use composite cache key

1.19.2

fix variable name

fix variable reference

aaaaaaaaaaaaaaaaaaaa

machine-learning/0001-fix-rocm-conv-thread-safety.patch

@@ -0,0 +1,150 @@
+From 350e3237eadb738a0d96295a62f2eed96653c315 Mon Sep 17 00:00:00 2001
+From: mertalev <101130780+mertalev@users.noreply.github.com>
+Date: Fri, 20 Dec 2024 00:59:21 -0500
+Subject: [PATCH 1/1] fix: avoid race condition for rocm conv algo caching
+
+---
+ onnxruntime/core/providers/rocm/nn/conv.cc         |  8 ++++----
+ onnxruntime/core/providers/rocm/nn/conv.h          | 14 ++++++++++++--
+ .../core/providers/rocm/nn/conv_transpose.cc       |  8 ++++----
+ 3 files changed, 20 insertions(+), 10 deletions(-)
+
+diff --git a/onnxruntime/core/providers/rocm/nn/conv.cc b/onnxruntime/core/providers/rocm/nn/conv.cc
+index d7f47d07a8..98b6b69212 100644
+--- a/onnxruntime/core/providers/rocm/nn/conv.cc
++++ b/onnxruntime/core/providers/rocm/nn/conv.cc
+@@ -127,7 +127,6 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
+ 
+     if (w_dims_changed) {
+       s_.last_w_dims = gsl::make_span(w_dims);
+-      s_.cached_benchmark_fwd_results.clear();
+     }
+ 
+     ORT_RETURN_IF_ERROR(conv_attrs_.ValidateInputShape(X->Shape(), W->Shape(), channels_last, channels_last));
+@@ -278,7 +277,8 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
+       HIP_CALL_THROW(hipMemsetAsync(s_.b_zero, 0, malloc_size, Stream(context)));
+     }
+ 
+-    if (!s_.cached_benchmark_fwd_results.contains(x_dims_miopen)) {
++    const std::size_t algo_key = HashConvAlgoKey(x_dims_miopen, w_dims);
++    if (!s_.cached_benchmark_fwd_results.contains(algo_key)) {
+       miopenConvAlgoPerf_t perf;
+       int algo_count = 1;
+       const ROCMExecutionProvider* rocm_ep = static_cast<const ROCMExecutionProvider*>(this->Info().GetExecutionProvider());
+@@ -301,9 +301,9 @@ Status Conv<T, NHWC>::UpdateState(OpKernelContext* context, bool bias_expected)
+           algo_search_workspace.get(),
+           max_ws_size,
+           false));  // Do not do exhaustive algo search.
+-      s_.cached_benchmark_fwd_results.insert(x_dims_miopen, {perf.fwd_algo, perf.memory});
++      s_.cached_benchmark_fwd_results.insert(algo_key, {perf.fwd_algo, perf.memory});
+     }
+-    const auto& perf = s_.cached_benchmark_fwd_results.at(x_dims_miopen);
++    const auto& perf = s_.cached_benchmark_fwd_results.at(algo_key);
+     s_.fwd_algo = perf.fwd_algo;
+     s_.workspace_bytes = perf.memory;
+   } else {
+diff --git a/onnxruntime/core/providers/rocm/nn/conv.h b/onnxruntime/core/providers/rocm/nn/conv.h
+index bc9846203e..b1ca5f8e4b 100644
+--- a/onnxruntime/core/providers/rocm/nn/conv.h
++++ b/onnxruntime/core/providers/rocm/nn/conv.h
+@@ -43,6 +43,11 @@ struct vector_hash {
+   }
+ };
+ 
++inline std::size_t HashConvAlgoKey(const TensorShapeVector& x_dims, const TensorShapeVector& w_dims) {
++  vector_hash vh;
++  return vh(x_dims) ^ vh(w_dims);
++}
++
+ template <typename Key, typename T,
+           typename Hash = std::hash<Key>,
+           typename KeyEqual = std::equal_to<Key>,
+@@ -52,6 +57,7 @@ class lru_unordered_map {
+   lru_unordered_map(size_t max_size) : max_size_(max_size) {}
+ 
+   void insert(const Key& key, const T& value) {
++    std::lock_guard<std::mutex> guard(mutex_);
+     auto it = items_.find(key);
+     if (it != items_.end()) {
+       it->second.value = value;
+@@ -69,6 +75,7 @@ class lru_unordered_map {
+   }
+ 
+   T& at(const Key& key) {
++    std::lock_guard<std::mutex> guard(mutex_);
+     auto it = items_.find(key);
+     if (it == items_.end()) {
+       throw std::out_of_range("There is no such key in cache");
+@@ -78,6 +85,7 @@ class lru_unordered_map {
+   }
+ 
+   bool contains(const Key& key) const {
++    std::lock_guard<std::mutex> guard(mutex_);
+     return items_.find(key) != items_.end();
+   }
+ 
+@@ -86,6 +94,7 @@ class lru_unordered_map {
+   }
+ 
+   void clear() {
++    std::lock_guard<std::mutex> guard(mutex_);
+     items_.clear();
+     lru_list_.clear();
+   }
+@@ -106,6 +115,7 @@ class lru_unordered_map {
+   size_t max_size_;
+   std::unordered_map<Key, value_type, Hash, KeyEqual, MapAllocator> items_;
+   list_type lru_list_;
++  mutable std::mutex mutex_;
+ };
+ 
+ // cached miopen descriptors
+@@ -148,8 +158,8 @@ struct MiopenConvState {
+     decltype(AlgoPerfType().memory) memory;
+   };
+ 
+-  lru_unordered_map<TensorShapeVector, PerfFwdResultParams, vector_hash> cached_benchmark_fwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
+-  lru_unordered_map<TensorShapeVector, PerfBwdResultParams, vector_hash> cached_benchmark_bwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
++  lru_unordered_map<std::size_t, PerfFwdResultParams> cached_benchmark_fwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
++  lru_unordered_map<std::size_t, PerfBwdResultParams> cached_benchmark_bwd_results{MAX_CACHED_ALGO_PERF_RESULTS};
+ 
+   // Some properties needed to support asymmetric padded Conv nodes
+   bool post_slicing_required;
+diff --git a/onnxruntime/core/providers/rocm/nn/conv_transpose.cc b/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
+index 7447113fdf..dea9bf2a05 100644
+--- a/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
++++ b/onnxruntime/core/providers/rocm/nn/conv_transpose.cc
+@@ -76,7 +76,6 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
+ 
+       if (w_dims_changed) {
+         s_.last_w_dims = gsl::make_span(w_dims);
+-        s_.cached_benchmark_bwd_results.clear();
+       }
+ 
+       ConvTransposeAttributes::Prepare p;
+@@ -127,7 +126,8 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
+ 
+       y_data = reinterpret_cast<HipT*>(p.Y->MutableData<T>());
+ 
+-      if (!s_.cached_benchmark_bwd_results.contains(x_dims)) {
++      const std::size_t algo_key = HashConvAlgoKey(x_dims, w_dims);
++      if (!s_.cached_benchmark_bwd_results.contains(algo_key)) {
+         IAllocatorUniquePtr<void> algo_search_workspace = GetScratchBuffer<void>(AlgoSearchWorkspaceSize, context->GetComputeStream());
+ 
+         miopenConvAlgoPerf_t perf;
+@@ -147,10 +147,10 @@ Status ConvTranspose<T, NHWC>::DoConvTranspose(OpKernelContext* context, bool dy
+             algo_search_workspace.get(),
+             AlgoSearchWorkspaceSize,
+             false));
+-        s_.cached_benchmark_bwd_results.insert(x_dims, {perf.bwd_data_algo, perf.memory});
++        s_.cached_benchmark_bwd_results.insert(algo_key, {perf.bwd_data_algo, perf.memory});
+       }
+ 
+-      const auto& perf = s_.cached_benchmark_bwd_results.at(x_dims);
++      const auto& perf = s_.cached_benchmark_bwd_results.at(algo_key);
+       s_.bwd_data_algo = perf.bwd_data_algo;
+       s_.workspace_bytes = perf.memory;
+     }
+-- 
+2.43.0
+

machine-learning/0001-guard-algo-benchmark-results.patch

@@ -1,58 +0,0 @@
-From 1f5d6323fa69ee16feab25f8e1398c1aed03ee08 Mon Sep 17 00:00:00 2001
-From: mertalev <101130780+mertalev@users.noreply.github.com>
-Date: Sun, 29 Dec 2024 14:07:51 -0500
-Subject: [PATCH] guard algo benchmark results
-
----
- onnxruntime/core/providers/rocm/nn/conv.h | 6 ++++++
- 1 file changed, 6 insertions(+)
-
-diff --git a/onnxruntime/core/providers/rocm/nn/conv.h b/onnxruntime/core/providers/rocm/nn/conv.h
-index bc9846203e..0086e064f1 100644
---- a/onnxruntime/core/providers/rocm/nn/conv.h
-+++ b/onnxruntime/core/providers/rocm/nn/conv.h
-@@ -52,6 +52,7 @@ class lru_unordered_map {
-   lru_unordered_map(size_t max_size) : max_size_(max_size) {}
- 
-   void insert(const Key& key, const T& value) {
-+    std::lock_guard<std::mutex> guard(mutex_);
-     auto it = items_.find(key);
-     if (it != items_.end()) {
-       it->second.value = value;
-@@ -69,6 +70,7 @@ class lru_unordered_map {
-   }
- 
-   T& at(const Key& key) {
-+    std::lock_guard<std::mutex> guard(mutex_);
-     auto it = items_.find(key);
-     if (it == items_.end()) {
-       throw std::out_of_range("There is no such key in cache");
-@@ -78,14 +80,17 @@ class lru_unordered_map {
-   }
- 
-   bool contains(const Key& key) const {
-+    std::lock_guard<std::mutex> guard(mutex_);
-     return items_.find(key) != items_.end();
-   }
- 
-   size_t size() const {
-+    std::lock_guard<std::mutex> guard(mutex_);
-     return items_.size();
-   }
- 
-   void clear() {
-+    std::lock_guard<std::mutex> guard(mutex_);
-     items_.clear();
-     lru_list_.clear();
-   }
-@@ -106,6 +111,7 @@ class lru_unordered_map {
-   size_t max_size_;
-   std::unordered_map<Key, value_type, Hash, KeyEqual, MapAllocator> items_;
-   list_type lru_list_;
-+  mutable std::mutex mutex_;
- };
- 
- // cached miopen descriptors
--- 
-2.43.0
-

machine-learning/Dockerfile

@@ -17,6 +17,7 @@ RUN mkdir /opt/armnn && \
 
 # Warning: 26.3Gb of disk space required to pull this image
 # https://github.com/microsoft/onnxruntime/blob/main/dockerfiles/Dockerfile.rocm
+# 6.2 or later fails to build as of writing
 FROM rocm/dev-ubuntu-22.04:6.1.2-complete AS builder-rocm
 
 WORKDIR /code
@@ -32,11 +33,12 @@ RUN wget -nv https://github.com/Kitware/CMake/releases/download/v3.27.3/cmake-3.
 ENV PATH /code/cmake-3.27.3-linux-x86_64/bin:${PATH}
 
 # Prepare onnxruntime repository & build onnxruntime
+# 1.20.1 fails to build as of writing
 RUN git clone --single-branch --branch v1.19.2 --recursive "https://github.com/Microsoft/onnxruntime" onnxruntime
 WORKDIR /code/onnxruntime
 # Fix for multi-threading based on comments in https://github.com/microsoft/onnxruntime/pull/19567
-COPY ./0001-guard-algo-benchmark-results.patch /tmp/
+COPY ./0001-fix-rocm-conv-thread-safety.patch /tmp/
-RUN git apply /tmp/0001-guard-algo-benchmark-results.patch
+RUN git apply /tmp/0001-fix-rocm-conv-thread-safety.patch
 
 RUN /bin/sh ./dockerfiles/scripts/install_common_deps.sh
 # Note: the `parallel` setting uses a substantial amount of RAM
@@ -112,7 +114,7 @@ COPY --from=builder-armnn \
     /opt/ann/build.sh \
     /opt/armnn/
 
-FROM rocm/dev-ubuntu-24.04:6.2.4-complete AS prod-rocm
+FROM rocm/dev-ubuntu-22.04:6.1.2-complete AS prod-rocm
 
 
 FROM prod-${DEVICE} AS prod