_map) {
+  auto prepacked_constant_weights = [this, &constant_initializers_use_count, &initializers_to_share_map](
                                         bool should_cache_prepacked_weights_for_shared_initializers) -> Status {
-    std::unordered_map<std::string, std::string> pre_packed_kernel_input_map;
     for (auto& node : GetGraphViewer().Nodes()) {
       auto kernel = GetMutableKernel(node.Index());
-      auto kernel_name = kernel->Info().node().Name();
       int input_idx = 0;
-      bool is_kernel_prepacked = false;
       for (auto& input_def : node.InputDefs()) {
         if (input_def->Exists()) {
           const std::string& input_name = input_def->Name();
@@ -421,27 +414,16 @@ Status SessionState::PrepackConstantInitializedTensors(InlinedHashMap<std::strin
             if (st->GetOrtValueNameIdxMap().GetIdx(input_name, ort_value_idx).IsOK()) {
               std::unordered_map<int, OrtValue>& constant_initialized_tensors = st->constant_initialized_tensors_;
 
-              if (constant_initialized_tensors.count(ort_value_idx) && !is_kernel_prepacked) {
+              if (constant_initialized_tensors.count(ort_value_idx)) {
                 bool is_packed = false;
                 const Tensor& const_initialized_tensor = constant_initialized_tensors[ort_value_idx].Get<Tensor>();
 
                 auto iter = initializers_to_share_map.find(input_name);
                 bool is_shared_initializer = (iter != initializers_to_share_map.end());
 
-                // found pre-packed constant initializers from data file, no need to do pre-packing again
-                // apply pre-packed tensor to kernel so kernel can use it directly
-                if (pre_packed_initializers.pre_packed_initializer_names_read_from_file.count(input_name) != 0) {
-                  is_packed = true;
-
-                  // kernel like Matmul_nbits will call prepack multiple times with input_B and possibly scales/zero_points.
-                  // If prepacked weights already read from ONNX data file (this happens we ORT reads data file with prepacked
-                  // weights serialized), only need to set prepacked weights once to kernel.
-                  is_kernel_prepacked = true;
-                  ORT_THROW_IF_ERROR(kernel->SetPrePackTensor(input_idx, const_initialized_tensor));
-                }
                 // Caching pre-packed weights is limited to shared initializers associated with the CPU EP for now
-                else if (is_shared_initializer && should_cache_prepacked_weights_for_shared_initializers &&
-                         node.GetExecutionProviderType() == kCpuExecutionProvider) {  // caching of pre-packed weights' turned ON
+                if (is_shared_initializer && should_cache_prepacked_weights_for_shared_initializers &&
+                    node.GetExecutionProviderType() == kCpuExecutionProvider) {  // caching of pre-packed weights' turned ON
 
                   AllocatorPtr allocator_for_caching = prepacked_weights_container_->GetOrCreateAllocator(CPU);
                   ORT_ENFORCE(allocator_for_caching.get() != nullptr);
@@ -453,7 +435,7 @@ Status SessionState::PrepackConstantInitializedTensors(InlinedHashMap<std::strin
                   // weight with the pre-packed weight generated by this instance of the same op_type because other static
                   // properties of the node like node attributes could play a role in the pre-packed weights' contents.
                   ORT_RETURN_IF_ERROR(kernel->PrePack(const_initialized_tensor, input_idx, allocator_for_caching,
-                                                      save_prepacked_constant_initializers, is_packed,
+                                                      is_packed,
                                                       &weights_to_be_filled_in));
 
                   if (is_packed) {
@@ -500,50 +482,18 @@ Status SessionState::PrepackConstantInitializedTensors(InlinedHashMap<std::strin
                   AllocatorPtr session_cpu_alloc = GetAllocator(kernel->Info().GetDevice(OrtMemType::OrtMemTypeDefault));
                   ORT_RETURN_IF_ERROR(kernel->PrePack(const_initialized_tensor, input_idx,
                                                       session_cpu_alloc,  // use allocator tied to this session
-                                                      save_prepacked_constant_initializers,
                                                       is_packed,
                                                       nullptr  // no caching required
                                                       ));
                 }
                 if (is_packed) {
-                  // if intended to save prepacked initializers, get prepacked tensors from kernel and save in hashmap,
-                  // will save to data file later
-                  if (save_prepacked_constant_initializers) {
-                    auto tensor = kernel->GetPrePackTensor(input_idx);
-
-                    if (tensor != std::nullopt) {
-                      // save prepacked initializers per initializer and kernel since one initializer could
-                      // be used by multiple kernels
-                      pre_packed_initializers.pre_packed_initializers_to_save[input_name][kernel_name] = std::move(tensor.value());
-
-                      pre_packed_kernel_input_map[kernel_name] = input_name;
-                    }
-                  }
-
                   ++number_of_prepacks_counter_;
 
-                  // if constant_initialized_tensor is already pre-packed, don't need to remove it
-                  if (pre_packed_initializers.pre_packed_initializer_names_read_from_file.count(input_name) == 0 &&
-                      constant_initializers_use_count.count(input_name) && --constant_initializers_use_count[input_name] == 0) {
+                  if (constant_initializers_use_count.count(input_name) && --constant_initializers_use_count[input_name] == 0) {
                     // release the constant initialized tensor
                     st->initialized_tensors_.erase(ort_value_idx);
                     constant_initialized_tensors.erase(ort_value_idx);
                   }
-                } else {
-                  // handle prepack for matmul_nbits, it will prepack several times but set is_packed
-                  // to false for scales and zero_points, we keep scales and zero_points as it is only
-                  // update packed_tensor to input_B.
-                  // TODO: this logic works with matmul_nbits kernel but if other kernels also call prepack
-                  // multiple times and use different initializers to store prepacked weights, this piece of logic
-                  // might introduce bug and need a per kernel strategy to update prepacked weights.
-                  if (save_prepacked_constant_initializers && pre_packed_kernel_input_map.count(kernel_name)) {
-                    auto tensor = kernel->GetPrePackTensor(input_idx);
-
-                    if (tensor != std::nullopt) {
-                      auto existing_input_name = pre_packed_kernel_input_map[kernel_name];
-                      pre_packed_initializers.pre_packed_initializers_to_save[existing_input_name][kernel_name] = std::move(tensor.value());
-                    }
-                  }
                 }
               }
               // stop searching in 2 cases:
@@ -1226,7 +1176,6 @@ static Status VerifyEachNodeIsAssignedToAnEp(const Graph& graph, const logging::
 
 Status SessionState::FinalizeSessionState(const std::basic_string<PATH_CHAR_TYPE>& graph_location,
                                           const KernelRegistryManager& kernel_registry_manager,
-                                          PrePackInitializers& pre_packed_initializers,
                                           bool remove_initializers,
                                           bool saving_ort_format) {
   // recursively create the subgraph session state instances and populate the kernel create info in them.
@@ -1240,7 +1189,7 @@ Status SessionState::FinalizeSessionState(const std::basic_string<PATH_CHAR_TYPE
   InlinedHashMap<std::string, size_t> constant_initializers_use_count;
   ComputeConstantInitializerUseCount(graph_, constant_initializers_use_count);
   return FinalizeSessionStateImpl(graph_location, kernel_registry_manager, nullptr, sess_options_,
-                                  remove_initializers, constant_initializers_use_count, pre_packed_initializers);
+                                  remove_initializers, constant_initializers_use_count);
 }
 
 static Status Index(const OrtValueNameIdxMap& ort_value_name_idx_map,
@@ -1374,7 +1323,6 @@ Status SessionState::FinalizeSessionStateImpl(const std::basic_string<PATH_CHAR_
                                               const SessionOptions& session_options,
                                               bool remove_initializers,
                                               InlinedHashMap<std::string, size_t>& constant_initializers_use_count,
-                                              PrePackInitializers& pre_packed_initializers,
                                               const InlinedHashMap<OrtValueName, OrtDevice>& outer_scope_node_arg_to_location_map,
                                               bool graph_info_already_created) {
   if (!graph_info_already_created) {
@@ -1474,8 +1422,6 @@ Status SessionState::FinalizeSessionStateImpl(const std::basic_string<PATH_CHAR_
   // For inference it is enabled by default, but users can choose to disable it via session options.
   const bool disable_prepacking =
       session_options.config_options.GetConfigOrDefault(kOrtSessionOptionsConfigDisablePrepacking, "0") == "1";
-  const bool save_prepacked_constant_initializers =
-      session_options.config_options.GetConfigOrDefault(kOrtSessionOptionsSavePrePackedConstantInitializers, "0") == "1";
   // Memory pattern tracer allocates all initializers on a single contiguous
   // buffer. This has the effect of reducing memory fragmentation.
   // Further more, in training scenarios NCCL kernels require initializers to be allocated
@@ -1528,9 +1474,7 @@ Status SessionState::FinalizeSessionStateImpl(const std::basic_string<PATH_CHAR_
     }
   }
 #endif
-  // This unorder set is used during model load with prepacked initializer saved in ONNX data file.
-  // ORT reads prepacked initializers and store them into this set so we could skip PrePack
-  // process later to save heap memory.
+
   ORT_RETURN_IF_ERROR(
       session_state_utils::SaveInitializedTensors(
           Env::Default(), graph_location, *graph_viewer_,
@@ -1545,7 +1489,7 @@ Status SessionState::FinalizeSessionStateImpl(const std::basic_string<PATH_CHAR_
             return Status::OK();
           },
           logger_, data_transfer_mgr_, external_data_loader_mgr_, *p_seq_exec_plan_, session_options,
-          memory_profile_func, name_to_buffered_tensor_, pre_packed_initializers.pre_packed_initializer_names_read_from_file));
+          memory_profile_func, name_to_buffered_tensor_));
 
 #if !defined(ORT_MINIMAL_BUILD) && defined(ORT_MEMORY_PROFILE)
   // Record Weight allocation info on device
@@ -1561,14 +1505,9 @@ Status SessionState::FinalizeSessionStateImpl(const std::basic_string<PATH_CHAR_
 
   ORT_RETURN_IF_ERROR(CreateKernels(kernel_registry_manager));
 
-  // pre-packed constant initializers only when:
-  //   1. pre-packing is not disabled
-  //   2. pre-packed not initializers found and loaded during model load
   if (!disable_prepacking) {
     ORT_RETURN_IF_ERROR(PrepackConstantInitializedTensors(constant_initializers_use_count,
-                                                          session_options.initializers_to_share_map,
-                                                          save_prepacked_constant_initializers,
-                                                          pre_packed_initializers));
+                                                          session_options.initializers_to_share_map));
   }
 
   ORT_RETURN_IF_ERROR(
@@ -1607,7 +1546,7 @@ Status SessionState::FinalizeSessionStateImpl(const std::basic_string<PATH_CHAR_
                                                                subgraph_outer_scope_node_arg_to_location_map));
       ORT_RETURN_IF_ERROR(subgraph_session_state.FinalizeSessionStateImpl(
           graph_location, kernel_registry_manager, &node, subgraph_session_options, remove_initializers,
-          constant_initializers_use_count, pre_packed_initializers, subgraph_outer_scope_node_arg_to_location_map, true));
+          constant_initializers_use_count, subgraph_outer_scope_node_arg_to_location_map, true));
 
       // setup all the info for handling the feeds and fetches used in subgraph execution
       auto* p_op_kernel = GetMutableKernel(node.Index());
diff --git a/onnxruntime/core/framework/session_state.h b/onnxruntime/core/framework/session_state.h
index a6023d2a62da7..e1674ba4b690b 100644
--- a/onnxruntime/core/framework/session_state.h
+++ b/onnxruntime/core/framework/session_state.h
@@ -312,25 +312,8 @@ class SessionState {
     return &name_to_buffered_tensor_;
   }
 
-  // Data structure stores prepacked initializers in format of Tensor.
-  struct PrePackInitializers {
-    // This map is used during model save for prepacked initializers.
-    // Since one constant initializer could be used by different kernels
-    // and prepacked differently, use an unordered_map to store prepacked
-    // initializer in format of <[initializer_name], <[kernel_name], [prepacked_initializer]>>
-    typedef std::unordered_map<std::string, std::unordered_map<std::string, Tensor>> PrePackedTensorsToSave;
-    PrePackedTensorsToSave pre_packed_initializers_to_save;
-
-    // This set is used during model load with prepacked initializer serialized in external data file.
-    // ORT reads prepacked initializers and store their name into this set so we could skip PrePack
-    // process later to save heap memory. Prepacked tensor itself is saved in session state's constant_initialized_tensors_.
-    typedef std::unordered_set<std::string> PrePackedTensorNamesReadFromFile;
-    PrePackedTensorNamesReadFromFile pre_packed_initializer_names_read_from_file;
-  };
-
   Status FinalizeSessionState(const std::basic_string<PATH_CHAR_TYPE>& graph_loc,
                               const KernelRegistryManager& kernel_registry_manager,
-                              PrePackInitializers& pre_packed_initializers,
                               bool remove_initializers = true,
                               bool saving_ort_format = false);
 
@@ -338,15 +321,6 @@ class SessionState {
     return parent_;
   }
 
-  Status FinalizeSessionState(const std::basic_string<PATH_CHAR_TYPE>& graph_loc,
-                              const KernelRegistryManager& kernel_registry_manager,
-                              bool remove_initializers = true,
-                              bool saving_ort_format = false) {
-    PrePackInitializers pre_packed_initializers;
-    return FinalizeSessionState(graph_loc, kernel_registry_manager, pre_packed_initializers,
-                                remove_initializers, saving_ort_format);
-  }
-
   // Clear all removable attributes if they exists.
   // The function logs the list of removable attributes for every node.
   void PruneRemovableAttributes();
@@ -406,13 +380,9 @@ class SessionState {
   /**
    * Prepack the constant initialized tensors for better performance.
    * The original constant initialized tensors will be removed to save memory.
-   * For model with prepacked initializer serialized into ONNX data file,
-   * PrePack will be skipped to save memory.
    */
   Status PrepackConstantInitializedTensors(InlinedHashMap<std::string, size_t>& constant_initializers_use_count,
-                                           const std::unordered_map<std::string, const OrtValue*>& initializers_to_share_map,
-                                           bool save_prepacked_constant_initializers,
-                                           PrePackInitializers& pre_packed_initializers);
+                                           const std::unordered_map<std::string, const OrtValue*>& initializers_to_share_map);
 
   SessionState* GetMutableSubgraphSessionState(onnxruntime::NodeIndex index, const std::string& attribute_name);
 
@@ -430,7 +400,6 @@ class SessionState {
                                   const SessionOptions& session_options,
                                   bool remove_initializers,
                                   InlinedHashMap<std::string, size_t>& constant_initializers_use_count,
-                                  PrePackInitializers& pre_packed_initializers,
                                   const InlinedHashMap<OrtValueName, OrtDevice>& outer_scope_node_arg_to_location_map = {},
                                   bool graph_info_already_created = false);
 
diff --git a/onnxruntime/core/framework/session_state_utils.cc b/onnxruntime/core/framework/session_state_utils.cc
index 3424f40e79c01..2c74805c57dce 100644
--- a/onnxruntime/core/framework/session_state_utils.cc
+++ b/onnxruntime/core/framework/session_state_utils.cc
@@ -21,6 +21,7 @@
 #include "core/framework/ort_value_pattern_planner.h"
 #include "core/framework/ort_value_name_idx_map.h"
 #include "core/framework/sequential_execution_plan.h"
+#include "core/framework/session_state.h"
 #include "core/framework/tensorprotoutils.h"
 #include "core/framework/utils.h"
 #include "core/framework/bfc_arena.h"
@@ -71,7 +72,6 @@ static inline common::Status ExtDataTensorProtoToTensor(const Env& env,
                                                         const std::basic_string<PATH_CHAR_TYPE>& proto_path,
                                                         const ONNX_NAMESPACE::TensorProto& tensor_proto,
                                                         Tensor& tensor, OrtCallback& ext_data_deleter,
-                                                        SessionState::PrePackInitializers::PrePackedTensorNamesReadFromFile& pre_packed_initializers_name_set,
                                                         Tensor* buffered_tensor = nullptr) {
   ORT_ENFORCE(utils::HasExternalData(tensor_proto));
 
@@ -79,7 +79,7 @@ static inline common::Status ExtDataTensorProtoToTensor(const Env& env,
   SafeInt<size_t> ext_data_len = 0;
   ORT_RETURN_IF_ERROR(utils::GetExtDataFromTensorProto(env, proto_path.c_str(), tensor_proto,
                                                        ext_data_buf, ext_data_len, ext_data_deleter,
-                                                       &pre_packed_initializers_name_set, buffered_tensor));
+                                                       buffered_tensor));
 
   // NB: creating a do-nothing allocator per tensor is wasteful; can perhaps be
   // avoided if the Tensor class implements the do-nothing behavior when given a
@@ -100,7 +100,6 @@ static common::Status DeserializeTensorProto(const Env& env, const std::basic_st
                                              const AllocatorPtr& alloc, const AllocatorPtr& default_cpu_alloc,
                                              OrtValue& ort_value, const DataTransferManager& data_transfer_mgr,
                                              const ExternalDataLoaderManager& external_data_loader_mgr,
-                                             SessionState::PrePackInitializers::PrePackedTensorNamesReadFromFile& pre_packed_initializers_name_set,
                                              bool use_device_allocator_for_initializers = false,
                                              Tensor* buffered_tensor = nullptr) {
   if (bool(alloc) == (m != nullptr)) {
@@ -140,7 +139,7 @@ static common::Status DeserializeTensorProto(const Env& env, const std::basic_st
       // TensorProtoToTensor it would copy the data, causing unnecessary overhead
       OrtCallback ext_data_deleter;
       ORT_RETURN_IF_ERROR(ExtDataTensorProtoToTensor(env, proto_path, tensor_proto, *p_tensor,
-                                                     ext_data_deleter, pre_packed_initializers_name_set, buffered_tensor));
+                                                     ext_data_deleter, buffered_tensor));
 
       ExtDataValueDeleter deleter{ext_data_deleter, p_tensor.get()};
       MLDataType ml_tensor_type = DataTypeImpl::GetType<Tensor>();
@@ -164,7 +163,7 @@ static common::Status DeserializeTensorProto(const Env& env, const std::basic_st
       OrtCallback ext_data_deleter;
       std::optional<ScopedOrtCallbackInvoker> scoped_ort_callback_invoker;
       ORT_RETURN_IF_ERROR(ExtDataTensorProtoToTensor(env, proto_path, tensor_proto, *p_deserialize_tensor,
-                                                     ext_data_deleter, pre_packed_initializers_name_set, buffered_tensor));
+                                                     ext_data_deleter, buffered_tensor));
       scoped_ort_callback_invoker = ScopedOrtCallbackInvoker(ext_data_deleter);
       // TODO!! Need a temp buffer allocator for non-escape buffers that maybe too big for stack allocation.
 
@@ -273,8 +272,7 @@ common::Status SaveInitializedTensors(
     const ExecutionPlanBase& exec_plan,
     const SessionOptions& session_options,
     const MemoryProfileFunction& memory_profile_func,
-    std::unordered_map<std::string, std::unique_ptr<Tensor>>& buffered_tensors,
-    SessionState::PrePackInitializers::PrePackedTensorNamesReadFromFile& pre_packed_initializers_name_set) {
+    std::unordered_map<std::string, std::unique_ptr<Tensor>>& buffered_tensors) {
   LOGS(logger, INFO) << "Saving initialized tensors.";
   ORT_ENFORCE(ort_value_name_idx_map.MaxIdx() > -1, "OrtValue indexes should have been populated.");
 
@@ -403,7 +401,6 @@ common::Status SaveInitializedTensors(
 
       Status st = DeserializeTensorProto(env, graph_loc, tensor_proto, (m.has_value()) ? &*m : nullptr, alloc,
                                          default_cpu_alloc, ort_value, data_transfer_mgr, external_data_loader_mgr,
-                                         pre_packed_initializers_name_set,
                                          use_device_allocator_for_initializers, p_tensor);
       if (!st.IsOK()) {
         std::ostringstream oss;
diff --git a/onnxruntime/core/framework/session_state_utils.h b/onnxruntime/core/framework/session_state_utils.h
index 4de501b6f7429..af27f5caba0f4 100644
--- a/onnxruntime/core/framework/session_state_utils.h
+++ b/onnxruntime/core/framework/session_state_utils.h
@@ -12,7 +12,6 @@
 #include "core/framework/tensor.h"
 #include "core/framework/tensor_allocator.h"
 #include "core/framework/session_options.h"
-#include "core/framework/session_state.h"
 #include "core/framework/sequential_execution_plan.h"
 #include "core/platform/path_lib.h"
 
@@ -51,8 +50,7 @@ common::Status SaveInitializedTensors(
     const ExecutionPlanBase& exec_plan,
     const SessionOptions& session_options,
     const MemoryProfileFunction& memory_profile_func,
-    std::unordered_map<std::string, std::unique_ptr<Tensor>>& buffered_tensors,
-    SessionState::PrePackInitializers::PrePackedTensorNamesReadFromFile& pre_packed_initializers_name_set);
+    std::unordered_map<std::string, std::unique_ptr<Tensor>>& buffered_tensors);
 
 common::Status AllocateTensor(
     const onnxruntime::MemBuffer* m,
diff --git a/onnxruntime/core/framework/tensor_external_data_info.cc b/onnxruntime/core/framework/tensor_external_data_info.cc
index bcd04effe2bd4..93146e66d9f24 100644
--- a/onnxruntime/core/framework/tensor_external_data_info.cc
+++ b/onnxruntime/core/framework/tensor_external_data_info.cc
@@ -40,8 +40,6 @@ Status ExternalDataInfo::Create(const RepeatedPtrField<StringStringEntryProto>&
         return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "parsing ", stringmap.value(), " failed");
     } else if (stringmap.key() == "checksum" && !stringmap.value().empty()) {
       out->checksum_ = stringmap.value();
-    } else if (stringmap.key() == "prepacked" && !stringmap.value().empty()) {
-      out->prepacked_ = stringmap.value() == "1";
     } else {
       return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "model format error!");
     }
diff --git a/onnxruntime/core/framework/tensor_external_data_info.h b/onnxruntime/core/framework/tensor_external_data_info.h
index c2490f5cc5bc2..afc8fda6c3037 100644
--- a/onnxruntime/core/framework/tensor_external_data_info.h
+++ b/onnxruntime/core/framework/tensor_external_data_info.h
@@ -23,8 +23,6 @@ class ExternalDataInfo {
 
   const std::string& GetChecksum() const { return checksum_; }
 
-  bool GetPrePacked() const noexcept { return prepacked_; }
-
   // If the value of 'offset' or 'length' field is larger the max value of ssize_t, this function will treat it as a
   // wrong value and return FAIL.
   static common::Status Create(
@@ -38,6 +36,5 @@ class ExternalDataInfo {
   // 0 means the whole file
   size_t length_ = 0;
   std::string checksum_;
-  bool prepacked_ = false;
 };
 }  // namespace onnxruntime
diff --git a/onnxruntime/core/framework/tensorprotoutils.cc b/onnxruntime/core/framework/tensorprotoutils.cc
index 0c69ee11f62bc..2af9f95ad059e 100644
--- a/onnxruntime/core/framework/tensorprotoutils.cc
+++ b/onnxruntime/core/framework/tensorprotoutils.cc
@@ -230,12 +230,11 @@ Status TensorProtoToOrtValueImpl(const Env& env, const std::filesystem::path& mo
 
 namespace utils {
 
-static Status GetExternalDataInfo(const ONNX_NAMESPACE::TensorProto& tensor_proto,
-                                  const std::filesystem::path& tensor_proto_dir,
-                                  std::basic_string<ORTCHAR_T>& external_file_path,
-                                  onnxruntime::FileOffsetType& file_offset,
-                                  SafeInt<size_t>& tensor_byte_size,
-                                  bool& pre_packed) {
+Status GetExternalDataInfo(const ONNX_NAMESPACE::TensorProto& tensor_proto,
+                           const std::filesystem::path& tensor_proto_dir,
+                           std::basic_string<ORTCHAR_T>& external_file_path,
+                           onnxruntime::FileOffsetType& file_offset,
+                           SafeInt<size_t>& tensor_byte_size) {
   ORT_RETURN_IF_NOT(onnxruntime::utils::HasExternalData(tensor_proto),
                     "Tensor does not have external data to read from.");
 
@@ -245,8 +244,6 @@ static Status GetExternalDataInfo(const ONNX_NAMESPACE::TensorProto& tensor_prot
   std::unique_ptr<onnxruntime::ExternalDataInfo> external_data_info;
   ORT_RETURN_IF_ERROR(onnxruntime::ExternalDataInfo::Create(tensor_proto.external_data(), external_data_info));
 
-  pre_packed = external_data_info->GetPrePacked();
-
   const auto& location = external_data_info->GetRelPath();
 
   external_file_path = location == onnxruntime::utils::kTensorProtoMemoryAddressTag ? std::filesystem::path(location)
@@ -268,11 +265,6 @@ void SetRawDataInTensorProto(ONNX_NAMESPACE::TensorProto& tensor_proto, std::str
   tensor_proto.set_raw_data(std::move(param));
 }
 
-Status GetExternalDataInfo(const ONNX_NAMESPACE::TensorProto& tensor_proto, const std::filesystem::path& tensor_proto_dir, std::basic_string<ORTCHAR_T>& external_file_path, onnxruntime::FileOffsetType& file_offset, SafeInt<size_t>& tensor_byte_size) {
-  bool pre_packed = false;
-  return GetExternalDataInfo(tensor_proto, tensor_proto_dir, external_file_path, file_offset, tensor_byte_size, pre_packed);
-}
-
 void ConvertRawDataInTensorProto(TensorProto* tensor) {
   size_t element_size = 1;
   char* bytes = NULL;
@@ -996,7 +988,7 @@ static Status GetFileContent(const Env& env, const std::filesystem::path& file_p
 Status GetExtDataFromTensorProto(const Env& env, const std::filesystem::path& model_path,
                                  const ONNX_NAMESPACE::TensorProto& tensor_proto, void*& ext_data_buf,
                                  SafeInt<size_t>& ext_data_len, OrtCallback& ext_data_deleter,
-                                 SessionState::PrePackInitializers::PrePackedTensorNamesReadFromFile* pre_packed_initializers_name_set, Tensor* buffered_tensor) {
+                                 Tensor* buffered_tensor) {
   ORT_ENFORCE(utils::HasExternalData(tensor_proto));
   std::basic_string<ORTCHAR_T> tensor_proto_dir;
   if (!model_path.empty()) {
@@ -1005,13 +997,8 @@ Status GetExtDataFromTensorProto(const Env& env, const std::filesystem::path& mo
   std::basic_string<ORTCHAR_T> external_data_file_path;
   FileOffsetType file_offset;
   SafeInt<size_t> raw_data_safe_len = 0;
-  bool pre_packed = false;
   ORT_RETURN_IF_ERROR(
-      GetExternalDataInfo(tensor_proto, tensor_proto_dir, external_data_file_path, file_offset, raw_data_safe_len, pre_packed));
-
-  if (pre_packed && pre_packed_initializers_name_set != nullptr) {
-    (*pre_packed_initializers_name_set).insert(tensor_proto.name());
-  }
+      GetExternalDataInfo(tensor_proto, tensor_proto_dir, external_data_file_path, file_offset, raw_data_safe_len));
 
   if (external_data_file_path == onnxruntime::utils::kTensorProtoMemoryAddressTag) {
     // the value in location is the memory address of the data
@@ -1121,7 +1108,7 @@ Status TensorProtoToTensor(const Env& env, const std::filesystem::path& model_pa
   OrtCallback& d = deleter_for_file_data.d;
 
   if (utils::HasExternalData(tensor_proto)) {
-    ORT_RETURN_IF_ERROR(GetExtDataFromTensorProto(env, model_path, tensor_proto, raw_data, raw_data_len, d, nullptr));
+    ORT_RETURN_IF_ERROR(GetExtDataFromTensorProto(env, model_path, tensor_proto, raw_data, raw_data_len, d));
   } else if (utils::HasRawData(tensor_proto)) {
     raw_data = const_cast<char*>(tensor_proto.raw_data().data());
     // TODO The line above has const-correctness issues. Below is a possible fix which copies the tensor_proto data
diff --git a/onnxruntime/core/framework/tensorprotoutils.h b/onnxruntime/core/framework/tensorprotoutils.h
index 770132f8e95fc..262f7adaca1cb 100644
--- a/onnxruntime/core/framework/tensorprotoutils.h
+++ b/onnxruntime/core/framework/tensorprotoutils.h
@@ -17,19 +17,26 @@
 #include "core/framework/external_data_loader.h"
 #include "core/framework/ort_value.h"
 #include "core/framework/mem_buffer.h"
-#include "core/framework/session_state.h"
 #include "core/framework/tensor_external_data_info.h"
 #include "core/graph/onnx_protobuf.h"
 #include "core/platform/env.h"
 
 namespace onnxruntime {
 namespace utils {
+/**
+ * This function is used to get the external data info from the given tensor proto.
+ * @param tensor_proto       given initializer tensor
+ * @param tensor_proto_dir   directory of the tensor proto file
+ * @param external_file_path output external file path
+ * @param file_offset        output tensor offset
+ * @param tensor_byte_size   output tensor byte size
+ * @returns                  Status::OK() if the function is executed successfully
+ */
 Status GetExternalDataInfo(const ONNX_NAMESPACE::TensorProto& tensor_proto,
                            const std::filesystem::path& tensor_proto_dir,
                            std::basic_string<ORTCHAR_T>& external_file_path,
                            onnxruntime::FileOffsetType& file_offset,
                            SafeInt<size_t>& tensor_byte_size);
-
 /**
  * This function is used to convert the endianess of Tensor data.
  * Mostly, will be used in big endian system to support the model file
@@ -165,7 +172,6 @@ common::Status GetExtDataFromTensorProto(const Env& env, const std::filesystem::
                                          const ONNX_NAMESPACE::TensorProto& tensor_proto,
                                          void*& ext_data_buf, SafeInt<size_t>& ext_data_len,
                                          OrtCallback& ext_data_deleter,
-                                         SessionState::PrePackInitializers::PrePackedTensorNamesReadFromFile* pre_packed_initializers_name_set,
                                          Tensor* buffered_tensor = nullptr);
 
 // Given a tensor proto with external data obtain a tensor using the specified custom external data loader.
diff --git a/onnxruntime/core/framework/utils.cc b/onnxruntime/core/framework/utils.cc
index 5402345447706..9eed0249711f9 100644
--- a/onnxruntime/core/framework/utils.cc
+++ b/onnxruntime/core/framework/utils.cc
@@ -1064,11 +1064,5 @@ bool IsOutputOnCpu(const Node& node, const KernelCreateInfo* p_kci, size_t index
   return false;
 }
 
-std::string GetPrepackedInitializerName(const std::string& initializer_name, const std::string& node_name) {
-  const std::string seperator = ":";
-
-  return initializer_name + seperator + node_name;
-}
-
 }  // namespace utils
 }  // namespace onnxruntime
diff --git a/onnxruntime/core/framework/utils.h b/onnxruntime/core/framework/utils.h
index db38ef1675595..afdb5a2cb27f5 100644
--- a/onnxruntime/core/framework/utils.h
+++ b/onnxruntime/core/framework/utils.h
@@ -234,8 +234,6 @@ constexpr ONNXTensorElementDataType GetONNXTensorElementDataType<UInt4x2>() {
 
 int32_t ONNXTensorElementDataTypeToProtoTensorType(ONNXTensorElementDataType);
 
-std::string GetPrepackedInitializerName(const std::string& initializer_name, const std::string& node_name);
-
 #ifdef ENABLE_TRAINING
 common::Status VerifyInputTensorsAllocatedContiguously(OpKernelContext* context);
 #endif
diff --git a/onnxruntime/core/graph/graph.cc b/onnxruntime/core/graph/graph.cc
index 3f50841f50913..e8a5855b36496 100644
--- a/onnxruntime/core/graph/graph.cc
+++ b/onnxruntime/core/graph/graph.cc
@@ -4084,75 +4084,10 @@ ONNX_NAMESPACE::GraphProto Graph::ToGraphProto() const {
   return result;
 }
 
-void Graph::SetUpExternalInitializer(const Graph::OffsetAlignmentInfo& align_info,
-                                     size_t tensor_bytes_size,
-                                     int64_t& external_offset,
-                                     std::ofstream& external_stream,
-                                     gsl::span<const uint8_t> raw_data,
-                                     ONNX_NAMESPACE::TensorProto& output_proto,
-                                     const std::filesystem::path& external_file_path,
-                                     const ONNX_NAMESPACE::TensorProto& initializer,
-                                     bool is_prepacked) {
-  // update external_offset for alignment
-  // need to do padding before write actual tensor data as we do offset alignment at the begin of
-  // large tensors (offset need to be page aligned and alloction granularity aligned) like below:
-  // \242\2557\256\023.\031&0000000000000000\332)k+\253\246\342\246(&\006!\347\232\374\236\325\026\032+\36XXXX
-  // |<---small tensor---->|<---padding--->|<------------------large tensor----------------------------->|
-  if (align_info.align_offset && static_cast<int64_t>(tensor_bytes_size) > align_info.align_threshold) {
-    // Align to the larger of the page size or the allocation granularity
-    int64_t alignment_factor = std::max(static_cast<int64_t>(4096), align_info.allocation_granularity);
-    // Align to the next page or alloc granularity boundary
-    int64_t new_external_offset = static_cast<int64_t>(
-                                      std::floor((external_offset + alignment_factor - 1) / alignment_factor)) *
-                                  alignment_factor;
-
-    // padding tensor with zeros for alignment
-    InlinedVector<uint8_t> paddings;
-    size_t padding_size = SafeInt<size_t>(new_external_offset - external_offset);
-    paddings.reserve(padding_size);
-    for (size_t index = 0; index != padding_size; ++index) {
-      paddings.push_back(0x0);
-    }
-    external_stream.write(reinterpret_cast<const char*>(paddings.data()), padding_size);
-
-    external_offset = new_external_offset;
-  }
-
-  external_stream.write(reinterpret_cast<const char*>(raw_data.data()), tensor_bytes_size);
-
-  output_proto.set_data_location(ONNX_NAMESPACE::TensorProto_DataLocation::TensorProto_DataLocation_EXTERNAL);
-  ONNX_NAMESPACE::StringStringEntryProto* location = output_proto.add_external_data();
-  location->set_key("location");
-  location->set_value(ToUTF8String(external_file_path.native()));
-  ONNX_NAMESPACE::StringStringEntryProto* offset = output_proto.add_external_data();
-  offset->set_key("offset");
-  offset->set_value(std::to_string(external_offset));
-  ONNX_NAMESPACE::StringStringEntryProto* length = output_proto.add_external_data();
-  length->set_key("length");
-  length->set_value(std::to_string(tensor_bytes_size));
-
-  if (is_prepacked) {
-    ONNX_NAMESPACE::StringStringEntryProto* pre_packed = output_proto.add_external_data();
-    pre_packed->set_key("prepacked");
-    pre_packed->set_value("1");
-  }
-
-  output_proto.set_name(initializer.name());
-  output_proto.set_data_type(initializer.data_type());
-  for (int i = 0; i != initializer.dims_size(); ++i) {
-    output_proto.add_dims(initializer.dims(i));
-  }
-  output_proto.set_doc_string(initializer.doc_string());
-
-  external_offset += tensor_bytes_size;
-}
-
 ONNX_NAMESPACE::GraphProto Graph::ToGraphProtoWithExternalInitializers(const std::filesystem::path& external_file_path,
                                                                        const std::filesystem::path& model_file_path,
                                                                        size_t initializer_size_threshold,
-                                                                       const OffsetAlignmentInfo& align_info,
-                                                                       bool save_prepacked_constant_initializers,
-                                                                       PrePackedTensorProtoToSave& pre_packed_initializers) const {
+                                                                       const OffsetAlignmentInfo& align_info) const {
   GraphProto result;
   ToGraphProtoInternal(result);
   ORT_ENFORCE(external_file_path.is_relative());
@@ -4171,34 +4106,6 @@ ONNX_NAMESPACE::GraphProto Graph::ToGraphProtoWithExternalInitializers(const std
 #endif
 
   for (const auto& initializer : graph_proto_->initializer()) {
-    bool use_pre_packed_initializer = false;
-    InlinedVector<TensorProto> pre_packed_initializers_tensor_proto;
-    // If this initializer has been prepacked, saved prepacked external initializer instead of original one.
-    // Since one initializer could be used by multiple kernels and been prepacked differently,
-    // Save each prepacked initializers seperately, chagne the initializer name to [initializer_name]:[node_name]
-    // to avoid conflict. Change the node input name accordingly.
-    // IT could potentially make the ONNX data file larger since we store multiple prepacked initializers into disk
-    // but this could be rare case.
-    if (save_prepacked_constant_initializers && pre_packed_initializers.count(initializer.name())) {
-      for (const auto& item : pre_packed_initializers[initializer.name()]) {
-        auto& node_name = item.first;
-        std::string prepacked_initializer_name = utils::GetPrepackedInitializerName(initializer.name(), node_name);
-        pre_packed_initializers_tensor_proto.push_back(item.second);
-        use_pre_packed_initializer = true;
-
-        for (auto& node : *result.mutable_node()) {
-          if (node.name() == node_name) {
-            int input_index = 0;
-            for (const auto& input : node.input()) {
-              if (input == initializer.name()) {
-                node.set_input(input_index, prepacked_initializer_name);
-              }
-              input_index += 1;
-            }
-          }
-        }
-      }
-    }
 #if !defined(DISABLE_SPARSE_TENSORS)
     if (sparse_end != sparse_tensor_names_.find(initializer.name())) {
       // Sparse tensors are added to the ONNX file.
@@ -4207,39 +4114,61 @@ ONNX_NAMESPACE::GraphProto Graph::ToGraphProtoWithExternalInitializers(const std
       ORT_ENFORCE(status.IsOK(), "Failed to convert dense initializer to sparse");
     } else {
 #endif
-      if (use_pre_packed_initializer) {
-        for (const auto& pre_packed_initializer : pre_packed_initializers_tensor_proto) {
-          // Dense tensors larger than the threshold are added to the external file.
-          TensorProto* output_proto = result.add_initializer();
-          std::vector<uint8_t> raw_data;
-          size_t tensor_bytes_size = 0;
-
-          ORT_THROW_IF_ERROR(utils::UnpackInitializerData(pre_packed_initializer, model_path, raw_data));
-          tensor_bytes_size = raw_data.size();
-          if (tensor_bytes_size < initializer_size_threshold) {
-            *output_proto = pre_packed_initializer;
-            continue;
-          }
+      // Dense tensors larger than the threshold are added to the external file.
+      TensorProto* output_proto = result.add_initializer();
+
+      std::vector<uint8_t> raw_data;
+      ORT_THROW_IF_ERROR(utils::UnpackInitializerData(initializer, model_path, raw_data));
+      size_t tensor_bytes_size = raw_data.size();
+      if (tensor_bytes_size < initializer_size_threshold) {
+        *output_proto = initializer;
+        continue;
+      }
 
-          SetUpExternalInitializer(align_info, tensor_bytes_size, external_offset, external_stream,
-                                   raw_data, *output_proto, external_file_path, pre_packed_initializer, true);
-        }
-      } else {
-        // Dense tensors larger than the threshold are added to the external file.
-        TensorProto* output_proto = result.add_initializer();
-        std::vector<uint8_t> raw_data;
-        size_t tensor_bytes_size = 0;
-
-        ORT_THROW_IF_ERROR(utils::UnpackInitializerData(initializer, model_path, raw_data));
-        tensor_bytes_size = raw_data.size();
-        if (tensor_bytes_size < initializer_size_threshold) {
-          *output_proto = initializer;
-          continue;
+      // update external_offset for alignment
+      // need to do padding before write actual tensor data as we do offset alignment at the begin of
+      // large tensors (offset need to be page aligned and alloction granularity aligned) like below:
+      // \242\2557\256\023.\031&0000000000000000\332)k+\253\246\342\246(&\006!\347\232\374\236\325\026\032+\36XXXX
+      // |<---small tensor---->|<---padding--->|<------------------large tensor----------------------------->|
+      if (align_info.align_offset && static_cast<int64_t>(tensor_bytes_size) > align_info.align_threshold) {
+        // Align to the larger of the page size or the allocation granularity
+        int64_t alignment_factor = std::max(static_cast<int64_t>(4096), align_info.allocation_granularity);
+        // Align to the next page or alloc granularity boundary
+        int64_t new_external_offset = static_cast<int64_t>(
+                                          std::floor((external_offset + alignment_factor - 1) / alignment_factor)) *
+                                      alignment_factor;
+
+        // padding tensor with zeros for alignment
+        for (int64_t index = external_offset; index != new_external_offset; ++index) {
+          external_stream << '0';
         }
 
-        SetUpExternalInitializer(align_info, tensor_bytes_size, external_offset, external_stream,
-                                 raw_data, *output_proto, external_file_path, initializer, false);
+        external_offset = new_external_offset;
       }
+
+      for (size_t index = 0; index != tensor_bytes_size; ++index) {
+        external_stream << raw_data[index];
+      }
+
+      output_proto->set_data_location(ONNX_NAMESPACE::TensorProto_DataLocation::TensorProto_DataLocation_EXTERNAL);
+      ONNX_NAMESPACE::StringStringEntryProto* location = output_proto->add_external_data();
+      location->set_key("location");
+      location->set_value(ToUTF8String(external_file_path.native()));
+      ONNX_NAMESPACE::StringStringEntryProto* offset = output_proto->add_external_data();
+      offset->set_key("offset");
+      offset->set_value(std::to_string(external_offset));
+      ONNX_NAMESPACE::StringStringEntryProto* length = output_proto->add_external_data();
+      length->set_key("length");
+      length->set_value(std::to_string(tensor_bytes_size));
+
+      output_proto->set_name(initializer.name());
+      output_proto->set_data_type(initializer.data_type());
+      for (int i = 0; i != initializer.dims_size(); ++i) {
+        output_proto->add_dims(initializer.dims(i));
+      }
+      output_proto->set_doc_string(initializer.doc_string());
+
+      external_offset += tensor_bytes_size;
 #if !defined(DISABLE_SPARSE_TENSORS)
     }
 #endif
diff --git a/onnxruntime/core/graph/model.cc b/onnxruntime/core/graph/model.cc
index ad1ec9c8dedb3..1bae63b510563 100644
--- a/onnxruntime/core/graph/model.cc
+++ b/onnxruntime/core/graph/model.cc
@@ -384,17 +384,13 @@ ModelProto Model::ToProto() const {
 ModelProto Model::ToGraphProtoWithExternalInitializers(const std::filesystem::path& external_file_name,
                                                        const std::filesystem::path& file_path,
                                                        size_t initializer_size_threshold,
-                                                       const Graph::OffsetAlignmentInfo& align_info,
-                                                       bool save_prepacked_constant_initializers,
-                                                       Graph::PrePackedTensorProtoToSave& pre_packed_initializers) const {
+                                                       const Graph::OffsetAlignmentInfo& align_info) const {
   ModelProto result(model_proto_);
   const auto& graph = *graph_;
   *(result.mutable_graph()) = graph.ToGraphProtoWithExternalInitializers(external_file_name,
                                                                          file_path,
                                                                          initializer_size_threshold,
-                                                                         align_info,
-                                                                         save_prepacked_constant_initializers,
-                                                                         pre_packed_initializers);
+                                                                         align_info);
   return result;
 }
 
@@ -612,9 +608,7 @@ static Status SaveModelWithExternalInitializers(Model& model,
                                                 const T& file_path,
                                                 const std::filesystem::path& external_file_name,
                                                 size_t initializer_size_threshold,
-                                                const Graph::OffsetAlignmentInfo& align_info,
-                                                bool save_prepacked_constant_initializers,
-                                                Graph::PrePackedTensorProtoToSave& pre_packed_initializers) {
+                                                const Graph::OffsetAlignmentInfo& align_info) {
   int fd = 0;
   Status status = Env::Default().FileOpenWr(file_path, fd);
   ORT_RETURN_IF_ERROR(status);
@@ -622,8 +616,7 @@ static Status SaveModelWithExternalInitializers(Model& model,
   ORT_TRY {
     status = Model::SaveWithExternalInitializers(model, fd, file_path, external_file_name,
                                                  initializer_size_threshold,
-                                                 align_info, save_prepacked_constant_initializers,
-                                                 pre_packed_initializers);
+                                                 align_info);
   }
   ORT_CATCH(const std::exception& ex) {
     ORT_HANDLE_EXCEPTION([&]() {
@@ -654,12 +647,9 @@ Status Model::Load(const PathString& file_path, std::shared_ptr<Model>& p_model,
 Status Model::SaveWithExternalInitializers(Model& model, const std::filesystem::path& file_path,
                                            const std::filesystem::path& external_file_name,
                                            size_t initializer_size_threshold,
-                                           const Graph::OffsetAlignmentInfo& align_info,
-                                           bool save_prepacked_constant_initializers,
-                                           Graph::PrePackedTensorProtoToSave& pre_packed_initializers) {
+                                           const Graph::OffsetAlignmentInfo& align_info) {
   return SaveModelWithExternalInitializers(model, file_path, external_file_name, initializer_size_threshold,
-                                           align_info, save_prepacked_constant_initializers,
-                                           pre_packed_initializers);
+                                           align_info);
 }
 
 Status Model::LoadFromBytes(int count, const void* p_bytes, /*out*/ ONNX_NAMESPACE::ModelProto& model_proto) {
@@ -776,9 +766,7 @@ Status Model::SaveWithExternalInitializers(Model& model,
                                            const std::filesystem::path& file_path,
                                            const std::filesystem::path& external_file_name,
                                            size_t initializer_size_threshold,
-                                           const Graph::OffsetAlignmentInfo& align_info,
-                                           bool save_prepacked_constant_initializers,
-                                           Graph::PrePackedTensorProtoToSave& pre_packed_initializers) {
+                                           const Graph::OffsetAlignmentInfo& align_info) {
   if (fd < 0) {
     return Status(ONNXRUNTIME, INVALID_ARGUMENT, "<fd> is less than 0.");
   }
@@ -787,8 +775,7 @@ Status Model::SaveWithExternalInitializers(Model& model,
 
   auto model_proto = model.ToGraphProtoWithExternalInitializers(external_file_name, file_path,
                                                                 initializer_size_threshold,
-                                                                align_info, save_prepacked_constant_initializers,
-                                                                pre_packed_initializers);
+                                                                align_info);
   google::protobuf::io::FileOutputStream output(fd);
   const bool result = model_proto.SerializeToZeroCopyStream(&output) && output.Flush();
   if (result) {
diff --git a/onnxruntime/core/graph/model.h b/onnxruntime/core/graph/model.h
index 38d9044ff9d31..9bcec6f78ca08 100644
--- a/onnxruntime/core/graph/model.h
+++ b/onnxruntime/core/graph/model.h
@@ -191,17 +191,13 @@ class Model {
   ONNX_NAMESPACE::ModelProto ToGraphProtoWithExternalInitializers(const std::filesystem::path& external_file_name,
                                                                   const std::filesystem::path& file_path,
                                                                   size_t initializer_size_threshold,
-                                                                  const Graph::OffsetAlignmentInfo& align_info,
-                                                                  bool save_prepacked_constant_initializers,
-                                                                  Graph::PrePackedTensorProtoToSave& pre_packed_initializers) const;
+                                                                  const Graph::OffsetAlignmentInfo& align_info) const;
 
   ONNX_NAMESPACE::ModelProto ToGraphProtoWithExternalInitializers(const std::filesystem::path& external_file_name,
                                                                   const std::filesystem::path& file_path,
                                                                   size_t initializer_size_threshold) const {
     Graph::OffsetAlignmentInfo default_align_info;
-    Graph::PrePackedTensorProtoToSave pre_packed_initializers;
-    return ToGraphProtoWithExternalInitializers(external_file_name, file_path, initializer_size_threshold, default_align_info,
-                                                false, pre_packed_initializers);
+    return ToGraphProtoWithExternalInitializers(external_file_name, file_path, initializer_size_threshold, default_align_info);
   }
 
   static common::Status Save(Model& model, const PathString& file_path);
@@ -214,18 +210,14 @@ class Model {
                                                      const std::filesystem::path& file_path,
                                                      const std::filesystem::path& external_file_path,
                                                      size_t initializer_size_threshold,
-                                                     const Graph::OffsetAlignmentInfo& align_info,
-                                                     bool save_prepacked_constant_initializers,
-                                                     Graph::PrePackedTensorProtoToSave& pre_packed_initializers);
+                                                     const Graph::OffsetAlignmentInfo& align_info);
 
   static common::Status SaveWithExternalInitializers(Model& model,
                                                      const std::filesystem::path& file_path,
                                                      const std::filesystem::path& external_file_path,
                                                      size_t initializer_size_threshold) {
     Graph::OffsetAlignmentInfo default_align_info;
-    Graph::PrePackedTensorProtoToSave pre_packed_initializers;
-    return SaveWithExternalInitializers(model, file_path, external_file_path, initializer_size_threshold, default_align_info,
-                                        false, pre_packed_initializers);
+    return SaveWithExternalInitializers(model, file_path, external_file_path, initializer_size_threshold, default_align_info);
   }
 
   static common::Status SaveWithExternalInitializers(Model& model,
@@ -233,9 +225,7 @@ class Model {
                                                      const std::filesystem::path& file_path,
                                                      const std::filesystem::path& external_file_path,
                                                      size_t initializer_size_threshold,
-                                                     const Graph::OffsetAlignmentInfo& align_info,
-                                                     bool save_prepacked_constant_initializers,
-                                                     Graph::PrePackedTensorProtoToSave& pre_packed_initializers);
+                                                     const Graph::OffsetAlignmentInfo& align_info);
 
   static common::Status SaveWithExternalInitializers(Model& model,
                                                      int fd,
@@ -243,9 +233,7 @@ class Model {
                                                      const std::filesystem::path& external_file_path,
                                                      size_t initializer_size_threshold) {
     Graph::OffsetAlignmentInfo default_align_info;
-    Graph::PrePackedTensorProtoToSave pre_packed_initializers;
-    return SaveWithExternalInitializers(model, fd, file_path, external_file_path, initializer_size_threshold, default_align_info,
-                                        false, pre_packed_initializers);
+    return SaveWithExternalInitializers(model, fd, file_path, external_file_path, initializer_size_threshold, default_align_info);
   }
 
   static common::Status Load(std::istream& model_istream, ONNX_NAMESPACE::ModelProto* p_model_proto);
diff --git a/onnxruntime/core/providers/cpu/fp16/fp16_conv.cc b/onnxruntime/core/providers/cpu/fp16/fp16_conv.cc
index 0a1a3a5995872..37db095e92570 100644
--- a/onnxruntime/core/providers/cpu/fp16/fp16_conv.cc
+++ b/onnxruntime/core/providers/cpu/fp16/fp16_conv.cc
@@ -51,7 +51,6 @@ class FusedConvFp16 final : public OpKernel {
   Status Compute(OpKernelContext* context) const override;
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed, /*out*/ PrePackedWeights* prepacked_weights) override;
 
   Status UseSharedPrePackedBuffers(std::vector<BufferUniquePtr>& prepacked_buffers,
@@ -102,7 +101,6 @@ class FusedConvFp16 final : public OpKernel {
 };
 
 Status FusedConvFp16::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                              bool /*save_prepacked_initializers*/,
                               /*out*/ bool& is_packed,
                               /*out*/ PrePackedWeights* prepacked_weights) {
   is_packed = false;
diff --git a/onnxruntime/core/providers/cpu/math/gemm.cc b/onnxruntime/core/providers/cpu/math/gemm.cc
index dbc7becdf2397..5406dd1a40446 100644
--- a/onnxruntime/core/providers/cpu/math/gemm.cc
+++ b/onnxruntime/core/providers/cpu/math/gemm.cc
@@ -248,7 +248,6 @@ template void Gemm<float>::ComputeGemm(CBLAS_TRANSPOSE trans_a, CBLAS_TRANSPOSE
 
 template <typename T>
 Status Gemm<T>::PrePack(const Tensor& /* tensor */, int /* input_idx */, AllocatorPtr /*alloc_for_caching*/,
-                        bool /*save_prepacked_initializers*/,
                         /*out*/ bool& is_packed,
                         /*out*/ PrePackedWeights* /*prepacked_weight_for_caching*/) {
   is_packed = false;
@@ -257,7 +256,7 @@ Status Gemm<T>::PrePack(const Tensor& /* tensor */, int /* input_idx */, Allocat
 
 template <>
 Status Gemm<float>::PrePack(const Tensor& tensor, int input_idx,
-                            AllocatorPtr alloc, bool /*save_prepacked_initializers*/, /*out*/ bool& is_packed,
+                            AllocatorPtr alloc, /*out*/ bool& is_packed,
                             /*out*/ PrePackedWeights* prepacked_weights) {
   is_packed = false;
 
diff --git a/onnxruntime/core/providers/cpu/math/gemm.h b/onnxruntime/core/providers/cpu/math/gemm.h
index 92f05a7921f8b..953949732560d 100644
--- a/onnxruntime/core/providers/cpu/math/gemm.h
+++ b/onnxruntime/core/providers/cpu/math/gemm.h
@@ -21,7 +21,6 @@ class Gemm : protected GemmBase, public OpKernel {
   Status Compute(OpKernelContext* context) const override;
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
diff --git a/onnxruntime/core/providers/cpu/math/matmul.cc b/onnxruntime/core/providers/cpu/math/matmul.cc
index 8f2c2c53b188b..2c6d23e4de908 100644
--- a/onnxruntime/core/providers/cpu/math/matmul.cc
+++ b/onnxruntime/core/providers/cpu/math/matmul.cc
@@ -173,7 +173,6 @@ bool GemmPackBBfloat16(AllocatorPtr& alloc,
 #endif
 
 Status MatMul<float>::PrePack(const Tensor& tensor, int input_idx, /*out*/ AllocatorPtr alloc,
-                              bool /*save_prepacked_initializers*/,
                               /*out*/ bool& is_packed,
                               /*out*/ PrePackedWeights* prepacked_weights) {
   is_packed = false;
diff --git a/onnxruntime/core/providers/cpu/math/matmul.h b/onnxruntime/core/providers/cpu/math/matmul.h
index 0bb0e6c2ef596..b9bbe36583879 100644
--- a/onnxruntime/core/providers/cpu/math/matmul.h
+++ b/onnxruntime/core/providers/cpu/math/matmul.h
@@ -37,7 +37,6 @@ class MatMul<float> final : public OpKernel {
   }
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
diff --git a/onnxruntime/core/providers/cpu/nn/conv_transpose.cc b/onnxruntime/core/providers/cpu/nn/conv_transpose.cc
index 2c7afddf38070..f0c1b0b409831 100644
--- a/onnxruntime/core/providers/cpu/nn/conv_transpose.cc
+++ b/onnxruntime/core/providers/cpu/nn/conv_transpose.cc
@@ -38,7 +38,6 @@ ONNX_CPU_OPERATOR_KERNEL(
 
 template <typename T>
 Status ConvTranspose<T>::PrePack(const Tensor& /*tensor*/, int /*input_idx*/, AllocatorPtr /*alloc*/,
-                                 bool /*save_prepacked_initializers*/,
                                  /*out*/ bool& is_packed,
                                  /*out*/ PrePackedWeights* /*prepacked_weights*/
 ) {
@@ -48,7 +47,6 @@ Status ConvTranspose<T>::PrePack(const Tensor& /*tensor*/, int /*input_idx*/, Al
 
 template <>
 Status ConvTranspose<float>::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                                     bool /*save_prepacked_initializers*/,
                                      /*out*/ bool& is_packed,
                                      /*out*/ PrePackedWeights* prepacked_weights) {
   is_packed = false;
diff --git a/onnxruntime/core/providers/cpu/nn/conv_transpose.h b/onnxruntime/core/providers/cpu/nn/conv_transpose.h
index d03b5566e334f..c82cd5ad49d7e 100644
--- a/onnxruntime/core/providers/cpu/nn/conv_transpose.h
+++ b/onnxruntime/core/providers/cpu/nn/conv_transpose.h
@@ -28,7 +28,6 @@ class ConvTranspose : public OpKernel {
   ConvTranspose(const OpKernelInfo& info) : OpKernel(info), conv_transpose_attrs_(info) {}
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
diff --git a/onnxruntime/core/providers/cpu/nn/layer_norm_impl.cc b/onnxruntime/core/providers/cpu/nn/layer_norm_impl.cc
index fe2bf1035bb65..24a5dcab225c4 100644
--- a/onnxruntime/core/providers/cpu/nn/layer_norm_impl.cc
+++ b/onnxruntime/core/providers/cpu/nn/layer_norm_impl.cc
@@ -229,7 +229,6 @@ Status LayerNormImpl::Compute(OpKernelContext* p_ctx) const {
 }
 
 Status LayerNormImpl::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                              bool /*save_prepacked_initializers*/,
                               bool& is_packed, PrePackedWeights* prepacked_weights) {
   ORT_UNUSED_PARAMETER(prepacked_weights);
 
diff --git a/onnxruntime/core/providers/cpu/nn/layer_norm_impl.h b/onnxruntime/core/providers/cpu/nn/layer_norm_impl.h
index abce87d03c14b..f8b528b398cba 100644
--- a/onnxruntime/core/providers/cpu/nn/layer_norm_impl.h
+++ b/onnxruntime/core/providers/cpu/nn/layer_norm_impl.h
@@ -15,7 +15,7 @@ class LayerNormImpl : public OpKernel {
   LayerNormImpl(const OpKernelInfo& op_kernel_info, bool simplified = false, bool contrib_op = false);
   Status Compute(OpKernelContext* p_op_kernel_context) const override;
 
-  Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc, bool save_prepacked_initializers,
+  Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
                  bool& is_packed, PrePackedWeights* prepacked_weights) override;
 
   // This method was created so that it can be called directly from `test/onnx/microbenchmark/layer_normalization.cc`.
diff --git a/onnxruntime/core/providers/cpu/quantization/matmul_integer_base.h b/onnxruntime/core/providers/cpu/quantization/matmul_integer_base.h
index 8a8ce27990069..e26eae19b8fd4 100644
--- a/onnxruntime/core/providers/cpu/quantization/matmul_integer_base.h
+++ b/onnxruntime/core/providers/cpu/quantization/matmul_integer_base.h
@@ -14,7 +14,6 @@ class MatMulIntegerBase : public OpKernel {
   MatMulIntegerBase(const OpKernelInfo& info) : OpKernel(info) {}
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool /*save_prepacked_initializers*/,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override {
     is_packed = false;
diff --git a/onnxruntime/core/providers/cpu/quantization/qlinearconv.cc b/onnxruntime/core/providers/cpu/quantization/qlinearconv.cc
index 736cde24591ff..7797cbe678bd4 100644
--- a/onnxruntime/core/providers/cpu/quantization/qlinearconv.cc
+++ b/onnxruntime/core/providers/cpu/quantization/qlinearconv.cc
@@ -25,7 +25,6 @@ class QLinearConv : public OpKernel {
   Status Compute(OpKernelContext* context) const override;
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
@@ -361,7 +360,6 @@ REGISTER_QLINEARCONV_INT8_KERNEL(kMSDomain, 1);
 
 template <typename ActType>
 Status QLinearConv<ActType>::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                                     bool /*save_prepacked_initializers*/,
                                      /*out*/ bool& is_packed,
                                      /*out*/ PrePackedWeights* prepacked_weights) {
   is_packed = false;
diff --git a/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.cc b/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.cc
index 7afd00eacef89..b78c5236e6fab 100644
--- a/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.cc
+++ b/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.cc
@@ -284,7 +284,6 @@ bool DeepCpuGruOp::TryPackRecurrentWeights(const Tensor& weights, AllocatorPtr&
 }
 
 Status DeepCpuGruOp::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                             bool /*save_prepacked_initializers*/,
                              bool& is_packed, PrePackedWeights* prepacked_weights) {
   is_packed = false;
 
diff --git a/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.h b/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.h
index 914077b2f2c15..5a6dd97c7c3f2 100644
--- a/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.h
+++ b/onnxruntime/core/providers/cpu/rnn/deep_cpu_gru.h
@@ -62,7 +62,6 @@ class DeepCpuGruOp final : public OpKernel {
 
  private:
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
@@ -198,4 +197,4 @@ class UniDirectionalGru {
 };
 }  // namespace detail
 
-}  // namespace onnxruntime
\ No newline at end of file
+}  // namespace onnxruntime
diff --git a/onnxruntime/core/providers/cpu/rnn/deep_cpu_lstm.cc b/onnxruntime/core/providers/cpu/rnn/deep_cpu_lstm.cc
index e4082e5d7634a..09bbf6c4c79e6 100644
--- a/onnxruntime/core/providers/cpu/rnn/deep_cpu_lstm.cc
+++ b/onnxruntime/core/providers/cpu/rnn/deep_cpu_lstm.cc
@@ -225,9 +225,7 @@ static void UseSharedPrePackedBuffersImpl(std::vector<BufferUniquePtr>& prepacke
 }
 
 Status DeepCpuLstmOp::PrePack(const Tensor& tensor, int input_idx,
-                              AllocatorPtr alloc,
-                              bool /*save_prepacked_initializers*/,
-                              /*out*/ bool& is_packed,
+                              AllocatorPtr alloc, /*out*/ bool& is_packed,
                               /*out*/ PrePackedWeights* prepacked_weights) {
   is_packed = false;
 
diff --git a/onnxruntime/core/providers/cpu/rnn/deep_cpu_lstm.h b/onnxruntime/core/providers/cpu/rnn/deep_cpu_lstm.h
index ff8ab9abf0eed..9c4c12954022a 100644
--- a/onnxruntime/core/providers/cpu/rnn/deep_cpu_lstm.h
+++ b/onnxruntime/core/providers/cpu/rnn/deep_cpu_lstm.h
@@ -19,7 +19,6 @@ class DeepCpuLstmOp final : public OpKernel, public LSTMBase {
   DeepCpuLstmOp(const OpKernelInfo& info) : OpKernel(info), LSTMBase(info) {}
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
diff --git a/onnxruntime/core/providers/cuda/nn/conv.cc b/onnxruntime/core/providers/cuda/nn/conv.cc
index 45a1d3bbc0414..3129f519da2e5 100644
--- a/onnxruntime/core/providers/cuda/nn/conv.cc
+++ b/onnxruntime/core/providers/cuda/nn/conv.cc
@@ -52,7 +52,6 @@ REGISTER_KERNEL_TYPED(MLFloat16, kMSInternalNHWCDomain, true)
 // First input (in this case X) is in case NHWC == true also in NHWC format, the other inputs in NCHW
 template <typename T, bool NHWC>
 Status Conv<T, NHWC>::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                              bool /*save_prepacked_initializers*/,
                               bool& is_packed, PrePackedWeights* /*prepacked_weights*/) {
   is_packed = false;
   // only layout of weight input is adjusted via PrePack
diff --git a/onnxruntime/core/providers/cuda/nn/conv.h b/onnxruntime/core/providers/cuda/nn/conv.h
index 6294566af3cb9..e4047a6af272e 100644
--- a/onnxruntime/core/providers/cuda/nn/conv.h
+++ b/onnxruntime/core/providers/cuda/nn/conv.h
@@ -219,7 +219,6 @@ class Conv : public CudaKernel {
   }
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  bool& is_packed, PrePackedWeights* prepacked_weights) override;
 
   Status ComputeInternal(OpKernelContext* context) const override;
diff --git a/onnxruntime/core/providers/cuda/nn/conv_transpose.cc b/onnxruntime/core/providers/cuda/nn/conv_transpose.cc
index 9c9a83460daeb..2972ae999adc4 100644
--- a/onnxruntime/core/providers/cuda/nn/conv_transpose.cc
+++ b/onnxruntime/core/providers/cuda/nn/conv_transpose.cc
@@ -45,8 +45,7 @@ REGISTER_KERNEL_TYPED(MLFloat16, kMSInternalNHWCDomain, true)
 
 // First input (in this case X) is in case NHWC == true also in NHWC format, the other inputs in NCHW
 template <typename T, bool NHWC>
-Status ConvTranspose<T, NHWC>::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                                       bool /*save_prepacked_initializers*/, bool& is_packed,
+Status ConvTranspose<T, NHWC>::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc, bool& is_packed,
                                        [[maybe_unused]] PrePackedWeights* prepacked_weights) {
   is_packed = false;
   // only layout of weight input is adjusted via PrePack
diff --git a/onnxruntime/core/providers/cuda/nn/conv_transpose.h b/onnxruntime/core/providers/cuda/nn/conv_transpose.h
index f23c2b94501f2..1a6957164d22f 100644
--- a/onnxruntime/core/providers/cuda/nn/conv_transpose.h
+++ b/onnxruntime/core/providers/cuda/nn/conv_transpose.h
@@ -22,7 +22,6 @@ class ConvTranspose : public CudaKernel {
 
   ConvTranspose(const OpKernelInfo& info) : CudaKernel(info), conv_transpose_attrs_(info) {};
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  bool& is_packed, [[maybe_unused]] PrePackedWeights* prepacked_weights) override;
   Status ComputeInternal(OpKernelContext* context) const override;
   Status DoConvTranspose(OpKernelContext* context, bool dynamic_padding) const;
diff --git a/onnxruntime/core/providers/js/operators/conv.h b/onnxruntime/core/providers/js/operators/conv.h
index 276b600cf40d2..b04df44954295 100644
--- a/onnxruntime/core/providers/js/operators/conv.h
+++ b/onnxruntime/core/providers/js/operators/conv.h
@@ -78,7 +78,6 @@ class ConvBase : public JsKernel {
   }
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* /* prepacked_weights */) override {
     is_packed = false;
diff --git a/onnxruntime/core/providers/js/operators/conv_transpose.h b/onnxruntime/core/providers/js/operators/conv_transpose.h
index baa93f825a203..5ff52e8fda4fa 100644
--- a/onnxruntime/core/providers/js/operators/conv_transpose.h
+++ b/onnxruntime/core/providers/js/operators/conv_transpose.h
@@ -126,10 +126,8 @@ class ConvTranspose : public JsKernel {
   }
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* /* prepacked_weights */) override {
-    ORT_UNUSED_PARAMETER(save_prepacked_initializers);
     is_packed = false;
 
     if (input_idx == 1) {
diff --git a/onnxruntime/core/providers/xnnpack/math/gemm.cc b/onnxruntime/core/providers/xnnpack/math/gemm.cc
index 68b55030c7363..35a06cb7eb89f 100644
--- a/onnxruntime/core/providers/xnnpack/math/gemm.cc
+++ b/onnxruntime/core/providers/xnnpack/math/gemm.cc
@@ -117,7 +117,6 @@ Gemm::Gemm(const OpKernelInfo& info) : GemmBase(info), XnnpackKernel(info, /*ena
 }
 
 Status Gemm::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr,
-                     bool /*save_prepacked_initializers*/,
                      /*out*/ bool& is_packed,
                      /*out*/ PrePackedWeights*) {
   is_packed = false;
diff --git a/onnxruntime/core/providers/xnnpack/math/gemm.h b/onnxruntime/core/providers/xnnpack/math/gemm.h
index d632eef015f9a..954aab0698b9c 100644
--- a/onnxruntime/core/providers/xnnpack/math/gemm.h
+++ b/onnxruntime/core/providers/xnnpack/math/gemm.h
@@ -23,7 +23,6 @@ class Gemm : protected GemmBase, public XnnpackKernel {
   static bool IsOnnxNodeSupported(const NodeUnit& node_unit, const GraphViewer& graph);
 
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
diff --git a/onnxruntime/core/providers/xnnpack/math/matmul.cc b/onnxruntime/core/providers/xnnpack/math/matmul.cc
index 71a11cb05d9af..44a6fb4ee835a 100644
--- a/onnxruntime/core/providers/xnnpack/math/matmul.cc
+++ b/onnxruntime/core/providers/xnnpack/math/matmul.cc
@@ -78,7 +78,6 @@ MatMul::MatMul(const OpKernelInfo& info) : XnnpackKernel(info, /*enable_caches*/
 }
 
 Status MatMul::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                       bool /*save_prepacked_initializers*/,
                        /*out*/ bool& is_packed,
                        /*out*/ PrePackedWeights* /*Not used*/) {
   is_packed = false;
diff --git a/onnxruntime/core/providers/xnnpack/math/matmul.h b/onnxruntime/core/providers/xnnpack/math/matmul.h
index 31a8c36ad418b..188cc73189af5 100644
--- a/onnxruntime/core/providers/xnnpack/math/matmul.h
+++ b/onnxruntime/core/providers/xnnpack/math/matmul.h
@@ -23,7 +23,6 @@ class MatMul : public XnnpackKernel {
   // Required for checking XNNpack restrictions on ORT side
   static bool IsOnnxNodeSupported(const NodeUnit& node_unit, const GraphViewer& graph);
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 
diff --git a/onnxruntime/core/providers/xnnpack/nn/conv.cc b/onnxruntime/core/providers/xnnpack/nn/conv.cc
index f2e697df475da..4e6b308e28ae5 100644
--- a/onnxruntime/core/providers/xnnpack/nn/conv.cc
+++ b/onnxruntime/core/providers/xnnpack/nn/conv.cc
@@ -18,7 +18,6 @@ namespace xnnpack {
 
 // use PrePack to handle the weight layout change as that's not a simple NCHW -> NHWC transpose
 Status Conv::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                     bool /*save_prepacked_initializers*/,
                      /*out*/ bool& is_packed,
                      /*out*/ PrePackedWeights* /*prepacked_weights*/) {
   is_packed = false;
diff --git a/onnxruntime/core/providers/xnnpack/nn/conv.h b/onnxruntime/core/providers/xnnpack/nn/conv.h
index 762b68c8bd49a..3630aae208d49 100644
--- a/onnxruntime/core/providers/xnnpack/nn/conv.h
+++ b/onnxruntime/core/providers/xnnpack/nn/conv.h
@@ -19,7 +19,6 @@ class Conv : public ConvBase {
 
   // use PrePack to handle the weight layout change as that's not a simple NCHW -> NHWC transpose
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 };
diff --git a/onnxruntime/core/providers/xnnpack/nn/conv_transpose.cc b/onnxruntime/core/providers/xnnpack/nn/conv_transpose.cc
index 5729565b2feb9..b6930a5fc92d1 100644
--- a/onnxruntime/core/providers/xnnpack/nn/conv_transpose.cc
+++ b/onnxruntime/core/providers/xnnpack/nn/conv_transpose.cc
@@ -15,7 +15,6 @@ namespace xnnpack {
 
 // use PrePack to handle the weight layout change as that's not a simple NCHW -> NHWC transpose
 Status ConvTranspose::PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                              bool /*save_prepacked_initializers*/,
                               /*out*/ bool& is_packed,
                               /*out*/ PrePackedWeights* /*prepacked_weights*/) {
   is_packed = false;
diff --git a/onnxruntime/core/providers/xnnpack/nn/conv_transpose.h b/onnxruntime/core/providers/xnnpack/nn/conv_transpose.h
index 0313515d10fa1..866b9b6b98365 100644
--- a/onnxruntime/core/providers/xnnpack/nn/conv_transpose.h
+++ b/onnxruntime/core/providers/xnnpack/nn/conv_transpose.h
@@ -18,7 +18,6 @@ class ConvTranspose : public ConvBase {
 
   // use PrePack to handle the weight layout change as that's not a simple NCHW -> NHWC transpose
   Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
-                 bool save_prepacked_initializers,
                  /*out*/ bool& is_packed,
                  /*out*/ PrePackedWeights* prepacked_weights) override;
 };
diff --git a/onnxruntime/core/session/inference_session.cc b/onnxruntime/core/session/inference_session.cc
index bc5db98e7c595..2ff9fa525fa3b 100644
--- a/onnxruntime/core/session/inference_session.cc
+++ b/onnxruntime/core/session/inference_session.cc
@@ -2062,11 +2062,9 @@ common::Status InferenceSession::Initialize() {
 #endif  // !defined(ORT_MINIMAL_BUILD) || defined(ORT_EXTENDED_MINIMAL_BUILD)
     }
 
-    SessionState::PrePackInitializers pre_packed_initializers;
     ORT_RETURN_IF_ERROR_SESSIONID_(
         session_state_->FinalizeSessionState(model_location_, kernel_registry_manager_,
                                              // need to keep the initializers if saving the optimized model
-                                             pre_packed_initializers,
                                              !saving_model,
                                              saving_ort_format));
 
@@ -2102,47 +2100,11 @@ common::Status InferenceSession::Initialize() {
                   kOrtSessionOptionsOptimizedModelExternalInitializersMinSizeInBytes, "1024"));
           Graph::OffsetAlignmentInfo align_info;
           align_info.align_offset = true;
-          bool save_prepacked_constant_initializers =
-              session_options_.config_options.GetConfigOrDefault(kOrtSessionOptionsSavePrePackedConstantInitializers, "0") == "1" ? true : false;
-          Graph::PrePackedTensorProtoToSave pre_packed_initializers_tensor_proto;
-          if (save_prepacked_constant_initializers) {
-            LOGS(*session_logger_, WARNING) << "Serialize prepacked initializers option has been turn on."
-                                            << "Use this option only when run model inference on PC with CPU."
-                                            << "Make sure to save and load model in same device as prepack is device specific."
-                                            << "Note: this feature in only work with ONNX model format."
-                                            << "Process of use this option is like below:"
-                                            << "1. Optimize model with external data file with save_prepacked_constant_initializers on:"
-                                            << "       sample: sess_options.add_session_config_entry('session.save_prepacked_constant_initializers',  ' 1 ')"
-                                            << "   With save_prepacked_constant_initializers option, prepacked initializer will be serialized into data file."
-                                            << "2. Load optimized model and external data file in same device, no prepack is need."
-                                            << "3. Run inference with optimized model.";
-
-            if (fbs::utils::IsOrtFormatModel(session_options_.optimized_model_filepath)) {
-              ORT_RETURN_IF_ERROR_SESSIONID_(
-                  ORT_MAKE_STATUS(ONNXRUNTIME, FAIL,
-                                  "Unable to serialize prepacked external constant initializer for ORT format model."
-                                  "Please use ONNX format model with save_prepacked_constant_initializers."));
-            }
-
-            // convert pre_packed_initializers to tensorproto format and save to external data file
-            for (const auto& name_item_pair : pre_packed_initializers.pre_packed_initializers_to_save) {
-              auto initializer_name = name_item_pair.first;
-
-              for (const auto& kernel_name_initializer_item_pair : name_item_pair.second) {
-                auto kernel_name = kernel_name_initializer_item_pair.first;
-                auto prepacked_initializer_name = utils::GetPrepackedInitializerName(initializer_name, kernel_name);
-
-                pre_packed_initializers_tensor_proto[initializer_name][kernel_name] = utils::TensorToTensorProto(kernel_name_initializer_item_pair.second, prepacked_initializer_name);
-              }
-            }
-          }
           ORT_RETURN_IF_ERROR_SESSIONID_(Model::SaveWithExternalInitializers(*model_,
                                                                              session_options_.optimized_model_filepath,
                                                                              optimized_model_external_initializers_file_name,
                                                                              optimized_model_external_initializers_min_size_in_bytes,
-                                                                             align_info,
-                                                                             save_prepacked_constant_initializers,
-                                                                             pre_packed_initializers_tensor_proto));
+                                                                             align_info));
         }
       }
     }
diff --git a/onnxruntime/test/framework/inference_session_test.cc b/onnxruntime/test/framework/inference_session_test.cc
index 9c7e6e9761728..c6a81e8a1c1ad 100644
--- a/onnxruntime/test/framework/inference_session_test.cc
+++ b/onnxruntime/test/framework/inference_session_test.cc
@@ -46,7 +46,6 @@
 #include "core/session/environment.h"
 #include "core/session/IOBinding.h"
 #include "core/session/inference_session_utils.h"
-#include "core/session/onnxruntime_cxx_api.h"
 #include "core/session/onnxruntime_session_options_config_keys.h"
 #include "core/session/onnxruntime_run_options_config_keys.h"
 #include "dummy_provider.h"
@@ -66,8 +65,6 @@ using namespace ONNX_NAMESPACE;
 using namespace onnxruntime::logging;
 using namespace onnxruntime::concurrency;
 
-extern std::unique_ptr<Ort::Env> ort_env;
-
 namespace {
 struct KernelRegistryAndStatus {
   std::shared_ptr<onnxruntime::KernelRegistry> kernel_registry = std::make_shared<onnxruntime::KernelRegistry>();
@@ -500,57 +497,6 @@ TEST(InferenceSessionTests, TestModelSerialization) {
   ASSERT_TRUE(session_object_emptyValidation.Initialize().IsOK());
 }
 
-// Test feature serialize prepack weight is only used in PC with CPU on inference,
-// disable this test for training, other device and eps
-#if !ENABLE_TRAINING && !defined(USE_CUDA) && !defined(__wasm__) && !defined(USE_DNNL) && !defined(USE_QNN) && !defined(__ANDROID__) && !defined(USE_COREML)
-// MLAS dispatcher used in matmul_nbits kernels here is 64 bit only
-#if defined(__amd64__) || defined(_M_AMD64) || defined(__aarch64__) || defined(_M_ARM64)
-TEST(InferenceSessionTests, TestPrePackSerialization) {
-  SessionOptions so;
-  std::string model_name = "model_with_matmul_nbits";
-
-  const std::string test_model = "testdata/prepack/" + model_name + ".onnx";
-  const std::string optimized_model = "testdata/prepack/" + model_name + "_opt.onnx";
-
-  so.session_logid = "InferenceSessionTests.TestPrepackSerialization";
-  so.enable_cpu_mem_arena = false;
-  so.graph_optimization_level = TransformerLevel::Default;
-  so.optimized_model_filepath = optimized_model;
-  std::string external_initializer_file_name = model_name + "_opt.onnx.data";
-
-  // enable serialize prepack initializer to data file
-  ASSERT_STATUS_OK(so.config_options.AddConfigEntry(kOrtSessionOptionsSavePrePackedConstantInitializers,
-                                                    "1"));
-  // always save external initializer to data file for test
-  ASSERT_STATUS_OK(so.config_options.AddConfigEntry(kOrtSessionOptionsOptimizedModelExternalInitializersMinSizeInBytes,
-                                                    "0"));
-  ASSERT_STATUS_OK(so.config_options.AddConfigEntry(kOrtSessionOptionsOptimizedModelExternalInitializersFileName,
-                                                    external_initializer_file_name.c_str()));
-
-  // optimize model with serialize prepack constant initializers
-  InferenceSessionWrapper session_object{so, GetEnvironment()};
-  ASSERT_TRUE(session_object.Load(test_model).IsOK());
-  ASSERT_TRUE(session_object.Initialize().IsOK());
-
-  // Verify prepack initializers are serialized into optimized model and data file
-  // load optimized model and check initializer are prepacked
-  auto logger = DefaultLoggingManager().CreateLogger("TestPrepackSerialization");
-  std::shared_ptr<Model> model;
-  auto load_status = Model::Load(ToWideString(optimized_model), model, nullptr, *logger);
-  ASSERT_EQ(Status::OK(), load_status);
-  Graph& graph = model->MainGraph();
-
-  bool found_prepack_initializer = false;
-  for (const auto& item : graph.GetAllInitializedTensors()) {
-    if (item.first.find(':') != std::string::npos) {
-      found_prepack_initializer = true;
-    }
-  }
-  ASSERT_TRUE(found_prepack_initializer);
-}
-#endif
-#endif
-
 #ifdef ORT_RUN_EXTERNAL_ONNX_TESTS
 static bool Compare(const InputDefList& f_arg, const InputDefList& s_arg) {
   if (f_arg.size() != s_arg.size()) {
diff --git a/onnxruntime/test/framework/save_model_with_external_initializers.cc b/onnxruntime/test/framework/save_model_with_external_initializers.cc
index 0f76cb61ace74..d0bc088175755 100644
--- a/onnxruntime/test/framework/save_model_with_external_initializers.cc
+++ b/onnxruntime/test/framework/save_model_with_external_initializers.cc
@@ -7,7 +7,6 @@
 #include "core/framework/data_types.h"
 #include "core/graph/model.h"
 #include "core/framework/tensorprotoutils.h"
-#include "core/framework/session_state.h"
 #include "test/test_environment.h"
 #include "test_utils.h"
 #include "test/util/include/asserts.h"
@@ -20,34 +19,19 @@ using namespace onnxruntime;
 namespace onnxruntime {
 namespace test {
 
-std::vector<std::string> split(const std::string& str, char delimiter) {
-  std::vector<std::string> result;
-  std::stringstream ss(str);
-  std::string token;
-
-  // Use getline with a delimiter to split the string
-  while (std::getline(ss, token, delimiter)) {
-    result.push_back(token);
-  }
-
-  return result;
-}
-
 Status LoadSaveAndCompareModel(const std::filesystem::path& input_onnx,
                                const std::filesystem::path& input_external_init_file,
                                const std::filesystem::path& output_onnx,
                                const std::filesystem::path& output_external_init_file,
                                size_t initializer_size_threshold,
-                               const Graph::OffsetAlignmentInfo& align_info,
-                               Graph::PrePackedTensorProtoToSave& pre_packed_initializers_tensor_proto,
-                               bool save_prepacked_constant_initializers = false) {
+                               const Graph::OffsetAlignmentInfo& align_info) {
   auto logger = DefaultLoggingManager().CreateLogger("LoadSaveAndCompareModel");
   std::shared_ptr<Model> model;
   ORT_RETURN_IF_ERROR(Model::Load(input_onnx, model, nullptr, *logger));
   std::filesystem::remove(output_onnx);
   std::filesystem::remove(output_external_init_file);
   ORT_RETURN_IF_ERROR(Model::SaveWithExternalInitializers(*model, output_onnx, output_external_init_file, initializer_size_threshold,
-                                                          align_info, save_prepacked_constant_initializers, pre_packed_initializers_tensor_proto));
+                                                          align_info));
 
   std::shared_ptr<Model> model_from_external;
   ORT_RETURN_IF_ERROR(Model::Load(output_onnx.native(), model_from_external, nullptr, *logger));
@@ -66,11 +50,10 @@ Status LoadSaveAndCompareModel(const std::filesystem::path& input_onnx,
   // Compare the initializers of the two versions.
   std::filesystem::path model_path{};
   std::filesystem::path external_data_path{};
-  for (const auto& i : initializers_from_external) {
+  for (const auto& i : initializers) {
     const std::string kInitName = i.first;
-    const ONNX_NAMESPACE::TensorProto* from_external_tensor_proto = i.second;
-    // prepack initializer will have name as [original name]:[kernel name] in case initializer used by multiple kernels
-    const ONNX_NAMESPACE::TensorProto* tensor_proto = save_prepacked_constant_initializers ? initializers[split(kInitName, ':')[0]] : initializers[kInitName];
+    const ONNX_NAMESPACE::TensorProto* tensor_proto = i.second;
+    const ONNX_NAMESPACE::TensorProto* from_external_tensor_proto = initializers_from_external[kInitName];
 
     std::vector<uint8_t> tensor_proto_data;
     model_path = input_onnx;
@@ -92,12 +75,8 @@ Status LoadSaveAndCompareModel(const std::filesystem::path& input_onnx,
       ORT_RETURN_IF_NOT(from_external_tensor_proto->data_location() == ONNX_NAMESPACE::TensorProto_DataLocation::TensorProto_DataLocation_EXTERNAL, "location mismatch");
     }
 
-    if (!save_prepacked_constant_initializers) {
-      ORT_RETURN_IF_NOT(tensor_proto_size == from_external_tensor_proto_size, "size mismatch");
-      ORT_RETURN_IF_NOT(memcmp(tensor_proto_data.data(), from_external_tensor_proto_data.data(), tensor_proto_size) == 0, "data mismatch");
-    } else {
-      ORT_RETURN_IF_NOT(from_external_tensor_proto_size >= tensor_proto_size, "prepack initializer's size is at least same as original tensor, might be larger");
-    }
+    ORT_RETURN_IF_NOT(tensor_proto_size == from_external_tensor_proto_size, "size mismatch");
+    ORT_RETURN_IF_NOT(memcmp(tensor_proto_data.data(), from_external_tensor_proto_data.data(), tensor_proto_size) == 0, "data mismatch");
 
     if (align_info.align_offset) {
       for (const StringStringEntryProto& entry : from_external_tensor_proto->external_data()) {
@@ -110,7 +89,6 @@ Status LoadSaveAndCompareModel(const std::filesystem::path& input_onnx,
       }
     }
   }
-
   // Cleanup.
   ORT_RETURN_IF_NOT(std::filesystem::remove(output_onnx), "delete file failed");
   ORT_RETURN_IF_NOT(std::filesystem::remove(external_data_path), "delete file failed");
@@ -120,15 +98,13 @@ Status LoadSaveAndCompareModel(const std::filesystem::path& input_onnx,
 // Original model does not have external initializers
 TEST(SaveWithExternalInitializers, Mnist) {
   Graph::OffsetAlignmentInfo align_info;
-  Graph::PrePackedTensorProtoToSave pre_packed_initializers_tensor_proto;
-  ASSERT_STATUS_OK(LoadSaveAndCompareModel(ORT_TSTR("testdata/mnist.onnx"), ORT_TSTR(""), ORT_TSTR("testdata/mnist_with_external_initializers.onnx"), ORT_TSTR("mnist_external_initializers.bin"), 100, align_info, pre_packed_initializers_tensor_proto));
+  ASSERT_STATUS_OK(LoadSaveAndCompareModel(ORT_TSTR("testdata/mnist.onnx"), ORT_TSTR(""), ORT_TSTR("testdata/mnist_with_external_initializers.onnx"), ORT_TSTR("mnist_external_initializers.bin"), 100, align_info));
 }
 
 // Original model has external initializers
 TEST(SaveWithExternalInitializers, ModelWithOriginalExternalData) {
   Graph::OffsetAlignmentInfo align_info;
-  Graph::PrePackedTensorProtoToSave pre_packed_initializers_tensor_proto;
-  ASSERT_STATUS_OK(LoadSaveAndCompareModel(ORT_TSTR("testdata/model_with_orig_ext_data.onnx"), ORT_TSTR("model_with_orig_ext_data.onnx.data"), ORT_TSTR("testdata/model_with_new_external_initializers.onnx"), ORT_TSTR("model_with_new_external_initializers.bin"), 0, align_info, pre_packed_initializers_tensor_proto));
+  ASSERT_STATUS_OK(LoadSaveAndCompareModel(ORT_TSTR("testdata/model_with_orig_ext_data.onnx"), ORT_TSTR("model_with_orig_ext_data.onnx.data"), ORT_TSTR("testdata/model_with_new_external_initializers.onnx"), ORT_TSTR("model_with_new_external_initializers.bin"), 0, align_info));
 }
 
 // Original model has external initializers, align offset
@@ -136,22 +112,7 @@ TEST(SaveWithExternalInitializers, ModelWithOriginalExternalDataAlignOffset) {
   Graph::OffsetAlignmentInfo align_info;
   align_info.align_offset = true;
   align_info.align_threshold = 0;
-  Graph::PrePackedTensorProtoToSave pre_packed_initializers_tensor_proto;
-  ASSERT_STATUS_OK(LoadSaveAndCompareModel(ORT_TSTR("testdata/model_with_orig_ext_data.onnx"), ORT_TSTR("model_with_orig_ext_data.onnx.data"), ORT_TSTR("testdata/model_with_new_external_initializers.onnx"), ORT_TSTR("model_with_new_external_initializers.bin"), 0, align_info, pre_packed_initializers_tensor_proto));
-}
-
-// Original model has external initializers, align offset and serialize prepacked external initializer to model file
-TEST(SaveWithExternalInitializers, ModelWithOriginalExternalDataAlignOffsetAndSavePrepackTensors) {
-  Graph::OffsetAlignmentInfo align_info;
-  align_info.align_offset = true;
-  align_info.align_threshold = 0;
-  std::shared_ptr<CPUAllocator> alloc = std::make_shared<CPUAllocator>();
-  TensorShape shape = {178};
-  // prepack both initializers for test purpose
-  Graph::PrePackedTensorProtoToSave pre_packed_initializers_tensor_proto;
-  pre_packed_initializers_tensor_proto["MatMul.Weight"]["MatMul_0"] = utils::TensorToTensorProto(Tensor(DataTypeImpl::GetType<uint8_t>(), shape, alloc), "MatMul.Weight:MatMul_0");
-  pre_packed_initializers_tensor_proto["scales"]["MatMul_0"] = utils::TensorToTensorProto(Tensor(DataTypeImpl::GetType<float>(), shape, alloc), "scales:MatMul_0");
-  ASSERT_STATUS_OK(LoadSaveAndCompareModel(ORT_TSTR("testdata/prepack/model_with_matmul_nbits.onnx"), ORT_TSTR("model_with_matmul_nbits.onnx.data"), ORT_TSTR("testdata/prepack/model_with_matmul_nbits_opt.onnx"), ORT_TSTR("model_with_matmul_nbits_opt.onnx.data"), 0, align_info, pre_packed_initializers_tensor_proto, true));
+  ASSERT_STATUS_OK(LoadSaveAndCompareModel(ORT_TSTR("testdata/model_with_orig_ext_data.onnx"), ORT_TSTR("model_with_orig_ext_data.onnx.data"), ORT_TSTR("testdata/model_with_new_external_initializers.onnx"), ORT_TSTR("model_with_new_external_initializers.bin"), 0, align_info));
 }
 
 }  // namespace test
diff --git a/onnxruntime/test/framework/session_state_test.cc b/onnxruntime/test/framework/session_state_test.cc
index 6265eccb7bd9b..b94d24a1b180b 100644
--- a/onnxruntime/test/framework/session_state_test.cc
+++ b/onnxruntime/test/framework/session_state_test.cc
@@ -372,11 +372,10 @@ class PrePackingTestOpKernel : public OpKernel {
     return Status::OK();
   }
 
-  Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc, bool save_prepacked_initializers,
+  Status PrePack(const Tensor& tensor, int input_idx, AllocatorPtr alloc,
                  /*out*/ bool& is_packed, /*out*/ PrePackedWeights* prepacked_weights) override {
     ORT_UNUSED_PARAMETER(tensor);
     ORT_UNUSED_PARAMETER(input_idx);
-    ORT_UNUSED_PARAMETER(save_prepacked_initializers);
 
     size_t weight_packed_len = 8;
     weight_packed_ = IAllocator::MakeUniquePtr<void>(alloc, weight_packed_len, true);
@@ -394,20 +393,9 @@ class PrePackingTestOpKernel : public OpKernel {
     return Status::OK();
   }
 
-  std::optional<Tensor> GetPrePackTensor(int input_idx) override {
-    ORT_UNUSED_PARAMETER(input_idx);
-    ++get_prepack_tensors_count;
-
-    TensorShape shape = {2};
-    packed_tensor = Tensor(DataTypeImpl::GetType<float>(), shape, std::make_shared<CPUAllocator>());
-    return std::move(packed_tensor);
-  }
-
   int prepack_calls_count = 0;
   int store_pre_packed_weight_calls_count = 0;
-  int get_prepack_tensors_count = 0;
   IAllocatorUniquePtr<void> weight_packed_;
-  Tensor packed_tensor;
 };
 
 static void CreateSimpleGraph(Graph& graph) {
@@ -542,7 +530,6 @@ static void PlaceAllNodesToCPUEP(Graph& graph) {
 struct PrepackingTestParam {
   bool test_subgraph;
   bool test_prepacking;
-  bool test_save_prepack_initializer;
 };
 
 class SessionStatePrepackingTest : public testing::TestWithParam<PrepackingTestParam> {};
@@ -585,8 +572,6 @@ TEST_P(SessionStatePrepackingTest, PrePackingTest) {
   sess_options.enable_mem_reuse = true;
   sess_options.config_options.configurations[kOrtSessionOptionsConfigDisablePrepacking] =
       test_param.test_prepacking ? "0" : "1";
-  sess_options.config_options.configurations[kOrtSessionOptionsSavePrePackedConstantInitializers] =
-      test_param.test_save_prepack_initializer ? "1" : "0";
 
   SessionState session_state(model.MainGraph(),
                              execution_providers,
@@ -612,47 +597,12 @@ TEST_P(SessionStatePrepackingTest, PrePackingTest) {
   kernel_registry_manager.RegisterKernelRegistry(kernel_registry);
 
   PlaceAllNodesToCPUEP(model.MainGraph());
-  SessionState::PrePackInitializers pre_packed_initializers;
   ASSERT_STATUS_OK(session_state.FinalizeSessionState(std::basic_string<PATH_CHAR_TYPE>(),
-                                                      kernel_registry_manager,
-                                                      pre_packed_initializers));
+                                                      kernel_registry_manager));
 
   const auto& const_initialized_tensors = session_state.GetConstantInitializedTensors();
   // check prepacking
   ASSERT_EQ(const_initialized_tensors.size(), size_t(test_param.test_prepacking ? 0 : 1));
-
-  // check get prepack tensor method called when set save_prepacked_constant_initializers
-  if (!test_param.test_subgraph) {
-    const auto* kernel = reinterpret_cast<const PrePackingTestOpKernel*>(session_state.GetKernel(0));
-    ASSERT_EQ(kernel->get_prepack_tensors_count, (test_param.test_prepacking && test_param.test_save_prepack_initializer) ? 1 : 0);
-  } else {
-    auto if_index = 1;
-    if (session_state.GetKernel(0)->Node().OpType() == "If") {
-      if_index = 0;
-    }
-
-    const auto& subgraph_session_states = session_state.GetSubgraphSessionStateMap();
-    const auto& if_node_session_states = subgraph_session_states.at(if_index);
-    const auto& session_state_1_then_branch_session_state = *if_node_session_states.at("then_branch");
-    const auto& session_state_1_else_branch_session_state = *if_node_session_states.at("else_branch");
-
-    const auto* kernel_if_0 = reinterpret_cast<const PrePackingTestOpKernel*>(session_state_1_then_branch_session_state.GetKernel(0));
-    const auto* kernel_if_1 = reinterpret_cast<const PrePackingTestOpKernel*>(session_state_1_else_branch_session_state.GetKernel(0));
-    ASSERT_EQ(kernel_if_0->get_prepack_tensors_count, (test_param.test_prepacking && test_param.test_save_prepack_initializer) ? 1 : 0);
-    ASSERT_EQ(kernel_if_1->get_prepack_tensors_count, (test_param.test_prepacking && test_param.test_save_prepack_initializer) ? 1 : 0);
-  }
-
-  // check pre_packed_initializers_to_save will be set properly when set save_prepacked_constant_initializers
-  if (!test_param.test_subgraph && test_param.test_prepacking && test_param.test_save_prepack_initializer) {
-    ASSERT_EQ(pre_packed_initializers.pre_packed_initializers_to_save.size(), size_t(1));
-    ASSERT_EQ(pre_packed_initializers.pre_packed_initializers_to_save.count("node_0_input_1"), size_t(1));
-    ASSERT_EQ(pre_packed_initializers.pre_packed_initializers_to_save["node_0_input_1"].count("node_0"), size_t(1));
-  } else if (test_param.test_subgraph && test_param.test_prepacking && test_param.test_save_prepack_initializer) {
-    ASSERT_EQ(pre_packed_initializers.pre_packed_initializers_to_save.size(), size_t(1));
-    ASSERT_EQ(pre_packed_initializers.pre_packed_initializers_to_save.count("if_shared"), size_t(1));
-    ASSERT_EQ(pre_packed_initializers.pre_packed_initializers_to_save["if_shared"].count("if_node_1"), size_t(1));
-    ASSERT_EQ(pre_packed_initializers.pre_packed_initializers_to_save["if_shared"].count("if_node_0"), size_t(1));
-  }
 }
 
 class SessionStateTestSharedInitalizersWithPrePacking : public ::testing::Test {
@@ -1050,14 +1000,10 @@ TEST_F(SessionStateTestSharedInitalizersWithPrePacking, test4) {
 
 INSTANTIATE_TEST_SUITE_P(SessionStateTests,
                          SessionStatePrepackingTest,
-                         testing::Values(PrepackingTestParam{false, false, false},
-                                         PrepackingTestParam{false, true, false},
-                                         PrepackingTestParam{true, false, false},
-                                         PrepackingTestParam{true, true, false},
-                                         PrepackingTestParam{false, false, true},
-                                         PrepackingTestParam{false, true, true},
-                                         PrepackingTestParam{true, false, true},
-                                         PrepackingTestParam{true, true, true}));
+                         testing::Values(PrepackingTestParam{false, false},
+                                         PrepackingTestParam{false, true},
+                                         PrepackingTestParam{true, false},
+                                         PrepackingTestParam{true, true}));
 #endif
 
 }  // namespace test
diff --git a/onnxruntime/test/shared_lib/test_inference.cc b/onnxruntime/test/shared_lib/test_inference.cc
index e19362e0ec32d..0be1c0b1965ac 100644
--- a/onnxruntime/test/shared_lib/test_inference.cc
+++ b/onnxruntime/test/shared_lib/test_inference.cc
@@ -4600,86 +4600,3 @@ TEST(CApiTest, OrtCustomOp_GetInPlace) {
   ASSERT_EQ(len, static_cast<size_t>(2));
   mock_gqa.ReleaseAliasMap(input_index, output_index);
 }
-
-TEST(CApiTest, Serialize_PrePack_Initializers) {
-  std::string model_name = "model_with_matmul_nbits";
-
-  const std::string test_model = "testdata/prepack/" + model_name + ".onnx";
-  const std::string optimized_model = "testdata/prepack/" + model_name + "_opt.onnx";
-  std::string external_initializer_file_name = model_name + "_opt.onnx.data";
-
-  // Generate optimized with prepacked weights serialized
-  Ort::SessionOptions session_options_opt;
-  session_options_opt.AddConfigEntry(kOrtSessionOptionsOptimizedModelExternalInitializersFileName, external_initializer_file_name.c_str());
-  session_options_opt.AddConfigEntry(kOrtSessionOptionsOptimizedModelExternalInitializersMinSizeInBytes, "0");
-  session_options_opt.AddConfigEntry(kOrtSessionOptionsSavePrePackedConstantInitializers, "1");
-
-#if defined(_WIN32) || defined(_WIN64)
-  std::wstring test_model_wide = onnxruntime::ToWideString(test_model);
-  session_options_opt.SetOptimizedModelFilePath(onnxruntime::ToWideString(optimized_model).c_str());
-  Ort::Session session_opt_model(*ort_env, test_model_wide.c_str(), session_options_opt);
-#else
-  session_options_opt.SetOptimizedModelFilePath(optimized_model.c_str());
-  Ort::Session session_opt_model(*ort_env, test_model.c_str(), session_options_opt);
-#endif
-
-  // Do inference with original model and optimized model and check output is identical
-  // set inputs and session options
-  Ort::SessionOptions session_options;
-  const char* input_names[] = {"A"};
-  const char* const output_names[] = {"Y"};
-  Ort::MemoryInfo info("Cpu", OrtDeviceAllocator, 0, OrtMemTypeDefault);
-
-  std::vector<Ort::Value> ort_inputs;
-  std::vector<float> input_0_data = {1.3f};
-  std::vector<int64_t> input_0_dims = {1, 1};
-  ort_inputs.emplace_back(
-      Ort::Value::CreateTensor<float>(info, const_cast<float*>(input_0_data.data()),
-                                      input_0_data.size(), input_0_dims.data(), input_0_dims.size()));
-
-  // run inference with original model
-  // Convert std::string to std::wstring
-#if defined(_WIN32) || defined(_WIN64)
-  Ort::Session session(*ort_env, test_model_wide.c_str(), session_options);
-#else
-  Ort::Session session(*ort_env, test_model.c_str(), session_options);
-#endif
-  auto ort_outputs = session.Run(Ort::RunOptions{}, input_names, ort_inputs.data(), ort_inputs.size(),
-                                 output_names, 1);
-
-  // run inference with optimized model which load serialized prepack initializer
-#if defined(_WIN32) || defined(_WIN64)
-  std::wstring optimized_model_wide = onnxruntime::ToWideString(optimized_model);
-  Ort::Session session_opt(*ort_env, optimized_model_wide.c_str(), session_options);
-#else
-  Ort::Session session_opt(*ort_env, optimized_model.c_str(), session_options);
-#endif
-  auto ort_outputs_opt = session_opt.Run(Ort::RunOptions{}, input_names, ort_inputs.data(), ort_inputs.size(),
-                                         output_names, 1);
-
-  // check output of original model and optimized model are equal
-  ASSERT_EQ(ort_outputs.size(), ort_outputs_opt.size());
-
-  for (size_t i = 0; i < ort_outputs.size(); ++i) {
-    const auto& sequences = ort_outputs[i];
-    ASSERT_TRUE(sequences.IsTensor());
-
-    const auto& sequences_opt = ort_outputs_opt[i];
-    ASSERT_TRUE(sequences_opt.IsTensor());
-
-    auto result_ts = sequences.GetTensorTypeAndShapeInfo();
-    auto result_ts_opt = sequences_opt.GetTensorTypeAndShapeInfo();
-
-    ASSERT_EQ(result_ts.GetElementType(), result_ts_opt.GetElementType());
-
-    ASSERT_EQ(result_ts.GetShape(), result_ts_opt.GetShape());
-
-    const auto* result_vals = sequences.GetTensorData<float>();
-    auto result_span = gsl::make_span(result_vals, ort_outputs.size());
-
-    const auto* result_vals_opt = sequences_opt.GetTensorData<float>();
-    auto result_span_opt = gsl::make_span(result_vals_opt, ort_outputs_opt.size());
-
-    ASSERT_TRUE(std::equal(result_span_opt.begin(), result_span_opt.end(), result_span.begin(), result_span.end()));
-  }
-}
\ No newline at end of file
diff --git a/onnxruntime/test/testdata/model_with_external_initializers.onnx b/onnxruntime/test/testdata/model_with_external_initializers.onnx
index 3538f01b53c18..f815b4000f98f 100644
--- a/onnxruntime/test/testdata/model_with_external_initializers.onnx
+++ b/onnxruntime/test/testdata/model_with_external_initializers.onnx
@@ -1,8 +1,7 @@
-
-onnx-example:�

-,
+onnx-example:�

+&
 
X
-Pads
Ypad0"Pad*
+Pads
Y"Pad*
 mode"constant�

 test-model*"BPadsj
 locationPads.binp
Z
@@ -17,4 +16,4 @@ test-model*"BPadsj
 
Y
 

 

-B
\ No newline at end of file
+B
\ No newline at end of file
diff --git a/onnxruntime/test/testdata/model_with_external_initializers.py b/onnxruntime/test/testdata/model_with_external_initializers.py
index dc64d4a41424a..8d2589a9e6564 100644
--- a/onnxruntime/test/testdata/model_with_external_initializers.py
+++ b/onnxruntime/test/testdata/model_with_external_initializers.py
@@ -35,10 +35,9 @@ def GenerateModel(model_name, external_data_name):  # noqa: N802
 
     # Create a node (NodeProto)
     node_def = helper.make_node(
-        "Pad",  # op type
+        "Pad",  # node name
         ["X", external_data_name],  # inputs
         ["Y"],  # outputs
-        "pad0",  # node name
         mode="constant",  # Attributes
     )
 
diff --git a/onnxruntime/test/testdata/model_with_orig_ext_data.onnx b/onnxruntime/test/testdata/model_with_orig_ext_data.onnx
index 47d0c68235099..6f9cce0bc5b4f 100644
--- a/onnxruntime/test/testdata/model_with_orig_ext_data.onnx
+++ b/onnxruntime/test/testdata/model_with_orig_ext_data.onnx
@@ -1,8 +1,7 @@
-
-onnx-example:�

-@
+	onnx-example:�

+:
 
X
-model_with_orig_ext_data
Ypad0"Pad*
+model_with_orig_ext_data
Y"Pad*
 mode"constant�

 test-model*JBmodel_with_orig_ext_dataj(
 locationmodel_with_orig_ext_data.binp
Z
@@ -17,4 +16,4 @@ test-model*JBmodel_with_orig_ext_dataj(
 
Y
 

 

-B
\ No newline at end of file
+B
\ No newline at end of file
diff --git a/onnxruntime/test/testdata/prepack/MatMul.Weight.bin b/onnxruntime/test/testdata/prepack/MatMul.Weight.bin
deleted file mode 100644
index 0f8a571589c1050d3b3e512801441efcb22cdf3c..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

literal 8
KcmZ3@00966U;wND

diff --git a/onnxruntime/test/testdata/prepack/model_with_external_initializers_and_prepack_kernel.py b/onnxruntime/test/testdata/prepack/model_with_external_initializers_and_prepack_kernel.py
deleted file mode 100644
index 86af461edc2c4..0000000000000
--- a/onnxruntime/test/testdata/prepack/model_with_external_initializers_and_prepack_kernel.py
+++ /dev/null
@@ -1,88 +0,0 @@
-# Copyright (c) Microsoft Corporation. All rights reserved.
-# Licensed under the MIT License.
-
-import os
-
-import numpy as np
-import onnx
-from onnx import TensorProto, helper
-from onnx.external_data_helper import set_external_data
-from onnx.numpy_helper import from_array
-
-M = 1
-K = 1
-N = 1
-q_cols = 1
-q_rows = 1
-q_scale_size = 1
-
-
-def create_external_data_tensor(value, tensor_name, data_type):
-    tensor = from_array(np.array(value))
-    tensor.name = tensor_name
-    tensor_filename = f"{tensor_name}.bin"
-    set_external_data(tensor, location=tensor_filename)
-
-    with open(os.path.join(tensor_filename), "wb") as data_file:
-        data_file.write(tensor.raw_data)
-    tensor.ClearField("raw_data")
-    tensor.data_location = onnx.TensorProto.EXTERNAL
-    tensor.data_type = data_type
-    return tensor
-
-
-def create_internal_data_tensor(value, tensor_name, data_type):
-    tensor = helper.make_tensor(name=tensor_name, data_type=data_type, dims=value.shape, vals=value.flatten().tolist())
-    print(tensor)
-    tensor.data_location = onnx.TensorProto.DEFAULT
-    return tensor
-
-
-def GenerateMatmulNBitsModel(model_name, external_data_name):  # noqa: N802
-    A = helper.make_tensor_value_info("A", TensorProto.FLOAT, [M, K])  # noqa: N806
-    Y = helper.make_tensor_value_info("Y", TensorProto.FLOAT, [M, N])  # noqa: N806
-
-    # Create a node (NodeProto)
-    node_def = helper.make_node(
-        op_type="MatMulNBits",  # op type
-        inputs=["A", external_data_name, "scales"],  # inputs
-        outputs=["Y"],  # outputs
-        name="MatMul_0",  # node name
-        domain="com.microsoft",  # Custom domain for this operator
-        accuracy_level=4,  # Attributes
-        bits=4,  # Attributes
-        block_size=32,  # Attributes
-        K=K,  # Attributes
-        N=N,  # Attributes
-    )
-
-    # Create the graph (GraphProto)
-    graph_def = helper.make_graph(
-        [node_def],
-        "test-model-matmul4bits",
-        [A],
-        [Y],
-        [
-            create_external_data_tensor([[171]], external_data_name, TensorProto.UINT8),
-            create_internal_data_tensor(np.array([1.5], dtype=np.float32), "scales", TensorProto.FLOAT),
-        ],
-    )
-
-    # Create the model
-    model_def = helper.make_model(
-        graph_def,
-        producer_name="onnx-example",
-        opset_imports=[helper.make_operatorsetid("", 14), helper.make_operatorsetid("com.microsoft", 1)],
-    )
-
-    print(f"The ir_version in model: {model_def.ir_version}\n")
-    print(f"The producer_name in model: {model_def.producer_name}\n")
-    print(f"The graph in model:\n{model_def.graph}")
-    onnx.checker.check_model(model_def)
-    print("The model is checked!")
-    with open(model_name, "wb") as model_file:
-        model_file.write(model_def.SerializeToString())
-
-
-if __name__ == "__main__":
-    GenerateMatmulNBitsModel("model_with_matmul_nbits.onnx", "MatMul.Weight")
diff --git a/onnxruntime/test/testdata/prepack/model_with_matmul_nbits.onnx b/onnxruntime/test/testdata/prepack/model_with_matmul_nbits.onnx
deleted file mode 100644
index 0e06a75a5a7e84e1fe2f090a4c7c6a513ed6344f..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

literal 333
zcmZ8cO-sZu6znTS!rR@_#t(`h$Q}zV9>l|5#9n3hD(j`BF={kv$|jZ7AK`D%f8tLw
zrC#dc!MvF_j~Rk=ZrXNVh&|Jt607eJKLOze7i;F$y(;g7e0p|xU^!F5QrMo7QK>JM
zvk`47>1<9AZZr6Ta6p?89b?Qm?{|#9*Gjwzl|{qB45P+d#wA5;l;N+nl^-HI_xftV
zjV`t1J7dkGqbE*SS7`GfRH2#Ey}BIi`4s^INmxyzzMLWP|Cp1erRk(a*~qqo{K&gt
o83n=5b@kV)3+@knYZ~L603{d_7^d;$_CHxg7$k9(;xuLgzX5qu+5i9m

diff --git a/orttraining/orttraining/models/bert/main.cc b/orttraining/orttraining/models/bert/main.cc
index ec7a458237c77..c4c7a98ba116a 100644
--- a/orttraining/orttraining/models/bert/main.cc
+++ b/orttraining/orttraining/models/bert/main.cc
@@ -42,7 +42,6 @@ static SessionOptions session_options = {
     ExecutionMode::ORT_SEQUENTIAL,     // execution_mode
     ExecutionOrder::PRIORITY_BASED,    // execution_order
     false,                             // enable_profiling
-    false,                             // save prepacked initializer
     ORT_TSTR(""),                      // optimized_model_filepath
     true,                              // enable_mem_pattern
     true,                              // enable_mem_reuse
diff --git a/orttraining/orttraining/models/pipeline_poc/main.cc b/orttraining/orttraining/models/pipeline_poc/main.cc
index 0e40d04ddac8c..1b7d6b9ea26f6 100644
--- a/orttraining/orttraining/models/pipeline_poc/main.cc
+++ b/orttraining/orttraining/models/pipeline_poc/main.cc
@@ -89,7 +89,6 @@ int main(int argc, char* argv[]) {
       ExecutionMode::ORT_SEQUENTIAL,     // execution_mode
       ExecutionOrder::DEFAULT,           // execution_order
       false,                             // enable_profiling
-      false,                             // save prepacked initializer
       ORT_TSTR(""),                      // optimized_model_filepath
       true,                              // enable_mem_pattern
       true,                              // enable_mem_reuse
diff --git a/orttraining/orttraining/models/runner/training_runner.cc b/orttraining/orttraining/models/runner/training_runner.cc
index 5a2f1cd13683e..dae6f613f4329 100644
--- a/orttraining/orttraining/models/runner/training_runner.cc
+++ b/orttraining/orttraining/models/runner/training_runner.cc
@@ -37,7 +37,6 @@ static SessionOptions SESSION_OPTION = {
     ExecutionMode::ORT_SEQUENTIAL,     // execution_mode
     ExecutionOrder::PRIORITY_BASED,    // execution_order
     false,                             // enable_profiling
-    false,                             // save prepacked initializer
     ORT_TSTR(""),                      // optimized_model_filepath
     true,                              // enable_mem_pattern
     true,                              // enable_mem_reuse

From 1f3b675453e8412e5c084bfb95997967d0c2eec2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Xavier=20Dupr=C3=A9?= <xadupre@users.noreply.github.com>
Date: Mon, 11 Nov 2024 19:48:25 +0100
Subject: [PATCH 2/4] Fix MatMulBnFusion to exclude cases when tensors are not
 2D tensors (#22762)

### Description
Fixes #22512, MatMul, Add can be fused into a single Gemm even if
tensors dimensions are > 2. The PR excludes that cases.



### Motivation and Context
ORT crashes on valid models due to that unexpected fusion.
---
 .../core/optimizer/matmul_bn_fusion.cc        |  17 ++++++++++
 .../test/optimizer/graph_transform_test.cc    |  29 ++++++++++++++++++
 .../fuse-matmul-bn-directly-dont-fuse.onnx    | Bin 0 -> 517 bytes
 3 files changed, 46 insertions(+)
 create mode 100644 onnxruntime/test/testdata/transform/fusion/fuse-matmul-bn-directly-dont-fuse.onnx

diff --git a/onnxruntime/core/optimizer/matmul_bn_fusion.cc b/onnxruntime/core/optimizer/matmul_bn_fusion.cc
index e944522c9c338..6b76dc626fba0 100644
--- a/onnxruntime/core/optimizer/matmul_bn_fusion.cc
+++ b/onnxruntime/core/optimizer/matmul_bn_fusion.cc
@@ -107,6 +107,22 @@ bool MatmulBNFusion::SatisfyCondition(const Graph& graph, const Node& node, cons
     return false;
   }
 
+  // Checks the first input of MatMul has 2 dimensions.
+  // The test for the second input is done in method Apply as it accesses the constant.
+  if (node.InputDefs()[0] == nullptr) {
+    // This should never happen but just in case.
+    return false;
+  }
+  auto shape_a = node.InputDefs()[0]->Shape();
+  if (shape_a == nullptr) {
+    // We cannot shape the rank. It is better to avoid fusing.
+    return false;
+  }
+  if (shape_a->dim_size() != 2) {
+    // Gemm only supports 2D tensors.
+    return false;
+  }
+
   // First output from BN is required. Others are optional. If any optional outputs exist we can't fuse.
   const auto& output_defs = batch_norm_node->OutputDefs();
   if (output_defs.size() > 1) {
@@ -165,6 +181,7 @@ Status MatmulBNFusion::Apply(Graph& graph, Node& matmul_node, RewriteRuleEffect&
       bias_tensor->dims_size() != 1 ||
       mean_tensor->dims_size() != 1 ||
       var_tensor->dims_size() != 1 ||
+      matmul_b_tensor->dims_size() != 2 ||
       scale_tensor->dims(0) != matmul_b_tensor->dims(1) ||
       bias_tensor->dims(0) != matmul_b_tensor->dims(1) ||
       mean_tensor->dims(0) != matmul_b_tensor->dims(1) ||
diff --git a/onnxruntime/test/optimizer/graph_transform_test.cc b/onnxruntime/test/optimizer/graph_transform_test.cc
index ee3a1baade005..67d60ea3a4ff6 100755
--- a/onnxruntime/test/optimizer/graph_transform_test.cc
+++ b/onnxruntime/test/optimizer/graph_transform_test.cc
@@ -1764,6 +1764,35 @@ TEST_F(GraphTransformationTests, FuseMatmulBNDirectly) {
   }
 }
 
+TEST_F(GraphTransformationTests, DoNotApplyFuseMatmulBNDirectly) {
+  constexpr const ORTCHAR_T* model_uri = MODEL_FOLDER "fusion/fuse-matmul-bn-directly-dont-fuse.onnx";
+
+  std::shared_ptr<Model> p_model;
+  ASSERT_STATUS_OK(Model::Load(model_uri, p_model, nullptr, *logger_));
+  Graph& graph = p_model->MainGraph();
+
+  std::string expected_output_name;
+  GraphViewer graphViewer(graph);
+  for (auto& node_index : graphViewer.GetNodesInTopologicalOrder()) {
+    auto& node = *graph.GetNode(node_index);
+    if (node.OpType() == "BatchNormalization") {
+      expected_output_name = node.OutputDefs()[0]->Name();
+    }
+  }
+
+  onnxruntime::GraphTransformerManager graph_transformation_mgr{5};
+  auto rule_transformer_L1 = std::make_unique<RuleBasedGraphTransformer>("RuleTransformerL1");
+  ASSERT_STATUS_OK(rule_transformer_L1->Register(std::make_unique<MatmulBNFusion>()));
+  ASSERT_STATUS_OK(graph_transformation_mgr.Register(std::move(rule_transformer_L1), TransformerLevel::Level1));
+
+  ASSERT_STATUS_OK(graph_transformation_mgr.ApplyTransformers(graph, TransformerLevel::Level1, *logger_));
+
+  std::map<std::string, int> op_to_count = CountOpsInGraph(graph);
+  ASSERT_EQ(op_to_count["BatchNormalization"], 1);
+  ASSERT_EQ(op_to_count["MatMul"], 1);
+  ASSERT_EQ(op_to_count["Gemm"], 0);
+}
+
 TEST_F(GraphTransformationTests, FuseMatmulBNWithOnlyReshape) {
   constexpr const ORTCHAR_T* model_uri = MODEL_FOLDER "fusion/fuse-matmul-bn-only-reshape.onnx";
 
diff --git a/onnxruntime/test/testdata/transform/fusion/fuse-matmul-bn-directly-dont-fuse.onnx b/onnxruntime/test/testdata/transform/fusion/fuse-matmul-bn-directly-dont-fuse.onnx
new file mode 100644
index 0000000000000000000000000000000000000000..8ca8282572db8d474327e5f88d7e8a1f60c47e15
GIT binary patch
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ij6ytIOdO0*%$g*@1r22(J}w@hEC)=+iG_<nfCB&x5vG&?

literal 0
HcmV?d00001


From 885a7acd451a6bfdfa85dd75b2844598ecf60374 Mon Sep 17 00:00:00 2001
From: Jian Chen <cjian@microsoft.com>
Date: Mon, 11 Nov 2024 16:05:34 -0500
Subject: [PATCH 3/4] Fix warning - LegacyKeyValueFormat: "ENV key=value"
 should be used instead of legacy "ENV key value" format (#22800)

### Description
This PR Fix warning - `LegacyKeyValueFormat: "ENV key=value" should be
used instead of legacy "ENV key value" format` from all Dockerfile



### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
---
 dockerfiles/Dockerfile.migraphx                           | 2 +-
 dockerfiles/Dockerfile.openvino                           | 6 +++---
 dockerfiles/Dockerfile.rocm                               | 2 +-
 dockerfiles/Dockerfile.tensorrt                           | 2 +-
 dockerfiles/Dockerfile.vitisai                            | 4 ++--
 orttraining/tools/amdgpu/Dockerfile.rocm4.3.1.pytorch     | 2 +-
 .../github/linux/docker/Dockerfile.manylinux2_28_cuda     | 4 ++--
 .../github/linux/docker/Dockerfile.manylinux2_28_rocm     | 2 +-
 .../docker/Dockerfile.package_ubi8_cuda11_8_tensorrt8_6   | 2 +-
 .../docker/Dockerfile.package_ubi8_cuda_tensorrt10_0      | 2 +-
 .../Dockerfile.package_ubi8_cuda_tensorrt10_0_torch       | 2 +-
 .../linux/docker/Dockerfile.package_ubuntu_2004_gpu       | 2 +-
 .../docker/Dockerfile.package_ubuntu_2004_gpu_ffmpeg      | 2 +-
 .../linux/docker/Dockerfile.ubuntu_cuda11_8_tensorrt8_6   | 4 ++--
 .../linux/docker/Dockerfile.ubuntu_cuda11_tensorrt10      | 4 ++--
 .../linux/docker/Dockerfile.ubuntu_cuda12_3_tensorrt8_6   | 4 ++--
 .../linux/docker/Dockerfile.ubuntu_cuda12_tensorrt10      | 4 ++--
 .../github/linux/docker/Dockerfile.ubuntu_openvino        | 8 ++++----
 .../github/linux/docker/Dockerfile.ubuntu_tensorrt_bin    | 4 ++--
 .../docker/inference/x86_64/default/cuda11/Dockerfile     | 4 ++--
 .../docker/inference/x86_64/default/cuda12/Dockerfile     | 4 ++--
 .../linux/docker/inference/x86_64/python/cuda/Dockerfile  | 4 ++--
 22 files changed, 37 insertions(+), 37 deletions(-)

diff --git a/dockerfiles/Dockerfile.migraphx b/dockerfiles/Dockerfile.migraphx
index c5d998d503899..876a07e4ffaf6 100644
--- a/dockerfiles/Dockerfile.migraphx
+++ b/dockerfiles/Dockerfile.migraphx
@@ -10,7 +10,7 @@ FROM rocm/pytorch:rocm6.2.3_ubuntu22.04_py3.10_pytorch_release_2.3.0
 ARG ONNXRUNTIME_REPO=https://github.com/Microsoft/onnxruntime
 ARG ONNXRUNTIME_BRANCH=main
 
-ENV PATH /code/cmake-3.27.3-linux-x86_64/bin:${PATH}
+ENV PATH=/code/cmake-3.27.3-linux-x86_64/bin:${PATH}
 
 RUN apt-get update &&\
     apt-get install -y migraphx
diff --git a/dockerfiles/Dockerfile.openvino b/dockerfiles/Dockerfile.openvino
index 39e75a68a369f..d1ebdae3cbdd6 100644
--- a/dockerfiles/Dockerfile.openvino
+++ b/dockerfiles/Dockerfile.openvino
@@ -11,7 +11,7 @@ FROM openvino/ubuntu22_runtime:${OPENVINO_VERSION} AS builder
 
 ENV WORKDIR_PATH=/home/openvino
 WORKDIR $WORKDIR_PATH
-ENV DEBIAN_FRONTEND noninteractive
+ENV DEBIAN_FRONTEND=noninteractive
 
 ARG DEVICE=CPU
 ARG ONNXRUNTIME_REPO=https://github.com/microsoft/onnxruntime.git
@@ -41,7 +41,7 @@ RUN tar cvf GPL_sources.tar.gz /sources
 # Deploy stage
 FROM openvino/ubuntu22_runtime:${OPENVINO_VERSION}
 
-ENV DEBIAN_FRONTEND noninteractive
+ENV DEBIAN_FRONTEND=noninteractive
 USER root
 COPY --from=builder /home/openvino/onnxruntime/build/Linux/Release/dist/*.whl ./
 COPY --from=builder /GPL_sources.tar.gz ./
@@ -50,7 +50,7 @@ ARG BUILD_UID=1001
 ARG BUILD_USER=onnxruntimedev
 RUN adduser --uid $BUILD_UID $BUILD_USER
 RUN usermod -a -G video,users ${BUILD_USER}
-ENV WORKDIR_PATH /home/${BUILD_USER}
+ENV WORKDIR_PATH=/home/${BUILD_USER}
 WORKDIR ${WORKDIR_PATH}
 
 USER ${BUILD_USER}
diff --git a/dockerfiles/Dockerfile.rocm b/dockerfiles/Dockerfile.rocm
index bef8d7a5f47d2..aca8c3feaff71 100644
--- a/dockerfiles/Dockerfile.rocm
+++ b/dockerfiles/Dockerfile.rocm
@@ -12,7 +12,7 @@ ARG ONNXRUNTIME_BRANCH=main
 
 WORKDIR /code
 
-ENV PATH /code/cmake-3.27.3-linux-x86_64/bin:${PATH}
+ENV PATH=/code/cmake-3.27.3-linux-x86_64/bin:${PATH}
 
 # Prepare onnxruntime repository & build onnxruntime
 RUN git clone --single-branch --branch ${ONNXRUNTIME_BRANCH} --recursive ${ONNXRUNTIME_REPO} onnxruntime &&\
diff --git a/dockerfiles/Dockerfile.tensorrt b/dockerfiles/Dockerfile.tensorrt
index ef51d41c5ff1b..24947df6308a6 100644
--- a/dockerfiles/Dockerfile.tensorrt
+++ b/dockerfiles/Dockerfile.tensorrt
@@ -17,7 +17,7 @@ RUN apt-get update &&\
 RUN unattended-upgrade
 
 WORKDIR /code
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/code/cmake-3.27.3-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
+ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/code/cmake-3.27.3-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
 
 # Prepare onnxruntime repository & build onnxruntime with TensorRT
 RUN git clone --single-branch --branch ${ONNXRUNTIME_BRANCH} --recursive ${ONNXRUNTIME_REPO} onnxruntime &&\
diff --git a/dockerfiles/Dockerfile.vitisai b/dockerfiles/Dockerfile.vitisai
index e11ab70a61332..c6226155e01e3 100644
--- a/dockerfiles/Dockerfile.vitisai
+++ b/dockerfiles/Dockerfile.vitisai
@@ -22,8 +22,8 @@ RUN apt-get update && \
     apt-get clean && \
     rm -rf /var/lib/apt/lists/*
 
-ENV PATH /code/cmake-3.27.3-linux-x86_64/bin:$PATH
-ENV LD_LIBRARY_PATH /opt/xilinx/xrt/lib:$LD_LIBRARY_PATH
+ENV PATH=/code/cmake-3.27.3-linux-x86_64/bin:$PATH
+ENV LD_LIBRARY_PATH=/opt/xilinx/xrt/lib:$LD_LIBRARY_PATH
 
 WORKDIR /code
 RUN . $VAI_ROOT/conda/etc/profile.d/conda.sh &&\
diff --git a/orttraining/tools/amdgpu/Dockerfile.rocm4.3.1.pytorch b/orttraining/tools/amdgpu/Dockerfile.rocm4.3.1.pytorch
index 3a408e2265fe7..29b8812c979e4 100644
--- a/orttraining/tools/amdgpu/Dockerfile.rocm4.3.1.pytorch
+++ b/orttraining/tools/amdgpu/Dockerfile.rocm4.3.1.pytorch
@@ -46,7 +46,7 @@ RUN cd MLNX_OFED_LINUX-${MOFED_VERSION}-${MOFED_OS}-x86_64 && \
     rm -r MLNX_OFED_LINUX-${MOFED_VERSION}-${MOFED_OS}-x86_64
 
 ENV PATH=${OLD_PATH}
-ENV unset OLD_PATH
+ENV unset=OLD_PATH
 
 # python env
 RUN pip3 install --upgrade setuptools
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_cuda b/tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_cuda
index 07885ba65af8a..77dd63298ff3c 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_cuda
+++ b/tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_cuda
@@ -42,5 +42,5 @@ ARG BUILD_USER=onnxruntimedev
 RUN adduser --uid $BUILD_UID $BUILD_USER
 WORKDIR /home/$BUILD_USER
 USER $BUILD_USER
-ENV PATH /usr/local/dotnet:$PATH
-ENV CUDA_MODULE_LOADING "LAZY"
\ No newline at end of file
+ENV PATH=/usr/local/dotnet:$PATH
+ENV CUDA_MODULE_LOADING="LAZY"
\ No newline at end of file
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_rocm b/tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_rocm
index e4c3af05053ba..9a265b4249f0b 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_rocm
+++ b/tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_rocm
@@ -201,5 +201,5 @@ ARG BUILD_USER=onnxruntimedev
 RUN adduser --uid $BUILD_UID $BUILD_USER
 WORKDIR /home/$BUILD_USER
 USER $BUILD_USER
-ENV PATH /usr/local/dotnet:$PATH
+ENV PATH=/usr/local/dotnet:$PATH
 ENV ORTMODULE_ONNX_OPSET_VERSION=$OPSET_VERSION
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda11_8_tensorrt8_6 b/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda11_8_tensorrt8_6
index a9da75ea87f07..9de88d1664b82 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda11_8_tensorrt8_6
+++ b/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda11_8_tensorrt8_6
@@ -9,7 +9,7 @@ ARG BASEIMAGE=nvidia/cuda:11.8.0-cudnn8-devel-ubi8
 ARG TRT_VERSION=8.6.1.6-1.cuda11.8
 FROM $BASEIMAGE AS base
 ARG TRT_VERSION
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
+ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
 
 RUN dnf install -y bash wget &&\
     dnf clean dbcache
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda_tensorrt10_0 b/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda_tensorrt10_0
index 5f21c8cbb5dfa..c2bae5fd7ee59 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda_tensorrt10_0
+++ b/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda_tensorrt10_0
@@ -9,7 +9,7 @@ ARG BASEIMAGE=nvidia/cuda:12.5.1-cudnn-devel-ubi8
 ARG TRT_VERSION=10.6.0.26-1.cuda12.6
 FROM $BASEIMAGE AS base
 ARG TRT_VERSION
-ENV PATH /opt/python/cp310-cp310/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
+ENV PATH=/opt/python/cp310-cp310/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
 
 RUN dnf install -y bash wget &&\
     dnf clean dbcache
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda_tensorrt10_0_torch b/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda_tensorrt10_0_torch
index eea205797af79..e1203f55106ce 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda_tensorrt10_0_torch
+++ b/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda_tensorrt10_0_torch
@@ -9,7 +9,7 @@ ARG BASEIMAGE=nvidia/cuda:11.8.0-cudnn8-devel-ubi8
 ARG TRT_VERSION=10.6.0.26-1.cuda11.8
 FROM $BASEIMAGE AS base
 ARG TRT_VERSION
-ENV PATH /opt/python/cp38-cp38/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
+ENV PATH=/opt/python/cp38-cp38/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
 
 RUN dnf install -y bash wget &&\
     dnf clean dbcache
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_2004_gpu b/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_2004_gpu
index 34c700c22a7c9..81aeada6a4a46 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_2004_gpu
+++ b/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_2004_gpu
@@ -10,7 +10,7 @@ ARG TRT_VERSION=10.6.0.26-1+cuda11.8
 ARG LD_LIBRARY_PATH_ARG=/usr/local/lib64:/usr/local/cuda/lib64
 FROM $BASEIMAGE AS base
 ARG TRT_VERSION
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
+ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
 ENV DEBIAN_FRONTEND=noninteractive
 
 ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH_ARG}:${LD_LIBRARY_PATH}
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_2004_gpu_ffmpeg b/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_2004_gpu_ffmpeg
index 1665a46d10f43..6ce5a59802641 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_2004_gpu_ffmpeg
+++ b/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_2004_gpu_ffmpeg
@@ -10,7 +10,7 @@ ARG TRT_VERSION=10.6.0.26-1+cuda11.8
 ARG LD_LIBRARY_PATH_ARG=/usr/local/lib64:/usr/local/cuda/lib64
 FROM $BASEIMAGE AS base
 ARG TRT_VERSION
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
+ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
 ENV DEBIAN_FRONTEND=noninteractive
 
 ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH_ARG}:${LD_LIBRARY_PATH}
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda11_8_tensorrt8_6 b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda11_8_tensorrt8_6
index dfc057b129f91..3b4d36a9a8fd8 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda11_8_tensorrt8_6
+++ b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda11_8_tensorrt8_6
@@ -10,7 +10,7 @@ FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04 AS base
 # The local directory into which to build and install CMAKE
 ARG ONNXRUNTIME_LOCAL_CODE_DIR=/code
 
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.30.1-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
+ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.30.1-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
 ENV DEBIAN_FRONTEND=noninteractive
 
 RUN apt-get update &&\
@@ -82,7 +82,7 @@ RUN if [ -z "$ONNXRUNTIME_COMMIT_ID" ] ; then echo "Building branch ${ONNXRUNTIM
     git reset --hard ${ONNXRUNTIME_COMMIT_ID} && git submodule update --recursive ; fi
 
 # Build ORT
-ENV CUDA_MODULE_LOADING "LAZY" 
+ENV CUDA_MODULE_LOADING="LAZY"
 ARG PARSER_CONFIG=""
 RUN /bin/sh build.sh ${PARSER_CONFIG} --parallel --build_shared_lib --cuda_home /usr/local/cuda --cudnn_home /usr/lib/x86_64-linux-gnu/ --use_tensorrt --tensorrt_home /usr/lib/x86_64-linux-gnu/ --config Release --build_wheel --skip_tests --skip_submodule_sync --cmake_extra_defines '"CMAKE_CUDA_ARCHITECTURES='${CMAKE_CUDA_ARCHITECTURES}'"'
 
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda11_tensorrt10 b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda11_tensorrt10
index 45c854f62cd37..22d5e3b0248a8 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda11_tensorrt10
+++ b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda11_tensorrt10
@@ -10,7 +10,7 @@ FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04 AS base
 # The local directory into which to build and install CMAKE
 ARG ONNXRUNTIME_LOCAL_CODE_DIR=/code
 
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.30.1-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
+ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.30.1-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
 ENV DEBIAN_FRONTEND=noninteractive
 
 RUN apt-get update &&\
@@ -98,7 +98,7 @@ RUN if [ -z "$ONNXRUNTIME_COMMIT_ID" ] ; then echo "Building branch ${ONNXRUNTIM
     git reset --hard ${ONNXRUNTIME_COMMIT_ID} && git submodule update --recursive ; fi
 
 # Build ORT
-ENV CUDA_MODULE_LOADING "LAZY"
+ENV CUDA_MODULE_LOADING="LAZY"
 ARG PARSER_CONFIG=""
 RUN /bin/sh build.sh ${PARSER_CONFIG} --parallel --build_shared_lib --cuda_home /usr/local/cuda --cudnn_home /usr/lib/x86_64-linux-gnu/ --use_tensorrt --tensorrt_home /usr/lib/x86_64-linux-gnu/ --config Release --build_wheel --skip_tests --skip_submodule_sync --cmake_extra_defines '"CMAKE_CUDA_ARCHITECTURES='${CMAKE_CUDA_ARCHITECTURES}'"'
 
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda12_3_tensorrt8_6 b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda12_3_tensorrt8_6
index f63112039fe8e..6d35df72894d8 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda12_3_tensorrt8_6
+++ b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda12_3_tensorrt8_6
@@ -10,7 +10,7 @@ FROM nvidia/cuda:12.3.1-devel-ubuntu20.04 AS base
 # The local directory into which to build and install CMAKE
 ARG ONNXRUNTIME_LOCAL_CODE_DIR=/code
 
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.30.1-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
+ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.30.1-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
 ENV DEBIAN_FRONTEND=noninteractive
 
 RUN apt-get update &&\
@@ -85,7 +85,7 @@ RUN if [ -z "$ONNXRUNTIME_COMMIT_ID" ] ; then echo "Building branch ${ONNXRUNTIM
     git reset --hard ${ONNXRUNTIME_COMMIT_ID} && git submodule update --recursive ; fi
 
 # Build ORT
-ENV CUDA_MODULE_LOADING "LAZY" 
+ENV CUDA_MODULE_LOADING="LAZY"
 ARG PARSER_CONFIG=""
 RUN /bin/sh build.sh ${PARSER_CONFIG} --parallel --build_shared_lib --cuda_home /usr/local/cuda --cudnn_home /usr/lib/x86_64-linux-gnu/ --use_tensorrt --tensorrt_home /usr/lib/x86_64-linux-gnu/ --config Release --build_wheel --skip_tests --skip_submodule_sync --cmake_extra_defines '"CMAKE_CUDA_ARCHITECTURES='${CMAKE_CUDA_ARCHITECTURES}'"'
 
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda12_tensorrt10 b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda12_tensorrt10
index 53b1072ded8f4..819d9bab7be75 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda12_tensorrt10
+++ b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_cuda12_tensorrt10
@@ -10,7 +10,7 @@ FROM nvidia/cuda:12.5.1-cudnn-devel-ubuntu20.04 AS base
 # The local directory into which to build and install CMAKE
 ARG ONNXRUNTIME_LOCAL_CODE_DIR=/code
 
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.30.1-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
+ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.30.1-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
 ENV DEBIAN_FRONTEND=noninteractive
 
 RUN apt-get update &&\
@@ -98,7 +98,7 @@ RUN if [ -z "$ONNXRUNTIME_COMMIT_ID" ] ; then echo "Building branch ${ONNXRUNTIM
     git reset --hard ${ONNXRUNTIME_COMMIT_ID} && git submodule update --recursive ; fi
 
 # Build ORT
-ENV CUDA_MODULE_LOADING "LAZY"
+ENV CUDA_MODULE_LOADING="LAZY"
 ARG PARSER_CONFIG=""
 RUN /bin/sh build.sh ${PARSER_CONFIG} --parallel --build_shared_lib --cuda_home /usr/local/cuda --cudnn_home /usr/lib/x86_64-linux-gnu/ --use_tensorrt --tensorrt_home /usr/lib/x86_64-linux-gnu/ --config Release --build_wheel --skip_tests --skip_submodule_sync --cmake_extra_defines '"CMAKE_CUDA_ARCHITECTURES='${CMAKE_CUDA_ARCHITECTURES}'"'
 
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_openvino b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_openvino
index 5f525c1310412..4c80e7a907630 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_openvino
+++ b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_openvino
@@ -12,10 +12,10 @@ RUN /tmp/scripts/install_python_deps.sh -p $PYTHON_VERSION -d EdgeDevice
 RUN apt update && apt install -y libnuma1 ocl-icd-libopencl1 && \
     rm -rf /var/lib/apt/lists/* /tmp/scripts
 
-ENV INTEL_OPENVINO_DIR /opt/intel/openvino_${OPENVINO_VERSION}
-ENV LD_LIBRARY_PATH $INTEL_OPENVINO_DIR/runtime/lib/intel64:$INTEL_OPENVINO_DIR/runtime/3rdparty/tbb/lib:/usr/local/openblas/lib:$LD_LIBRARY_PATH
-ENV OpenVINO_DIR $INTEL_OPENVINO_DIR/runtime/cmake
-ENV IE_PLUGINS_PATH $INTEL_OPENVINO_DIR/runtime/lib/intel64
+ENV INTEL_OPENVINO_DIR=/opt/intel/openvino_${OPENVINO_VERSION}
+ENV LD_LIBRARY_PATH=$INTEL_OPENVINO_DIR/runtime/lib/intel64:$INTEL_OPENVINO_DIR/runtime/3rdparty/tbb/lib:/usr/local/openblas/lib:$LD_LIBRARY_PATH
+ENV OpenVINO_DIR=$INTEL_OPENVINO_DIR/runtime/cmake
+ENV IE_PLUGINS_PATH=$INTEL_OPENVINO_DIR/runtime/lib/intel64
 ENV DEBIAN_FRONTEND=noninteractive
 
 RUN cd /opt && mkdir -p intel && cd intel && \
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_tensorrt_bin b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_tensorrt_bin
index 797495abef57b..4f58dc89333ba 100644
--- a/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_tensorrt_bin
+++ b/tools/ci_build/github/linux/docker/Dockerfile.ubuntu_tensorrt_bin
@@ -10,7 +10,7 @@ FROM nvidia/cuda:12.5.1-cudnn-devel-ubuntu20.04 AS base
 # The local directory into which to build and install CMAKE
 ARG ONNXRUNTIME_LOCAL_CODE_DIR=/code
 
-ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.30.1-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
+ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.30.1-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
 ENV DEBIAN_FRONTEND=noninteractive
 
 RUN apt-get update &&\
@@ -92,7 +92,7 @@ RUN if [ -z "$ONNXRUNTIME_COMMIT_ID" ] ; then echo "Building branch ${ONNXRUNTIM
     git reset --hard ${ONNXRUNTIME_COMMIT_ID} && git submodule update --recursive ; fi
 
 # Build ORT
-ENV CUDA_MODULE_LOADING "LAZY" 
+ENV CUDA_MODULE_LOADING="LAZY"
 ARG PARSER_CONFIG=""
 RUN /bin/sh build.sh ${PARSER_CONFIG} --parallel --build_shared_lib --cuda_home /usr/local/cuda --cudnn_home /usr/lib/x86_64-linux-gnu/ --use_tensorrt --tensorrt_home /usr/lib/x86_64-linux-gnu/ --config Release --build_wheel --skip_tests --skip_submodule_sync --cmake_extra_defines '"CMAKE_CUDA_ARCHITECTURES='${CMAKE_CUDA_ARCHITECTURES}'"'
 
diff --git a/tools/ci_build/github/linux/docker/inference/x86_64/default/cuda11/Dockerfile b/tools/ci_build/github/linux/docker/inference/x86_64/default/cuda11/Dockerfile
index 6702474d75801..9be2ff7560bae 100644
--- a/tools/ci_build/github/linux/docker/inference/x86_64/default/cuda11/Dockerfile
+++ b/tools/ci_build/github/linux/docker/inference/x86_64/default/cuda11/Dockerfile
@@ -31,11 +31,11 @@ else \
     echo "TRT_VERSION is none skipping Tensor RT Installation" ; \
 fi
 
-ENV PATH /usr/lib/jvm/msopenjdk-11/bin:$PATH
+ENV PATH=/usr/lib/jvm/msopenjdk-11/bin:$PATH
 ENV LANG=en_US.UTF-8
 ENV LC_ALL=en_US.UTF-8
 ENV JAVA_HOME=/usr/lib/jvm/msopenjdk-11
-ENV CUDAHOSTCXX /opt/rh/gcc-toolset-11/root/usr/bin/g++
+ENV CUDAHOSTCXX=/opt/rh/gcc-toolset-11/root/usr/bin/g++
 ADD scripts /tmp/scripts
 RUN cd /tmp/scripts && /tmp/scripts/install_deps.sh && rm -rf /tmp/scripts
 
diff --git a/tools/ci_build/github/linux/docker/inference/x86_64/default/cuda12/Dockerfile b/tools/ci_build/github/linux/docker/inference/x86_64/default/cuda12/Dockerfile
index 4059de23b2480..c039c641bef27 100644
--- a/tools/ci_build/github/linux/docker/inference/x86_64/default/cuda12/Dockerfile
+++ b/tools/ci_build/github/linux/docker/inference/x86_64/default/cuda12/Dockerfile
@@ -35,11 +35,11 @@ fi
 ENV LANG=en_US.UTF-8
 ENV LC_ALL=en_US.UTF-8
 
-ENV CUDAHOSTCXX /opt/rh/gcc-toolset-12/root/usr/bin/g++
+ENV CUDAHOSTCXX=/opt/rh/gcc-toolset-12/root/usr/bin/g++
 ADD scripts /tmp/scripts
 RUN sed -i 's/enabled\s*=\s*1/enabled = 1\nexclude=dotnet* aspnet* netstandard*/g' /etc/yum.repos.d/ubi.repo && \
 	rpm -Uvh https://packages.microsoft.com/config/centos/8/packages-microsoft-prod.rpm && dnf install -y msopenjdk-11 && cd /tmp/scripts && /tmp/scripts/install_deps.sh && rm -rf /tmp/scripts
-ENV PATH /usr/lib/jvm/msopenjdk-11/bin:$PATH
+ENV PATH=/usr/lib/jvm/msopenjdk-11/bin:$PATH
 ENV JAVA_HOME=/usr/lib/jvm/msopenjdk-11
 ARG BUILD_UID=1001
 ARG BUILD_USER=onnxruntimedev
diff --git a/tools/ci_build/github/linux/docker/inference/x86_64/python/cuda/Dockerfile b/tools/ci_build/github/linux/docker/inference/x86_64/python/cuda/Dockerfile
index f6f3ad7384592..a69b98f86ba1b 100644
--- a/tools/ci_build/github/linux/docker/inference/x86_64/python/cuda/Dockerfile
+++ b/tools/ci_build/github/linux/docker/inference/x86_64/python/cuda/Dockerfile
@@ -32,8 +32,8 @@ else \
     echo "TRT_VERSION is x${TRT_VERSION} skipping Tensor RT Installation" ; \
 fi
 
-ENV PATH /usr/local/cuda/bin:$PATH
-ENV CUDA_MODULE_LOADING "LAZY"
+ENV PATH=/usr/local/cuda/bin:$PATH
+ENV CUDA_MODULE_LOADING="LAZY"
 
 ADD scripts /tmp/scripts
 RUN cd /tmp/scripts && /tmp/scripts/install_centos.sh && rm -rf /tmp/scripts

From b1e0930eab19436590505790e331744804b12caa Mon Sep 17 00:00:00 2001
From: Adrian Lizarraga <adlizarraga@microsoft.com>
Date: Mon, 11 Nov 2024 15:20:07 -0800
Subject: [PATCH 4/4] Fix build for linux python wheel (#22801)

### Description
Fixes command for building Linux python packages by preventing an empty
`-p` command-line option from being passed to a subsequent build script:
https://github.com/microsoft/onnxruntime/blob/1f3b675453e8412e5c084bfb95997967d0c2eec2/tools/ci_build/github/linux/run_python_dockerbuild.sh#L37



### Motivation and Context
A recent [PR
](https://github.com/microsoft/onnxruntime/pull/22773)introduced a new
optional command-line option (`-p`) to pass custom python exe paths. We
need to check if the option is empty before forwarding the option to a
separate build script.
---
 tools/ci_build/github/linux/run_python_dockerbuild.sh | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/tools/ci_build/github/linux/run_python_dockerbuild.sh b/tools/ci_build/github/linux/run_python_dockerbuild.sh
index 8285776b58e4a..2fec98e569919 100755
--- a/tools/ci_build/github/linux/run_python_dockerbuild.sh
+++ b/tools/ci_build/github/linux/run_python_dockerbuild.sh
@@ -18,6 +18,10 @@ done
 mkdir -p "${HOME}/.onnx"
 DOCKER_SCRIPT_OPTIONS="-d ${DEVICE} -c ${BUILD_CONFIG}"
 
+if [ "${PYTHON_EXES}" != "" ] ; then
+    DOCKER_SCRIPT_OPTIONS+=" -p ${PYTHON_EXES}"
+fi
+
 if [ "${BUILD_EXTR_PAR}" != "" ] ; then
     DOCKER_SCRIPT_OPTIONS+=" -x ${BUILD_EXTR_PAR}"
 fi
@@ -34,7 +38,7 @@ docker run --rm \
     -e ORT_DISABLE_PYTHON_PACKAGE_LOCAL_VERSION \
     -e DEFAULT_TRAINING_PACKAGE_DEVICE \
     $ADDITIONAL_DOCKER_PARAMETER \
-    $DOCKER_IMAGE tools/ci_build/github/linux/build_linux_python_package.sh -c $BUILD_CONFIG -p $PYTHON_EXES $DOCKER_SCRIPT_OPTIONS
+    $DOCKER_IMAGE tools/ci_build/github/linux/build_linux_python_package.sh $DOCKER_SCRIPT_OPTIONS
 
 sudo rm -rf "${BUILD_BINARIESDIRECTORY}/${BUILD_CONFIG}/onnxruntime" "${BUILD_BINARIESDIRECTORY}/${BUILD_CONFIG}/pybind11" \
     "${BUILD_BINARIESDIRECTORY}/${BUILD_CONFIG}/models" "${BUILD_BINARIESDIRECTORY}/${BUILD_CONFIG}/_deps" \