| /external/tensorflow/tensorflow/core/framework/ |
| 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 …]
|
| 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 …]
|
| /external/tensorflow/tensorflow/core/profiler/ |
| 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 …]
|
| 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 …]
|
| /external/perfetto/protos/perfetto/trace/android/ |
| 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 …]
|
| /external/tensorflow/tensorflow/core/grappler/costs/ |
| D | op_performance_data.proto | 7 http://www.apache.org/licenses/LICENSE-2.0
29 int64 intra_op_parallelism = 1;
77 // The node name (optional). Makes it easier to associate the performance data
78 // with a specific graph node.
79 string node = 5; field
81 // Temporary memory used by this node (in bytes).
82 int64 temporary_memory_size = 2;
85 int64 compute_cost = 3;
88 int64 compute_time = 6;
91 int64 memory_time = 7;
[all …]
|
| /external/perfetto/protos/perfetto/metrics/android/ |
| D | monitor_contention_metric.proto | 8 * http://www.apache.org/licenses/LICENSE-2.0
25 message Node { message
27 optional int64 node_parent_id = 1;
28 optional int64 node_child_id = 24;
29 optional int64 node_id = 2;
30 optional int64 ts = 3;
31 optional int64 dur = 4;
32 optional int64 monotonic_dur = 25;
56 optional int64 binder_reply_ts = 17;
62 optional int64 thread_state_dur = 2;
[all …]
|
| /external/googleapis/google/cloud/automl/v1/ |
| 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 …]
|
| /external/google-cloud-java/java-automl/proto-google-cloud-automl-v1/src/main/proto/google/cloud/automl/v1/ |
| 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 …]
|
| /external/swiftshader/third_party/llvm-10.0/llvm/lib/IR/ |
| 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 …]
|
| /external/googleapis/google/cloud/automl/v1beta1/ |
| 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 …]
|
| /external/google-cloud-java/java-automl/proto-google-cloud-automl-v1beta1/src/main/proto/google/cloud/automl/v1beta1/ |
| 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 …]
|
| /external/llvm/lib/IR/ |
| D | MDBuilder.cpp | 1 //===---- llvm/MDBuilder.cpp - Builder for LLVM metadata ------------------===//
8 //===----------------------------------------------------------------------===//
13 //===----------------------------------------------------------------------===//
83 // To ensure uniqueness the root node is self-referential. in createAnonymousAARoot()
94 // !0 = metadata !{} <- dummy in createAnonymousAARoot()
95 // !1 = metadata !{metadata !0} <- root in createAnonymousAARoot()
96 // Replace the dummy operand with the root node itself and delete the dummy. in createAnonymousAARoot()
97 Root->replaceOperandWith(0, Root); in createAnonymousAARoot()
100 // !1 = metadata !{metadata !1} <- self-referential root in createAnonymousAARoot()
108 /// \brief Return metadata for a non-root TBAA node with the given name,
[all …]
|
| /external/tensorflow/tensorflow/core/profiler/internal/ |
| D | tfprof_show_multi.cc | 7 http://www.apache.org/licenses/LICENSE-2.0
34 return ShowInternal(opts, &timeline)->proto(); in Show()
38 absl::PrintF("%s%s", prefix, ret->formatted_str); in Show()
43 prefix + ret->formatted_str); in Show()
52 return ret->proto(); in Show()
56 bool TFMultiShow::ShouldShow(const ShowMultiNode* node, const Options& opts, in ShouldShow() argument
59 if (node->name() == kTFProfRoot) return true; in ShouldShow()
61 // TODO(xpan): Think more carefully about node filtering in code view. in ShouldShow()
68 if (node->proto().total_requested_bytes() < opts.min_bytes || in ShouldShow()
69 node->proto().total_peak_bytes() < opts.min_peak_bytes || in ShouldShow()
[all …]
|
| 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 …]
|
| /external/swiftshader/third_party/llvm-16.0/llvm/lib/IR/ |
| 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 …]
|
| /external/googleapis/google/cloud/dataproc/v1/ |
| 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 …]
|
| /external/tensorflow/tensorflow/compiler/xrt/ |
| D | xrt.proto | 34 // The number of "model-parallel" cores per replica. If this is
42 // The arg/result shapes for each core of a model-parallel
44 // single-core computation.
63 // stateful_input_indices is only useful when using XRT-compiled
94 // Node in a tree describing a tuple constructed from input handles. A
95 // node is an internal node if tuples is non-empty, in which case
96 // input_index and release_input_handle are ignored. Otherwise a node
97 // is a leaf node. Each leaf XLATupleNode is the index of an input
122 int64 run_id = 3;
131 // Which model-parallel computation to run from the compiled bundle.
[all …]
|
| /external/angle/third_party/glslang/src/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 …]
|
| /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 …]
|
| /external/tensorflow/tensorflow/core/ops/ |
| D | nccl_ops.cc | 7 http://www.apache.org/licenses/LICENSE-2.0
28 .Attr("T: {half, float, float64, int32, int64}")
40 .Attr("T: {half, float, float64, int32, int64}")
48 .Attr("T: {half, float, float64, int32, int64}")
54 Replacement node for NcclReduce.
57 The graph should be constructed so that 'num_devices-1' devices run
71 .Attr("T: {half, float, float64, int32, int64}")
77 Replacement node for NcclReduce.
81 The graph should be constructed so that 'num_devices-1' devices run
97 .Attr("T: {half, float, float64, int32, int64}")
[all …]
|
| /external/tensorflow/tensorflow/core/kernels/mkl/ |
| D | mkl_conv_ops_test.cc | 7 http://www.apache.org/licenses/LICENSE-2.0
31 // TODO(intel-tf): Add numerical tests that will compare results of default
34 // -------------------------------------------------------------------------- //
36 // -------------------------------------------------------------------------- //
108 Node* input = test::graph::Constant(graph, input_t, "input"); in DefaultConv2D()
109 Node* filter = test::graph::Constant(graph, filter_t, "filter"); in DefaultConv2D()
111 Node* conv2d; in DefaultConv2D()
112 TF_CHECK_OK(NodeBuilder(graph->NewName("conv_2d"), "Conv2D") in DefaultConv2D()
129 Node* input = test::graph::Constant(graph, input_t, "input"); in MklConv2D()
130 Node* filter = test::graph::Constant(graph, filter_t, "filter"); in MklConv2D()
[all …]
|
| /external/tensorflow/tensorflow/python/ops/ |
| D | state_ops.py | 7 # http://www.apache.org/licenses/LICENSE-2.0
27 # go/tf-wildcard-import
28 # pylint: disable=wildcard-import
30 # pylint: enable=wildcard-import
36 # pylint: disable=protected-access,g-doc-return-or-yield,g-doc-args
61 If non-empty, this variable is placed in the given container.
64 If non-empty, this variable is named in the given bucket
65 with this shared_name. Otherwise, the node name is used instead.
120 Should be from a `Variable` node. May be uninitialized.
143 `float64`, `int64`, `int32`, `uint8`, `uint16`, `int16`, `int8`,
[all …]
|
| /external/tensorflow/tensorflow/lite/kernels/ |
| D | fill.cc | 7 http://www.apache.org/licenses/LICENSE-2.0
39 TfLiteIntArray* output_shape = TfLiteIntArrayCreate(dims->dims->data[0]); in ResizeOutputImpl()
40 for (int i = 0; i < output_shape->size; ++i) { in ResizeOutputImpl()
44 TF_LITE_KERNEL_LOG(context, "Fill dimensions must be >= 0", dims->type); in ResizeOutputImpl()
47 output_shape->data[i] = data; in ResizeOutputImpl()
49 return context->ResizeTensor(context, output, output_shape); in ResizeOutputImpl()
54 switch (dims->type) { in ResizeOutput()
62 "Fill only currently supports int32, int64 for input 0, " in ResizeOutput()
64 dims->type); in ResizeOutput()
71 TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { in Prepare() argument
[all …]
|
| /external/tensorflow/tensorflow/core/common_runtime/ |
| D | eval_const_tensor.cc | 7 http://www.apache.org/licenses/LICENSE-2.0
35 // Returns a Tensor containing the underlyiing constant value of a Node if the
36 // node contains a constant value.
37 Status EvaluateConstantNode(const Node& node, Tensor* output, bool* success) { in EvaluateConstantNode() argument
39 if (node.IsConstant()) { in EvaluateConstantNode()
40 if (output->FromProto(node.def().attr().at("value").tensor())) { in EvaluateConstantNode()
49 Status EvaluateConstantIntFromScalarEdge(const Node& node, int input_idx, in EvaluateConstantIntFromScalarEdge() argument
50 int64* output, bool* success) { in EvaluateConstantIntFromScalarEdge()
54 TF_RETURN_IF_ERROR(node.input_edge(input_idx, &edge)); in EvaluateConstantIntFromScalarEdge()
55 TF_RETURN_IF_ERROR(EvaluateConstantNode(*edge->src(), &scalar, success)); in EvaluateConstantIntFromScalarEdge()
[all …]
|