repo stringlengths 1 152 ⌀ | file stringlengths 14 221 | code stringlengths 501 25k | file_length int64 501 25k | avg_line_length float64 20 99.5 | max_line_length int64 21 134 | extension_type stringclasses 2
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null | pytorch-main/caffe2/core/distributions_stubs.h | #ifndef CAFFE2_CORE_DISTRIBUTIONS_STUBS_H_
#define CAFFE2_CORE_DISTRIBUTIONS_STUBS_H_
#include <c10/macros/Macros.h>
/**
* This file provides distributions compatible with
* ATen/core/DistributionsHelper.h but backed with the std RNG implementation
* instead of the ATen one.
*
* Caffe2 mobile builds currently do... | 2,161 | 27.447368 | 77 | h |
null | pytorch-main/caffe2/core/event.h | #ifndef CAFFE2_CORE_EVENT_H_
#define CAFFE2_CORE_EVENT_H_
#include <chrono>
#include <c10/core/DeviceType.h>
#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
#include "caffe2/proto/caffe2_pb.h"
namespace caffe2 {
constexpr int MaxDeviceTypes =
DeviceTypeProto::PROTO_COMPILE_TIME_MAX_DEVICE_TYPES... | 12,420 | 31.94695 | 80 | h |
null | pytorch-main/caffe2/core/event_cpu.h | #include "caffe2/core/event.h"
#include <atomic>
#include <condition_variable>
namespace caffe2 {
struct CPUEventWrapper {
explicit CPUEventWrapper(const DeviceOption& option)
: status_(EventStatus::EVENT_INITIALIZED) {
CAFFE_ENFORCE(
option.device_type() == PROTO_CPU ||
option.device... | 1,192 | 23.854167 | 66 | h |
null | pytorch-main/caffe2/core/export_c10_op_to_caffe2.h | #pragma once
#include <c10/macros/Macros.h>
#include <c10/util/Registry.h>
#include "caffe2/core/operator.h"
// TODO Also register c10 operators on mobile
#if !defined(CAFFE2_IS_XPLAT_BUILD) && !defined(C10_MOBILE)
#include <ATen/core/dispatch/Dispatcher.h>
#include <ATen/core/ivalue.h>
#include <c10/util/ArrayRef.h>... | 9,539 | 35.136364 | 124 | h |
null | pytorch-main/caffe2/core/export_caffe2_op_to_c10.h | #pragma once
#include <c10/macros/Macros.h>
#if defined(EXPOSE_C2_OPS) || \
!defined(CAFFE2_IS_XPLAT_BUILD) && !defined(C10_MOBILE)
#include <ATen/core/dispatch/OperatorOptions.h>
#include <ATen/core/function_schema.h>
#include <ATen/core/grad_mode.h>
#include <ATen/core/op_registration/op_registration.h>
#includ... | 12,349 | 42.639576 | 130 | h |
null | pytorch-main/caffe2/core/graph.h | #pragma once
#include "caffe2/core/common.h"
#include "caffe2/proto/caffe2_pb.h"
#include "caffe2/utils/proto_utils.h"
#include "caffe2/utils/string_utils.h"
#include <algorithm>
#include <unordered_map>
#include <unordered_set>
namespace caffe2 {
namespace transform {
/**
* Graph representation of an operator.
... | 5,258 | 28.216667 | 80 | h |
null | pytorch-main/caffe2/core/init.h | #ifndef CAFFE2_CORE_INIT_H_
#define CAFFE2_CORE_INIT_H_
#include "caffe2/core/common.h"
#include "caffe2/core/flags.h"
#include "caffe2/core/logging.h"
namespace caffe2 {
namespace internal {
class TORCH_API Caffe2InitializeRegistry {
public:
typedef bool (*InitFunction)(int*, char***);
// Registry() is defined... | 6,496 | 35.094444 | 80 | h |
null | pytorch-main/caffe2/core/memonger.h | #ifndef CAFFE2_CORE_MEMONGER_H_
#define CAFFE2_CORE_MEMONGER_H_
#include <unordered_set>
#include "caffe2/core/common.h"
#include "caffe2/core/workspace.h"
#include "caffe2/proto/caffe2_pb.h"
namespace caffe2 {
// op schema check
TORCH_API void run_schema_check(const NetDef& net);
namespace memonger {
TORCH_API N... | 817 | 23.058824 | 64 | h |
null | pytorch-main/caffe2/core/module.h | /**
* A global dictionary that holds information about what Caffe2 modules have
* been loaded in the current runtime, and also utility functions to load
* modules.
*/
#ifndef CAFFE2_CORE_MODULE_H_
#define CAFFE2_CORE_MODULE_H_
#include <algorithm>
#include <cstdio>
#include <cstdlib>
#include <functional>
#include... | 2,473 | 33.361111 | 79 | h |
null | pytorch-main/caffe2/core/net.h | #ifndef CAFFE2_CORE_NET_H_
#define CAFFE2_CORE_NET_H_
#include <atomic>
#include <climits>
#include <cstddef>
#include <thread> // NOLINT
#include <typeinfo>
#include <unordered_map>
#include <vector>
#include "c10/core/thread_pool.h"
#include "c10/util/Registry.h"
#include "caffe2/core/blob.h"
#include "caffe2/core/... | 4,634 | 25.335227 | 79 | h |
null | pytorch-main/caffe2/core/net_async_base.h | #ifndef CAFFE2_CORE_NET_ASYNC_BASE_H_
#define CAFFE2_CORE_NET_ASYNC_BASE_H_
#include <c10/macros/Macros.h>
#include "c10/core/thread_pool.h"
#include "c10/util/Registry.h"
#include "caffe2/core/common.h"
#include "caffe2/core/net.h"
#include "caffe2/core/net_dag_utils.h"
#include "caffe2/core/prof_dag_counters.h"
#inc... | 7,397 | 30.084034 | 80 | h |
null | pytorch-main/caffe2/core/net_async_scheduling.h | #ifndef CAFFE2_CORE_NET_ASYNC_SCHEDULING_H_
#define CAFFE2_CORE_NET_ASYNC_SCHEDULING_H_
#include "caffe2/core/net_async_base.h"
namespace caffe2 {
class TORCH_API AsyncSchedulingNet : public AsyncNetBase {
public:
AsyncSchedulingNet(
const std::shared_ptr<const NetDef>& net_def,
Workspace* ws);
~Asy... | 993 | 22.116279 | 63 | h |
null | pytorch-main/caffe2/core/net_async_task_future.h | #ifndef CAFFE2_NET_ASYNC_TASK_FUTURE_H
#define CAFFE2_NET_ASYNC_TASK_FUTURE_H
#include <atomic>
#include <condition_variable>
#include <functional>
#include <memory>
#include <mutex>
#include <string>
#include <vector>
namespace caffe2 {
// Represents the state of AsyncTask execution, that can be queried with
// IsC... | 1,925 | 24.012987 | 73 | h |
null | pytorch-main/caffe2/core/net_async_task_graph.h | #ifndef CAFFE2_NET_ASYNC_TASK_GRAPH_H
#define CAFFE2_NET_ASYNC_TASK_GRAPH_H
#include "caffe2/core/net_async_base.h"
#include "caffe2/core/net_async_task.h"
#include "caffe2/core/net_async_task_future.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
// AsyncTaskGraph represents an execution of a net, it owns t... | 2,253 | 27.531646 | 80 | h |
null | pytorch-main/caffe2/core/net_async_tracing.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 5,093 | 26.836066 | 77 | h |
null | pytorch-main/caffe2/core/net_dag_utils.h | #ifndef CAFFE2_CORE_NET_DAG_UTILS_H_
#define CAFFE2_CORE_NET_DAG_UTILS_H_
#include <atomic>
#include <climits>
#include <cstddef>
#include <thread> // NOLINT
#include <typeinfo>
#include <unordered_map>
#include <unordered_set>
#include <vector>
#include "c10/util/Registry.h"
#include "caffe2/core/blob.h"
#include "c... | 2,146 | 29.671429 | 80 | h |
null | pytorch-main/caffe2/core/net_parallel.h | #ifndef CAFFE2_CORE_NET_PARALLEL_H
#define CAFFE2_CORE_NET_PARALLEL_H
#include "caffe2/core/net_async_base.h"
#include "caffe2/core/net_async_task_graph.h"
C10_DECLARE_string(caffe2_task_graph_engine);
namespace caffe2 {
class ParallelNetExecutorHelper;
class TORCH_API ParallelNet : public NetBase {
public:
Par... | 2,144 | 23.94186 | 77 | h |
null | pytorch-main/caffe2/core/net_simple.h | #ifndef CAFFE2_CORE_NET_SIMPLE_H_
#define CAFFE2_CORE_NET_SIMPLE_H_
#include <vector>
#include "c10/util/Registry.h"
#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/net.h"
#include "caffe2/core/tensor.h"
#include "caffe2/core/workspace.h"
#include "caffe2/proto/caffe2_pb.h"
nam... | 2,606 | 25.876289 | 79 | h |
null | pytorch-main/caffe2/core/net_simple_refcount.h | #ifndef CAFFE2_CORE_NET_SIMPLE_REFCOUNT_H_
#define CAFFE2_CORE_NET_SIMPLE_REFCOUNT_H_
#include <vector>
#include "c10/util/Registry.h"
#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/net.h"
#include "caffe2/core/net_simple.h"
#include "caffe2/core/tensor.h"
#include "caffe2/core... | 2,097 | 33.966667 | 80 | h |
null | pytorch-main/caffe2/core/observer.h | #pragma once
#include <memory>
#include <unordered_set>
#include "caffe2/core/logging.h"
namespace caffe2 {
/**
* Use this to implement a Observer using the Observer Pattern template.
*/
template <class T>
class ObserverBase {
public:
explicit ObserverBase(T* subject) : subject_(subject) {}
virtual void S... | 3,809 | 22.090909 | 80 | h |
null | pytorch-main/caffe2/core/operator_gradient.h | #ifndef CAFFE2_CORE_OPERATOR_GRADIENT_H_
#define CAFFE2_CORE_OPERATOR_GRADIENT_H_
#include "c10/util/Registry.h"
#include "caffe2/core/operator_schema.h"
#include "caffe2/proto/caffe2_pb.h"
#include "caffe2/utils/proto_utils.h"
namespace caffe2 {
/* @brief A struct that abstracts on top of dense and sparse blobs.
*... | 10,222 | 29.245562 | 80 | h |
null | pytorch-main/caffe2/core/operator_schema.h | #ifndef CAFFE2_CORE_OPERATOR_SCHEMA_H_
#define CAFFE2_CORE_OPERATOR_SCHEMA_H_
#include <climits>
#include <functional>
#include <initializer_list>
#include <ostream>
#include <set>
#include <unordered_map>
#include <vector>
#include <c10/util/irange.h>
#include <c10/util/Registry.h>
#include <caffe2/core/common.h>
#i... | 18,533 | 29.23491 | 80 | h |
null | pytorch-main/caffe2/core/prof_dag_counters.h | #ifndef PROF_DAG_COUNTERS_H
#define PROF_DAG_COUNTERS_H
#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/timer.h"
#include "caffe2/proto/caffe2_pb.h"
#include "caffe2/proto/prof_dag.pb.h"
#include <unordered_map>
namespace caffe2 {
class ProfDAGStats {
public:
ProfDAGStats()... | 2,751 | 21.933333 | 73 | h |
null | pytorch-main/caffe2/core/qtensor.h | #ifndef CAFFE2_CORE_QTENSOR_H_
#define CAFFE2_CORE_QTENSOR_H_
#include "caffe2/core/common.h"
#include "caffe2/core/context.h"
#include "caffe2/core/tensor.h"
#include <c10/util/accumulate.h>
#include <c10/util/irange.h>
#include <c10/util/typeid.h>
#include <algorithm>
#include <climits>
#include <cstddef>
#include ... | 6,657 | 24.412214 | 98 | h |
null | pytorch-main/caffe2/core/qtensor_serialization.h | #ifndef CAFFE2_CORE_QTENSOR_SERIALIZATION_H_
#define CAFFE2_CORE_QTENSOR_SERIALIZATION_H_
#include "caffe2/core/blob_serialization.h"
#include "caffe2/core/qtensor.h"
namespace caffe2 {
constexpr auto kQTensorBlobQType = "QTensor";
template <class Context>
class QTensorSerializer : public BlobSerializerBase {
publ... | 2,641 | 28.355556 | 79 | h |
null | pytorch-main/caffe2/core/scope_guard.h | /**
* Copyright 2016 Facebook
* @author Tudor Bosman (tudorb@fb.com)
*/
#pragma once
#include <cstddef>
#include <functional>
#include <new>
#include <type_traits>
#include <utility>
namespace caffe2 {
// Copied from folly/ScopeGuard.h
namespace detail {
class ScopeGuardImplBase {
public:
void dismiss() noe... | 4,675 | 28.408805 | 80 | h |
null | pytorch-main/caffe2/core/static_tracepoint_elfx86.h | #pragma once
// Default constraint for the probe arguments as operands.
#ifndef CAFFE_SDT_ARG_CONSTRAINT
#define CAFFE_SDT_ARG_CONSTRAINT "nor"
#endif
// Instruction to emit for the probe.
#define CAFFE_SDT_NOP nop
// Note section properties.
#define CAFFE_SDT_NOTE_NAME "stapsdt"
#defi... | 5,555 | 54.009901 | 80 | h |
null | pytorch-main/caffe2/core/stats.h | #pragma once
#include <atomic>
#include <memory>
#include <mutex>
#include <string>
#include <unordered_map>
#include <vector>
#include "caffe2/core/logging.h"
#include "caffe2/core/static_tracepoint.h"
namespace caffe2 {
class TORCH_API StatValue {
std::atomic<int64_t> v_{0};
public:
int64_t increment(int64_t... | 10,443 | 28.091922 | 80 | h |
null | pytorch-main/caffe2/core/storage.h | #ifndef CAFFE2_CORE_STORAGE_H_
#define CAFFE2_CORE_STORAGE_H_
#include <cstddef>
#include <cstdint>
#include <fstream>
#include <sstream>
#include <type_traits>
#include <typeinfo>
#include <vector>
#include "caffe2/core/allocator.h"
#include "caffe2/core/common.h"
#include "caffe2/core/context.h"
#include "caffe2/co... | 733 | 20.588235 | 36 | h |
null | pytorch-main/caffe2/core/tensor.h | #ifndef CAFFE2_CORE_TENSOR_H_
#define CAFFE2_CORE_TENSOR_H_
#include <c10/macros/Macros.h>
#include "caffe2/core/storage.h"
#include <c10/core/SymIntArrayRef.h>
#include <ATen/core/UndefinedTensorImpl.h>
#include <c10/core/TensorOptions.h>
#include <c10/util/ExclusivelyOwned.h>
#include <c10/util/ExclusivelyOwnedTens... | 19,521 | 27.921481 | 108 | h |
null | pytorch-main/caffe2/core/test_utils.h | #ifndef CAFFE2_UTILS_TEST_UTILS_H_
#define CAFFE2_UTILS_TEST_UTILS_H_
#include "caffe2/core/tensor.h"
#include "caffe2/core/workspace.h"
#include "caffe2/utils/proto_utils.h"
#include <c10/macros/Macros.h>
#include <c10/util/irange.h>
#include <cmath>
#include <string>
#include <vector>
// Utilities that make it ea... | 6,322 | 27.481982 | 79 | h |
null | pytorch-main/caffe2/core/timer.h | #ifndef CAFFE2_CORE_TIMER_H_
#define CAFFE2_CORE_TIMER_H_
#include <chrono>
#include "caffe2/core/common.h"
namespace caffe2 {
/**
* @brief A simple timer object for measuring time.
*
* This is a minimal class around a std::chrono::high_resolution_clock that
* serves as a utility class for testing code.
*/
cla... | 1,218 | 23.877551 | 76 | h |
null | pytorch-main/caffe2/core/transform.h | #pragma once
#include "caffe2/core/common.h"
#include "caffe2/core/graph.h"
#include "caffe2/core/workspace.h"
#include "caffe2/proto/caffe2_pb.h"
#include "caffe2/utils/proto_utils.h"
namespace caffe2 {
/**
* The Transform Base Object
*
* A Transform is an operation which manipulates a Caffe2 NetDef.
* You can ... | 5,741 | 31.811429 | 80 | h |
null | pytorch-main/caffe2/core/types.h | #ifndef CAFFE2_CORE_TYPES_H_
#define CAFFE2_CORE_TYPES_H_
#include <cstdint>
#include <string>
#include <type_traits>
#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
#include <c10/util/typeid.h>
#include "caffe2/proto/caffe2_pb.h"
#include <c10/util/Half.h>
namespace caffe2 {
// Storage orders that... | 2,249 | 25.785714 | 79 | h |
null | pytorch-main/caffe2/core/workspace.h | #ifndef CAFFE2_CORE_WORKSPACE_H_
#define CAFFE2_CORE_WORKSPACE_H_
#include "caffe2/core/common.h"
#include "caffe2/core/observer.h"
#include <climits>
#include <cstddef>
#include <mutex>
#include <typeinfo>
#include <unordered_map>
#include <unordered_set>
#include <vector>
#include "c10/util/Registry.h"
#include "c... | 11,305 | 31.962099 | 80 | h |
null | pytorch-main/caffe2/core/hip/common_miopen.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 6,281 | 34.094972 | 99 | h |
null | pytorch-main/caffe2/core/hip/miopen_wrapper.h | // Copyright 2004-present Facebook. All Rights Reserved.
#ifndef CAFFE2_CORE_MIOPEN_WRAPPERS_H_
#define CAFFE2_CORE_MIOPEN_WRAPPERS_H_
#include "caffe2/core/hip/common_miopen.h"
#include "caffe2/core/hip/context_gpu.h"
#include <c10/hip/HIPGuard.h>
namespace caffe2 {
class MIOPENWrapper;
/**
* MIOPENWorkspace is ... | 5,150 | 29.844311 | 94 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Converters/Dot.h | #ifndef NOM_CONVERTERS_DOT_H
#define NOM_CONVERTERS_DOT_H
#include "c10/util/irange.h"
#include "nomnigraph/Graph/Algorithms.h"
#include "nomnigraph/Graph/Graph.h"
#include "nomnigraph/Support/Casting.h"
#include <functional>
#include <iostream>
#include <map>
#include <queue>
#include <sstream>
#include <unordered_m... | 9,062 | 31.483871 | 78 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Graph/Algorithms.h | //===- nomnigraph/Graph/Algorithms.h - Graph algorithms ---------*- C++ -*-===//
//
// TODO Licensing.
//
//===----------------------------------------------------------------------===//
//
// This file defines algorithms that only require Graph level annotations.
// Tarjans is defined.
//
//===------------------------... | 6,493 | 29.345794 | 83 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Graph/BinaryMatchImpl.h | #ifndef NOM_GRAPH_BINARYMATCHIMPL_H
#define NOM_GRAPH_BINARYMATCHIMPL_H
#include "nomnigraph/Graph/Graph.h"
namespace nom {
namespace algorithm {
/// \brief A binary graph matching algorithm based on Kahn's algorithm.
template <typename F, typename T, typename... U>
std::vector<Subgraph<T, U...>> binaryMatch(Graph<T... | 2,874 | 25.376147 | 84 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Graph/Graph.h | //===- nomnigraph/Graph/Graph.h - Basic graph implementation ----*- C++ -*-===//
//
// This file defines a basic graph API for generic and flexible use with
// graph algorithms.
//
//===----------------------------------------------------------------------===//
#ifndef NOM_GRAPH_GRAPH_H
#define NOM_GRAPH_GRAPH_H
#inc... | 15,333 | 26.284698 | 80 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Graph/TarjansImpl.h | #ifndef NOM_GRAPH_TARJANSIMPL_H
#define NOM_GRAPH_TARJANSIMPL_H
#include <unordered_map>
#include "nomnigraph/Graph/Graph.h"
namespace nom {
namespace algorithm {
template <typename T, typename... U>
struct GraphWrapper {
struct NodeWrapper {
using NodeRef = typename Graph<T, U...>::NodeRef;
NodeWrapper(N... | 5,526 | 30.050562 | 84 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Graph/TopoSort.h | #ifndef NOM_GRAPH_TOPO_SORT_H
#define NOM_GRAPH_TOPO_SORT_H
#include <unordered_map>
#include "nomnigraph/Graph/Graph.h"
namespace nom {
namespace algorithm {
/// \brief Topological sort using DFS.
///
/// This algorithm takes a Graph object and returns node references in
/// topological order.
template <typename G... | 2,130 | 24.070588 | 77 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Representations/Compiler.h | #ifndef NOM_REPRESENTATIONS_COMPILER_H
#define NOM_REPRESENTATIONS_COMPILER_H
#include "caffe2/core/common.h"
#include "nomnigraph/Graph/Graph.h"
#include "nomnigraph/Support/Casting.h"
namespace nom {
namespace repr {
class TORCH_API Value {
public:
enum class ValueKind { Value, Instruction, Data };
Value(Valu... | 2,304 | 21.598039 | 72 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Representations/ControlFlow.h | #ifndef NOM_REPRESENTATIONS_CONTROLFLOW_H
#define NOM_REPRESENTATIONS_CONTROLFLOW_H
#include "caffe2/core/common.h"
#include "nomnigraph/Graph/Graph.h"
#include "nomnigraph/Representations/Compiler.h"
#include <unordered_map>
namespace nom {
namespace repr {
/// \brief A basic block holds a reference to a subgraph
... | 5,822 | 30.475676 | 78 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Representations/NeuralNet.h | //=== nomnigraph/Representations/NeuralNet.h - NN interface -----*- C++ -*-===//
//
// TODO Licensing.
//
//===----------------------------------------------------------------------===//
//
// This file defines classes that can be used in a
// nom::Graph<nom::repr::NeuralNetOperator, nom::repr::NeuralNetData> graph.
//... | 15,713 | 28.482176 | 80 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Support/Casting.h | //===- nomnigraph/Support/Casting.h - Allow casting checks ------*- C++ -*-===//
//
// This is taken directly from LLVM's source code.
//
// The original file is distributed under the University of Illinois Open Source
// License.
//
//===----------------------------------------------------------------------===//
//
//... | 14,766 | 31.242358 | 80 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Support/Common.h | //== nomnigraph/Support/Common.h - Common class implementations --*- C++ -*-==//
//
// TODO Licensing.
//
//===----------------------------------------------------------------------===//
//
// This file defines basic classes that are useful to inherit from.
//
//===------------------------------------------------------... | 3,279 | 25.885246 | 80 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Transformations/Match.h | //=== nomnigraph/Transformations/Match.h - Graph matching utils -*- C++ -*-===//
//
// TODO Licensing.
//
//===----------------------------------------------------------------------===//
//
// This file defines utilities for matching subgraphs.
//
//===-------------------------------------------------------------------... | 2,523 | 25.568421 | 80 | h |
null | pytorch-main/caffe2/core/nomnigraph/include/nomnigraph/Transformations/SubgraphMatcher.h | #ifndef NOM_TRANFORMATIONS_SUBGRAPH_MATCHER_H
#define NOM_TRANFORMATIONS_SUBGRAPH_MATCHER_H
#include "c10/util/irange.h"
#include "caffe2/core/common.h"
#include "nomnigraph/Graph/Graph.h"
#include <functional>
#include <memory>
#include <sstream>
#include <unordered_map>
#include <vector>
namespace nom {
namespace... | 14,898 | 33.648837 | 80 | h |
null | pytorch-main/caffe2/core/nomnigraph/tests/test_util.h | #ifndef NOM_TESTS_TEST_UTIL_H
#define NOM_TESTS_TEST_UTIL_H
#include "caffe2/core/common.h"
#include "nomnigraph/Graph/Graph.h"
#include "nomnigraph/Graph/Algorithms.h"
#include "nomnigraph/Representations/NeuralNet.h"
#include "nomnigraph/Converters/Dot.h"
#include <map>
class TestClass {
public:
TestClass() {}
... | 3,129 | 24.867769 | 95 | h |
null | pytorch-main/caffe2/cuda_rtc/common_rtc.h | #ifndef CAFFE2_CUDA_RTC_COMMON_RTC_H_
#define CAFFE2_CUDA_RTC_COMMON_RTC_H_
#include <sstream>
#include <string>
#include <cuda.h>
#include <nvrtc.h>
#define NVRTC_CHECK(condition) \
do { \
nvrtcResult res... | 4,300 | 31.583333 | 79 | h |
null | pytorch-main/caffe2/db/create_db_op.h | #ifndef CAFFE2_DB_CREATE_DB_OP_H_
#define CAFFE2_DB_CREATE_DB_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/db.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
template <class Context>
class CreateDBOp final : public Operator<Context> {
public:
CreateDBOp(const OperatorDef& operator_def, Wor... | 1,190 | 26.697674 | 77 | h |
null | pytorch-main/caffe2/distributed/file_store_handler.h | #pragma once
#include <caffe2/distributed/store_handler.h>
namespace caffe2 {
class TORCH_API FileStoreHandler : public StoreHandler {
public:
explicit FileStoreHandler(const std::string& path, const std::string& prefix);
~FileStoreHandler() override;
void set(const std::string& name, const std::string& data... | 1,039 | 24.365854 | 80 | h |
null | pytorch-main/caffe2/distributed/file_store_handler_op.h | #pragma once
#include "file_store_handler.h"
#include <caffe2/core/operator.h>
namespace caffe2 {
template <class Context>
class FileStoreHandlerCreateOp final : public Operator<Context> {
public:
explicit FileStoreHandlerCreateOp(
const OperatorDef& operator_def,
Workspace* ws)
: Operator<Cont... | 979 | 23.5 | 80 | h |
null | pytorch-main/caffe2/distributed/redis_store_handler.h | #pragma once
#include <caffe2/distributed/store_handler.h>
extern "C" {
#include <hiredis/hiredis.h>
}
#include <string>
namespace caffe2 {
class TORCH_API RedisStoreHandler : public StoreHandler {
public:
explicit RedisStoreHandler(std::string& host, int port, std::string& prefix);
virtual ~RedisStoreHandler... | 1,060 | 21.574468 | 79 | h |
null | pytorch-main/caffe2/distributed/redis_store_handler_op.h | #pragma once
#include "redis_store_handler.h"
#include <caffe2/core/operator.h>
#include <string>
namespace caffe2 {
template <class Context>
class RedisStoreHandlerCreateOp final : public Operator<Context> {
public:
explicit RedisStoreHandlerCreateOp(
const OperatorDef& operator_def,
Workspace* ws)... | 1,143 | 24.422222 | 79 | h |
null | pytorch-main/caffe2/distributed/store_handler.h | #pragma once
#include <chrono>
#include <cstdint>
#include <stdexcept>
#include <string>
#include <vector>
#include "caffe2/core/common.h"
namespace caffe2 {
class TORCH_API StoreHandler {
public:
static constexpr std::chrono::milliseconds kDefaultTimeout =
std::chrono::seconds(30);
static constexpr std:... | 2,522 | 26.725275 | 80 | h |
null | pytorch-main/caffe2/experiments/operators/fully_connected_op_decomposition.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 8,170 | 26.982877 | 80 | h |
null | pytorch-main/caffe2/experiments/operators/fully_connected_op_prune.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 11,801 | 27.926471 | 79 | h |
null | pytorch-main/caffe2/experiments/operators/fully_connected_op_sparse.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 4,601 | 22.84456 | 78 | h |
null | pytorch-main/caffe2/experiments/operators/funhash_op.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 7,342 | 29.983122 | 75 | h |
null | pytorch-main/caffe2/experiments/operators/sparse_funhash_op.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 7,548 | 30.194215 | 80 | h |
null | pytorch-main/caffe2/experiments/operators/sparse_matrix_reshape_op.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 4,305 | 31.870229 | 75 | h |
null | pytorch-main/caffe2/experiments/operators/tt_contraction_op.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 4,750 | 26.462428 | 78 | h |
null | pytorch-main/caffe2/experiments/operators/tt_pad_op.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 2,779 | 28.263158 | 77 | h |
null | pytorch-main/caffe2/ideep/ideep_utils.h | #pragma once
#include <caffe2/core/macros.h> // For caffe2 macros.
#include <caffe2/utils/eigen_utils.h>
// All caffe2 ideep related headers
#include <ideep.hpp>
#include <caffe2/ideep/utils/ideep_context.h>
#include <caffe2/ideep/utils/ideep_operator.h>
namespace caffe2 {
enum ConvAlgorithm {
CONV_ALGORITHM_AUTO... | 2,209 | 44.102041 | 80 | h |
null | pytorch-main/caffe2/ideep/operators/conv_pool_base_op.h | #ifndef CAFFE2_IDEEP_OPERATORS_CONV_POOL_BASE_OP_H_
#define CAFFE2_IDEEP_OPERATORS_CONV_POOL_BASE_OP_H_
#include <vector>
#include "caffe2/ideep/ideep_utils.h"
#include "caffe2/operators/conv_pool_op_base.h"
namespace caffe2 {
class IDEEPConvPoolOpBase : public ConvPoolOpBase<IDEEPContext> {
public:
IDEEPConvPoo... | 2,115 | 26.128205 | 69 | h |
null | pytorch-main/caffe2/ideep/operators/conv_transpose_unpool_base_op.h | #pragma once
#include "caffe2/ideep/ideep_utils.h"
#include "caffe2/proto/caffe2_legacy.pb.h"
using namespace caffe2;
namespace {
class IDEEPConvTransposeUnpoolBase : public IDEEPOperator {
public:
USE_IDEEP_DEF_ALIASES();
USE_IDEEP_OPERATOR_FUNCTIONS();
IDEEPConvTransposeUnpoolBase(const OperatorDef& opera... | 7,792 | 28.518939 | 78 | h |
null | pytorch-main/caffe2/ideep/operators/operator_fallback_ideep.h | #pragma once
#include <caffe2/core/common.h>
#include <caffe2/core/context.h>
#include <caffe2/core/operator.h>
#include <caffe2/ideep/ideep_utils.h>
#include <caffe2/proto/caffe2_pb.h>
namespace caffe2 {
/**
* @brief A templated class to allow one to wrap a CPU operator as an IDEEP
* operator.
*
* This class ca... | 7,776 | 39.717277 | 91 | h |
null | pytorch-main/caffe2/ideep/utils/ideep_context.h | #pragma once
#include <cstdlib>
#include <ctime>
#include <random>
#include <caffe2/core/context.h>
namespace caffe2 {
class IDEEPContext final : public BaseContext {
public:
typedef std::mt19937 rand_gen_type;
IDEEPContext() : random_seed_(RandomNumberSeed()) {}
explicit IDEEPContext(const DeviceOption& opt... | 4,170 | 23.25 | 80 | h |
null | pytorch-main/caffe2/ideep/utils/ideep_operator.h | #pragma once
#include <ideep.hpp>
#include <caffe2/core/operator.h>
#include <caffe2/proto/caffe2_pb.h>
namespace caffe2 {
C10_DECLARE_REGISTRY(
IDEEPOperatorRegistry,
OperatorBase,
const OperatorDef&,
Workspace*);
#define REGISTER_IDEEP_OPERATOR_CREATOR(key, ...) \
C10_REGISTER_CREATOR(IDEEPOpera... | 5,379 | 34.629139 | 80 | h |
null | pytorch-main/caffe2/image/transform_gpu.h | #ifndef CAFFE2_IMAGE_TRANSFORM_GPU_H_
#define CAFFE2_IMAGE_TRANSFORM_GPU_H_
/**
*
* Copyright (c) 2016, NVIDIA CORPORATION, All rights reserved
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributi... | 1,705 | 37.772727 | 82 | h |
null | pytorch-main/caffe2/mobile/contrib/ios/ios_caffe.h |
#ifdef __cplusplus
#include <string>
#include <vector>
#include "caffe2/mobile/contrib/ios/ios_caffe_defines.h"
#include "caffe2/mobile/contrib/ios/ios_caffe_predictor.h"
#include "caffe2/predictor/predictor.h"
extern "C" {
IOS_CAFFE_EXPORT Caffe2IOSPredictor* MakeCaffe2Predictor(const std::string& init_net_str,
... | 1,102 | 41.423077 | 92 | h |
null | pytorch-main/caffe2/mobile/contrib/ios/ios_caffe_predictor.h |
#pragma once
#include <string>
#include "caffe2/core/net.h"
#include "caffe2/mobile/contrib/ios/ios_caffe_defines.h"
#include "caffe2/predictor/predictor.h"
struct Tensor {
std::vector<int64_t> dims;
uint8_t* data;
};
class IOS_CAFFE_EXPORT Caffe2IOSPredictor final {
public:
/**
@allowMetalOperators Allow... | 1,312 | 34.486486 | 98 | h |
null | pytorch-main/caffe2/mobile/contrib/ios/mpscnn/mpscnn.h |
#pragma once
#include "caffe2/core/net.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
static constexpr const char* kMPSCNNReadCountArg = "__mpscnn_read_count__";
static constexpr const char* kMPSCNNOutputIsTempImageArg = "__mpscnn_output_is_temp_img__";
static constexpr const int kMetalMaxTextureArrLength = 204... | 948 | 38.541667 | 99 | h |
null | pytorch-main/caffe2/mobile/contrib/ios/mpscnn/mpscnn_context.h |
#pragma once
#import <Metal/MTLBuffer.h>
#import <Metal/MTLDevice.h>
#import <Metal/MTLLibrary.h>
#include <array>
#include <mutex>
#include <string>
#include <thread>
#include <unordered_map>
namespace caffe2 {
struct MPSCNNContext {
public:
id<MTLDevice> device;
id<MTLCommandQueue> commandQueue;
id<MTLLib... | 791 | 22.294118 | 96 | h |
null | pytorch-main/caffe2/mobile/contrib/ios/mpscnn/mpscnn_graph_mask.h |
#pragma once
#include "caffe2/core/net.h"
#include "mpscnn.h"
namespace caffe2 {
// We currently only try to convert a fixed set of operators that handle a subset of a full
// CNN. We also only run when MPSCNN is available, provides a speedup.
// On failure, returns false. On success, returns true, and sets the MPSCN... | 698 | 40.117647 | 93 | h |
null | pytorch-main/caffe2/mobile/contrib/libopencl-stub/include/CL/cl_ext.h | /*******************************************************************************
* Copyright (c) 2008 - 2012 The Khronos Group Inc.
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and/or associated documentation files (the
* "Materials"), to deal in the Materials... | 11,540 | 44.797619 | 121 | h |
null | pytorch-main/caffe2/mobile/contrib/libopencl-stub/include/CL/cl_gl.h | /**********************************************************************************
* Copyright (c) 2008 - 2012 The Khronos Group Inc.
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and/or associated documentation files (the
* "Materials"), to deal in the Materi... | 7,343 | 44.055215 | 107 | h |
null | pytorch-main/caffe2/mobile/contrib/libopencl-stub/include/CL/cl_gl_ext.h | /**********************************************************************************
* Copyright (c) 2008-2012 The Khronos Group Inc.
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and/or associated documentation files (the
* "Materials"), to deal in the Material... | 2,630 | 36.585714 | 94 | h |
null | pytorch-main/caffe2/mobile/contrib/libopencl-stub/include/CL/opencl.h | /*******************************************************************************
* Copyright (c) 2008-2012 The Khronos Group Inc.
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and/or associated documentation files (the
* "Materials"), to deal in the Materials w... | 1,754 | 30.909091 | 81 | h |
null | pytorch-main/caffe2/mobile/contrib/libvulkan-stub/include/vulkan/vk_platform.h | //
// File: vk_platform.h
//
/*
** Copyright (c) 2014-2015 The Khronos Group Inc.
**
** Licensed under the Apache License, Version 2.0 (the "License");
** you may not use this file except in compliance with the License.
** You may obtain a copy of the License at
**
** http://www.apache.org/licenses/LICENSE-2.0
**
*... | 3,903 | 31.264463 | 99 | h |
null | pytorch-main/caffe2/mobile/contrib/nnapi/dlnnapi.c | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 4,073 | 30.338462 | 77 | c |
null | pytorch-main/caffe2/mobile/contrib/nnapi/nnapi.h | #include "caffe2/core/operator.h"
#include "caffe2/core/tensor.h"
#include "caffe2/core/types.h"
#include "caffe2/utils/proto_utils.h"
#include "NeuralNetworks.h"
#include "dlnnapi.h"
namespace caffe2 {
class NNApi {
public:
using TensorVector = std::vector<TensorCPU*>;
// Three different modes:
// ANEURALNE... | 2,669 | 23.495413 | 73 | h |
null | pytorch-main/caffe2/mobile/contrib/ulp2/ulp.h | #pragma once
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor.h"
namespace caffe2 {
constexpr size_t k2b1bXBits = 2;
struct ConvArgs {
int stride_w{1};
int stride_h{1};
int pad_l{0};
int pad_t{0};
int pad_b{0};
int pad_r{0};
};
using ParallelFor = std::function<void(size_t, std::function<... | 2,346 | 32.528571 | 100 | h |
null | pytorch-main/caffe2/mpi/mpi_common.h | #ifndef CAFFE2_MPI_MPI_COMMON_H_
#define CAFFE2_MPI_MPI_COMMON_H_
#include <mpi.h>
#include <mutex>
#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
namespace caffe2 {
inline void CheckInitializedMPI() {
int flag;
MPI_Initialized(&flag);
CAFFE_ENFORCE(flag, "MPI does not seem to have been init... | 4,756 | 28.73125 | 79 | h |
null | pytorch-main/caffe2/mpi/mpi_ops.h | #ifndef CAFFE2_MPI_MPI_OPS_H_
#define CAFFE2_MPI_MPI_OPS_H_
#include <mpi.h>
#include "caffe2/core/operator.h"
#include "caffe2/mpi/mpi_common.h"
namespace caffe2 {
// TODO(jiayq): if needed, write up the use of color and key with MPI split.
// Currently, the operator simply creates a communicator that has the
// s... | 7,787 | 30.277108 | 80 | h |
null | pytorch-main/caffe2/observers/operator_attaching_net_observer.h | #pragma once
#include "caffe2/core/net.h"
#include "caffe2/core/observer.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
// Thin class that attaches the observer to all operators in the net
template <typename TOpObserver, typename TNetObserver>
class OperatorAttachingNetObserver : public ObserverBase<NetBase... | 907 | 27.375 | 69 | h |
null | pytorch-main/caffe2/observers/profile_observer.h | /**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable ... | 3,258 | 27.587719 | 79 | h |
null | pytorch-main/caffe2/observers/runcnt_observer.h | #pragma once
#include "caffe2/core/net.h"
#include "caffe2/core/observer.h"
#include "caffe2/core/operator.h"
#include "caffe2/observers/operator_attaching_net_observer.h"
namespace caffe2 {
class RunCountNetObserver;
class TORCH_API RunCountOperatorObserver final
: public ObserverBase<OperatorBase> {
public:
... | 1,391 | 24.777778 | 80 | h |
null | pytorch-main/caffe2/observers/time_observer.h | #ifndef CAFFE2_CONTRIB_OBSERVERS_TIME_OBSERVER_H_
#define CAFFE2_CONTRIB_OBSERVERS_TIME_OBSERVER_H_
#include <unordered_map>
#include "caffe2/core/common.h"
#include "caffe2/core/net.h"
#include "caffe2/core/observer.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/timer.h"
#include "caffe2/observers/operat... | 1,862 | 24.520548 | 80 | h |
null | pytorch-main/caffe2/onnx/backend.h | #pragma once
#include "caffe2/onnx/backend_rep.h"
#include "caffe2/onnx/device.h"
#include "caffe2/onnx/helper.h"
#include "caffe2/proto/caffe2_pb.h"
#include "onnx/onnx_pb.h"
#include <functional>
#include <string>
#include <unordered_map>
#include <unordered_set>
constexpr int kKnownOpsetVersion = 9;
namespace ca... | 8,674 | 29.762411 | 80 | h |
null | pytorch-main/caffe2/onnx/backend_rep.h | #pragma once
#include "caffe2/predictor/predictor.h"
#include "caffe2/proto/caffe2_pb.h"
#include <memory>
#include <string>
#include <vector>
namespace caffe2 {
namespace onnx {
class TORCH_API Caffe2BackendRep {
public:
void Run(
const caffe2::Predictor::TensorList& inputs,
caffe2::Predictor::Tensor... | 1,137 | 21.313725 | 64 | h |
null | pytorch-main/caffe2/onnx/helper.h | #pragma once
#include "caffe2/core/common.h"
#include "onnx/onnx_pb.h"
#include <set>
#include <string>
#include <unordered_set>
namespace caffe2 {
namespace onnx {
using ::ONNX_NAMESPACE::AttributeProto;
using ::ONNX_NAMESPACE::NodeProto;
// \brief This class generates unique dummy names
class TORCH_API DummyName... | 2,819 | 22.898305 | 75 | h |
null | pytorch-main/caffe2/onnx/offline_tensor.h | #pragma once
#include <c10/core/Storage.h>
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor.h"
namespace caffe2 {
#ifndef C10_MOBILE
struct TORCH_API OfflineTensor {
// A shell tensor to record shape and dtype
Tensor shape_tensor{CPU};
void setShapeAndType(
const std::vector<int>& sizes,
... | 1,645 | 29.481481 | 75 | h |
null | pytorch-main/caffe2/onnx/onnx_exporter.h | #pragma once
#include "caffe2/core/common.h"
#include "caffe2/core/tensor.h"
#include "caffe2/onnx/helper.h"
#include "caffe2/proto/caffe2_pb.h"
#include "onnx/onnx_pb.h"
#include <string>
#include <unordered_map>
#include <vector>
namespace caffe2 {
namespace onnx {
namespace {
using ::ONNX_NAMESPACE::AttributePro... | 4,843 | 32.178082 | 80 | h |
null | pytorch-main/caffe2/onnx/onnxifi_graph_info.h | #pragma once
#include <functional>
#include <memory>
#include <mutex>
#include <unordered_map>
#include "caffe2/core/logging.h"
#include "caffe2/opt/shape_info.h"
#include "foxi/onnxifi_loader.h"
namespace caffe2 {
namespace onnx {
struct BackendGraphInfo {
onnxBackendID backend_id;
onnxBackend backend;
onnxG... | 3,539 | 29.782609 | 80 | h |
null | pytorch-main/caffe2/onnx/torch_ops/operator_sets.h | #pragma once
#include "onnx/defs/schema.h"
namespace ONNX_NAMESPACE {
class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(
PyTorch,
1,
SparseLengthsSumFused8BitRowwise);
class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(PyTorch, 1, SparseLengthsSum);
class ONNX_OPERATOR_SET_SCHEMA_CLASS_NAME(PyTorch, 1, SparseLengthsWeigh... | 1,779 | 36.87234 | 80 | h |
null | pytorch-main/caffe2/operators/accumulate_op.h | #ifndef CAFFE2_OPERATORS_ACCUMULATE_OP_H_
#define CAFFE2_OPERATORS_ACCUMULATE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename T, class Context>
class AccumulateOp final : public Operator<Context> {
public:
template <clas... | 1,073 | 24.571429 | 73 | h |
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