Cherry for release 1.12.0 final

onnxruntime/contrib_ops/cpu/transformers/beam_search_device_helper.cc

@@ -197,7 +197,6 @@ void InitBeamState(transformers::IBeamSearchState<T>* beam_state,
 
   // T5 does not need position, so next_positions is empty for T5.
   if (!beam_state->next_positions.empty()) {
-    memset(beam_state->next_positions.data(), 0, beam_state->next_positions.size_bytes());
     gsl::copy(sequence_lengths, beam_state->next_positions);
   }
 
@@ -274,13 +273,13 @@ Status ProcessLogits(const OrtValue& logits,                                 //
   // Get scores for candidates of next token: next_token_scores = log_softmax(next_token_logits, dim=-1)
   gsl::span<T>& next_token_scores = beam_state->next_token_scores;
   ORT_RETURN_IF_ERROR(
-    SoftmaxCPU<T>(
-      batch_beam_size,  // rows
-      vocab_size,       // elements per row
-      (input_length == 1 && logits_batch_size == batch_beam_size) ? logits_data : next_token_logits.data(),
-      next_token_scores.data(),
-      true,
-      thread_pool));
+      SoftmaxCPU<T>(
+          batch_beam_size,  // rows
+          vocab_size,       // elements per row
+          (input_length == 1 && logits_batch_size == batch_beam_size) ? logits_data : next_token_logits.data(),
+          next_token_scores.data(),
+          true,
+          thread_pool));
 
 #ifdef DEBUG_BEAM_SEARCH
   dumper->Print("next_token_scores after softmax", next_token_scores.data(), batch_size, num_beams, vocab_size);
@@ -428,12 +427,12 @@ Status UpdateGptFeeds(
     std::vector<OrtValue>& next_inputs,
     int current_length,
     OrtValue& position_ids,
+    bool increase_position,
     gsl::span<const int32_t> beam_next_tokens,
     gsl::span<const int32_t> beam_indices,
     int num_beams,
     int gpt_subgraph_first_past_input_idx,
-    int gpt_subgraph_first_present_output_idx,
-    const transformers::IConsoleDumper* dumper) {
+    int gpt_subgraph_first_present_output_idx) {
   // last_outputs: logits, present_0, present_1, ...
   // next_inputs: input_ids, position_id, attention_mask, past_0, past_1
   ORT_UNUSED_PARAMETER(stream);
@@ -454,10 +453,12 @@ Status UpdateGptFeeds(
   }
   next_inputs[0] = input_ids;
 
-  // Update position IDs
-  int32_t* position_data = position_ids.GetMutable<Tensor>()->MutableData<int32_t>();
-  for (int i = 0; i < batch_beam_size; i++) {
-    position_data[i]++;
+  if (increase_position) {
+    // Update position IDs
+    int32_t* position_data = position_ids.GetMutable<Tensor>()->MutableData<int32_t>();
+    for (int i = 0; i < batch_beam_size; i++) {
+      position_data[i]++;
+    }
   }
   next_inputs[1] = position_ids;
 
@@ -477,14 +478,6 @@ Status UpdateGptFeeds(
   }
   next_inputs[2] = attention_mask;
 
-#ifdef DEBUG_BEAM_SEARCH
-  dumper->Print("input_ids", input_ids);
-  dumper->Print("position_ids", position_ids);
-  dumper->Print("attention_mask", attention_mask);
-#else
-  ORT_UNUSED_PARAMETER(dumper);
-#endif
-
   // Update past state
   if (num_beams == 1) {
     // feed present_* output to past_* inputs one by one
@@ -725,12 +718,12 @@ template Status UpdateGptFeeds<float>(
     std::vector<OrtValue>& next_inputs,
     int current_length,
     OrtValue& position_ids,
+    bool increase_position,
     gsl::span<const int32_t> beam_next_tokens,
     gsl::span<const int32_t> beam_indices,
     int num_beams,
     int gpt_subgraph_first_past_input_idx,
-    int gpt_subgraph_first_present_output_idx,
-    const transformers::IConsoleDumper* dumper);
+    int gpt_subgraph_first_present_output_idx);
 
 template Status UpdateDecoderFeeds<float>(
     AllocatorPtr allocator,
@@ -751,28 +744,28 @@ template Status UpdateDecoderFeeds<float>(
 template void ExpandInputs<int32_t>(const OrtValue& input, int num_beams, AllocatorPtr allocator, OrtValue& expanded);
 
 template Status ExpandBuffer<int32_t>(
-  void* stream,
-  const OrtValue& input,
-  int num_beams,
-  AllocatorPtr allocator,
-  OrtValue& expanded,
-  bool only_copy_shape);
+    void* stream,
+    const OrtValue& input,
+    int num_beams,
+    AllocatorPtr allocator,
+    OrtValue& expanded,
+    bool only_copy_shape);
 
 template Status ExpandBuffer<float>(
-  void* stream,
-  const OrtValue& input,
-  int num_beams,
-  AllocatorPtr allocator,
-  OrtValue& expanded,
-  bool only_copy_shape);
+    void* stream,
+    const OrtValue& input,
+    int num_beams,
+    AllocatorPtr allocator,
+    OrtValue& expanded,
+    bool only_copy_shape);
 
 template Status ExpandBuffer<MLFloat16>(
-  void* stream,
-  const OrtValue& input,
-  int num_beams,
-  AllocatorPtr allocator,
-  OrtValue& expanded,
-  bool only_copy_shape);
+    void* stream,
+    const OrtValue& input,
+    int num_beams,
+    AllocatorPtr allocator,
+    OrtValue& expanded,
+    bool only_copy_shape);
 
 }  // namespace BeamSearchCpuDeviceHelper
 }  // namespace contrib

onnxruntime/contrib_ops/cpu/transformers/beam_search_device_helper.h

@@ -96,12 +96,12 @@ using UpdateGptFeedsFunc = std::function<Status(
     std::vector<OrtValue>& next_inputs,
     int current_length,
     OrtValue& position_ids,
+    bool increase_position,
     gsl::span<const int32_t> beam_next_tokens,
     gsl::span<const int32_t> beam_indices,
     int num_beams,
     int gpt_subgraph_first_past_input_idx,
-    int gpt_subgraph_first_present_output_idx,
-    const transformers::IConsoleDumper* dumper)>;
+    int gpt_subgraph_first_present_output_idx)>;
 
 // Create encoder inputs (for encoder-decoder model like T5).
 using CreateEncoderInputsFunc = std::function<Status(
@@ -142,7 +142,6 @@ using ExpandBufferFunc = std::function<Status(
     bool only_copy_shape)>;
 }  // namespace BeamSearchDeviceHelper
 
-
 // These are CPU specific device helper implementations
 namespace BeamSearchCpuDeviceHelper {
 Status TopK(
@@ -208,12 +207,12 @@ Status UpdateGptFeeds(
     std::vector<OrtValue>& next_inputs,
     int current_length,
     OrtValue& position_ids,
+    bool increase_position,
     gsl::span<const int32_t> beam_next_tokens,
     gsl::span<const int32_t> beam_indices,
     int num_beams,
     int gpt_subgraph_first_past_input_idx,
-    int gpt_subgraph_first_present_output_idx,
-    const transformers::IConsoleDumper* dumper);
+    int gpt_subgraph_first_present_output_idx);
 
 // ---------------------------------------------------------------
 // Functions for encoder-decoder model like T5

onnxruntime/contrib_ops/cpu/transformers/beam_search_impl_gpt.h

@@ -56,6 +56,7 @@ class BeamSearchGpt : public BeamSearchBase<T> {
       std::vector<OrtValue>& next_inputs,
       int current_length,
       OrtValue& position_ids,
+      bool increase_position,
       gsl::span<const int32_t> beam_next_tokens,
       gsl::span<const int32_t> beam_indices);
 
@@ -93,6 +94,7 @@ Status BeamSearchGpt<T>::UpdateFeeds(
     std::vector<OrtValue>& next_inputs,
     int current_length,
     OrtValue& position_ids,
+    bool increase_position,
     gsl::span<const int32_t> beam_next_tokens,
     gsl::span<const int32_t> beam_indices) {
   return update_feeds_func_(this->temp_space_allocator_,
@@ -101,12 +103,12 @@ Status BeamSearchGpt<T>::UpdateFeeds(
                             next_inputs,
                             current_length,
                             position_ids,
+                            increase_position,
                             beam_next_tokens,
                             beam_indices,
                             this->parameters_->num_beams,
                             gpt_subgraph_.GetFirstPastInputIndex(),
-                            gpt_subgraph_.GetFirstPresentOutputIndex(),
-                            this->GetConsoleDumper());
+                            gpt_subgraph_.GetFirstPresentOutputIndex());
 }
 
 template <typename T>
@@ -186,11 +188,7 @@ Status BeamSearchGpt<T>::Execute(const FeedsFetchesManager& feeds_fetches_manage
 
 #ifdef DEBUG_BEAM_SEARCH
   const IConsoleDumper* dumper = this->GetConsoleDumper();
-  dumper->Print("input_ids", feeds[0]);
-  dumper->Print("position_ids", feeds[1]);
-  dumper->Print("attention_mask", feeds[2]);
 #endif
-
   // Position ids for all iterations except the first. It uses memory buffer owned by next_positions.
   OrtValue position_ids;
   int64_t dims[] = {parameters->BatchBeamSize(), 1};
@@ -205,9 +203,19 @@ Status BeamSearchGpt<T>::Execute(const FeedsFetchesManager& feeds_fetches_manage
   int iteration_counter = 0;
   while (current_length < parameters->max_length) {
     iteration_counter++;
+
 #ifdef DEBUG_BEAM_SEARCH
     auto cur_len = std::to_string(current_length);
     dumper->Print("***CurrentLength", cur_len, true);
+    dumper->Print("iteration", iteration_counter, true);
+
+    dumper->Print("input_ids", feeds[0]);
+    dumper->Print("position_ids", feeds[1]);
+    dumper->Print("attention_mask", feeds[2]);
+    for (size_t i = 3; i < feeds.size(); i++) {
+      dumper->Print("past", static_cast<int>(i) - 3, true);
+      dumper->Print("", feeds[i]);
+    }
 #endif
 
     status = utils::ExecuteSubgraph(this->decoder_session_state_,
@@ -241,8 +249,11 @@ Status BeamSearchGpt<T>::Execute(const FeedsFetchesManager& feeds_fetches_manage
 
     // Prepare inputs for next round of subgraph call.
     if (current_length < parameters->max_length) {
+      // For the first iteration, position_ids is initialized as sequence lengths. We can add it to feeds directly.
+      // For the remaining iterations, we need increase position_ids first, then add it to feeds.
+      bool increase_position = (iteration_counter > 1);
       ORT_RETURN_IF_ERROR(UpdateFeeds(fetches, feeds, current_length,
-                                      position_ids,
+                                      position_ids, increase_position,
                                       beam_next_tokens.as_span<const int32_t>(),
                                       beam_indices.as_span<const int32_t>()));
     }

onnxruntime/contrib_ops/cuda/transformers/beam_search_device_helper.cc

@@ -258,9 +258,8 @@ Status ProcessLogits(const OrtValue& logits,                                 //
 
   // The output will be float for consideration of precision and easy integration with remaining parts.
   float* Y_data = next_token_scores.data();
-  const CudaT* X_data = (input_length == 1 && logits_batch_size == batch_beam_size) ?
-                        logits_data :
-                        reinterpret_cast<const CudaT*>(next_token_logits.data());
+  bool is_single_token = (input_length == 1 && logits_batch_size == batch_beam_size);
+  const CudaT* X_data = is_single_token ? logits_data : reinterpret_cast<const CudaT*>(next_token_logits.data());
 
   dispatch_blockwise_softmax_forward<CudaT, float, float, true>(
       cuda_stream, Y_data, X_data, vocab_size, vocab_size, batch_size * num_beams);
@@ -500,12 +499,12 @@ Status UpdateGptFeeds(
     std::vector<OrtValue>& next_inputs,
     int current_length,
     OrtValue& position_ids,
+    bool increase_position,
     gsl::span<const int32_t> beam_next_tokens,
     gsl::span<const int32_t> beam_indices,
     int num_beams,
     int gpt_subgraph_first_past_input_idx,
-    int gpt_subgraph_first_present_output_idx,
-    const transformers::IConsoleDumper* dumper) {
+    int gpt_subgraph_first_present_output_idx) {
   // Update input_ids with next tokens.
   int batch_beam_size = static_cast<int>(beam_next_tokens.length());
   int64_t dims[] = {batch_beam_size, 1};
@@ -519,7 +518,7 @@ Status UpdateGptFeeds(
   next_inputs[0] = input_ids;
 
   // Update position IDs
-  int32_t* position_data = position_ids.GetMutable<Tensor>()->MutableData<int32_t>();
+  int32_t* position_data = increase_position ? position_ids.GetMutable<Tensor>()->MutableData<int32_t>() : nullptr;
   next_inputs[1] = position_ids;
 
   // Update attention mask
@@ -538,14 +537,6 @@ Status UpdateGptFeeds(
 
   next_inputs[2] = attention_mask;
 
-#ifdef DEBUG_BEAM_SEARCH
-  dumper->Print("input_ids", input_ids);
-  dumper->Print("position_ids", position_ids);
-  dumper->Print("attention_mask", attention_mask);
-#else
-  ORT_UNUSED_PARAMETER(dumper);
-#endif
-
   // Update past state
   if (num_beams == 1) {
     const int k = gpt_subgraph_first_past_input_idx - gpt_subgraph_first_present_output_idx;
@@ -662,12 +653,12 @@ Status ExpandBuffer(void* stream,
   for (int i = 0; i < batch_size; i++) {
     for (int j = 0; j < num_beams; j++) {
       CUDA_RETURN_IF_ERROR(
-        cudaMemcpyAsync(
-          target,
-          input_data + i * chunk_size,
-          sizeof(T) * chunk_size,
-          cudaMemcpyDeviceToDevice,
-          cuda_stream));
+          cudaMemcpyAsync(
+              target,
+              input_data + i * chunk_size,
+              sizeof(T) * chunk_size,
+              cudaMemcpyDeviceToDevice,
+              cuda_stream));
       target += chunk_size;
     }
   }
@@ -714,12 +705,12 @@ template Status UpdateGptFeeds<float>(
     std::vector<OrtValue>& next_inputs,
     int current_length,
     OrtValue& position_ids,
+    bool increase_position,
     gsl::span<const int32_t> beam_next_tokens,
     gsl::span<const int32_t> beam_indices,
     int num_beams,
     int gpt_subgraph_first_past_input_idx,
-    int gpt_subgraph_first_present_output_idx,
-    const transformers::IConsoleDumper* dumper);
+    int gpt_subgraph_first_present_output_idx);
 
 // Float16
 template void InitBeamState<MLFloat16>(transformers::IBeamSearchState<MLFloat16>* beam_state,
@@ -748,12 +739,12 @@ template Status UpdateGptFeeds<MLFloat16>(
     std::vector<OrtValue>& next_inputs,
     int current_length,
     OrtValue& position_ids,
+    bool increase_position,
     gsl::span<const int32_t> beam_next_tokens,
     gsl::span<const int32_t> beam_indices,
     int num_beams,
     int gpt_subgraph_first_past_input_idx,
-    int gpt_subgraph_first_present_output_idx,
-    const transformers::IConsoleDumper* dumper);
+    int gpt_subgraph_first_present_output_idx);
 
 template Status UpdateDecoderFeeds<float>(
     AllocatorPtr allocator,

onnxruntime/contrib_ops/cuda/transformers/beam_search_device_helper.h

@@ -68,12 +68,12 @@ Status UpdateGptFeeds(
     std::vector<OrtValue>& next_inputs,
     int current_length,
     OrtValue& position_ids,
+    bool increase_position,
     gsl::span<const int32_t> beam_next_tokens,
     gsl::span<const int32_t> beam_indices,
     int num_beams,
     int gpt_subgraph_first_past_input_idx,
-    int gpt_subgraph_first_present_output_idx,
-    const transformers::IConsoleDumper* dumper);
+    int gpt_subgraph_first_present_output_idx);
 
 // ---------------------------------------------------------------
 // Functions for encoder-decoder model like T5

onnxruntime/contrib_ops/cuda/transformers/beam_search_impl.cu

@@ -248,9 +248,11 @@ __global__ void UpdateGptInputsKernel(const T* old_mask_data,
     int j = index % current_length;
     mask_data[index] = (j < current_length - 1) ? old_mask_data[i * (current_length - 1) + j] : static_cast<T>(1);
 
-    // Update sequence length (or next positions).
-    if (index < batch_beam_size) {
-      next_positions[index]++;
+    if (next_positions != nullptr) {
+      // Update sequence length (or next positions).
+      if (index < batch_beam_size) {
+        next_positions[index]++;
+      }
     }
   }
 }

onnxruntime/core/common/cpuid_arch_definition.h

@@ -0,0 +1,14 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+// This file defines the CPUIDINFO_ARCH_* symbols.
+
+#pragma once
+
+#if defined(_M_IX86) || (defined(_M_X64) && !defined(_M_ARM64EC)) || defined(__i386__) || defined(__x86_64__)
+#define CPUIDINFO_ARCH_X86
+#endif
+
+#if defined(_M_ARM64) || defined(__aarch64__) || defined(_M_ARM) || defined(__arm__)
+#define CPUIDINFO_ARCH_ARM
+#endif  // ARM or ARM64