/aosp_15_r20/prebuilts/go/linux-x86/src/cmd/vendor/github.com/google/pprof/internal/graph/ |
D | graph.go | 7 // http://www.apache.org/licenses/LICENSE-2.0 33 …javaRegExp = regexp.MustCompile(`^(?:[a-z]\w*\.)*([A-Z][\w\$]*\.(?:<init>|[a-z][\w\$]*(?:\$\d+)?))… 36 goRegExp = regexp.MustCompile(`^(?:[\w\-\.]+\/)+([^.]+\..+)`) 38 goVerRegExp = regexp.MustCompile(`^(.*?)/v(?:[2-9]|[1-9][0-9]+)([./].*)$`) 42 // -symbolize=demangle=templates flag is used, they will not be. 44 …cppRegExp = regexp.MustCompile(`^(?:[_a-zA-Z]\w*::)+(_*[A-Z]\w*::~?[_a-zA-Z]\w*(?:<… 56 SampleValue func(s []int64) int64 // Function to compute the value of a sample 57 …SampleMeanDivisor func(s []int64) int64 // Function to compute the divisor for mean graphs, o… 58 FormatTag func(int64, string) string // Function to format a sample tag value into a string 65 KeptNodes NodeSet // If non-nil, only use nodes in this set [all …]
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/aosp_15_r20/prebuilts/go/linux-x86/src/internal/profile/ |
D | graph.go | 7 // http://www.apache.org/licenses/LICENSE-2.0 28 SampleValue func(s []int64) int64 // Function to compute the value of a sample 29 SampleMeanDivisor func(s []int64) int64 // Function to compute the divisor for mean graphs, or nil 33 KeptNodes NodeSet // If non-nil, only use nodes in this set 37 type Nodes []*Node 39 // Node is an entry on a profiling report. It represents a unique 41 type Node struct { struct 42 // Info describes the source location associated to this node. 45 // Function represents the function that this node belongs to. On 46 // graphs with sub-function resolution (eg line number or [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/core/framework/ |
H A D | model.proto | 8 // Class of a node in the performance model. 31 // General representation of a node in the model. 32 message Node { message 33 // Unique node ID. 34 int64 id = 1; 36 // Human-readable name of the node. 39 // An indication whether autotuning is enabled for this node. 42 // The number of bytes stored in this node's buffer. 43 int64 buffered_bytes = 4; 45 // The number of elements stored in this node's buffer. [all …]
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H A D | step_stats.proto | 14 // An allocation/de-allocation operation performed by the allocator. 17 int64 alloc_micros = 1; 18 // Number of bytes allocated, or de-allocated if negative. 19 int64 alloc_bytes = 2; 24 // These are per-node allocator memory stats. 25 int64 total_bytes = 2; 26 int64 peak_bytes = 3; 28 int64 live_bytes = 4; 34 int64 allocator_bytes_in_use = 5; 37 // Output sizes recorded for a single execution of a graph node. [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/core/profiler/ |
H A D | tfprof_output.proto | 10 // Flatten tensor in row-major. 13 repeated int64 value_int64 = 3; 17 // A node in TensorFlow graph. Used by scope/graph view. 24 // A node can be defined once but run multiple times in tf.while_loop. 26 int64 run_count = 21; 27 int64 exec_micros = 2; 28 int64 accelerator_exec_micros = 17; 29 int64 cpu_exec_micros = 18; 32 int64 requested_bytes = 3; 34 int64 peak_bytes = 24; [all …]
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H A D | tfprof_log.proto | 14 int64 file_id = 6; 19 int64 function_id = 7; 22 int64 line_id = 8; 34 int64 float_ops = 2; 47 map<int64, string> id_to_string = 2; 55 map<int64, ProfileNode> nodes = 1; 62 repeated int64 steps = 3; 66 map<int64, string> id_to_string = 4; 70 // graph node name. 74 // A unique id for the node. [all …]
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/aosp_15_r20/prebuilts/go/linux-x86/src/cmd/compile/internal/compare/ |
D | compare.go | 2 // Use of this source code is governed by a BSD-style 24 // Memrun finds runs of struct fields for which memory-only algs are appropriate. 28 func Memrun(t *types.Type, start int) (size int64, next int) { 36 if types.IsPaddedField(t, next-1) { 39 // Also, stop before a blank or non-memory field. 47 if off := t.Field(start).Offset; off&(align-1) != 0 { 52 size := t.Field(next).End() - t.Field(start).Offset 58 return t.Field(next-1).End() - t.Field(start).Offset, next 85 // memory-only fields in the struct. 86 func EqStructCost(t *types.Type) int64 { [all …]
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/aosp_15_r20/prebuilts/go/linux-x86/src/cmd/compile/internal/walk/ |
D | compare.go | 2 // Use of this source code is governed by a BSD-style 23 func fakePC(n ir.Node) ir.Node { argument 25 // in the calculation of the fakePC for the IR node. 30 binary.Write(hash, binary.LittleEndian, int64(n.Pos().Line())) 31 binary.Write(hash, binary.LittleEndian, int64(n.Pos().Col())) 32 …// We also include the string representation of the node to distinguish autogenerated expression s… 36 return ir.NewInt(base.Pos, int64(hash.Sum32())) 42 func walkCompare(n *ir.BinaryExpr, init *ir.Nodes) ir.Node { 55 // rewrite into types-equal && data-equal. 62 // Preserve side-effects in case of short-circuiting; see #32187. [all …]
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D | switch.go | 2 // Use of this source code is governed by a BSD-style 30 return // Was fatal, but eliminating every possible source of double-walking is hard 57 // with all cases being side-effect free, 58 // use a zero-cost alias of the byte slice. 80 var defaultGoto ir.Node 95 var rtype ir.Node 128 exprname ir.Node // value being switched on 136 lo, hi ir.Node 137 rtype ir.Node // *runtime._type for OEQ node 138 jmp ir.Node [all …]
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D | select.go | 2 // Use of this source code is governed by a BSD-style 33 func walkSelectCases(cases []*ir.CommClause) []ir.Node { 37 // optimization: zero-case select 39 return []ir.Node{mkcallstmt("block")} 42 // optimization: one-case select: single op. 99 // optimization: two-case select but one is default: single non-blocking op. 110 var cond ir.Node 132 as := ir.NewAssignListStmt(r.Pos(), ir.OAS2, []ir.Node{cond, n.Lhs[1]}, []ir.Node{call}) 139 return []ir.Node{r, ir.NewBranchStmt(base.Pos, ir.OBREAK, nil)} 143 ncas-- [all …]
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/aosp_15_r20/out/soong/.intermediates/external/tensorflow/tensorflow_core_proto_cpp_lite/android_arm64_armv8-2a_cortex-a55_static_apex33/gen/proto/tensorflow/core/framework/ |
D | model.pb.h | 45 // Internal implementation detail -- do not use these members. 134 … /* @@protoc_insertion_point(class_definition:tensorflow.data.model.ModelProto.Node.Parameter) */ { 182 GetOwningArena() == other->GetOwningArena()) { in Swap() 184 if (GetOwningArena() == other->GetOwningArena()) { in Swap() 193 GOOGLE_DCHECK(GetOwningArena() == other->GetOwningArena()); in Swap() 197 // implements Message ---------------------------------------------- in Swap() 226 return "tensorflow.data.model.ModelProto.Node.Parameter"; in Swap() 235 // nested types ---------------------------------------------------- in Swap() 237 // accessors ------------------------------------------------------- in Swap() 306 // @@protoc_insertion_point(class_scope:tensorflow.data.model.ModelProto.Node.Parameter) in Swap() [all …]
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D | cost_graph.pb.cc | 31 union { // NOLINT(misc-non-private-member-variables-in-classes) 47 union { // NOLINT(misc-non-private-member-variables-in-classes) 76 union { // NOLINT(misc-non-private-member-variables-in-classes) 90 union { // NOLINT(misc-non-private-member-variables-in-classes) 104 union { // NOLINT(misc-non-private-member-variables-in-classes) 122 // @@protoc_insertion_point(arena_constructor:tensorflow.CostGraphDef.Node.InputInfo) in CostGraphDef_Node_InputInfo() 134 static_cast<size_t>(reinterpret_cast<char*>(&_impl_.preceding_port_) - in CostGraphDef_Node_InputInfo() 136 // @@protoc_insertion_point(copy_constructor:tensorflow.CostGraphDef.Node.InputInfo) in CostGraphDef_Node_InputInfo() 151 // @@protoc_insertion_point(destructor:tensorflow.CostGraphDef.Node.InputInfo) in ~CostGraphDef_Node_InputInfo() 168 // @@protoc_insertion_point(message_clear_start:tensorflow.CostGraphDef.Node.InputInfo) in Clear() [all …]
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D | model.pb.cc | 37 union { // NOLINT(misc-non-private-member-variables-in-classes) 67 union { // NOLINT(misc-non-private-member-variables-in-classes) 78 union { // NOLINT(misc-non-private-member-variables-in-classes) 94 union { // NOLINT(misc-non-private-member-variables-in-classes) 110 union { // NOLINT(misc-non-private-member-variables-in-classes) 158 5, // 0 -> UNKNOWN 159 3, // 1 -> INTERLEAVE_MANY 160 0, // 2 -> ASYNC_INTERLEAVE_MANY 161 4, // 3 -> KNOWN_RATIO 162 1, // 4 -> ASYNC_KNOWN_RATIO [all …]
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D | cost_graph.pb.h | 43 // Internal implementation detail -- do not use these members. 76 …ssageLite /* @@protoc_insertion_point(class_definition:tensorflow.CostGraphDef.Node.InputInfo) */ { 124 GetOwningArena() == other->GetOwningArena()) { in Swap() 126 if (GetOwningArena() == other->GetOwningArena()) { in Swap() 135 GOOGLE_DCHECK(GetOwningArena() == other->GetOwningArena()); in Swap() 139 // implements Message ---------------------------------------------- in Swap() 168 return "tensorflow.CostGraphDef.Node.InputInfo"; in Swap() 177 // nested types ---------------------------------------------------- in Swap() 179 // accessors ------------------------------------------------------- in Swap() 203 // @@protoc_insertion_point(class_scope:tensorflow.CostGraphDef.Node.InputInfo) in Swap() [all …]
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/aosp_15_r20/external/perfetto/protos/perfetto/trace/android/ |
H A D | camera_event.proto | 8 * http://www.apache.org/licenses/LICENSE-2.0 32 optional int64 frame_number = 3; 38 optional int64 request_id = 4; 44 optional int64 request_received_ns = 5; 48 optional int64 request_processing_started_ns = 6; 51 optional int64 start_of_exposure_ns = 7; 54 optional int64 start_of_frame_ns = 8; 57 optional int64 responses_all_sent_ns = 9; 87 // A profiling event corresponding to a single node processing within the camera 92 optional int64 node_id = 1; [all …]
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/aosp_15_r20/external/deqp-deps/glslang/glslang/MachineIndependent/ |
D | intermOut.cpp | 2 // Copyright (C) 2002-2005 3Dlabs Inc. Ltd. 3 // Copyright (C) 2012-2016 LunarG, Inc. 4 // Copyright (C) 2017, 2022-2024 Arm Limited. 62 // Use this class to carry along data from node to node in 75 virtual bool visitBinary(TVisit, TIntermBinary* node); 76 virtual bool visitUnary(TVisit, TIntermUnary* node); 77 virtual bool visitAggregate(TVisit, TIntermAggregate* node); 78 virtual bool visitSelection(TVisit, TIntermSelection* node); 79 virtual void visitConstantUnion(TIntermConstantUnion* node); 80 virtual void visitSymbol(TIntermSymbol* node); [all …]
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/aosp_15_r20/external/swiftshader/third_party/llvm-10.0/llvm/lib/IR/ |
H A D | MDBuilder.cpp | 1 //===---- llvm/MDBuilder.cpp - Builder for LLVM metadata ------------------===// 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 7 //===----------------------------------------------------------------------===// 12 //===----------------------------------------------------------------------===// 70 SmallVector<GlobalValue::GUID, 2> OrderID(Imports->begin(), Imports->end()); in createFunctionEntryCount() 112 Type *Int64 = Type::getInt64Ty(Context); in createCallbackEncoding() local 113 Ops.push_back(createConstant(ConstantInt::get(Int64, CalleeArgNo))); in createCallbackEncoding() 116 Ops.push_back(createConstant(ConstantInt::get(Int64, ArgNo, true))); in createCallbackEncoding() 129 auto *NewCBCalleeIdxAsCM = cast<ConstantAsMetadata>(NewCB->getOperand(0)); in mergeCallbackEncodings() 131 cast<ConstantInt>(NewCBCalleeIdxAsCM->getValue())->getZExtValue(); in mergeCallbackEncodings() [all …]
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/aosp_15_r20/external/googleapis/google/cloud/automl/v1/ |
H A D | image.proto | 7 // http://www.apache.org/licenses/LICENSE-2.0 50 // Optional. The train budget of creating this model, expressed in milli node 51 // hours i.e. 1,000 value in this field means 1 node hour. The actual 57 // and 800,000 milli node hours, inclusive. The default value is 192, 000 59 // `mobile-low-latency-1`, `mobile-versatile-1`, `mobile-high-accuracy-1`, 60 // `mobile-core-ml-low-latency-1`, `mobile-core-ml-versatile-1`, 61 // `mobile-core-ml-high-accuracy-1`, the train budget must be between 1,000 62 // and 100,000 milli node hours, inclusive. The default value is 24, 000 which 64 int64 train_budget_milli_node_hours = 16 [(google.api.field_behavior) = OPTIONAL]; 67 // milli node hours, i.e. 1,000 value in this field means 1 node hour. [all …]
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/aosp_15_r20/external/google-cloud-java/java-automl/proto-google-cloud-automl-v1/src/main/proto/google/cloud/automl/v1/ |
H A D | image.proto | 7 // http://www.apache.org/licenses/LICENSE-2.0 50 // Optional. The train budget of creating this model, expressed in milli node 51 // hours i.e. 1,000 value in this field means 1 node hour. The actual 57 // and 800,000 milli node hours, inclusive. The default value is 192, 000 59 // `mobile-low-latency-1`, `mobile-versatile-1`, `mobile-high-accuracy-1`, 60 // `mobile-core-ml-low-latency-1`, `mobile-core-ml-versatile-1`, 61 // `mobile-core-ml-high-accuracy-1`, the train budget must be between 1,000 62 // and 100,000 milli node hours, inclusive. The default value is 24, 000 which 64 int64 train_budget_milli_node_hours = 16 [(google.api.field_behavior) = OPTIONAL]; 67 // milli node hours, i.e. 1,000 value in this field means 1 node hour. [all …]
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/aosp_15_r20/prebuilts/go/linux-x86/src/text/template/parse/ |
D | node.go | 2 // Use of this source code is governed by a BSD-style 17 // A Node is an element in the parse tree. The interface is trivial. 20 type Node interface { interface 23 // Copy does a deep copy of the Node and all its components. 26 Copy() Node 27 Position() Pos // byte position of start of node in full original input string 29 // It is unexported so all implementations of Node are in this package. 35 // NodeType identifies the type of a parse tree node. 47 // for embedding in a Node. Embedded in all non-trivial Nodes. 54 NodeAction // A non-control action such as a field evaluation. [all …]
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/aosp_15_r20/prebuilts/go/linux-x86/src/cmd/vendor/github.com/google/pprof/internal/report/ |
D | report.go | 7 // http://www.apache.org/licenses/LICENSE-2.0 16 // human-readable report. 72 SampleValue func(s []int64) int64 73 SampleMeanDivisor func(s []int64) int64 137 nodeCutoff := abs64(int64(float64(totalValue) * o.NodeFraction)) 138 edgeCutoff := abs64(int64(float64(totalValue) * o.EdgeFraction)) 144 droppedNodes = len(g.Nodes) - len(nodesKept) 149 droppedNodes = len(g.Nodes) - len(nodesKept) 190 // Find the appropriate units for the smallest non-zero sample 194 var minValue int64 [all …]
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/aosp_15_r20/external/tensorflow/tensorflow/core/profiler/internal/ |
H A D | tfprof_timeline.cc | 7 http://www.apache.org/licenses/LICENSE-2.0 50 event["pid"] = Json::Int64(pid); in CreateEvent() 51 event["tid"] = Json::Int64(tid); in CreateEvent() 52 event["ts"] = Json::Int64(ts); in CreateEvent() 60 event["pid"] = Json::Int64(pid); in EmitPID() 71 event["dur"] = Json::Int64(duration); in EmitRegion() 80 event["id"] = Json::Int64(flow_id); in EmitFlowStart() 88 event["id"] = Json::Int64(flow_id); in EmitFlowEnd() 98 args["Allocator Bytes in Use"] = Json::Int64(bytes); in EmitCounter() 113 for (const string& t : it->second) { in EmitCounter() [all …]
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/aosp_15_r20/external/googleapis/google/cloud/dataproc/v1/ |
H A D | shared.proto | 7 // http://www.apache.org/licenses/LICENSE-2.0 89 // [Duration](https://developers.google.com/protocol-buffers/docs/proto3#json)). 100 // [Duration](https://protobuf.dev/programming-guides/proto3/#json). 118 // workload is running, and then create and manage project-level, per-location 170 // (https://cloud.google.com/dataproc-serverless/pricing)). 176 // (https://cloud.google.com/dataproc-serverless/docs/release-notes) 190 // (https://cloud.google.com/dataproc-serverless/pricing)). 191 int64 milli_dcu_seconds = 1 [(google.api.field_behavior) = OPTIONAL]; 195 // (https://cloud.google.com/dataproc-serverless/pricing)). 196 int64 shuffle_storage_gb_seconds = 2 [(google.api.field_behavior) = OPTIONAL]; [all …]
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/aosp_15_r20/external/pytorch/torch/onnx/ |
H A D | symbolic_helper.py | 1 # mypy: allow-untyped-defs 17 # Monkey-patch graph manipulation methods on Graph, used for the ONNX symbolics 30 # --------------------------------------------------------------------------------- 32 # --------------------------------------------------------------------------------- 58 node = value.node() 59 if node.mustBeNone(): 61 if node.kind() == "onnx::Constant": 62 node_val = _node_get(node, "value") 79 f"ONNX symbolic does not understand the Constant node '{node}' " 83 elif node.kind() == "prim::ListConstruct": [all …]
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/aosp_15_r20/external/googleapis/google/cloud/automl/v1beta1/ |
H A D | image.proto | 7 // http://www.apache.org/licenses/LICENSE-2.0 51 int64 train_budget = 2; 56 int64 train_cost = 3; 63 // * `cloud` - Model to be used via prediction calls to AutoML API. 65 // * `mobile-low-latency-1` - A model that, in addition to providing 70 // * `mobile-versatile-1` - A model that, in addition to providing 74 // * `mobile-high-accuracy-1` - A model that, in addition to providing 80 // * `mobile-core-ml-low-latency-1` - A model that, in addition to providing 85 // * `mobile-core-ml-versatile-1` - A model that, in addition to providing 89 // * `mobile-core-ml-high-accuracy-1` - A model that, in addition to [all …]
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