diff --git a/.gitmodules b/.gitmodules
index 036a248070855..7bb49e98bfec1 100644
--- a/.gitmodules
+++ b/.gitmodules
@@ -8,6 +8,3 @@
path = cmake/external/emsdk
url = https://github.com/emscripten-core/emsdk.git
branch = 3.1.44
-[submodule "cmake/external/onnxruntime-extensions"]
- path = cmake/external/onnxruntime-extensions
- url = https://github.com/microsoft/onnxruntime-extensions.git
diff --git a/VERSION_NUMBER b/VERSION_NUMBER
index 15b989e398fc7..41c11ffb730cf 100644
--- a/VERSION_NUMBER
+++ b/VERSION_NUMBER
@@ -1 +1 @@
-1.16.0
+1.16.1
diff --git a/docs/python/README.rst b/docs/python/README.rst
index 7d978b0941235..f3cd6123f3431 100644
--- a/docs/python/README.rst
+++ b/docs/python/README.rst
@@ -8,6 +8,11 @@ For more information on ONNX Runtime, please see `aka.ms/onnxruntime `_
or the `Github project `_.
"""
-__version__ = "1.16.0"
+__version__ = "1.16.1"
__author__ = "Microsoft"
# we need to do device version validation (for example to check Cuda version for an onnxruntime-training package).
diff --git a/onnxruntime/contrib_ops/cuda/bert/attention.cc b/onnxruntime/contrib_ops/cuda/bert/attention.cc
index a79ad96b94d91..c911b6e76701c 100644
--- a/onnxruntime/contrib_ops/cuda/bert/attention.cc
+++ b/onnxruntime/contrib_ops/cuda/bert/attention.cc
@@ -140,27 +140,29 @@ Status Attention::ComputeInternal(OpKernelContext* context) const {
#endif
if (!use_flash_attention) {
- if (is_unidirectional_ && enable_fused_causal_attention_) { // GPT
- // GPT fused kernels requires left side padding. mask can be:
- // none (no padding), 1D sequence lengths or 2d mask.
- // Fused kernels don't support different sequence lengths of q and kv, so only apply to the first token
- // where past state is empty.
- bool is_mask_2d_key_padding = parameters.mask_type == AttentionMaskType::MASK_2D_KEY_PADDING;
- bool use_causal_fused_runner = (nullptr == mask_index || is_mask_1d_seq_len || is_mask_2d_key_padding) &&
- nullptr == relative_position_bias &&
- parameters.past_sequence_length == 0 &&
- parameters.hidden_size == parameters.v_hidden_size &&
- FusedMHARunnerFP16v2::is_supported(sm, parameters.head_size, sequence_length,
- enable_trt_flash_attention_, true);
- if (use_causal_fused_runner) {
- // Here we assume that num_heads, head_size and is_unidirectional does not change for an Attention node.
- if (nullptr == fused_fp16_runner_.get()) {
- fused_fp16_runner_ = FusedMHARunnerFP16v2::Create(num_heads_, parameters.head_size, sm, is_unidirectional_,
- enable_trt_flash_attention_, parameters.scale);
+ if (is_unidirectional_) { // GPT
+ if (enable_fused_causal_attention_) {
+ // GPT fused kernels requires left side padding. mask can be:
+ // none (no padding), 1D sequence lengths or 2d mask.
+ // Fused kernels don't support different sequence lengths of q and kv, so only apply to the first token
+ // where past state is empty.
+ bool is_mask_2d_key_padding = parameters.mask_type == AttentionMaskType::MASK_2D_KEY_PADDING;
+ bool use_causal_fused_runner = (nullptr == mask_index || is_mask_1d_seq_len || is_mask_2d_key_padding) &&
+ nullptr == relative_position_bias &&
+ parameters.past_sequence_length == 0 &&
+ parameters.hidden_size == parameters.v_hidden_size &&
+ FusedMHARunnerFP16v2::is_supported(sm, parameters.head_size, sequence_length,
+ enable_trt_flash_attention_, true);
+ if (use_causal_fused_runner) {
+ // Here we assume that num_heads, head_size and is_unidirectional does not change for an Attention node.
+ if (nullptr == fused_fp16_runner_.get()) {
+ fused_fp16_runner_ = FusedMHARunnerFP16v2::Create(num_heads_, parameters.head_size, sm, is_unidirectional_,
+ enable_trt_flash_attention_, parameters.scale);
+ }
+
+ // Here we assume all causal kernels can be loaded into shared memory. TODO: add a function to check.
+ fused_runner = fused_fp16_runner_.get();
}
-
- // Here we assume all causal kernels can be loaded into shared memory. TODO: add a function to check.
- fused_runner = fused_fp16_runner_.get();
}
} else { // BERT
bool use_fused_runner = !disable_fused_self_attention_ &&
diff --git a/onnxruntime/core/providers/cpu/ml/tree_ensemble_aggregator.h b/onnxruntime/core/providers/cpu/ml/tree_ensemble_aggregator.h
index aba9a798cf786..b9f3050e59c5b 100644
--- a/onnxruntime/core/providers/cpu/ml/tree_ensemble_aggregator.h
+++ b/onnxruntime/core/providers/cpu/ml/tree_ensemble_aggregator.h
@@ -64,6 +64,18 @@ enum MissingTrack : uint8_t {
kFalse = 0
};
+template
+struct TreeNodeElement;
+
+template
+union PtrOrWeight {
+ TreeNodeElement* ptr;
+ struct WeightData {
+ int32_t weight;
+ int32_t n_weights;
+ } weight_data;
+};
+
template
struct TreeNodeElement {
int feature_id;
@@ -71,24 +83,19 @@ struct TreeNodeElement {
// Stores the node threshold or the weights if the tree has one target.
T value_or_unique_weight;
- // onnx specification says hitrates is used to store information about the node,
+ // The onnx specification says hitrates is used to store information about the node,
// but this information is not used for inference.
// T hitrates;
- // True node, false node are obtained by computing `this + truenode_inc_or_first_weight`,
- // `this + falsenode_inc_or_n_weights` if the node is not a leaf.
- // In case of a leaf, these attributes are used to indicate the position of the weight
- // in array `TreeEnsembleCommon::weights_`. If the number of targets or classes is one,
- // the weight is also stored in `value_or_unique_weight`.
- // This implementation assumes a tree has less than 2^31 nodes,
- // and the total number of leave in the set of trees is below 2^31.
- // A node cannot point to itself.
- int32_t truenode_inc_or_first_weight;
- // In case of a leaf, the following attribute indicates the number of weights
- // in array `TreeEnsembleCommon::weights_`. If not a leaf, it indicates
- // `this + falsenode_inc_or_n_weights` is the false node.
- // A node cannot point to itself.
- int32_t falsenode_inc_or_n_weights;
+ // PtrOrWeight acts as a tagged union, with the "tag" being whether the node is a leaf or not (see `is_not_leaf`).
+
+ // If it is not a leaf, it is a pointer to the true child node when traversing the decision tree. The false branch is
+ // always 1 position away from the TreeNodeElement in practice in `TreeEnsembleCommon::nodes_` so it is not stored.
+
+ // If it is a leaf, it contains `weight` and `n_weights` attributes which are used to indicate the position of the
+ // weight in array `TreeEnsembleCommon::weights_`. If the number of targets or classes is one, the weight is also
+ // stored in `value_or_unique_weight`.
+ PtrOrWeight truenode_or_weight;
uint8_t flags;
inline NODE_MODE mode() const { return NODE_MODE(flags & 0xF); }
@@ -189,8 +196,8 @@ class TreeAggregatorSum : public TreeAggregator>& predictions,
const TreeNodeElement& root,
gsl::span> weights) const {
- auto it = weights.begin() + root.truenode_inc_or_first_weight;
- for (int32_t i = 0; i < root.falsenode_inc_or_n_weights; ++i, ++it) {
+ auto it = weights.begin() + root.truenode_or_weight.weight_data.weight;
+ for (int32_t i = 0; i < root.truenode_or_weight.weight_data.n_weights; ++i, ++it) {
ORT_ENFORCE(it->i < (int64_t)predictions.size());
predictions[onnxruntime::narrow(it->i)].score += it->value;
predictions[onnxruntime::narrow(it->i)].has_score = 1;
@@ -292,8 +299,8 @@ class TreeAggregatorMin : public TreeAggregator>& predictions,
const TreeNodeElement& root,
gsl::span> weights) const {
- auto it = weights.begin() + root.truenode_inc_or_first_weight;
- for (int32_t i = 0; i < root.falsenode_inc_or_n_weights; ++i, ++it) {
+ auto it = weights.begin() + root.truenode_or_weight.weight_data.weight;
+ for (int32_t i = 0; i < root.truenode_or_weight.weight_data.n_weights; ++i, ++it) {
predictions[onnxruntime::narrow(it->i)].score =
(!predictions[onnxruntime::narrow(it->i)].has_score || it->value < predictions[onnxruntime::narrow(it->i)].score)
? it->value
@@ -349,8 +356,8 @@ class TreeAggregatorMax : public TreeAggregator>& predictions,
const TreeNodeElement& root,
gsl::span> weights) const {
- auto it = weights.begin() + root.truenode_inc_or_first_weight;
- for (int32_t i = 0; i < root.falsenode_inc_or_n_weights; ++i, ++it) {
+ auto it = weights.begin() + root.truenode_or_weight.weight_data.weight;
+ for (int32_t i = 0; i < root.truenode_or_weight.weight_data.n_weights; ++i, ++it) {
predictions[onnxruntime::narrow(it->i)].score =
(!predictions[onnxruntime::narrow(it->i)].has_score || it->value > predictions[onnxruntime::narrow(it->i)].score)
? it->value
diff --git a/onnxruntime/core/providers/cpu/ml/tree_ensemble_common.h b/onnxruntime/core/providers/cpu/ml/tree_ensemble_common.h
index 161bb2b0820eb..8f847fe66aa73 100644
--- a/onnxruntime/core/providers/cpu/ml/tree_ensemble_common.h
+++ b/onnxruntime/core/providers/cpu/ml/tree_ensemble_common.h
@@ -85,6 +85,13 @@ class TreeEnsembleCommon : public TreeEnsembleCommonAttributes {
template
void ComputeAgg(concurrency::ThreadPool* ttp, const Tensor* X, Tensor* Y, Tensor* label, const AGG& agg) const;
+
+ private:
+ size_t AddNodes(const size_t i, const InlinedVector& cmodes, const InlinedVector& truenode_ids,
+ const InlinedVector& falsenode_ids, const std::vector& nodes_featureids,
+ const std::vector& nodes_values_as_tensor, const std::vector& node_values,
+ const std::vector& nodes_missing_value_tracks_true, std::vector& updated_mapping,
+ int64_t tree_id, const InlinedVector& node_tree_ids);
};
template
@@ -186,7 +193,7 @@ Status TreeEnsembleCommon::Init(
max_tree_depth_ = 1000;
ORT_ENFORCE(nodes_modes.size() < std::numeric_limits::max());
- // additional members
+ // Additional members
size_t limit;
uint32_t i;
InlinedVector cmodes;
@@ -195,18 +202,14 @@ Status TreeEnsembleCommon::Init(
int fpos = -1;
for (i = 0, limit = nodes_modes.size(); i < limit; ++i) {
cmodes.push_back(MakeTreeNodeMode(nodes_modes[i]));
- if (cmodes[i] == NODE_MODE::LEAF)
- continue;
+ if (cmodes[i] == NODE_MODE::LEAF) continue;
if (fpos == -1) {
fpos = static_cast(i);
continue;
}
- if (cmodes[i] != cmodes[fpos])
- same_mode_ = false;
+ if (cmodes[i] != cmodes[fpos]) same_mode_ = false;
}
- // filling nodes
-
n_nodes_ = nodes_treeids.size();
limit = static_cast(n_nodes_);
InlinedVector node_tree_ids;
@@ -214,156 +217,185 @@ Status TreeEnsembleCommon::Init(
nodes_.clear();
nodes_.reserve(limit);
roots_.clear();
- std::unordered_map idi;
- idi.reserve(limit);
+ std::unordered_map node_tree_ids_map;
+ node_tree_ids_map.reserve(limit);
+
+ InlinedVector truenode_ids, falsenode_ids;
+ truenode_ids.reserve(limit);
+ falsenode_ids.reserve(limit);
max_feature_id_ = 0;
+ // Build node_tree_ids and node_tree_ids_map and truenode_ids and falsenode_ids
for (i = 0; i < limit; ++i) {
- TreeNodeElementId node_tree_id{static_cast(nodes_treeids[i]),
- static_cast(nodes_nodeids[i])};
- TreeNodeElement node;
- node.feature_id = static_cast(nodes_featureids[i]);
- if (node.feature_id > max_feature_id_) {
- max_feature_id_ = node.feature_id;
- }
- node.value_or_unique_weight = nodes_values_as_tensor.empty()
- ? static_cast(nodes_values[i])
- : nodes_values_as_tensor[i];
-
- /* hitrates is not used for inference, they are ignored.
- if (nodes_hitrates_as_tensor.empty()) {
- node.hitrates = static_cast(i < nodes_hitrates.size() ? nodes_hitrates[i] : -1);
- } else {
- node.hitrates = i < nodes_hitrates_as_tensor.size() ? nodes_hitrates_as_tensor[i] : -1;
- } */
-
- node.flags = static_cast(cmodes[i]);
- node.truenode_inc_or_first_weight = 0; // nodes_truenodeids[i] if not a leaf
- node.falsenode_inc_or_n_weights = 0; // nodes_falsenodeids[i] if not a leaf
-
- if (i < static_cast(nodes_missing_value_tracks_true.size()) && nodes_missing_value_tracks_true[i] == 1) {
- node.flags |= static_cast(MissingTrack::kTrue);
- }
- auto p = idi.insert(std::pair(node_tree_id, i));
+ TreeNodeElementId node_tree_id{static_cast(nodes_treeids[i]), static_cast(nodes_nodeids[i])};
+ auto p = node_tree_ids_map.insert(std::pair(node_tree_id, i));
if (!p.second) {
ORT_THROW("Node ", node_tree_id.node_id, " in tree ", node_tree_id.tree_id, " is already there.");
}
- nodes_.emplace_back(node);
node_tree_ids.emplace_back(node_tree_id);
}
- InlinedVector truenode_ids, falsenode_ids;
- truenode_ids.reserve(limit);
- falsenode_ids.reserve(limit);
TreeNodeElementId coor;
- i = 0;
- for (auto it = nodes_.begin(); it != nodes_.end(); ++it, ++i) {
- if (!it->is_not_leaf()) {
+ for (i = 0; i < limit; ++i) {
+ if (cmodes[i] == NODE_MODE::LEAF) {
truenode_ids.push_back(0);
falsenode_ids.push_back(0);
- continue;
- }
-
- TreeNodeElementId& node_tree_id = node_tree_ids[i];
- coor.tree_id = node_tree_id.tree_id;
- coor.node_id = static_cast(nodes_truenodeids[i]);
- ORT_ENFORCE((coor.node_id >= 0 && coor.node_id < n_nodes_));
+ } else {
+ TreeNodeElementId& node_tree_id = node_tree_ids[i];
+ coor.tree_id = node_tree_id.tree_id;
+ coor.node_id = static_cast(nodes_truenodeids[i]);
+ ORT_ENFORCE((coor.node_id >= 0 && coor.node_id < n_nodes_));
+
+ auto found = node_tree_ids_map.find(coor);
+ if (found == node_tree_ids_map.end()) {
+ ORT_THROW("Unable to find node ", coor.tree_id, "-", coor.node_id, " (truenode).");
+ }
+ if (found->second == truenode_ids.size()) {
+ ORT_THROW("A node cannot point to itself: ", coor.tree_id, "-", node_tree_id.node_id, " (truenode).");
+ }
+ truenode_ids.emplace_back(found->second);
- auto found = idi.find(coor);
- if (found == idi.end()) {
- ORT_THROW("Unable to find node ", coor.tree_id, "-", coor.node_id, " (truenode).");
- }
- if (found->second == truenode_ids.size()) {
- ORT_THROW("A node cannot point to itself: ", coor.tree_id, "-", node_tree_id.node_id, " (truenode).");
+ coor.node_id = static_cast(nodes_falsenodeids[i]);
+ ORT_ENFORCE((coor.node_id >= 0 && coor.node_id < n_nodes_));
+ found = node_tree_ids_map.find(coor);
+ if (found == node_tree_ids_map.end()) {
+ ORT_THROW("Unable to find node ", coor.tree_id, "-", coor.node_id, " (falsenode).");
+ }
+ if (found->second == falsenode_ids.size()) {
+ ORT_THROW("A node cannot point to itself: ", coor.tree_id, "-", node_tree_id.node_id, " (falsenode).");
+ }
+ falsenode_ids.emplace_back(found->second);
+ // We could also check that truenode_ids[truenode_ids.size() - 1] != falsenode_ids[falsenode_ids.size() - 1]).
+ // It is valid but no training algorithm would produce a tree where left and right nodes are the same.
}
- truenode_ids.emplace_back(found->second);
+ }
- coor.node_id = static_cast(nodes_falsenodeids[i]);
- ORT_ENFORCE((coor.node_id >= 0 && coor.node_id < n_nodes_));
- found = idi.find(coor);
- if (found == idi.end()) {
- ORT_THROW("Unable to find node ", coor.tree_id, "-", coor.node_id, " (falsenode).");
- }
- if (found->second == falsenode_ids.size()) {
- ORT_THROW("A node cannot point to itself: ", coor.tree_id, "-", node_tree_id.node_id, " (falsenode).");
+ // Let's construct nodes_ such that the false branch is always the next element in nodes_.
+ // updated_mapping will translates the old position of each node to the new node position in nodes_.
+ std::vector updated_mapping(nodes_treeids.size(), 0);
+ int64_t previous_tree_id = -1;
+ for (i = 0; i < n_nodes_; ++i) {
+ if (previous_tree_id == -1 || (previous_tree_id != node_tree_ids[i].tree_id)) {
+ // New tree.
+ int64_t tree_id = node_tree_ids[i].tree_id;
+ size_t root_position =
+ AddNodes(i, cmodes, truenode_ids, falsenode_ids, nodes_featureids, nodes_values_as_tensor, nodes_values,
+ nodes_missing_value_tracks_true, updated_mapping, tree_id, node_tree_ids);
+ roots_.push_back(&nodes_[root_position]);
+ previous_tree_id = tree_id;
}
- falsenode_ids.emplace_back(found->second);
- // We could also check that truenode_ids[truenode_ids.size() - 1] != falsenode_ids[falsenode_ids.size() - 1]).
- // It is valid but no training algorithm would produce a tree where left and right nodes are the same.
}
- // sort targets
+ n_trees_ = roots_.size();
+ if (((int64_t)nodes_.size()) != n_nodes_) {
+ ORT_THROW("Number of nodes in nodes_ (", nodes_.size(), ") is different from n_nodes (", n_nodes_, ").");
+ }
+
+ // Sort targets
InlinedVector> indices;
indices.reserve(target_class_nodeids.size());
for (i = 0, limit = target_class_nodeids.size(); i < limit; i++) {
- indices.emplace_back(std::pair(
- TreeNodeElementId{target_class_treeids[i], target_class_nodeids[i]},
- i));
+ indices.emplace_back(
+ std::pair(TreeNodeElementId{target_class_treeids[i], target_class_nodeids[i]}, i));
}
+
std::sort(indices.begin(), indices.end());
- // Initialize the leaves.
TreeNodeElementId ind;
SparseValue w;
size_t indi;
for (indi = 0, limit = target_class_nodeids.size(); indi < limit; ++indi) {
ind = indices[indi].first;
i = indices[indi].second;
- auto found = idi.find(ind);
- if (found == idi.end()) {
+ auto found = node_tree_ids_map.find(ind);
+ if (found == node_tree_ids_map.end()) {
ORT_THROW("Unable to find node ", ind.tree_id, "-", ind.node_id, " (weights).");
}
- TreeNodeElement& leaf = nodes_[found->second];
+ TreeNodeElement& leaf = nodes_[updated_mapping[found->second]];
if (leaf.is_not_leaf()) {
// An exception should be raised in that case. But this case may happen in
// models converted with an old version of onnxmltools. These weights are ignored.
// ORT_THROW("Node ", ind.tree_id, "-", ind.node_id, " is not a leaf.");
continue;
}
-
w.i = target_class_ids[i];
- w.value = target_class_weights_as_tensor.empty()
- ? static_cast(target_class_weights[i])
- : target_class_weights_as_tensor[i];
- if (leaf.falsenode_inc_or_n_weights == 0) {
- leaf.truenode_inc_or_first_weight = static_cast(weights_.size());
+ w.value = target_class_weights_as_tensor.empty() ? static_cast(target_class_weights[i])
+ : target_class_weights_as_tensor[i];
+ if (leaf.truenode_or_weight.weight_data.n_weights == 0) {
+ leaf.truenode_or_weight.weight_data.weight = static_cast(weights_.size());
leaf.value_or_unique_weight = w.value;
}
- ++leaf.falsenode_inc_or_n_weights;
+ ++leaf.truenode_or_weight.weight_data.n_weights;
weights_.push_back(w);
}
- // Initialize all the nodes but the leaves.
- int64_t previous = -1;
- for (i = 0, limit = static_cast(n_nodes_); i < limit; ++i) {
- if ((previous == -1) || (previous != node_tree_ids[i].tree_id))
- roots_.push_back(&(nodes_[idi[node_tree_ids[i]]]));
- previous = node_tree_ids[i].tree_id;
- if (!nodes_[i].is_not_leaf()) {
- if (nodes_[i].falsenode_inc_or_n_weights == 0) {
- ORT_THROW("Target is missing for leaf ", ind.tree_id, "-", ind.node_id, ".");
- }
- continue;
- }
- ORT_ENFORCE(truenode_ids[i] != i); // That would mean the left node is itself, leading to an infinite loop.
- nodes_[i].truenode_inc_or_first_weight = static_cast(truenode_ids[i] - i);
- ORT_ENFORCE(falsenode_ids[i] != i); // That would mean the right node is itself, leading to an infinite loop.
- nodes_[i].falsenode_inc_or_n_weights = static_cast(falsenode_ids[i] - i);
- }
-
- n_trees_ = roots_.size();
has_missing_tracks_ = false;
- for (auto itm = nodes_missing_value_tracks_true.begin();
- itm != nodes_missing_value_tracks_true.end(); ++itm) {
+ for (auto itm = nodes_missing_value_tracks_true.begin(); itm != nodes_missing_value_tracks_true.end(); ++itm) {
if (*itm) {
has_missing_tracks_ = true;
break;
}
}
+
return Status::OK();
}
+template
+size_t TreeEnsembleCommon::AddNodes(
+ const size_t i, const InlinedVector& cmodes, const InlinedVector& truenode_ids,
+ const InlinedVector& falsenode_ids, const std::vector& nodes_featureids,
+ const std::vector& nodes_values_as_tensor, const std::vector& node_values,
+ const std::vector& nodes_missing_value_tracks_true, std::vector& updated_mapping, int64_t tree_id,
+ const InlinedVector& node_tree_ids) {
+ // Validate this index maps to the same tree_id as the one we should be building.
+ if (node_tree_ids[i].tree_id != tree_id) {
+ ORT_THROW("Tree id mismatch. Expected ", tree_id, " but got ", node_tree_ids[i].tree_id, " at position ", i);
+ }
+
+ if (updated_mapping[i] != 0) {
+ // In theory we should not accept any cycles, however in practice LGBM conversion implements set membership via a
+ // series of "Equals" nodes, with the true branches directed at the same child node (a cycle).
+ // We may instead seek to formalize set membership in the future.
+ return updated_mapping[i];
+ }
+
+ size_t node_pos = nodes_.size();
+ updated_mapping[i] = node_pos;
+
+ TreeNodeElement node;
+ node.flags = static_cast(cmodes[i]);
+ node.feature_id = static_cast(nodes_featureids[i]);
+ if (node.feature_id > max_feature_id_) {
+ max_feature_id_ = node.feature_id;
+ }
+ node.value_or_unique_weight =
+ nodes_values_as_tensor.empty() ? static_cast(node_values[i]) : nodes_values_as_tensor[i];
+ if (i < static_cast(nodes_missing_value_tracks_true.size()) && nodes_missing_value_tracks_true[i] == 1) {
+ node.flags |= static_cast(MissingTrack::kTrue);
+ }
+ nodes_.push_back(std::move(node));
+ if (nodes_[node_pos].is_not_leaf()) {
+ size_t false_branch =
+ AddNodes(falsenode_ids[i], cmodes, truenode_ids, falsenode_ids, nodes_featureids, nodes_values_as_tensor,
+ node_values, nodes_missing_value_tracks_true, updated_mapping, tree_id, node_tree_ids);
+ if (false_branch != node_pos + 1) {
+ ORT_THROW("False node must always be the next node, but it isn't at index ", node_pos, " with flags ",
+ static_cast(nodes_[node_pos].flags));
+ }
+ size_t true_branch =
+ AddNodes(truenode_ids[i], cmodes, truenode_ids, falsenode_ids, nodes_featureids, nodes_values_as_tensor,
+ node_values, nodes_missing_value_tracks_true, updated_mapping, tree_id, node_tree_ids);
+ // We don't need to store the false branch pointer since we know it is always in the immediate next entry in nodes_.
+ // nodes_[node_pos].falsenode_inc_or_n_weights.ptr = &nodes_[false_branch];
+ nodes_[node_pos].truenode_or_weight.ptr = &nodes_[true_branch];
+ } else {
+ nodes_[node_pos].truenode_or_weight.weight_data.weight = 0;
+ nodes_[node_pos].truenode_or_weight.weight_data.n_weights = 0;
+ }
+ return node_pos;
+}
+
template
Status TreeEnsembleCommon::compute(OpKernelContext* ctx,
const Tensor* X,
@@ -637,22 +669,19 @@ void TreeEnsembleCommon::ComputeAgg(concur
}
} // namespace detail
-#define TREE_FIND_VALUE(CMP) \
- if (has_missing_tracks_) { \
- while (root->is_not_leaf()) { \
- val = x_data[root->feature_id]; \
- root += (val CMP root->value_or_unique_weight || \
- (root->is_missing_track_true() && _isnan_(val))) \
- ? root->truenode_inc_or_first_weight \
- : root->falsenode_inc_or_n_weights; \
- } \
- } else { \
- while (root->is_not_leaf()) { \
- val = x_data[root->feature_id]; \
- root += val CMP root->value_or_unique_weight \
- ? root->truenode_inc_or_first_weight \
- : root->falsenode_inc_or_n_weights; \
- } \
+#define TREE_FIND_VALUE(CMP) \
+ if (has_missing_tracks_) { \
+ while (root->is_not_leaf()) { \
+ val = x_data[root->feature_id]; \
+ root = (val CMP root->value_or_unique_weight || (root->is_missing_track_true() && _isnan_(val))) \
+ ? root->truenode_or_weight.ptr \
+ : root + 1; \
+ } \
+ } else { \
+ while (root->is_not_leaf()) { \
+ val = x_data[root->feature_id]; \
+ root = val CMP root->value_or_unique_weight ? root->truenode_or_weight.ptr : root + 1; \
+ } \
}
inline bool _isnan_(float x) { return std::isnan(x); }
@@ -671,15 +700,14 @@ TreeEnsembleCommon::ProcessTreeNodeLeave(
if (has_missing_tracks_) {
while (root->is_not_leaf()) {
val = x_data[root->feature_id];
- root += (val <= root->value_or_unique_weight ||
- (root->is_missing_track_true() && _isnan_(val)))
- ? root->truenode_inc_or_first_weight
- : root->falsenode_inc_or_n_weights;
+ root = (val <= root->value_or_unique_weight || (root->is_missing_track_true() && _isnan_(val)))
+ ? root->truenode_or_weight.ptr
+ : root + 1;
}
} else {
while (root->is_not_leaf()) {
val = x_data[root->feature_id];
- root += val <= root->value_or_unique_weight ? root->truenode_inc_or_first_weight : root->falsenode_inc_or_n_weights;
+ root = val <= root->value_or_unique_weight ? root->truenode_or_weight.ptr : root + 1;
}
}
break;
@@ -703,42 +731,36 @@ TreeEnsembleCommon::ProcessTreeNodeLeave(
}
} else { // Different rules to compare to node thresholds.
ThresholdType threshold;
- while (root->is_not_leaf()) {
+ while (1) {
val = x_data[root->feature_id];
threshold = root->value_or_unique_weight;
switch (root->mode()) {
case NODE_MODE::BRANCH_LEQ:
- root += val <= threshold || (root->is_missing_track_true() && _isnan_(val))
- ? root->truenode_inc_or_first_weight
- : root->falsenode_inc_or_n_weights;
+ root = val <= threshold || (root->is_missing_track_true() && _isnan_(val)) ? root->truenode_or_weight.ptr
+ : root + 1;
break;
case NODE_MODE::BRANCH_LT:
- root += val < threshold || (root->is_missing_track_true() && _isnan_(val))
- ? root->truenode_inc_or_first_weight
- : root->falsenode_inc_or_n_weights;
+ root = val < threshold || (root->is_missing_track_true() && _isnan_(val)) ? root->truenode_or_weight.ptr
+ : root + 1;
break;
case NODE_MODE::BRANCH_GTE:
- root += val >= threshold || (root->is_missing_track_true() && _isnan_(val))
- ? root->truenode_inc_or_first_weight
- : root->falsenode_inc_or_n_weights;
+ root = val >= threshold || (root->is_missing_track_true() && _isnan_(val)) ? root->truenode_or_weight.ptr
+ : root + 1;
break;
case NODE_MODE::BRANCH_GT:
- root += val > threshold || (root->is_missing_track_true() && _isnan_(val))
- ? root->truenode_inc_or_first_weight
- : root->falsenode_inc_or_n_weights;
+ root = val > threshold || (root->is_missing_track_true() && _isnan_(val)) ? root->truenode_or_weight.ptr
+ : root + 1;
break;
case NODE_MODE::BRANCH_EQ:
- root += val == threshold || (root->is_missing_track_true() && _isnan_(val))
- ? root->truenode_inc_or_first_weight
- : root->falsenode_inc_or_n_weights;
+ root = val == threshold || (root->is_missing_track_true() && _isnan_(val)) ? root->truenode_or_weight.ptr
+ : root + 1;
break;
case NODE_MODE::BRANCH_NEQ:
- root += val != threshold || (root->is_missing_track_true() && _isnan_(val))
- ? root->truenode_inc_or_first_weight
- : root->falsenode_inc_or_n_weights;
+ root = val != threshold || (root->is_missing_track_true() && _isnan_(val)) ? root->truenode_or_weight.ptr
+ : root + 1;
break;
case NODE_MODE::LEAF:
- break;
+ return root;
}
}
}
diff --git a/onnxruntime/core/providers/cpu/quantization/qlinearconv.cc b/onnxruntime/core/providers/cpu/quantization/qlinearconv.cc
index e9fc8d857b831..21a256eee6f14 100644
--- a/onnxruntime/core/providers/cpu/quantization/qlinearconv.cc
+++ b/onnxruntime/core/providers/cpu/quantization/qlinearconv.cc
@@ -77,7 +77,8 @@ class QLinearConv : public OpKernel {
W_zero_point_value = W_zero_point_data[0];
for (int64_t i = 1; i < W_zero_point_size; i++) {
ORT_ENFORCE(W_zero_point_data[i] == W_zero_point_value,
- "QLinearConv : zero point of per-channel filter must be same");
+ "QLinearConv : zero point of per-channel filter must be same. "
+ "This happens by design if the quantization is symmetric.");
}
}
diff --git a/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc b/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc
index fba46d5a871ed..88a576f3ffa73 100644
--- a/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc
+++ b/onnxruntime/core/providers/tensorrt/tensorrt_execution_provider.cc
@@ -1138,46 +1138,35 @@ bool TensorrtExecutionProvider::IsGraphCaptureEnabled() const {
return cuda_graph_enable_;
}
-bool TensorrtExecutionProvider::IsGraphCaptured() const {
- return GetPerThreadContext().IsGraphCaptured();
-}
-
-Status TensorrtExecutionProvider::ReplayGraph() {
- return GetPerThreadContext().ReplayGraph();
-}
-
-void TensorrtExecutionProvider::PerThreadContext::SetGraphStream(cudaStream_t stream) {
- cuda_graph_.SetStream(stream);
-}
-
-bool TensorrtExecutionProvider::PerThreadContext::IsGraphCaptureAllowed() const {
+bool TensorrtExecutionProvider::IsGraphCaptureAllowed() const {
return regular_run_count_before_graph_capture_ >= min_num_runs_before_cuda_graph_capture_;
}
-void TensorrtExecutionProvider::PerThreadContext::CaptureBegin() {
+void TensorrtExecutionProvider::CaptureBegin() {
cuda_graph_.Reset();
cuda_graph_.CaptureBegin();
}
-void TensorrtExecutionProvider::PerThreadContext::CaptureEnd() {
+void TensorrtExecutionProvider::CaptureEnd() {
cuda_graph_.CaptureEnd();
is_graph_captured_ = true;
}
-bool TensorrtExecutionProvider::PerThreadContext::IsGraphCaptured() const {
+bool TensorrtExecutionProvider::IsGraphCaptured() const {
return is_graph_captured_;
}
-Status TensorrtExecutionProvider::PerThreadContext::ReplayGraph() {
+Status TensorrtExecutionProvider::ReplayGraph() {
ORT_ENFORCE(IsGraphCaptured());
// Please note that CUDAGraph::Replay() is not thread safe.
- // The cuda graph object is maintained by a per thread basis,
+ // ORT TRT calls ReplayGraph() in compute_func() where synchromization is enforced due to lock_guard(),
// therefore calling CUDAGraph::Replay() here is guaranteed to be thread safe.
return cuda_graph_.Replay();
}
-void TensorrtExecutionProvider::PerThreadContext::IncrementRegularRunCountBeforeGraphCapture() {
- // The cuda graph object is maintained by a per thread basis,
+void TensorrtExecutionProvider::IncrementRegularRunCountBeforeGraphCapture() {
+ // Please note that this function is not thread safe.
+ // ORT TRT calls this function in compute_func() where synchronization is enforced due to lock_guard(),
// therefore following increment is guaranteed to be thread safe.
++regular_run_count_before_graph_capture_;
}
@@ -1208,18 +1197,6 @@ Status TensorrtExecutionProvider::OnRunEnd(bool sync_stream) {
if (sync_stream && external_stream_) {
CUDA_RETURN_IF_ERROR(cudaStreamSynchronize(stream_));
}
-
- // The reason of !IsGraphCaptureEnabled():
- // If cuda graph is enabled, the per thread context will not be released
- // because the per thread cuda graph needs to be maintained and replayed for
- // the next run.
- // The reason of PerThreadContextCache()->find(this) != PerThreadContextCache()->end():
- // In extreme cases (e.g., 1-op graph and that op fallbacks to CPU),
- // PerThreadContext won't be created and there is nothing to release.
- if (!IsGraphCaptureEnabled() &&
- PerThreadContextCache()->find(this) != PerThreadContextCache()->end()) {
- ReleasePerThreadContext();
- }
return Status::OK();
}
@@ -2373,6 +2350,7 @@ common::Status TensorrtExecutionProvider::Compile(const std::vectorallocate_func, context->release_func, context->allocator_handle, context->node_name,
- &parsers_[context->node_name], &engines_[context->node_name], &builders_[context->node_name],
+ &parsers_[context->node_name], &engines_[context->node_name], &contexts_[context->node_name], &builders_[context->node_name],
&networks_[context->node_name], input_info_[context->node_name], output_info_[context->node_name],
input_shape_ranges_[context->node_name], &tensorrt_mu_, fp16_enable_, int8_enable_, int8_calibration_cache_available_,
dla_enable_, dla_core_, &max_workspace_size_, trt_node_name_with_precision, engine_cache_enable_, cache_path_,
@@ -2434,6 +2404,7 @@ common::Status TensorrtExecutionProvider::Compile(const std::vectorinput_shape_ranges;
auto trt_builder = trt_state->builder->get();
auto trt_engine = trt_state->engine->get();
+ auto trt_context = trt_state->context->get();
auto trt_profiles = trt_state->profiles;
auto max_context_mem_size_ptr = trt_state->max_context_mem_size_ptr;
int num_inputs = static_cast(input_indexes.size());
@@ -2490,7 +2461,7 @@ common::Status TensorrtExecutionProvider::Compile(const std::vectorengine->reset();
*(trt_state->engine) = std::unique_ptr(
trt_state->runtime->deserializeCudaEngine(engine_buf.get(), engine_size, nullptr));
- if (*(trt_state->engine) == nullptr) {
+ if (!(*(trt_state->engine))) {
return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL, "TensorRT EP Failed to Build Engine.");
}
LOGS_DEFAULT(VERBOSE) << "[TensorRT EP] DeSerialized " + engine_cache_path;
@@ -2515,7 +2486,7 @@ common::Status TensorrtExecutionProvider::Compile(const std::vectorengine->reset();
*(trt_state->engine) = std::unique_ptr(trt_state->runtime->deserializeCudaEngine(engine_buf.get(), engine_size, nullptr));
- if (*(trt_state->engine) == nullptr) {
+ if (!(*(trt_state->engine))) {
return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL,
"TensorRT EP could not deserialize engine from encrypted cache: " + engine_cache_path);
}
@@ -2544,10 +2515,7 @@ common::Status TensorrtExecutionProvider::Compile(const std::vectorcontext->reset();
trt_state->engine->reset();
auto trt_config = std::unique_ptr(trt_builder->createBuilderConfig());
trt_config->setMaxWorkspaceSize(*(trt_state->max_workspace_size_ptr));
@@ -2648,7 +2616,7 @@ common::Status TensorrtExecutionProvider::Compile(const std::vectortrt_node_name_with_precision << " took: " << std::chrono::duration_cast(engine_build_stop - engine_build_start).count() << "ms" << std::endl;
}
}
- if (*(trt_state->engine) == nullptr) {
+ if (!(*(trt_state->engine))) {
return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL, "TensorRT EP Failed to Build Engine.");
}
trt_engine = trt_state->engine->get();
@@ -2689,32 +2657,20 @@ common::Status TensorrtExecutionProvider::Compile(const std::vector new_context;
+ if (context_update) {
if (trt_state->context_memory_sharing_enable) {
- new_context.reset(trt_state->engine->get()->createExecutionContextWithoutDeviceMemory());
+ *(trt_state->context) = std::unique_ptr(
+ trt_state->engine->get()->createExecutionContextWithoutDeviceMemory());
} else {
- new_context.reset(trt_state->engine->get()->createExecutionContext());
+ *(trt_state->context) = std::unique_ptr(
+ trt_state->engine->get()->createExecutionContext());
}
- auto context_status = GetPerThreadContext().UpdateTensorRTContext(fused_node_name, std::move(new_context));
- if (!context_status) {
+ if (!(*(trt_state->context))) {
return ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL, "TensorRT EP failed to create context.");
}
- GetPerThreadContext().UpdateProfileShapes(fused_node_name, shape_ranges);
+ trt_context = trt_state->context->get();
}
- // Get the reference to the IExecutionContext object that is maintained on a per thread basis.
- nvinfer1::IExecutionContext& trt_context = GetPerThreadContext().GetTensorRTContext(fused_node_name);
-
// Get input and output binding names
int total_bindings = trt_engine->getNbBindings();
std::vector buffers(total_bindings);
@@ -2750,12 +2706,12 @@ common::Status TensorrtExecutionProvider::Compile(const std::vectorisShapeBinding(binding_index)) {
- trt_context.setInputShapeBinding(binding_index, &tensor_shape_values[input_name][0]);
+ trt_context->setInputShapeBinding(binding_index, &tensor_shape_values[input_name][0]);
} else {
for (int j = 0, end = nb_dims; j < end; ++j) {
dimensions.d[j] = static_cast(tensor_shapes[j]);
}
- const bool status = trt_context.setBindingDimensions(binding_index, dimensions);
+ const bool status = trt_context->setBindingDimensions(binding_index, dimensions);
if (!status) {
ORT_THROW_IF_ERROR(ORT_MAKE_STATUS(ONNXRUNTIME, EP_FAIL,
"TensorRT EP cannot set the dynamic dimensions of a binding"));
@@ -2894,7 +2850,7 @@ common::Status TensorrtExecutionProvider::Compile(const std::vectorsecond;
}
- nvinfer1::Dims dimensions = trt_context.getBindingDimensions(static_cast(binding_index));
+ nvinfer1::Dims dimensions = trt_context->getBindingDimensions(static_cast(binding_index));
int nb_dims = dimensions.nbDims;
std::vector output_shapes(nb_dims);
for (int j = 0, end = nb_dims; j < end; ++j) {
@@ -3028,20 +2984,20 @@ common::Status TensorrtExecutionProvider::Compile(const std::vector *max_context_mem_size_ptr) {
*max_context_mem_size_ptr = mem_size;
}
- trt_context.setDeviceMemory(IAllocator::MakeUniquePtrFromOrtAllocator(alloc, *max_context_mem_size_ptr).get());
+ trt_context->setDeviceMemory(IAllocator::MakeUniquePtrFromOrtAllocator(alloc, *max_context_mem_size_ptr).get());
}
// Start CUDA graph capture.
// Note: The reason we don't put graph capture in OnRunStart() like CUDA EP does is because
// current ORT TRT doesn't get cuda stream until compute time and graph capture requires cuda stream.
- if (cuda_graph_enable_ && GetPerThreadContext().IsGraphCaptureAllowed() && !GetPerThreadContext().IsGraphCaptured()) {
+ if (cuda_graph_enable_ && IsGraphCaptureAllowed() && !IsGraphCaptured()) {
LOGS_DEFAULT(INFO) << "Capturing the cuda graph for this model";
- GetPerThreadContext().SetGraphStream(stream);
- GetPerThreadContext().CaptureBegin();
+ cuda_graph_.SetStream(stream);
+ CaptureBegin();
}
// Run TRT inference
- if (!trt_context.enqueueV2(&buffers[0], stream, nullptr)) {
+ if (!trt_context->enqueueV2(&buffers[0], stream, nullptr)) {
return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "TensorRT EP execution context enqueue failed.");
}
@@ -3072,14 +3028,14 @@ common::Status TensorrtExecutionProvider::Compile(const std::vector* parser = nullptr;
std::unique_ptr* engine = nullptr;
+ std::unique_ptr* context = nullptr;
std::unique_ptr* builder = nullptr;
std::unique_ptr* network = nullptr;
std::vector> input_info;
@@ -246,6 +247,7 @@ class TensorrtExecutionProvider : public IExecutionProvider {
// For those non thread safe operations, TRT EP uses (1) lock_guard or (2) PerThreadContext to make sure synchronization.
std::unordered_map> parsers_;
std::unordered_map> engines_;
+ std::unordered_map> contexts_;
std::unordered_map> builders_;
std::unordered_map> networks_;
std::unordered_map>> input_info_;
@@ -256,6 +258,21 @@ class TensorrtExecutionProvider : public IExecutionProvider {
std::unordered_map input_shape_ranges_; // The profile shape ranges that the engine is built with
std::unordered_map> profiles_;
+ // for external stream, we need to create its cudnn/cublass handle before cuda EP enable cuda graph capture
+ cudnnHandle_t external_cudnn_handle_ = nullptr;
+ cublasHandle_t external_cublas_handle_ = nullptr;
+
+ CUDAGraph cuda_graph_;
+ bool is_graph_captured_ = false;
+ int regular_run_count_before_graph_capture_ = 0;
+ // There is chance (currently only happens in CUDA EP) that the second regular run allocates GPU memory for causes like:
+ // (1) memory pattern is enabled. (2) arena allocation for stream.
+ // Since no GPU memory allocation is allowed during graph capturing, we need at least two regular runs
+ // to allocate enough memory in Arena before graph capturing.
+ const int min_num_runs_before_cuda_graph_capture_ = 1; // required min regular runs before graph capture for the necessary memory allocations.
+
+ // [Note] We don't use PerThreadContext for now since it has issue with multithreading
+ //
// TRT or CUDA objects that must be maintained on a per thread basis will be put under this PerThreadContext data structure.
// For example, TensorRT execution context and CUDA graph are the ones to be put here.
class PerThreadContext final {
diff --git a/onnxruntime/core/session/onnxruntime_c_api.cc b/onnxruntime/core/session/onnxruntime_c_api.cc
index 15fe5acfe0fd2..a4776623c529e 100644
--- a/onnxruntime/core/session/onnxruntime_c_api.cc
+++ b/onnxruntime/core/session/onnxruntime_c_api.cc
@@ -2711,9 +2711,8 @@ static constexpr OrtApi ort_api_1_to_16 = {
&OrtApis::GetTensorRTProviderOptionsByName,
&OrtApis::UpdateCUDAProviderOptionsWithValue,
&OrtApis::GetCUDAProviderOptionsByName,
- // End of Version 16 - DO NOT MODIFY ABOVE (see above text for more information)
-
&OrtApis::KernelContext_GetResource,
+ // End of Version 16 - DO NOT MODIFY ABOVE (see above text for more information)
};
// OrtApiBase can never change as there is no way to know what version of OrtApiBase is returned by OrtGetApiBase.
@@ -2742,10 +2741,10 @@ static_assert(offsetof(OrtApi, ReleaseKernelInfo) / sizeof(void*) == 218, "Size
static_assert(offsetof(OrtApi, ReleaseCANNProviderOptions) / sizeof(void*) == 224, "Size of version 13 API cannot change");
static_assert(offsetof(OrtApi, GetSessionConfigEntry) / sizeof(void*) == 238, "Size of version 14 API cannot change");
static_assert(offsetof(OrtApi, GetBuildInfoString) / sizeof(void*) == 254, "Size of version 15 API cannot change");
-static_assert(offsetof(OrtApi, GetCUDAProviderOptionsByName) / sizeof(void*) == 264, "Size of version 16 API cannot change");
+static_assert(offsetof(OrtApi, KernelContext_GetResource) / sizeof(void*) == 265, "Size of version 16 API cannot change");
// So that nobody forgets to finish an API version, this check will serve as a reminder:
-static_assert(std::string_view(ORT_VERSION) == "1.16.0",
+static_assert(std::string_view(ORT_VERSION) == "1.16.1",
"ORT_Version change detected, please follow below steps to ensure OrtApi is updated properly");
// 1. Update the hardcoded version string in above static_assert to silence it
// 2. If there were any APIs added to ort_api_1_to_16 above:
diff --git a/onnxruntime/python/tools/quantization/calibrate.py b/onnxruntime/python/tools/quantization/calibrate.py
index bdf00f21100bf..26e74a6dfbac9 100644
--- a/onnxruntime/python/tools/quantization/calibrate.py
+++ b/onnxruntime/python/tools/quantization/calibrate.py
@@ -22,7 +22,7 @@
class TensorData:
- _allowed = frozenset(["avg", "std", "lowest", "highest", "hist", "hist_edges"])
+ _allowed = frozenset(["avg", "std", "lowest", "highest", "hist", "hist_edges", "bins"])
def __init__(self, **kwargs):
for k, v in kwargs.items():
@@ -55,7 +55,7 @@ def __init__(self, calibration_method, data: Dict[str, Union[TensorData, Tuple]]
self.data[k] = TensorData(lowest=v[0], highest=v[1])
continue
if len(v) == 4:
- self.data[k] = TensorData(lowest=v[0], highest=v[1], histogram=v[2], bins=v[3])
+ self.data[k] = TensorData(lowest=v[0], highest=v[1], hist=v[2], bins=v[3])
continue
raise TypeError(f"Unexpected tuple for {k:r}, it has {len(v)} elements: {v}.")
if not isinstance(v, TensorData):
diff --git a/onnxruntime/python/tools/quantization/operators/conv.py b/onnxruntime/python/tools/quantization/operators/conv.py
index d23459b478e6a..23f9eaf4b0e0b 100644
--- a/onnxruntime/python/tools/quantization/operators/conv.py
+++ b/onnxruntime/python/tools/quantization/operators/conv.py
@@ -157,7 +157,7 @@ def quantize(self):
nodes,
) = self.quantizer.quantize_activation(node, [0])
quant_weight_tuple = self.quantizer.quantize_weight_per_channel(
- node.input[1], onnx_proto.TensorProto.INT8, 0
+ node.input[1], onnx_proto.TensorProto.INT8, 0 # self.quantizer.weight_qType?
)
quantized_input_names.append(quant_weight_tuple[0])
zero_point_names.append(quant_weight_tuple[1])
diff --git a/onnxruntime/python/tools/quantization/operators/lstm.py b/onnxruntime/python/tools/quantization/operators/lstm.py
index 7e91f9b76ca36..90a52cb528b32 100644
--- a/onnxruntime/python/tools/quantization/operators/lstm.py
+++ b/onnxruntime/python/tools/quantization/operators/lstm.py
@@ -47,10 +47,10 @@ def quantize(self):
R.dims[0] = R_num_dir * R_4_hidden_size
quant_input_weight_tuple = self.quantizer.quantize_weight_per_channel(
- node.input[1], onnx_proto.TensorProto.INT8, 0
+ node.input[1], onnx_proto.TensorProto.INT8, 0 # self.quantizer.weight_qType?
)
quant_recurrent_weight_tuple = self.quantizer.quantize_weight_per_channel(
- node.input[2], onnx_proto.TensorProto.INT8, 0
+ node.input[2], onnx_proto.TensorProto.INT8, 0 # self.quantizer.weight_qType?
)
W_quant_weight = model.get_initializer(quant_input_weight_tuple[0]) # noqa: N806
diff --git a/onnxruntime/python/tools/quantization/qdq_quantizer.py b/onnxruntime/python/tools/quantization/qdq_quantizer.py
index f87a9d8228bac..a03f6431fbd08 100644
--- a/onnxruntime/python/tools/quantization/qdq_quantizer.py
+++ b/onnxruntime/python/tools/quantization/qdq_quantizer.py
@@ -266,7 +266,13 @@ def _add_qdq_pair_for_initializer(self, weight_proto, tensor_type, axis=None):
raise ValueError("Per-Channel support with QDQ format requires onnx opset version 13 or above.")
q_weight_name, zp_name, scale_name = self.quantize_weight_per_channel(
weight_name,
- self.weight_qType if tensor_type is QDQQuantTensorType.WEIGHT else self.activation_qType,
+ # Quantization type is forced to be TensorProto.INT8.
+ # when the expected value would be (see below)
+ # self.weight_qType if tensor_type is QDQQuantTensorType.WEIGHT else self.activation_qType.
+ # QLinearConv expects to have a unique value for all channels.
+ # This code does not enforce that but it is necessarily the case when the
+ # quantization is symmetric (as for INT8).
+ onnx_proto.TensorProto.INT8,
axis,
keep_float_weight=self.add_qdq_pair_to_weight,
)
diff --git a/onnxruntime/python/tools/quantization/shape_inference.py b/onnxruntime/python/tools/quantization/shape_inference.py
index eff3dc0bcdc35..b7d4726610387 100644
--- a/onnxruntime/python/tools/quantization/shape_inference.py
+++ b/onnxruntime/python/tools/quantization/shape_inference.py
@@ -99,7 +99,10 @@ def quant_pre_process(
sess_option = onnxruntime.SessionOptions()
sess_option.optimized_model_filepath = opt_model_path
sess_option.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_BASIC
- _ = onnxruntime.InferenceSession(input_model_path, sess_option, providers=["CPUExecutionProvider"])
+ sess = onnxruntime.InferenceSession(input_model_path, sess_option, providers=["CPUExecutionProvider"])
+ # Close the session to avoid the cleanup error on Windows for temp folders
+ # https://github.com/microsoft/onnxruntime/issues/17627
+ del sess
except Exception:
logger.error(
"ONNX Runtime Model Optimization Failed! Consider rerun with option `--skip_optimization'."
diff --git a/onnxruntime/test/python/quantization/resnet_code.py b/onnxruntime/test/python/quantization/resnet_code.py
new file mode 100644
index 0000000000000..74e3652673c99
--- /dev/null
+++ b/onnxruntime/test/python/quantization/resnet_code.py
@@ -0,0 +1,13763 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+import numpy
+from onnx import numpy_helper
+from onnx.helper import make_graph, make_model, make_node, make_opsetid, make_tensor_value_info, set_model_props
+
+
+def create_model():
+ initializers = []
+ nodes = []
+ inputs = []
+ outputs = []
+ functions = []
+
+ # opsets
+ opsets = {"": 13}
+
+ # initializers
+
+ list_value = [
+ -0.013732648454606533,
+ -0.005861935671418905,
+ 0.06889285147190094,
+ -0.1172710582613945,
+ 0.08841240406036377,
+ -0.03748627379536629,
+ 0.016256270930171013,
+ -0.1059316024184227,
+ 0.08246039599180222,
+ 0.14295539259910583,
+ -0.32958757877349854,
+ 0.1631188541650772,
+ 0.05412565544247627,
+ -0.10758306831121445,
+ 0.12607362866401672,
+ -0.4987836182117462,
+ 0.7441706657409668,
+ -0.24774713814258575,
+ -0.30415549874305725,
+ 0.4033295810222626,
+ -0.13447114825248718,
+ 0.04623159021139145,
+ 0.2380414456129074,
+ -1.226112723350525,
+ 2.150630235671997,
+ -1.702580213546753,
+ 0.5305419564247131,
+ -0.06836353242397308,
+ -0.20055373013019562,
+ 0.7035881280899048,
+ -0.8389442563056946,
+ -0.1904432326555252,
+ 1.2609282732009888,
+ -1.0670661926269531,
+ 0.4142579436302185,
+ 0.04739700257778168,
+ -0.3265092074871063,
+ 1.1873037815093994,
+ -1.6817731857299805,
+ 0.9709527492523193,
+ -0.09095840901136398,
+ -0.12556785345077515,
+ 0.0835147574543953,
+ -0.24109329283237457,
+ 0.032948240637779236,
+ 0.46304041147232056,
+ -0.6594106554985046,
+ 0.349990576505661,
+ -0.04113377630710602,
+ 0.016451245173811913,
+ 0.008994563482701778,
+ -0.028321878984570503,
+ -0.05336569994688034,
+ 0.16036668419837952,
+ -0.12088149785995483,
+ 0.031160499900579453,
+ -0.0618649423122406,
+ 0.07205374538898468,
+ 0.15965768694877625,
+ -0.3389044404029846,
+ 0.21603335440158844,
+ 0.04029613360762596,
+ -0.0813034325838089,
+ 0.1019665077328682,
+ -0.4873599112033844,
+ 0.7873126268386841,
+ -0.2951086163520813,
+ -0.43754327297210693,
+ 0.5905176401138306,
+ -0.21821773052215576,
+ 0.06022067740559578,
+ 0.26326146721839905,
+ -1.6453089714050293,
+ 2.606400728225708,
+ -1.8939754962921143,
+ 0.5196341276168823,
+ 0.0055860355496406555,
+ -0.2335057258605957,
+ 0.9807199239730835,
+ -1.2137882709503174,
+ -0.2699125409126282,
+ 1.7379733324050903,
+ -1.4401814937591553,
+ 0.435971736907959,
+ -0.04829222336411476,
+ -0.24543480575084686,
+ 1.3292583227157593,
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+ -0.14181238412857056,
+ 0.10612589120864868,
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+ value = numpy.array(list_value, dtype=numpy.float32).reshape((64, 3, 7, 7))
+ tensor = numpy_helper.from_array(value, name="onnx::Conv_501")
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+ initializers.append(tensor)
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+ value = numpy.array(list_value, dtype=numpy.float32)
+ tensor = numpy_helper.from_array(value, name="onnx::Conv_502")
+
+ initializers.append(tensor)
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+ value = numpy.array(list_value, dtype=numpy.float32).reshape((64, 64, 1, 1))
+ tensor = numpy_helper.from_array(value, name="onnx::Conv_504")
+
+ initializers.append(tensor)
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+ 3.754193067550659,
+ -5.167671203613281,
+ 3.2778055667877197,
+ -9.067073822021484,
+ 2.6243438720703125,
+ 1.7002031803131104,
+ 5.476454734802246,
+ 2.510835647583008,
+ 3.856968402862549,
+ 2.3172807693481445,
+ 12.462139129638672,
+ 7.355924129486084,
+ 4.140628814697266,
+ 4.807559967041016,
+ 5.7524309158325195,
+ 4.128836154937744,
+ 11.4532470703125,
+ -12.482564926147461,
+ 5.590144157409668,
+ 0.9172697067260742,
+ 4.356811046600342,
+ 0.9934853315353394,
+ -4.3548994064331055,
+ 15.853201866149902,
+ -5.241130828857422,
+ 5.9644365310668945,
+ ]
+ value = numpy.array(list_value, dtype=numpy.float32)
+ tensor = numpy_helper.from_array(value, name="onnx::Conv_505")
+
+ initializers.append(tensor)
+
+ # inputs
+
+ inputs.append(make_tensor_value_info("input", 1, ["batch_size", 3, 32, 32]))
+
+ # outputs
+
+ outputs.append(make_tensor_value_info("/layer1/layer1.0/relu/Relu_output_0", 1, ["batch_size", 64, 8, 8]))
+
+ # nodes
+
+ node = make_node(
+ "Conv",
+ ["input", "onnx::Conv_501", "onnx::Conv_502"],
+ ["/conv1/Conv_output_0"],
+ name="/conv1/Conv",
+ dilations=[1, 1],
+ group=1,
+ kernel_shape=[7, 7],
+ pads=[3, 3, 3, 3],
+ strides=[2, 2],
+ domain="",
+ )
+ nodes.append(node)
+
+ node = make_node("Relu", ["/conv1/Conv_output_0"], ["/relu/Relu_output_0"], name="/relu/Relu", domain="")
+ nodes.append(node)
+
+ node = make_node(
+ "MaxPool",
+ ["/relu/Relu_output_0"],
+ ["/maxpool/MaxPool_output_0"],
+ name="/maxpool/MaxPool",
+ ceil_mode=0,
+ kernel_shape=[3, 3],
+ pads=[1, 1, 1, 1],
+ strides=[2, 2],
+ domain="",
+ )
+ nodes.append(node)
+
+ node = make_node(
+ "Conv",
+ ["/maxpool/MaxPool_output_0", "onnx::Conv_504", "onnx::Conv_505"],
+ ["/layer1/layer1.0/conv1/Conv_output_0"],
+ name="/layer1/layer1.0/conv1/Conv",
+ dilations=[1, 1],
+ group=1,
+ kernel_shape=[1, 1],
+ pads=[0, 0, 0, 0],
+ strides=[1, 1],
+ domain="",
+ )
+ nodes.append(node)
+
+ node = make_node(
+ "Relu",
+ ["/layer1/layer1.0/conv1/Conv_output_0"],
+ ["/layer1/layer1.0/relu/Relu_output_0"],
+ name="/layer1/layer1.0/relu/Relu",
+ domain="",
+ )
+ nodes.append(node)
+
+ # opsets
+ opset_imports = [make_opsetid(domain, 1 if version is None else version) for domain, version in opsets.items()]
+
+ # graph
+ graph = make_graph(nodes, "torch_jit", inputs, outputs, initializers)
+ # '7'
+
+ onnx_model = make_model(graph, opset_imports=opset_imports, functions=functions)
+ onnx_model.ir_version = 7
+ onnx_model.producer_name = "pytorch"
+ onnx_model.producer_version = ""
+ onnx_model.domain = ""
+ onnx_model.model_version = 0
+ onnx_model.doc_string = ""
+ set_model_props(onnx_model, {})
+
+ return onnx_model
diff --git a/onnxruntime/test/python/quantization/test_quantize_static_resnet.py b/onnxruntime/test/python/quantization/test_quantize_static_resnet.py
new file mode 100644
index 0000000000000..1efa283af6881
--- /dev/null
+++ b/onnxruntime/test/python/quantization/test_quantize_static_resnet.py
@@ -0,0 +1,138 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+import os
+import random
+import tempfile
+import unittest
+
+import numpy as np
+import onnx
+from numpy.testing import assert_allclose
+from onnx.numpy_helper import to_array
+from resnet_code import create_model
+
+from onnxruntime import InferenceSession
+from onnxruntime import __version__ as ort_version
+from onnxruntime.quantization import QuantFormat, QuantType, quantize_static
+from onnxruntime.quantization.calibrate import CalibrationDataReader, CalibrationMethod
+
+
+class FakeResnetCalibrationDataReader(CalibrationDataReader):
+ def __init__(self, batch_size: int = 16):
+ super().__init__()
+ self.dataset = [
+ (np.random.rand(1, 3, 32, 32).astype(np.float32), random.randint(0, 9)) for _ in range(batch_size)
+ ]
+ self.iterator = iter(self.dataset)
+
+ def get_next(self) -> dict:
+ try:
+ return {"input": next(self.iterator)[0]}
+ except Exception:
+ return None
+
+
+class TestStaticQuantizationResNet(unittest.TestCase):
+ def test_quantize_static_resnet(self):
+ kwargs = {
+ "activation_type": QuantType.QUInt8,
+ "weight_type": QuantType.QInt8,
+ "calibrate_method": CalibrationMethod.Percentile,
+ "extra_options": {
+ "ActivationSymmetric": False,
+ "EnableSubgraph": False,
+ "ForceQuantizeNoInputCheck": False,
+ "MatMulConstBOnly": False,
+ "WeightSymmetric": True,
+ "extra.Sigmoid.nnapi": False,
+ },
+ "nodes_to_exclude": None,
+ "nodes_to_quantize": None,
+ "op_types_to_quantize": None,
+ "per_channel": True,
+ "quant_format": QuantFormat.QDQ,
+ "reduce_range": False,
+ }
+
+ proto = create_model()
+
+ with tempfile.TemporaryDirectory() as temp:
+ model = os.path.join(temp, "resnet_first_nodes.onnx")
+ with open(model, "wb") as f:
+ f.write(proto.SerializeToString())
+
+ for per_channel in [True, False]:
+ kwargs["per_channel"] = per_channel
+ dataloader = FakeResnetCalibrationDataReader(16)
+ with self.subTest(per_channel=per_channel):
+ qdq_file = os.path.join(
+ temp, f"preprocessed-small-qdq-{1 if per_channel else 0}-ort-{ort_version}.onnx"
+ )
+ quantize_static(
+ model_input=model,
+ model_output=qdq_file,
+ calibration_data_reader=dataloader,
+ use_external_data_format=False,
+ **kwargs,
+ )
+
+ # With onnxruntime==1.15.1, the initializer 'onnx::Conv_504_zero_point' is:
+ # * uint8(128) if per_channel is False
+ # * int8([0, 0, ....]) if per_channel is True
+ # With onnxruntime>1.16.0
+ # * uint8(128) if per_channel is False
+ # * uint8([128, 128, ..., 127, ...]) if per_channel is True
+ # QLinearConv : zero point of per-channel filter must be same.
+ # That's why the quantization forces a symmetric quantization into INT8.
+ # zero_point is guaranted to be zero whatever the channel is.
+
+ with open(qdq_file, "rb") as f:
+ onx = onnx.load(f)
+ for init in onx.graph.initializer:
+ arr = to_array(init)
+ if (
+ arr.dtype == np.int8
+ and "zero_point" not in init.name
+ and not init.name.endswith("quantized")
+ ):
+ raise AssertionError(
+ f"Initializer {init.name!r} has type {arr.dtype} and "
+ f"shape {arr.shape} but should be {np.uint8}."
+ )
+
+ sess = InferenceSession(qdq_file, providers=["CPUExecutionProvider"])
+ shape = (1, 3, 32, 32)
+ size = np.prod(shape)
+ dummy = (np.arange(size) / float(size)).astype(np.float32).reshape(shape)
+ got = sess.run(None, {"input": dummy})
+ self.assertEqual(got[0].shape, (1, 64, 8, 8))
+ self.assertEqual(got[0].dtype, np.float32)
+ if per_channel:
+ expected = np.array(
+ [
+ [[1.0862497091293335, 0.9609132409095764], [1.0862497091293335, 0.9191343784332275]],
+ [[0.7520190477371216, 1.0026921033859253], [1.0444709062576294, 1.0862497091293335]],
+ [[0.0, 0.0], [0.0, 0.0]],
+ [[0.0, 0.0], [0.9609132409095764, 0.7937979102134705]],
+ ],
+ dtype=np.float32,
+ )
+ assert_allclose(expected, got[0][0, :4, :2, :2], atol=0.2)
+ else:
+ expected = np.array(
+ [
+ [[1.428238868713379, 1.2602107524871826], [1.3442248106002808, 1.2182037830352783]],
+ [[0.8821475505828857, 1.0921826362609863], [1.1341897249221802, 1.1761966943740845]],
+ [[0.0, 0.0], [0.0, 0.0]],
+ [[0.0, 0.0], [1.2182037830352783, 1.050175666809082]],
+ ],
+ dtype=np.float32,
+ )
+ assert_allclose(expected, got[0][0, :4, :2, :2], atol=0.2)
+
+
+if __name__ == "__main__":
+ unittest.main(verbosity=2)
diff --git a/tools/ci_build/github/azure-pipelines/c-api-noopenmp-packaging-pipelines.yml b/tools/ci_build/github/azure-pipelines/c-api-noopenmp-packaging-pipelines.yml
index e37ca985fb6d1..608112181bd4b 100644
--- a/tools/ci_build/github/azure-pipelines/c-api-noopenmp-packaging-pipelines.yml
+++ b/tools/ci_build/github/azure-pipelines/c-api-noopenmp-packaging-pipelines.yml
@@ -356,19 +356,32 @@ stages:
- checkout: self
submodules: false
- template: templates/set-version-number-variables-step.yml
- - task: DownloadPipelineArtifact@2
- displayName: 'Download Final Jar'
- inputs:
- buildType: 'current'
- artifactName: 'onnxruntime-java-gpu'
- targetPath: '$(Build.BinariesDirectory)/final-jar'
- - task: Bash@3
+ - template: templates/flex-downloadPipelineArtifact.yml
+ parameters:
+ StepName: 'Download Final Jar'
+ ArtifactName: onnxruntime-java-gpu
+ TargetPath: '$(Build.BinariesDirectory)/final-jar'
+ SpecificArtifact: ${{ parameters.specificArtifact }}
+ BuildId: ${{ parameters.BuildId }}
+
+ - template: templates/get-docker-image-steps.yml
+ parameters:
+ Dockerfile: tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda11_8_tensorrt8_6
+ Context: tools/ci_build/github/linux/docker/
+ DockerBuildArgs: "--build-arg BUILD_UID=$( id -u )"
+ Repository: onnxruntimeubi8packagestest
+ UpdateDepsTxt: false
+
+ - bash: |
+ docker run --rm \
+ --gpus all \
+ --volume $(Build.SourcesDirectory):/onnxruntime_src \
+ --volume $(Build.BinariesDirectory):/build \
+ --volume /data/models:/build/models:ro \
+ onnxruntimeubi8packagestest \
+ /bin/bash /onnxruntime_src/tools/ci_build/github/linux/java_linux_final_test.sh -r /build -v $(OnnxRuntimeVersion)
displayName: 'Test'
- inputs:
- targetType: filePath
- filePath: 'tools/ci_build/github/linux/java_linux_final_test.sh'
- arguments: '-r $(Build.BinariesDirectory) -v $(OnnxRuntimeVersion)'
- template: templates/component-governance-component-detection-steps.yml
parameters:
diff --git a/tools/ci_build/github/azure-pipelines/linux-ci-pipeline.yml b/tools/ci_build/github/azure-pipelines/linux-ci-pipeline.yml
index b784ef72d6517..420bffc6c6cda 100644
--- a/tools/ci_build/github/azure-pipelines/linux-ci-pipeline.yml
+++ b/tools/ci_build/github/azure-pipelines/linux-ci-pipeline.yml
@@ -45,10 +45,6 @@ stages:
clean: true
submodules: none
- - task: NodeTool@0
- inputs:
- versionSpec: '16.x'
-
- task: UsePythonVersion@0
inputs:
versionSpec: '3.8'
@@ -74,7 +70,6 @@ stages:
inputs:
script: |
mkdir -p $HOME/.onnx
- mkdir -p $(Pipeline.Workspace)/ccache
docker run --rm \
--volume /data/onnx:/data/onnx:ro \
--volume $(Build.SourcesDirectory):/onnxruntime_src \
@@ -90,7 +85,7 @@ stages:
set -ex; \
ccache -s; \
/opt/python/cp38-cp38/bin/python3 /onnxruntime_src/tools/ci_build/build.py \
- --build_dir /build --cmake_generator Ninja \
+ --build_dir /build --cmake_generator 'Ninja' \
--config Debug Release \
--skip_submodule_sync \
--build_shared_lib \
@@ -105,43 +100,31 @@ stages:
ccache -z"
workingDirectory: $(Build.SourcesDirectory)
- - task: UseDotNet@2
- displayName: "Setup dotnet"
- inputs:
- version: '6.0.408'
-
- - task: DotNetCoreCLI@2
- displayName: "Restore C# packages"
- inputs:
- command: 'restore'
- projects: '$(Build.SourcesDirectory)/csharp/OnnxRuntime.DesktopOnly.CSharp.sln'
-
- # the props file was generated with docker container paths. convert to the 'real' path by replacing the
- # the container path of '/build'. The '>' prefix is to match the closing angle bracket of the tag.
- # e.g. /build/... so we only match the start of a path.
- # We use powershell so we don't need extra escaping of the '/' chars in the path.
- - task: CmdLine@2
- displayName: 'Update props from docker path to local and create models link'
- inputs:
- script: |
- pwsh -Command '(Get-Content $(Build.SourcesDirectory)/csharp/Directory.Build.props) -replace ">/build", ">$(Build.BinariesDirectory)" | Set-Content $(Build.SourcesDirectory)/csharp/Directory.Build.props'
- cat $(Build.SourcesDirectory)/csharp/Directory.Build.props
- ln -s /data/models $(Build.BinariesDirectory)/models
-
- - task: DotNetCoreCLI@2
- displayName: 'dotnet build C# sln'
- inputs:
- command: 'build'
- projects: '$(Build.SourcesDirectory)/csharp/OnnxRuntime.DesktopOnly.CSharp.sln'
-
- - task: DotNetCoreCLI@2
- displayName: 'dotnet test C#'
- inputs:
- command: 'test'
- projects: '$(Build.SourcesDirectory)/csharp/OnnxRuntime.DesktopOnly.CSharp.sln'
- # extra logging so all tests are listed in output to validate what's actually run
- arguments: '-f net6.0 --no-build -l "console;verbosity=normal"'
- workingDirectory: $(Build.SourcesDirectory)/csharp
+ - script: |
+ ln -s /data/models $(Build.BinariesDirectory)/models
+ displayName: link model dir
+
+ - bash: |
+ mkdir -p $HOME/.onnx
+ docker run --rm \
+ --volume /data/onnx:/data/onnx:ro \
+ --volume $(Build.SourcesDirectory):/onnxruntime_src \
+ --volume $(Build.BinariesDirectory):/build \
+ --volume /data/models:/build/models:ro \
+ --volume $HOME/.onnx:/home/onnxruntimedev/.onnx \
+ -e ALLOW_RELEASED_ONNX_OPSET_ONLY=0 \
+ -e NIGHTLY_BUILD \
+ -e BUILD_BUILDNUMBER \
+ onnxruntimecpubuild \
+ /bin/bash -c "
+ set -ex; \
+ pushd /onnxruntime_src/csharp; \
+ dotnet restore /onnxruntime_src/csharp/OnnxRuntime.DesktopOnly.CSharp.sln; \
+ dotnet build /onnxruntime_src/csharp/OnnxRuntime.DesktopOnly.CSharp.sln; \
+ dotnet test /onnxruntime_src/csharp/OnnxRuntime.DesktopOnly.CSharp.sln -f net6.0 --no-build -l \"console;verbosity=normal\"; \
+ popd
+ "
+ displayName: 'Dotnet build C# sln and Test'
- task: CmdLine@2
displayName: 'Install python deps and run java tests'
@@ -245,8 +228,11 @@ stages:
- stage: arm64_test
dependsOn: ['arm64_build']
jobs:
- - template: templates/py-packaging-linux-test.yml
+ - template: templates/py-packaging-linux-test-cpu.yml
parameters:
arch: 'aarch64'
machine_pool: 'onnxruntime-linux-ARM64-CPU-2019'
- device: 'CPU'
+ base_image: 'arm64v8/centos:7'
+ devtoolset_rootpath: /opt/rh/devtoolset-10/root
+ ld_library_path_arg: /opt/rh/devtoolset-10/root/usr/lib64:/opt/rh/devtoolset-10/root/usr/lib:/opt/rh/devtoolset-10/root/usr/lib64/dyninst:/opt/rh/devtoolset-10/root/usr/lib/dyninst:/usr/local/lib64
+ prepend_path: '/opt/rh/devtoolset-10/root/usr/bin:'
diff --git a/tools/ci_build/github/azure-pipelines/linux-cpu-aten-pipeline.yml b/tools/ci_build/github/azure-pipelines/linux-cpu-aten-pipeline.yml
index 5dc8fffbfecf8..461a62496c3b4 100644
--- a/tools/ci_build/github/azure-pipelines/linux-cpu-aten-pipeline.yml
+++ b/tools/ci_build/github/azure-pipelines/linux-cpu-aten-pipeline.yml
@@ -50,10 +50,6 @@ jobs:
clean: true
submodules: recursive
- - task: NodeTool@0
- inputs:
- versionSpec: '16.x'
-
- template: templates/get-docker-image-steps.yml
parameters:
Dockerfile: tools/ci_build/github/linux/docker/Dockerfile.manylinux2014_aten_cpu
diff --git a/tools/ci_build/github/azure-pipelines/linux-multi-gpu-tensorrt-ci-pipeline.yml b/tools/ci_build/github/azure-pipelines/linux-multi-gpu-tensorrt-ci-pipeline.yml
index c1f1c39c855c0..f0c4422c7eac9 100644
--- a/tools/ci_build/github/azure-pipelines/linux-multi-gpu-tensorrt-ci-pipeline.yml
+++ b/tools/ci_build/github/azure-pipelines/linux-multi-gpu-tensorrt-ci-pipeline.yml
@@ -33,5 +33,3 @@ jobs:
JobName: 'Linux_CI_Multi_GPU_TensorRT_Dev'
# The latest TensorRT container only supports ubuntu20.04 and python 3.8
RunDockerBuildArgs: '-o ubuntu20.04 -d tensorrt -x "--enable_multi_device_test"'
- DoNugetPack: 'false'
- ArtifactName: 'drop-linux'
diff --git a/tools/ci_build/github/azure-pipelines/linux-openvino-ci-pipeline.yml b/tools/ci_build/github/azure-pipelines/linux-openvino-ci-pipeline.yml
index 2938b87ec6420..0264086c12ddc 100644
--- a/tools/ci_build/github/azure-pipelines/linux-openvino-ci-pipeline.yml
+++ b/tools/ci_build/github/azure-pipelines/linux-openvino-ci-pipeline.yml
@@ -32,6 +32,4 @@ jobs:
AgentPool : 'Linux-CPU-2019'
JobName: 'Linux_CI_Dev'
RunDockerBuildArgs: '-o ubuntu20.04 -d openvino -v 2023.0.0 -x "--use_openvino CPU_FP32 --build_wheel"'
- DoNugetPack: 'false'
- ArtifactName: 'drop-linux'
TimeoutInMinutes: 120
diff --git a/tools/ci_build/github/azure-pipelines/nuget/templates/test_linux.yml b/tools/ci_build/github/azure-pipelines/nuget/templates/test_linux.yml
index cbe4e805bb219..b07d9a6089c17 100644
--- a/tools/ci_build/github/azure-pipelines/nuget/templates/test_linux.yml
+++ b/tools/ci_build/github/azure-pipelines/nuget/templates/test_linux.yml
@@ -50,19 +50,52 @@ stages:
script: |
ln -sf /data/models $(Build.BinariesDirectory)
- - task: Bash@3
- displayName: 'Run Package Test'
- inputs:
- targetType: filePath
- filePath: '$(Build.SourcesDirectory)/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests/runtest.sh'
- arguments: '$(Build.BinariesDirectory)/nuget-artifact $(NuGetPackageVersionNumber)'
- workingDirectory: $(Build.BinariesDirectory)
- env:
- OnnxRuntimeBuildDirectory: $(Build.BinariesDirectory)
- DisableContribOps: $(DisableContribOps)
- DisableMlOps: $(DisableMlOps)
- IsReleaseBuild: $(IsReleaseBuild)
- PACKAGENAME: ${{ parameters.NugetPackageName }}
+ - ${{if contains(parameters.StageSuffix , 'GPU') }}:
+ - template: ../../templates/get-docker-image-steps.yml
+ parameters:
+ Dockerfile: tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_cuda11_8_tensorrt8_6
+ Context: tools/ci_build/github/linux/docker/
+ DockerBuildArgs: "--build-arg BUILD_UID=$( id -u )"
+ Repository: onnxruntimepackagestest
+ - bash: |
+ docker run --rm \
+ --gpus all \
+ --volume $(Build.SourcesDirectory):/onnxruntime_src \
+ --volume $(Build.BinariesDirectory):/build \
+ --volume /data/models:/build/models:ro \
+ -e BUILD_SOURCESDIRECTORY='/onnxruntime_src' \
+ -e OnnxRuntimeBuildDirectory='/build' \
+ -e DisableContribOps='$(DisableContribOps)' \
+ -e DisableMlOps='$(DisableMlOps)' \
+ -e IsReleaseBuild='$(IsReleaseBuild)' \
+ -e PACKAGENAME='${{ parameters.NugetPackageName }}' \
+ onnxruntimepackagestest \
+ /bin/bash -c "
+ set -ex; \
+ pushd /build; \
+ bash /onnxruntime_src/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests/runtest.sh /build/nuget-artifact $(NuGetPackageVersionNumber); \
+ popd
+ "
+ displayName: 'Run Package Test'
+ - ${{ else }}:
+ - task: CmdLine@2
+ displayName: 'Create symlink for test models'
+ inputs:
+ script: |
+ ln -sf /data/models $(Build.BinariesDirectory)
+ - task: Bash@3
+ displayName: 'Run Package Test'
+ inputs:
+ targetType: filePath
+ filePath: '$(Build.SourcesDirectory)/csharp/test/Microsoft.ML.OnnxRuntime.EndToEndTests/runtest.sh'
+ arguments: '$(Build.BinariesDirectory)/nuget-artifact $(NuGetPackageVersionNumber)'
+ workingDirectory: $(Build.BinariesDirectory)
+ env:
+ OnnxRuntimeBuildDirectory: $(Build.BinariesDirectory)
+ DisableContribOps: $(DisableContribOps)
+ DisableMlOps: $(DisableMlOps)
+ IsReleaseBuild: $(IsReleaseBuild)
+ PACKAGENAME: ${{ parameters.NugetPackageName }}
- template: ../../templates/component-governance-component-detection-steps.yml
parameters:
diff --git a/tools/ci_build/github/azure-pipelines/orttraining-linux-ci-pipeline.yml b/tools/ci_build/github/azure-pipelines/orttraining-linux-ci-pipeline.yml
index f5b221f23f8c4..355faa8b985ee 100644
--- a/tools/ci_build/github/azure-pipelines/orttraining-linux-ci-pipeline.yml
+++ b/tools/ci_build/github/azure-pipelines/orttraining-linux-ci-pipeline.yml
@@ -51,10 +51,6 @@ jobs:
clean: true
submodules: none
- - task: NodeTool@0
- inputs:
- versionSpec: '16.x'
-
- task: UsePythonVersion@0
inputs:
versionSpec: '3.8'
@@ -85,6 +81,7 @@ jobs:
mkdir -p $(Pipeline.Workspace)/ccache
docker run --rm \
--volume /data/onnx:/data/onnx:ro \
+ --volume /data/models:/build/models:ro \
--volume $(Build.SourcesDirectory):/onnxruntime_src \
--volume $(Build.BinariesDirectory):/build \
--volume $HOME/.onnx:/home/onnxruntimedev/.onnx \
@@ -107,53 +104,11 @@ jobs:
--enable_onnx_tests \
--enable_training \
--use_cache \
- --build_java --build_nodejs --update --build; \
+ --build_java --build_nodejs; \
ccache -sv; \
ccache -z"
workingDirectory: $(Build.SourcesDirectory)
- - task: CmdLine@2
- displayName: 'Install python deps and run java tests'
- inputs:
- script: |
- set -e -x
- python3 -m pip uninstall -y ort-nightly-gpu ort-nightly onnxruntime onnxruntime-gpu onnxruntime-training onnxruntime-directml ort-nightly-directml onnx -qq
- cp $(Build.SourcesDirectory)/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt $(Build.BinariesDirectory)/requirements.txt
- # Test ORT with the latest ONNX release.
- sed -i "s/git+http:\/\/github\.com\/onnx\/onnx.*/onnx/" $(Build.BinariesDirectory)/requirements.txt
- python3 -m pip install -r $(Build.BinariesDirectory)/requirements.txt
- mkdir $(Build.BinariesDirectory)/requirements_torch_cpu/
- cp $(Build.SourcesDirectory)/tools/ci_build/github/linux/docker/scripts/training/ortmodule/stage1/requirements_torch_cpu/requirements.txt $(Build.BinariesDirectory)/requirements_torch_cpu/requirements.txt
- python3 -m pip install -r $(Build.BinariesDirectory)/requirements_torch_cpu/requirements.txt
- cd $(Build.SourcesDirectory)/java
- $(Build.SourcesDirectory)/java/gradlew "cmakeCheck" "-DcmakeBuildDir=$(Build.BinariesDirectory)/Release"
-
- - task: CmdLine@2
- displayName: 'Install Release python package'
- inputs:
- script: |
- rm -rf $(Build.BinariesDirectory)/Release/onnxruntime $(Build.BinariesDirectory)/Release/pybind11
- python3 -m pip install $(Build.BinariesDirectory)/Release/dist/*.whl
-
- - task: PythonScript@0
- displayName: 'Run Release unit tests'
- inputs:
- scriptPath: $(Build.SourcesDirectory)/tools/ci_build/build.py
- workingDirectory: $(Build.BinariesDirectory)/Release
- arguments: >-
- --build_dir $(Build.BinariesDirectory)
- --cmake_generator Ninja
- --config Release
- --test
- --skip_submodule_sync
- --build_shared_lib
- --parallel
- --build_wheel
- --enable_onnx_tests
- --enable_training
- --build_nodejs
- --ctest_path ""
-
- task: PublishTestResults@2
displayName: 'Publish unit test results'
inputs:
diff --git a/tools/ci_build/github/azure-pipelines/orttraining-linux-gpu-ci-pipeline.yml b/tools/ci_build/github/azure-pipelines/orttraining-linux-gpu-ci-pipeline.yml
index 16d70a58a0827..da0a2a6026190 100644
--- a/tools/ci_build/github/azure-pipelines/orttraining-linux-gpu-ci-pipeline.yml
+++ b/tools/ci_build/github/azure-pipelines/orttraining-linux-gpu-ci-pipeline.yml
@@ -18,7 +18,6 @@ jobs:
parameters:
AgentPool : 'Onnxruntime-Linux-GPU-NC6sv3'
JobName: 'Onnxruntime_Linux_GPU_Training'
- SubmoduleCheckoutMode: 'recursive'
RunDockerBuildArgs: >
-o ubuntu20.04 -d gpu
-t onnxruntime_orttraining_ortmodule_tests_image
@@ -26,24 +25,16 @@ jobs:
-e
-x "
--enable_training
- --config $(buildConfig)
+ --config Release
--use_cuda --cuda_version=11.8 --cuda_home=/usr/local/cuda-11.8 --cudnn_home=/usr/local/cuda-11.8
--build_wheel
--enable_nvtx_profile
--cmake_extra_defines CMAKE_CUDA_ARCHITECTURES=70
"
- DoNugetPack: 'false'
RunInjectedPipeline: 'true'
InjectedPipeline: 'orttraining-linux-gpu-ortmodule-test-ci-pipeline.yml'
DockerImageTag: 'onnxruntime_orttraining_ortmodule_tests_image'
- BuildConfig: $(buildConfig)
- ArtifactName: 'drop-linux'
TimeoutInMinutes: 140
# Enable unreleased onnx opsets in CI builds
# This facilitates testing the implementation for the new opsets
AllowReleasedOpsetOnly: '0'
- Strategy:
- maxParallel: 2
- matrix:
- Release:
- buildConfig: Release
diff --git a/tools/ci_build/github/azure-pipelines/py-package-test-pipeline.yml b/tools/ci_build/github/azure-pipelines/py-package-test-pipeline.yml
index c684e08ba1258..2db68d3bf1952 100644
--- a/tools/ci_build/github/azure-pipelines/py-package-test-pipeline.yml
+++ b/tools/ci_build/github/azure-pipelines/py-package-test-pipeline.yml
@@ -3,24 +3,38 @@ resources:
- pipeline: build
source: 'Python packaging pipeline'
trigger: true
+ branch: rel-1.16.0 # branch to pick the artifact, Used only for manual triggered pipeline runs for testing the pipeline itself
+ #TODO: Remove the following dependency. Running python tests should not need to use manylinux.
+ repositories:
+ - repository: manylinux # The name used to reference this repository in the checkout step
+ type: Github
+ endpoint: Microsoft
+ name: pypa/manylinux
+ ref: 5eda9aded5462201e6310105728d33016e637ea7
stages:
- stage: Linux_Test_CPU_x86_64_stage
jobs:
- - template: templates/py-packaging-linux-test.yml
+ - template: templates/py-packaging-linux-test-cpu.yml
parameters:
arch: 'x86_64'
machine_pool: 'onnxruntime-Ubuntu2004-AMD-CPU'
- device: 'CPU'
+ base_image: 'centos:7'
+ devtoolset_rootpath: /opt/rh/devtoolset-11/root
+ ld_library_path_arg: /opt/rh/devtoolset-11/root/usr/lib64:/opt/rh/devtoolset-11/root/usr/lib:/opt/rh/devtoolset-11/root/usr/lib64/dyninst:/opt/rh/devtoolset-11/root/usr/lib/dyninst:/usr/local/lib64
+ prepend_path: '/opt/rh/devtoolset-11/root/usr/bin:'
- stage: Linux_Test_CPU_aarch64_stage
dependsOn: []
jobs:
- - template: templates/py-packaging-linux-test.yml
+ - template: templates/py-packaging-linux-test-cpu.yml
parameters:
arch: 'aarch64'
machine_pool: 'aiinfra-linux-ARM64-CPU-2019'
- device: 'CPU'
+ base_image: 'arm64v8/centos:7'
+ devtoolset_rootpath: /opt/rh/devtoolset-10/root
+ ld_library_path_arg: /opt/rh/devtoolset-10/root/usr/lib64:/opt/rh/devtoolset-10/root/usr/lib:/opt/rh/devtoolset-10/root/usr/lib64/dyninst:/opt/rh/devtoolset-10/root/usr/lib/dyninst:/usr/local/lib64
+ prepend_path: '/opt/rh/devtoolset-10/root/usr/bin:'
- stage: Packages_Somking_Test
dependsOn: []
@@ -31,19 +45,6 @@ stages:
machine_pool:
vmImage: 'macOS-13'
itemPattern: '*/*mac*x86_64.whl'
- - template: templates/py-package-smoking-test.yml
- parameters:
- job_name: Test_WIN_64_Wheels
- itemPattern: '*/*win_amd64.whl'
- machine_pool:
- vmImage: 'windows-2022'
- - template: templates/py-package-smoking-test.yml
- parameters:
- job_name: Test_WIN_32_Wheels
- itemPattern: '*/*win32.whl'
- python_arch: 'x86'
- machine_pool:
- vmImage: 'windows-2022'
- template: templates/py-package-smoking-test.yml
parameters:
job_name: Test_LINUX_x86_64_Wheels
@@ -61,7 +62,7 @@ stages:
- Linux_Test_CPU_aarch64_stage
- Packages_Somking_Test
jobs:
- - template: templates/py-packaging-linux-test.yml
+ - template: templates/py-packaging-linux-test-cuda.yml
parameters:
arch: 'x86_64'
machine_pool: 'Onnxruntime-Linux-GPU'
diff --git a/tools/ci_build/github/azure-pipelines/templates/flex-downloadPipelineArtifact.yml b/tools/ci_build/github/azure-pipelines/templates/flex-downloadPipelineArtifact.yml
index 0f4e0553d05bf..a83451a1b33d9 100644
--- a/tools/ci_build/github/azure-pipelines/templates/flex-downloadPipelineArtifact.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/flex-downloadPipelineArtifact.yml
@@ -18,7 +18,7 @@ parameters:
steps:
- task: DownloadPipelineArtifact@2
- displayName: ${{ parameters.StepName }}}
+ displayName: ${{ parameters.StepName }}
inputs:
artifactName: ${{ parameters.ArtifactName}}
targetPath: '${{ parameters.TargetPath }}'
diff --git a/tools/ci_build/github/azure-pipelines/templates/jobs/win-ci-vs-2022-job.yml b/tools/ci_build/github/azure-pipelines/templates/jobs/win-ci-vs-2022-job.yml
index 82bbebf133ba3..b05602a57b166 100644
--- a/tools/ci_build/github/azure-pipelines/templates/jobs/win-ci-vs-2022-job.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/jobs/win-ci-vs-2022-job.yml
@@ -100,7 +100,7 @@ jobs:
- task: NodeTool@0
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
force32bit: ${{ parameters.isX86 }}
diff --git a/tools/ci_build/github/azure-pipelines/templates/linux-ci.yml b/tools/ci_build/github/azure-pipelines/templates/linux-ci.yml
index 05b2dee77e689..7b9788d90b17d 100644
--- a/tools/ci_build/github/azure-pipelines/templates/linux-ci.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/linux-ci.yml
@@ -1,23 +1,14 @@
parameters:
AgentPool : 'onnxruntime-Ubuntu2004-AMD-CPU'
StageName : 'Linux_CI_Dev'
- SubmoduleCheckoutMode: ''
RunDockerBuildArgs: '-o ubuntu20.04 -d cpu -x "--build_wheel"'
- DoNodejsPack: 'false'
- DoNugetPack: 'false'
NuPackScript: ''
RunInjectedPipeline: 'false'
InjectedPipeline: ''
DockerImageTag: ''
- BuildConfig: ''
- ArtifactName: 'drop-linux'
TimeoutInMinutes: 120
# Controls whether unreleased onnx opsets are allowed. Default is set to 1
AllowReleasedOpsetOnly: '1'
- # to inject strategy, you need to pass in the whole yaml structure -
- # https://docs.microsoft.com/en-us/azure/devops/pipelines/yaml-schema?view=azure-devops&tabs=schema#strategies
- # see example in orttraining-linux-gpu-ci-pipeline.yml
- Strategy: ''
jobs:
- job: ${{ parameters.StageName }}
@@ -28,16 +19,8 @@ jobs:
ALLOW_RELEASED_ONNX_OPSET_ONLY: ${{ parameters.AllowReleasedOpsetOnly }}
skipComponentGovernanceDetection: true
pool: ${{ parameters.AgentPool }}
- ${{ if ne(parameters.Strategy, '') }}:
- strategy:
- ${{ parameters.Strategy }}
steps:
- checkout: self
- ${{ if ne(parameters.SubmoduleCheckoutMode, '') }}:
- submodules: ${{ parameters.SubmoduleCheckoutMode }}
- - task: NodeTool@0
- inputs:
- versionSpec: '16.x'
- template: run-docker-build-steps.yml
parameters:
RunDockerBuildArgs: '${{ parameters.RunDockerBuildArgs }}'
@@ -48,31 +31,10 @@ jobs:
searchFolder: '$(Build.BinariesDirectory)'
testRunTitle: 'Unit Test Run'
condition: succeededOrFailed()
- - ${{ if eq(parameters['DoNugetPack'], 'true') }}:
- - script: |
- ${{ parameters.NuPackScript }}
- displayName: 'Create Artifacts'
- - task: PublishPipelineArtifact@0
- displayName: 'Publish Pipeline Artifact'
- inputs:
- artifactName: ${{ parameters.ArtifactName }}
- targetPath: '$(Build.ArtifactStagingDirectory)'
- - ${{ if eq(parameters['DoNodejsPack'], 'true') }}:
- - script: |
- npm pack
- cp $(Build.SourcesDirectory)/js/node/onnxruntime-*.tgz $(Build.ArtifactStagingDirectory)
- cp -R $(Build.SourcesDirectory)/js/node/prebuilds $(Build.ArtifactStagingDirectory)/prebuilds
- workingDirectory: '$(Build.SourcesDirectory)/js/node'
- displayName: 'Create NPM Package'
- - task: PublishPipelineArtifact@0
- displayName: 'Publish Pipeline Artifact: ${{ parameters.ArtifactName }}'
- inputs:
- artifactName: ${{ parameters.ArtifactName }}
- targetPath: '$(Build.ArtifactStagingDirectory)'
- ${{ if eq(parameters['RunInjectedPipeline'], 'true') }}:
- template: |
${{ parameters.InjectedPipeline }}
parameters:
DockerImageTag: ${{ parameters.DockerImageTag }}
- BuildConfig: ${{ parameters.BuildConfig }}
+ BuildConfig: Release
- template: clean-agent-build-directory-step.yml
diff --git a/tools/ci_build/github/azure-pipelines/templates/linux-wasm-ci.yml b/tools/ci_build/github/azure-pipelines/templates/linux-wasm-ci.yml
index 93945a1cb5e96..4ee442a122878 100644
--- a/tools/ci_build/github/azure-pipelines/templates/linux-wasm-ci.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/linux-wasm-ci.yml
@@ -79,7 +79,7 @@ jobs:
architecture: $(buildArch)
- task: NodeTool@0
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
- template: download-deps.yml
- task: PythonScript@0
@@ -94,7 +94,6 @@ jobs:
cd '$(Build.SourcesDirectory)/cmake/external/emsdk'
./emsdk install 3.1.44 ccache-git-emscripten-64bit
./emsdk activate 3.1.44 ccache-git-emscripten-64bit
- ln -s $(Build.SourcesDirectory)/cmake/external/emsdk/ccache/git-emscripten_64bit/bin/ccache /usr/local/bin/ccache
displayName: 'emsdk install and activate ccache for emscripten'
condition: eq('${{ parameters.WithCache }}', 'true')
diff --git a/tools/ci_build/github/azure-pipelines/templates/mac-cpu-packing-jobs.yml b/tools/ci_build/github/azure-pipelines/templates/mac-cpu-packing-jobs.yml
index adfcd98e37230..f5e5435cfaca0 100644
--- a/tools/ci_build/github/azure-pipelines/templates/mac-cpu-packing-jobs.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/mac-cpu-packing-jobs.yml
@@ -50,7 +50,7 @@ jobs:
versionSpec: 3.11
- task: NodeTool@0
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
- template: set-version-number-variables-step.yml
diff --git a/tools/ci_build/github/azure-pipelines/templates/py-package-smoking-test.yml b/tools/ci_build/github/azure-pipelines/templates/py-package-smoking-test.yml
index cee3bd9c9e968..8d5ca19a73535 100644
--- a/tools/ci_build/github/azure-pipelines/templates/py-package-smoking-test.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/py-package-smoking-test.yml
@@ -39,36 +39,22 @@ jobs:
versionSpec: $(PythonVersion)
architecture: ${{ parameters.python_arch }}
- - task: DownloadPipelineArtifact@2
- displayName: 'Download Pipeline Artifact'
- inputs:
- artifactName: 'onnxruntime'
- targetPath: '$(Build.BinariesDirectory)/whl'
- itemPattern: ${{parameters.itemPattern}}
- # The public ADO project
- ${{ if eq(variables['System.CollectionId'], 'f3ad12f2-e480-4533-baf2-635c95467d29') }}:
- buildType: current
- # The private ADO project
- ${{ if eq(variables['System.CollectionId'], 'bc038106-a83b-4dab-9dd3-5a41bc58f34c') }}:
- project: '530acbc4-21bc-487d-8cd8-348ff451d2ff'
- definition: 841
- preferTriggeringPipeline: true
- runVersion: 'latest'
- buildType: specific
+ - download: build # pipeline resource identifier.
+ artifact: 'onnxruntime'
- task: Bash@3
inputs:
targetType: 'inline'
script: |
set -ex
- files=(whl/*.whl)
+ files=(*.whl)
FILE_NAME="${files[0]}"
FILE_NAME=$(basename $FILE_NAME)
PYTHON_PACKAGE_NAME=$(echo "$FILE_NAME" | cut -f 1 -d '-')
- python3 -m pip install --find-links "$(Build.BinariesDirectory)/whl" $PYTHON_PACKAGE_NAME
- pip show $PYTHON_PACKAGE_NAME
- python -c "import onnxruntime as ort; print(ort.__version__)"
- workingDirectory: $(Build.BinariesDirectory)
+ python3 -m pip install --find-links "$(Pipeline.Workspace)/build/onnxruntime" $PYTHON_PACKAGE_NAME
+ python3 -m pip show $PYTHON_PACKAGE_NAME
+ python3 -c "import onnxruntime as ort; print(ort.__version__)"
+ workingDirectory: $(Pipeline.Workspace)/build/onnxruntime
displayName: Test Package Installation
- task: mspremier.PostBuildCleanup.PostBuildCleanup-task.PostBuildCleanup@3
diff --git a/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test-cpu.yml b/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test-cpu.yml
new file mode 100644
index 0000000000000..00e40b520e867
--- /dev/null
+++ b/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test-cpu.yml
@@ -0,0 +1,111 @@
+parameters:
+- name: arch
+ type: string
+
+- name: base_image
+ type: string
+
+- name: devtoolset_rootpath
+ type: string
+
+- name: ld_library_path_arg
+ type: string
+
+- name: prepend_path
+ type: string
+
+- name: machine_pool
+ type: string
+
+- name: extra_job_id
+ type: string
+ default: ''
+
+- name: python_wheel_suffix
+ type: string
+ default: ''
+
+
+# TODO: Ideally it should fetch information from the build that triggers it
+- name: cmake_build_type
+ type: string
+ default: 'Release'
+ values:
+ - Debug
+ - Release
+ - RelWithDebInfo
+ - MinSizeRel
+
+- name: timeout
+ type: number
+ default: 120
+
+jobs:
+- job: Linux_Test_CPU${{ parameters.extra_job_id }}_${{ parameters.arch }}
+ timeoutInMinutes: ${{ parameters.timeout }}
+ variables:
+ skipComponentGovernanceDetection: true
+ workspace:
+ clean: all
+ pool: ${{ parameters.machine_pool }}
+ steps:
+ - checkout: self
+ clean: true
+ submodules: none
+ # The public ADO project
+ - ${{ if eq(variables['System.CollectionId'], 'f3ad12f2-e480-4533-baf2-635c95467d29') }}:
+ - download: current # pipeline resource identifier.
+ artifact: 'drop-linux-cpu-${{ parameters.arch }}'
+
+ - download: current # pipeline resource identifier.
+ artifact: 'onnxruntime${{ parameters.python_wheel_suffix }}'
+
+ - bash: |
+ set -e -x
+ mv "$(Pipeline.Workspace)/drop-linux-cpu-${{ parameters.arch }}" $(Build.BinariesDirectory)/${{parameters.cmake_build_type}}
+ mv "$(Pipeline.Workspace)/onnxruntime${{ parameters.python_wheel_suffix }}" "$(Build.BinariesDirectory)/whl"
+ cp -r "$(Build.BinariesDirectory)/whl" $(Build.BinariesDirectory)/tmp
+ find "$(Build.BinariesDirectory)/tmp" -name '*.whl' -exec bash -c 'unzip -d "${1%.*}" "$1"' _ {} \;
+ # The private ADO project
+ - ${{ if eq(variables['System.CollectionId'], 'bc038106-a83b-4dab-9dd3-5a41bc58f34c') }}:
+ - download: build # pipeline resource identifier.
+ artifact: 'drop-linux-cpu-${{ parameters.arch }}'
+
+ - download: build # pipeline resource identifier.
+ artifact: 'onnxruntime${{ parameters.python_wheel_suffix }}'
+
+ - bash: |
+ set -e -x
+ ls $(Pipeline.Workspace)/build
+ mv "$(Pipeline.Workspace)/build/drop-linux-cpu-${{ parameters.arch }}" $(Build.BinariesDirectory)/${{parameters.cmake_build_type}}
+ mv "$(Pipeline.Workspace)/build/onnxruntime${{ parameters.python_wheel_suffix }}" "$(Build.BinariesDirectory)/whl"
+ cp -r "$(Build.BinariesDirectory)/whl" $(Build.BinariesDirectory)/tmp
+ find "$(Build.BinariesDirectory)/tmp" -name '*.whl' -exec bash -c 'unzip -d "${1%.*}" "$1"' _ {} \;
+
+ # The BinSkim task uses a dotnet program which doesn't support ARM CPUs yet
+ - ${{ if eq(parameters.arch, 'x86_64') }}:
+ - task: BinSkim@4
+ displayName: 'Run BinSkim'
+ inputs:
+ AnalyzeTargetGlob: '$(Build.BinariesDirectory)/tmp/**/*.so'
+ continueOnError: true
+
+ - template: get-docker-image-steps.yml
+ parameters:
+ Dockerfile: tools/ci_build/github/linux/docker/inference/x64/python/cpu/Dockerfile.manylinux2014_cpu
+ Context: tools/ci_build/github/linux/docker/inference/x64/python/cpu
+ DockerBuildArgs: "--build-arg BUILD_UID=$( id -u ) --build-arg BASEIMAGE=${{ parameters.base_image }} --build-arg PLATFORM=${{ parameters.arch }} --build-arg PREPEND_PATH=${{ parameters.prepend_path }} --build-arg LD_LIBRARY_PATH_ARG=${{ parameters.ld_library_path_arg }} --build-arg DEVTOOLSET_ROOTPATH=${{ parameters.devtoolset_rootpath }}"
+ Repository: onnxruntimecpubuildpython${{ parameters.arch }}
+ ${{ if eq(parameters.arch, 'aarch64') }}:
+ UpdateDepsTxt: false
+
+ - task: Bash@3
+ displayName: 'Bash Script'
+ inputs:
+ targetType: filePath
+ filePath: tools/ci_build/github/linux/run_python_dockertest.sh
+ arguments: -d CPU -c ${{parameters.cmake_build_type}} -i onnxruntimecpubuildpython${{ parameters.arch }}
+
+ - task: mspremier.PostBuildCleanup.PostBuildCleanup-task.PostBuildCleanup@3
+ displayName: 'Clean Agent Directories'
+ condition: always()
diff --git a/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test-cuda.yml b/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test-cuda.yml
new file mode 100644
index 0000000000000..c521245b33a77
--- /dev/null
+++ b/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test-cuda.yml
@@ -0,0 +1,93 @@
+parameters:
+- name: arch
+ type: string
+
+- name: device
+ type: string
+ values:
+ - CPU
+ - GPU
+
+- name: machine_pool
+ type: string
+
+- name: extra_job_id
+ type: string
+ default: ''
+
+- name: python_wheel_suffix
+ type: string
+ default: ''
+
+
+# TODO: Ideally it should fetch information from the build that triggers it
+- name: cmake_build_type
+ type: string
+ default: 'Release'
+ values:
+ - Debug
+ - Release
+ - RelWithDebInfo
+ - MinSizeRel
+
+- name: timeout
+ type: number
+ default: 120
+
+jobs:
+- job: Linux_Test_GPU${{ parameters.extra_job_id }}_${{ parameters.arch }}
+ timeoutInMinutes: ${{ parameters.timeout }}
+ variables:
+ skipComponentGovernanceDetection: true
+ workspace:
+ clean: all
+ pool: ${{ parameters.machine_pool }}
+ steps:
+ - checkout: self
+ clean: true
+ submodules: none
+ # The public ADO project
+ # - ${{ if eq(variables['System.CollectionId'], 'f3ad12f2-e480-4533-baf2-635c95467d29') }}:
+
+ # The private ADO project
+ - ${{ if eq(variables['System.CollectionId'], 'bc038106-a83b-4dab-9dd3-5a41bc58f34c') }}:
+ - download: build # pipeline resource identifier.
+ artifact: 'drop-linux-gpu-${{ parameters.arch }}'
+
+ - download: build # pipeline resource identifier.
+ artifact: 'onnxruntime${{ parameters.python_wheel_suffix }}'
+
+ - bash: |
+ set -e -x
+ ls $(Pipeline.Workspace)/build
+ mv "$(Pipeline.Workspace)/build/drop-linux-gpu-${{ parameters.arch }}" $(Build.BinariesDirectory)/${{parameters.cmake_build_type}}
+ mv "$(Pipeline.Workspace)/build/onnxruntime${{ parameters.python_wheel_suffix }}" "$(Build.BinariesDirectory)/whl"
+ cp -r "$(Build.BinariesDirectory)/whl" $(Build.BinariesDirectory)/tmp
+ find "$(Build.BinariesDirectory)/tmp" -name '*.whl' -exec bash -c 'unzip -d "${1%.*}" "$1"' _ {} \;
+
+ # The BinSkim task uses a dotnet program which doesn't support ARM CPUs yet
+ - ${{ if eq(parameters.arch, 'x86_64') }}:
+ - task: BinSkim@4
+ displayName: 'Run BinSkim'
+ inputs:
+ AnalyzeTargetGlob: '$(Build.BinariesDirectory)/tmp/**/*.so'
+ continueOnError: true
+
+
+ - template: get-docker-image-steps.yml
+ parameters:
+ Dockerfile: tools/ci_build/github/linux/docker/Dockerfile.manylinux2014_cuda11_8_tensorrt8_6
+ Context: tools/ci_build/github/linux/docker
+ DockerBuildArgs: "--network=host --build-arg POLICY=manylinux2014 --build-arg PLATFORM=x86_64 --build-arg DEVTOOLSET_ROOTPATH=/opt/rh/devtoolset-11/root --build-arg PREPEND_PATH=/opt/rh/devtoolset-11/root/usr/bin: --build-arg LD_LIBRARY_PATH_ARG=/opt/rh/devtoolset-11/root/usr/lib64:/opt/rh/devtoolset-11/root/usr/lib:/opt/rh/devtoolset-11/root/usr/lib64/dyninst:/opt/rh/devtoolset-11/root/usr/lib/dyninst:/usr/local/lib64 --build-arg BUILD_UID=$( id -u ) --build-arg PLATFORM=${{ parameters.arch }}"
+ Repository: onnxruntimecuda118xtrt86build${{ parameters.arch }}
+
+ - task: Bash@3
+ displayName: 'Bash Script'
+ inputs:
+ targetType: filePath
+ filePath: tools/ci_build/github/linux/run_python_dockertest.sh
+ arguments: -d GPU -c ${{parameters.cmake_build_type}} -i onnxruntimecuda118xtrt86build${{ parameters.arch }}
+
+ - task: mspremier.PostBuildCleanup.PostBuildCleanup-task.PostBuildCleanup@3
+ displayName: 'Clean Agent Directories'
+ condition: always()
diff --git a/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test.yml b/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test.yml
deleted file mode 100644
index 8ddc917e8591e..0000000000000
--- a/tools/ci_build/github/azure-pipelines/templates/py-packaging-linux-test.yml
+++ /dev/null
@@ -1,85 +0,0 @@
-parameters:
-- name: arch
- type: string
-
-- name: device
- type: string
-
-- name: machine_pool
- type: string
-
-- name: extra_job_id
- type: string
- default: ''
-
-- name: python_wheel_suffix
- type: string
- default: ''
-
-
-# TODO: Ideally it should fetch information from the build that triggers it
-- name: cmake_build_type
- type: string
- default: 'Release'
- values:
- - Debug
- - Release
- - RelWithDebInfo
- - MinSizeRel
-
-- name: timeout
- type: number
- default: 120
-
-jobs:
-- job: Linux_Test_${{ parameters.device }}${{ parameters.extra_job_id }}_${{ parameters.arch }}
- timeoutInMinutes: ${{ parameters.timeout }}
- variables:
- skipComponentGovernanceDetection: true
- workspace:
- clean: all
- pool: ${{ parameters.machine_pool }}
- steps:
- - task: DownloadPipelineArtifact@2
- displayName: 'Download Pipeline Artifact'
- inputs:
- artifactName: 'drop-linux-${{ lower(parameters.device) }}-${{ parameters.arch }}'
- targetPath: '$(Build.BinariesDirectory)/${{parameters.cmake_build_type}}'
- # The public ADO project
- ${{ if eq(variables['System.CollectionId'], 'f3ad12f2-e480-4533-baf2-635c95467d29') }}:
- buildType: current
- # The private ADO project
- ${{ if eq(variables['System.CollectionId'], 'bc038106-a83b-4dab-9dd3-5a41bc58f34c') }}:
- project: '530acbc4-21bc-487d-8cd8-348ff451d2ff'
- definition: 841
- preferTriggeringPipeline: true
- runVersion: 'latest'
- buildType: specific
-
- - task: DownloadPipelineArtifact@2
- displayName: 'Download Pipeline Artifact'
- inputs:
- artifactName: 'onnxruntime${{ parameters.python_wheel_suffix }}'
- targetPath: '$(Build.BinariesDirectory)/whl'
- # The public ADO project
- ${{ if eq(variables['System.CollectionId'], 'f3ad12f2-e480-4533-baf2-635c95467d29') }}:
- buildType: current
- # The private ADO project
- ${{ if eq(variables['System.CollectionId'], 'bc038106-a83b-4dab-9dd3-5a41bc58f34c') }}:
- project: '530acbc4-21bc-487d-8cd8-348ff451d2ff'
- definition: 841
- preferTriggeringPipeline: true
- runVersion: 'latest'
- buildType: specific
-
-
- - task: Bash@3
- displayName: 'Bash Script'
- inputs:
- targetType: filePath
- filePath: tools/ci_build/github/linux/run_python_tests.sh
- arguments: -d ${{ parameters.device }} -c ${{parameters.cmake_build_type}}
-
- - task: mspremier.PostBuildCleanup.PostBuildCleanup-task.PostBuildCleanup@3
- displayName: 'Clean Agent Directories'
- condition: always()
diff --git a/tools/ci_build/github/azure-pipelines/templates/react-native-ci.yml b/tools/ci_build/github/azure-pipelines/templates/react-native-ci.yml
index 8c54e71448992..e63939ae0114c 100644
--- a/tools/ci_build/github/azure-pipelines/templates/react-native-ci.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/react-native-ci.yml
@@ -80,7 +80,7 @@ stages:
- task: NodeTool@0
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
- script:
brew install coreutils ninja npm yarn
diff --git a/tools/ci_build/github/azure-pipelines/templates/web-browserstack-ci.yml b/tools/ci_build/github/azure-pipelines/templates/web-browserstack-ci.yml
index 4494fd36b336e..96e6ff89cd4f1 100644
--- a/tools/ci_build/github/azure-pipelines/templates/web-browserstack-ci.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/web-browserstack-ci.yml
@@ -29,7 +29,7 @@ jobs:
- task: NodeTool@0
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
- task: DownloadPipelineArtifact@2
inputs:
patterns: 'Release_*/**/*'
diff --git a/tools/ci_build/github/azure-pipelines/templates/web-ci.yml b/tools/ci_build/github/azure-pipelines/templates/web-ci.yml
index e0a85cc1973bc..55535173bc341 100644
--- a/tools/ci_build/github/azure-pipelines/templates/web-ci.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/web-ci.yml
@@ -74,7 +74,7 @@ stages:
displayName: 'Checkout submodule onnx'
- task: NodeTool@0
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
- template: linux-web-init-and-check.yml
- task: Bash@3
displayName: 'Extract commit SHA and save to __commit.txt'
diff --git a/tools/ci_build/github/azure-pipelines/templates/win-ci.yml b/tools/ci_build/github/azure-pipelines/templates/win-ci.yml
index 80d285f3fd3fb..8d28b4ce580b4 100644
--- a/tools/ci_build/github/azure-pipelines/templates/win-ci.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/win-ci.yml
@@ -101,7 +101,7 @@ stages:
- task: NodeTool@0
condition: and(succeeded(), eq('${{ parameters.buildNodejs}}', true))
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
- template: jobs/set-winenv.yml
parameters:
diff --git a/tools/ci_build/github/azure-pipelines/templates/win-wasm-ci.yml b/tools/ci_build/github/azure-pipelines/templates/win-wasm-ci.yml
index 9d36e2dbe4944..406683af80222 100644
--- a/tools/ci_build/github/azure-pipelines/templates/win-wasm-ci.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/win-wasm-ci.yml
@@ -74,7 +74,7 @@ jobs:
architecture: $(buildArch)
- task: NodeTool@0
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
- template: download-deps.yml
- task: PythonScript@0
diff --git a/tools/ci_build/github/azure-pipelines/templates/win-web-ci.yml b/tools/ci_build/github/azure-pipelines/templates/win-web-ci.yml
index 713396dd64532..90fc30141a916 100644
--- a/tools/ci_build/github/azure-pipelines/templates/win-web-ci.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/win-web-ci.yml
@@ -72,7 +72,7 @@ jobs:
displayName: 'Testing: force EOL to lf on windows for /js/**'
- task: NodeTool@0
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
- task: DownloadPipelineArtifact@2
inputs:
patterns: '${{ parameters.BuildConfig }}_*/**/*'
diff --git a/tools/ci_build/github/azure-pipelines/templates/win-web-multi-browsers.yml b/tools/ci_build/github/azure-pipelines/templates/win-web-multi-browsers.yml
index 723567389579d..f7876f15029c1 100644
--- a/tools/ci_build/github/azure-pipelines/templates/win-web-multi-browsers.yml
+++ b/tools/ci_build/github/azure-pipelines/templates/win-web-multi-browsers.yml
@@ -33,7 +33,7 @@ jobs:
displayName: 'Checkout submodule onnx'
- task: NodeTool@0
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
- task: DownloadPipelineArtifact@2
inputs:
patterns: 'Release_*/**/*'
diff --git a/tools/ci_build/github/azure-pipelines/win-ci-fuzz-testing.yml b/tools/ci_build/github/azure-pipelines/win-ci-fuzz-testing.yml
index 0eb78412de418..58c0b8d353582 100644
--- a/tools/ci_build/github/azure-pipelines/win-ci-fuzz-testing.yml
+++ b/tools/ci_build/github/azure-pipelines/win-ci-fuzz-testing.yml
@@ -27,7 +27,7 @@ jobs:
- task: NodeTool@0
inputs:
- versionSpec: '16.x'
+ versionSpec: '18.x'
- task: BatchScript@1
displayName: 'setup env'
diff --git a/tools/ci_build/github/linux/build_cuda_c_api_package.sh b/tools/ci_build/github/linux/build_cuda_c_api_package.sh
index 730c295e967b1..5ce1c2d2e80f8 100755
--- a/tools/ci_build/github/linux/build_cuda_c_api_package.sh
+++ b/tools/ci_build/github/linux/build_cuda_c_api_package.sh
@@ -1,4 +1,7 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
export CFLAGS="-Wp,-D_FORTIFY_SOURCE=2 -Wp,-D_GLIBCXX_ASSERTIONS -fstack-protector-strong -fstack-clash-protection -fcf-protection -O3 -Wl,--strip-all"
export CXXFLAGS="-Wp,-D_FORTIFY_SOURCE=2 -Wp,-D_GLIBCXX_ASSERTIONS -fstack-protector-strong -fstack-clash-protection -fcf-protection -O3 -Wl,--strip-all"
docker run --gpus all -e CFLAGS -e CXXFLAGS -e NVIDIA_VISIBLE_DEVICES=all --rm --volume \
diff --git a/tools/ci_build/github/linux/build_linux_arm64_python_package.sh b/tools/ci_build/github/linux/build_linux_arm64_python_package.sh
index 516f320cd64c4..a1a0d428c68f9 100755
--- a/tools/ci_build/github/linux/build_linux_arm64_python_package.sh
+++ b/tools/ci_build/github/linux/build_linux_arm64_python_package.sh
@@ -1,4 +1,7 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
set -e -x
# This script invokes build.py
diff --git a/tools/ci_build/github/linux/build_yocto.sh b/tools/ci_build/github/linux/build_yocto.sh
index e948a105c0cce..fab5173353d20 100755
--- a/tools/ci_build/github/linux/build_yocto.sh
+++ b/tools/ci_build/github/linux/build_yocto.sh
@@ -1,4 +1,7 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
set -e -o -x
SCRIPT_DIR="$( dirname "${BASH_SOURCE[0]}" )"
TARGET_FOLDER="/datadrive/ARM"
diff --git a/tools/ci_build/github/linux/copy_strip_binary.sh b/tools/ci_build/github/linux/copy_strip_binary.sh
index 5832b0ec2ee65..af8f0ecb9c125 100755
--- a/tools/ci_build/github/linux/copy_strip_binary.sh
+++ b/tools/ci_build/github/linux/copy_strip_binary.sh
@@ -1,4 +1,6 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
set -e -o -x
while getopts r:a:l:c:s:t: parameter_Option
@@ -44,6 +46,7 @@ fi
cp $SOURCE_DIR/include/onnxruntime/core/session/onnxruntime_c_api.h $BINARY_DIR/$ARTIFACT_NAME/include
cp $SOURCE_DIR/include/onnxruntime/core/session/onnxruntime_cxx_api.h $BINARY_DIR/$ARTIFACT_NAME/include
cp $SOURCE_DIR/include/onnxruntime/core/session/onnxruntime_cxx_inline.h $BINARY_DIR/$ARTIFACT_NAME/include
+cp $SOURCE_DIR/include/onnxruntime/core/session/onnxruntime_float16.h $BINARY_DIR/$ARTIFACT_NAME/include
cp $SOURCE_DIR/include/onnxruntime/core/providers/cpu/cpu_provider_factory.h $BINARY_DIR/$ARTIFACT_NAME/include
cp $SOURCE_DIR/include/onnxruntime/core/session/onnxruntime_session_options_config_keys.h $BINARY_DIR/$ARTIFACT_NAME/include
cp $SOURCE_DIR/include/onnxruntime/core/session/onnxruntime_run_options_config_keys.h $BINARY_DIR/$ARTIFACT_NAME/include
diff --git a/tools/ci_build/github/linux/create_package.sh b/tools/ci_build/github/linux/create_package.sh
index ed012a5abcc6f..305d261838bb1 100755
--- a/tools/ci_build/github/linux/create_package.sh
+++ b/tools/ci_build/github/linux/create_package.sh
@@ -1,4 +1,6 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
set -e
SCRIPT=`realpath $0`
SCRIPT_DIR=`dirname $SCRIPT`
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda11_8_tensorrt8_6 b/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda11_8_tensorrt8_6
new file mode 100644
index 0000000000000..cdf504c8e3b03
--- /dev/null
+++ b/tools/ci_build/github/linux/docker/Dockerfile.package_ubi8_cuda11_8_tensorrt8_6
@@ -0,0 +1,45 @@
+# --------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------
+# Dockerfile to Test ONNX Runtime on UBI8 with CUDA 11.8 and TensorRT 8.6
+
+# Build base image with required system packages
+FROM nvidia/cuda:11.8.0-cudnn8-devel-ubi8 AS base
+
+ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${PATH}
+
+RUN dnf install -y bash wget &&\
+ dnf clean dbcache
+
+# Install python3
+RUN dnf install -y \
+ python3.8 \
+ python38-pip \
+ python38-wheel &&\
+ cd /usr/local/bin &&\
+ ln -s /usr/bin/python3 python3.8 &&\
+ ln -s /usr/bin/pip3 pip3.8;
+
+RUN pip3 install --upgrade pip
+RUN pip3 install setuptools>=41.0.0
+
+# Install TensorRT
+RUN dnf install -y libnvinfer8 libnvonnxparsers8 libnvparsers8 libnvinfer-plugin8 libnvinfer-lean8 libnvinfer-vc-plugin8 libnvinfer-dispatch8
+RUN v="8.6.1.6-1+cuda11.8" &&\
+ dnf downgrade -y libnvinfer8-${v} libnvinfer8-${v} libnvonnxparsers8-${v} libnvparsers8-${v} libnvinfer-plugin8-${v} libnvinfer-lean8-${v} libnvinfer-vc-plugin8-${v} libnvinfer-dispatch8-${v} &&\
+ dnf install -y dnf-plugin-versionlock &&\
+ dnf versionlock libnvinfer8 libnvonnxparsers8 libnvparsers8 libnvinfer-plugin8 libnvinfer-lean8 libnvinfer-vc-plugin8 libnvinfer-dispatch8
+RUN dnf clean dbcache
+
+
+ADD scripts /tmp/scripts
+RUN cd /tmp/scripts && /tmp/scripts/install_dotnet.sh && /tmp/scripts/install_java.sh && rm -rf /tmp/scripts
+
+# Build final image from base.
+FROM base as final
+ARG BUILD_USER=onnxruntimedev
+ARG BUILD_UID=1000
+RUN adduser --uid $BUILD_UID $BUILD_USER
+WORKDIR /home/$BUILD_USER
+USER $BUILD_USER
diff --git a/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_cuda11_8_tensorrt8_6 b/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_cuda11_8_tensorrt8_6
new file mode 100644
index 0000000000000..c211fa9b9e2b8
--- /dev/null
+++ b/tools/ci_build/github/linux/docker/Dockerfile.package_ubuntu_cuda11_8_tensorrt8_6
@@ -0,0 +1,53 @@
+# --------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+# --------------------------------------------------------------
+# Dockerfile to run ONNXRuntime with TensorRT integration
+
+# Build base image with required system packages
+FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu20.04 AS base
+
+# The local directory into which to build and install CMAKE
+ARG ONNXRUNTIME_LOCAL_CODE_DIR=/code
+
+ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/src/tensorrt/bin:${ONNXRUNTIME_LOCAL_CODE_DIR}/cmake-3.27.3-linux-x86_64/bin:/opt/miniconda/bin:${PATH}
+ENV DEBIAN_FRONTEND=noninteractive
+
+RUN apt-get update &&\
+ apt-get install -y sudo git bash unattended-upgrades wget
+RUN unattended-upgrade
+
+# Install python3
+RUN apt-get install -y --no-install-recommends \
+ python3 \
+ python3-pip \
+ python3-dev \
+ python3-wheel &&\
+ cd /usr/local/bin &&\
+ ln -s /usr/bin/python3 python &&\
+ ln -s /usr/bin/pip3 pip;
+
+RUN pip install --upgrade pip
+RUN pip install setuptools>=41.0.0
+
+# Install TensorRT
+RUN v="8.6.1.6-1+cuda11.8" &&\
+ apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub &&\
+ apt-get update &&\
+ sudo apt-get install -y libnvinfer8=${v} libnvonnxparsers8=${v} libnvparsers8=${v} libnvinfer-plugin8=${v} libnvinfer-lean8=${v} libnvinfer-vc-plugin8=${v} libnvinfer-dispatch8=${v}\
+ libnvinfer-headers-dev=${v} libnvinfer-headers-plugin-dev=${v} libnvinfer-dev=${v} libnvonnxparsers-dev=${v} libnvparsers-dev=${v} libnvinfer-plugin-dev=${v} libnvinfer-lean-dev=${v} libnvinfer-vc-plugin-dev=${v} libnvinfer-dispatch-dev=${v}\
+ python3-libnvinfer=${v} libnvinfer-samples=${v} tensorrt-dev=${v} tensorrt-libs=${v}
+
+# Install Valgrind
+RUN apt-get install -y valgrind
+
+ADD scripts /tmp/scripts
+RUN cd /tmp/scripts && /tmp/scripts/install_dotnet.sh && rm -rf /tmp/scripts
+
+# Build final image from base.
+FROM base as final
+ARG BUILD_USER=onnxruntimedev
+ARG BUILD_UID=1000
+RUN adduser --uid $BUILD_UID $BUILD_USER
+WORKDIR /home/$BUILD_USER
+USER $BUILD_USER
diff --git a/tools/ci_build/github/linux/docker/inference/x64/python/cpu/scripts/requirements.txt b/tools/ci_build/github/linux/docker/inference/x64/python/cpu/scripts/requirements.txt
index c0c6505ca010d..8a9c4dac1dd58 100644
--- a/tools/ci_build/github/linux/docker/inference/x64/python/cpu/scripts/requirements.txt
+++ b/tools/ci_build/github/linux/docker/inference/x64/python/cpu/scripts/requirements.txt
@@ -6,5 +6,5 @@ setuptools>=41.4.0
wheel
git+http://github.com/onnx/onnx.git@e2525550194ce3d8a2c4a3af451c9d9b3ae6650e#egg=onnx
protobuf==3.20.2
-sympy==1.10.1
+sympy==1.12
flatbuffers
diff --git a/tools/ci_build/github/linux/docker/scripts/install_dotnet.sh b/tools/ci_build/github/linux/docker/scripts/install_dotnet.sh
new file mode 100755
index 0000000000000..d89a5e84c1ac1
--- /dev/null
+++ b/tools/ci_build/github/linux/docker/scripts/install_dotnet.sh
@@ -0,0 +1,24 @@
+#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+set -e -x
+
+if [ -f /etc/redhat-release ]; then
+ rpm -Uvh https://packages.microsoft.com/config/centos/7/packages-microsoft-prod.rpm
+ yum install -y dotnet-sdk-6.0
+elif [ -f /etc/os-release ]; then
+ # Get Ubuntu version
+ declare repo_version=$(if command -v lsb_release &> /dev/null; then lsb_release -r -s; else grep -oP '(?<=^VERSION_ID=).+' /etc/os-release | tr -d '"'; fi)
+ # Download Microsoft signing key and repository
+ wget https://packages.microsoft.com/config/ubuntu/$repo_version/packages-microsoft-prod.deb -O packages-microsoft-prod.deb
+ # Install Microsoft signing key and repository
+ dpkg -i packages-microsoft-prod.deb
+ # Clean up
+ rm packages-microsoft-prod.deb
+ # Update packages
+ apt-get update && apt-get install -y dotnet-sdk-6.0
+else
+ echo "Unsupported OS"
+ exit 1
+fi
diff --git a/tools/ci_build/github/linux/docker/scripts/install_java.sh b/tools/ci_build/github/linux/docker/scripts/install_java.sh
new file mode 100755
index 0000000000000..d11e29f693b8b
--- /dev/null
+++ b/tools/ci_build/github/linux/docker/scripts/install_java.sh
@@ -0,0 +1,12 @@
+#!/bin/bash
+set -e -x
+
+if [ -f /etc/redhat-release ]; then
+ dnf install -y java-11-openjdk-devel \
+ && dnf clean dbcache
+elif [ -f /etc/os-release ]; then
+ apt-get update && apt-get install -y openjdk-11-jdk
+else
+ echo "Unsupported OS"
+ exit 1
+fi
diff --git a/tools/ci_build/github/linux/docker/scripts/manylinux/install_deps.sh b/tools/ci_build/github/linux/docker/scripts/manylinux/install_deps.sh
index d0aea8b4489a1..e569e58d549f2 100755
--- a/tools/ci_build/github/linux/docker/scripts/manylinux/install_deps.sh
+++ b/tools/ci_build/github/linux/docker/scripts/manylinux/install_deps.sh
@@ -13,6 +13,9 @@ else
exit 1
fi
+# Install dotnet
+source $(cd "$(dirname "${BASH_SOURCE[0]}")/.." &> /dev/null && pwd)/install_dotnet.sh
+
if [ ! -d "/opt/conda/bin" ]; then
PYTHON_EXES=("/opt/python/cp38-cp38/bin/python3.8" "/opt/python/cp39-cp39/bin/python3.9" "/opt/python/cp310-cp310/bin/python3.10" "/opt/python/cp311-cp311/bin/python3.11")
else
diff --git a/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt b/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt
index c8ff7a804e1df..6b8003c01c24d 100644
--- a/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt
+++ b/tools/ci_build/github/linux/docker/scripts/manylinux/requirements.txt
@@ -6,6 +6,6 @@ setuptools>=41.4.0
wheel
git+http://github.com/onnx/onnx.git@e2525550194ce3d8a2c4a3af451c9d9b3ae6650e#egg=onnx
protobuf==3.20.2
-sympy==1.10.1
+sympy==1.12
flatbuffers
neural-compressor>=2.2.1
diff --git a/tools/ci_build/github/linux/docker/scripts/requirements.txt b/tools/ci_build/github/linux/docker/scripts/requirements.txt
index 2248652c98043..9dbe856753faa 100644
--- a/tools/ci_build/github/linux/docker/scripts/requirements.txt
+++ b/tools/ci_build/github/linux/docker/scripts/requirements.txt
@@ -7,7 +7,7 @@ setuptools>=41.4.0
wheel>=0.35.1
git+http://github.com/onnx/onnx.git@e2525550194ce3d8a2c4a3af451c9d9b3ae6650e#egg=onnx
argparse
-sympy==1.10.1
+sympy==1.12
flatbuffers
protobuf==3.20.2
packaging
diff --git a/tools/ci_build/github/linux/extract_and_bundle_gpu_package.sh b/tools/ci_build/github/linux/extract_and_bundle_gpu_package.sh
index 9492b7bcf59a6..a442a93203174 100755
--- a/tools/ci_build/github/linux/extract_and_bundle_gpu_package.sh
+++ b/tools/ci_build/github/linux/extract_and_bundle_gpu_package.sh
@@ -1,4 +1,6 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
set -e -o -x
while getopts a: parameter_Option
diff --git a/tools/ci_build/github/linux/java_copy_strip_binary.sh b/tools/ci_build/github/linux/java_copy_strip_binary.sh
index 329c1b0ab9b9e..8004e37a73fa0 100755
--- a/tools/ci_build/github/linux/java_copy_strip_binary.sh
+++ b/tools/ci_build/github/linux/java_copy_strip_binary.sh
@@ -1,4 +1,6 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
set -e -o -x
while getopts r:a:l:n:c:h:v: parameter_Option
diff --git a/tools/ci_build/github/linux/run_python_dockerbuild.sh b/tools/ci_build/github/linux/run_python_dockerbuild.sh
index 18ac6482827f9..2ab01eacada34 100755
--- a/tools/ci_build/github/linux/run_python_dockerbuild.sh
+++ b/tools/ci_build/github/linux/run_python_dockerbuild.sh
@@ -1,4 +1,7 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
set -e -x
BUILD_CONFIG="Release"
diff --git a/tools/ci_build/github/linux/run_python_dockertest.sh b/tools/ci_build/github/linux/run_python_dockertest.sh
new file mode 100755
index 0000000000000..7b080a9047d9a
--- /dev/null
+++ b/tools/ci_build/github/linux/run_python_dockertest.sh
@@ -0,0 +1,31 @@
+#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+set -e -x
+BUILD_CONFIG="Release"
+
+while getopts "i:d:x:c:" parameter_Option
+do case "${parameter_Option}"
+in
+i) DOCKER_IMAGE=${OPTARG};;
+d) DEVICE=${OPTARG};;
+c) BUILD_CONFIG=${OPTARG};;
+esac
+done
+
+if [ $DEVICE = "GPU" ]; then
+ ADDITIONAL_DOCKER_PARAMETER="--gpus all"
+fi
+
+mkdir -p $HOME/.onnx
+docker run --rm \
+ --volume /data/onnx:/data/onnx:ro \
+ --volume $BUILD_SOURCESDIRECTORY:/onnxruntime_src \
+ --volume $BUILD_BINARIESDIRECTORY:/build \
+ --volume /data/models:/build/models:ro \
+ --volume $HOME/.onnx:/home/onnxruntimedev/.onnx \
+ -w /onnxruntime_src \
+ -e NIGHTLY_BUILD \
+ -e BUILD_BUILDNUMBER \
+ $ADDITIONAL_DOCKER_PARAMETER \
+ $DOCKER_IMAGE tools/ci_build/github/linux/run_python_tests.sh -d $DEVICE -c $BUILD_CONFIG
diff --git a/tools/ci_build/github/linux/run_python_tests.sh b/tools/ci_build/github/linux/run_python_tests.sh
index 90362a3315e06..cecb790b19b2a 100755
--- a/tools/ci_build/github/linux/run_python_tests.sh
+++ b/tools/ci_build/github/linux/run_python_tests.sh
@@ -15,7 +15,8 @@ c) BUILD_CONFIG=${OPTARG};;
esac
done
-cd $BUILD_BINARIESDIRECTORY
+export PATH=/opt/python/cp38-cp38/bin:$PATH
+cd /build
files=(whl/*.whl)
FILE_NAME="${files[0]}"
FILE_NAME=$(basename $FILE_NAME)
@@ -23,7 +24,7 @@ PYTHON_PACKAGE_NAME=$(echo "$FILE_NAME" | cut -f 1 -d '-')
echo "Package name:$PYTHON_PACKAGE_NAME"
-BUILD_ARGS="--build_dir $BUILD_BINARIESDIRECTORY --config $BUILD_CONFIG --test --skip_submodule_sync --parallel --enable_lto --build_wheel "
+BUILD_ARGS="--build_dir /build --config $BUILD_CONFIG --test --skip_submodule_sync --parallel --enable_lto --build_wheel "
ARCH=$(uname -m)
@@ -34,20 +35,15 @@ fi
if [ $BUILD_DEVICE == "GPU" ]; then
BUILD_ARGS="$BUILD_ARGS --use_cuda --use_tensorrt --cuda_version=11.8 --tensorrt_home=/usr --cuda_home=/usr/local/cuda-11.8 --cudnn_home=/usr/local/cuda-11.8"
fi
-# We assume the machine doesn't have gcc and python development header files, so we don't build onnxruntime from source
-sudo rm -rf /build /onnxruntime_src
-sudo ln -s $BUILD_SOURCESDIRECTORY /onnxruntime_src
-python3 -m pip uninstall -y $PYTHON_PACKAGE_NAME ort-nightly-gpu ort-nightly onnxruntime onnxruntime-gpu onnxruntime-training onnxruntime-directml ort-nightly-directml onnx -qq
+python3 -m pip install --upgrade pip
# Install the packages that are needed for installing the onnxruntime python package
-python3 -m pip install -r $BUILD_BINARIESDIRECTORY/$BUILD_CONFIG/requirements.txt
+python3 -m pip install -r /build/$BUILD_CONFIG/requirements.txt
# Install the packages that are needed for running test scripts
-# Install the latest ONNX release which may contain not fixed bugs. However, it is what most people use.
-python3 -m pip install onnx pytest
+python3 -m pip install pytest
# The "--no-index" flag is crucial. The local whl folder is just an additional source. Pypi's doc says "there is no
# ordering in the locations that are searched" if we don't disable the default one with "--no-index"
-python3 -m pip install --no-index --find-links $BUILD_BINARIESDIRECTORY/whl $PYTHON_PACKAGE_NAME
-ln -s /data/models $BUILD_BINARIESDIRECTORY
-cd $BUILD_BINARIESDIRECTORY/$BUILD_CONFIG
+python3 -m pip install --no-index --find-links /build/whl $PYTHON_PACKAGE_NAME
+cd /build/$BUILD_CONFIG
# Restore file permissions
xargs -a perms.txt chmod a+x
-python3 $BUILD_SOURCESDIRECTORY/tools/ci_build/build.py $BUILD_ARGS --ctest_path ''
+python3 /onnxruntime_src/tools/ci_build/build.py $BUILD_ARGS --ctest_path ''
diff --git a/tools/ci_build/github/linux/test_custom_ops_pytorch_export.sh b/tools/ci_build/github/linux/test_custom_ops_pytorch_export.sh
index 56f5ff9f9eac0..ee4339c24d399 100755
--- a/tools/ci_build/github/linux/test_custom_ops_pytorch_export.sh
+++ b/tools/ci_build/github/linux/test_custom_ops_pytorch_export.sh
@@ -1,4 +1,6 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
pip3 install --user --upgrade pip
diff --git a/tools/ci_build/github/linux/upload_ortsrv_binaries.sh b/tools/ci_build/github/linux/upload_ortsrv_binaries.sh
index 9d6f9406e4181..dcbea27847a8a 100755
--- a/tools/ci_build/github/linux/upload_ortsrv_binaries.sh
+++ b/tools/ci_build/github/linux/upload_ortsrv_binaries.sh
@@ -1,4 +1,6 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
set -e -o -x
while getopts a:r:i:c:p:b: parameter_Option
diff --git a/tools/ci_build/github/linux/yocto_build_toolchain.sh b/tools/ci_build/github/linux/yocto_build_toolchain.sh
index 26d4f583487c6..a4e7fe7a38255 100755
--- a/tools/ci_build/github/linux/yocto_build_toolchain.sh
+++ b/tools/ci_build/github/linux/yocto_build_toolchain.sh
@@ -1,4 +1,6 @@
#!/bin/bash
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
set -e
YOCTO_VERSION="4.19"
diff --git a/winml/test/model/model_tests.cpp b/winml/test/model/model_tests.cpp
index 43b904ce77ad0..b2dd331ccef2c 100644
--- a/winml/test/model/model_tests.cpp
+++ b/winml/test/model/model_tests.cpp
@@ -379,13 +379,6 @@ std::string GetFullNameOfTest(ITestCase* testCase, winml::LearningModelDeviceKin
name += tokenizedModelPath[tokenizedModelPath.size() - 2] += "_"; // model name
name += tokenizedModelPath[tokenizedModelPath.size() - 3]; // opset version
- // To introduce models from model zoo, the model path is structured like this "///?.onnx"
- std::string source = tokenizedModelPath[tokenizedModelPath.size() - 4];
- // `models` means the root of models, to be ompatible with the old structure, that is, the source name is empty.
- if (source != "models") {
- name += "_" + source;
- }
-
std::replace_if(
name.begin(), name.end(), [](char c) { return !google::protobuf::ascii_isalnum(c); }, '_'
);
@@ -404,6 +397,13 @@ std::string GetFullNameOfTest(ITestCase* testCase, winml::LearningModelDeviceKin
ModifyNameIfDisabledTest(/*inout*/ name, deviceKind);
}
+ // To introduce models from model zoo, the model path is structured like this "///?.onnx"
+ std::string source = tokenizedModelPath[tokenizedModelPath.size() - 4];
+ // `models` means the root of models, to be ompatible with the old structure, that is, the source name is empty.
+ if (source != "models") {
+ name += "_" + source;
+ }
+
return name;
}