FM / core

/usr/local/lib64/python3.6/site-packages/torch/include/caffe2/core/

/usr/local/lib64/python3.6/site-packages/torch/include/caffe2/core

Name	Size	Mode	Actions
allocator.h	136	0644	edit dl rm
blob.h	4168	0644	edit dl rm
blob_serialization.h	10791	0644	edit dl rm
blob_serializer_base.h	3905	0644	edit dl rm
blob_stats.h	1127	0644	edit dl rm
common.h	4329	0644	edit dl rm
common_cudnn.h	9893	0644	edit dl rm
common_gpu.h	21414	0644	edit dl rm
common_omp.h	156	0644	edit dl rm
context.h	6174	0644	edit dl rm
context_base.h	4382	0644	edit dl rm
context_gpu.h	11014	0644	edit dl rm
cudnn_wrappers.h	6956	0644	edit dl rm
db.h	9352	0644	edit dl rm
distributions_stubs.h	2161	0644	edit dl rm
event.h	12420	0644	edit dl rm
event_cpu.h	1192	0644	edit dl rm
export_c10_op_to_caffe2.h	9487	0644	edit dl rm
export_caffe2_op_to_c10.h	11101	0644	edit dl rm
flags.h	74	0644	edit dl rm
graph.h	5258	0644	edit dl rm
init.h	6496	0644	edit dl rm
logging.h	75	0644	edit dl rm
macros.h	3426	0644	edit dl rm
memonger.h	817	0644	edit dl rm
module.h	2473	0644	edit dl rm
net.h	4634	0644	edit dl rm
net_async_base.h	7397	0644	edit dl rm
net_async_scheduling.h	993	0644	edit dl rm
net_async_task.h	833	0644	edit dl rm
net_async_task_future.h	1925	0644	edit dl rm
net_async_task_graph.h	2253	0644	edit dl rm
net_async_tracing.h	5093	0644	edit dl rm
net_dag_utils.h	2146	0644	edit dl rm
net_parallel.h	2144	0644	edit dl rm
net_simple.h	2606	0644	edit dl rm
net_simple_refcount.h	2097	0644	edit dl rm
numa.h	72	0644	edit dl rm
observer.h	3809	0644	edit dl rm
operator.h	58872	0644	edit dl rm
operator_gradient.h	10222	0644	edit dl rm
operator_schema.h	18477	0644	edit dl rm
plan_executor.h	219	0644	edit dl rm
prof_dag_counters.h	2751	0644	edit dl rm
qtensor.h	6615	0644	edit dl rm
qtensor_serialization.h	2624	0644	edit dl rm
scope_guard.h	4675	0644	edit dl rm
static_tracepoint.h	398	0644	edit dl rm
static_tracepoint_elfx86.h	5555	0644	edit dl rm
stats.h	10365	0644	edit dl rm
storage.h	733	0644	edit dl rm
tensor.h	18668	0644	edit dl rm
tensor_impl.h	351	0644	edit dl rm
tensor_int8.h	450	0644	edit dl rm
test_utils.h	6285	0644	edit dl rm
timer.h	1218	0644	edit dl rm
transform.h	5741	0644	edit dl rm
types.h	2248	0644	edit dl rm
workspace.h	11305	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/torch/include/caffe2/core/workspace.h (11305B)

#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 "caffe2/core/blob.h"
#include "caffe2/core/net.h"
#include "caffe2/proto/caffe2_pb.h"
#include "caffe2/utils/signal_handler.h"
#include "caffe2/utils/threadpool/ThreadPool.h"

C10_DECLARE_bool(caffe2_print_blob_sizes_at_exit);

namespace caffe2 {

class NetBase;

struct TORCH_API StopOnSignal {
  StopOnSignal()
      : handler_(std::make_shared<SignalHandler>(
            SignalHandler::Action::STOP,
            SignalHandler::Action::STOP)) {}

StopOnSignal(const StopOnSignal& other) : handler_(other.handler_) {}

bool operator()(int /*iter*/) {
    return handler_->CheckForSignals() != SignalHandler::Action::STOP;
  }

std::shared_ptr<SignalHandler> handler_;
};

/**
 * Workspace is a class that holds all the related objects created during
 * runtime: (1) all blobs, and (2) all instantiated networks. It is the owner of
 * all these objects and deals with the scaffolding logistics.
 */
class TORCH_API Workspace {
 public:
  typedef std::function<bool(int)> ShouldContinue;
  /**
   * Initializes an empty workspace.
   */
  Workspace() : Workspace(".", nullptr) {}

/**
   * Initializes an empty workspace with the given root folder.
   *
   * For any operators that are going to interface with the file system, such
   * as load operators, they will write things under this root folder given
   * by the workspace.
   */
  explicit Workspace(const string& root_folder)
      : Workspace(root_folder, nullptr) {}

/**
   * Initializes a workspace with a shared workspace.
   *
   * When we access a Blob, we will first try to access the blob that exists
   * in the local workspace, and if not, access the blob that exists in the
   * shared workspace. The caller keeps the ownership of the shared workspace
   * and is responsible for making sure that its lifetime is longer than the
   * created workspace.
   */
  explicit Workspace(const Workspace* shared) : Workspace(".", shared) {}

/**
   * Initializes workspace with parent workspace, blob name remapping
   * (new name -> parent blob name), no other blobs are inherited from
   * parent workspace
   */
  Workspace(
      const Workspace* shared,
      const std::unordered_map<string, string>& forwarded_blobs)
      : Workspace(".", nullptr) {
    CAFFE_ENFORCE(shared, "Parent workspace must be specified");
    for (const auto& forwarded : forwarded_blobs) {
      CAFFE_ENFORCE(
          shared->HasBlob(forwarded.second),
          "Invalid parent workspace blob: ",
          forwarded.second);
      forwarded_blobs_[forwarded.first] =
          std::make_pair(shared, forwarded.second);
    }
  }

/**
   * Initializes a workspace with a root folder and a shared workspace.
   */
  Workspace(const string& root_folder, const Workspace* shared)
      : root_folder_(root_folder), shared_(shared), bookkeeper_(bookkeeper()) {
    std::lock_guard<std::mutex> guard(bookkeeper_->wsmutex);
    bookkeeper_->workspaces.insert(this);
  }

~Workspace() {
    if (FLAGS_caffe2_print_blob_sizes_at_exit) {
      PrintBlobSizes();
    }
    // This is why we have a bookkeeper_ shared_ptr instead of a naked static! A
    // naked static makes us vulnerable to out-of-order static destructor bugs.
    std::lock_guard<std::mutex> guard(bookkeeper_->wsmutex);
    bookkeeper_->workspaces.erase(this);
  }

/**
   * Adds blob mappings from workspace to the blobs from parent workspace.
   * Creates blobs under possibly new names that redirect read/write operations
   * to the blobs in the parent workspace.
   * Arguments:
   *  parent - pointer to parent workspace
   *  forwarded_blobs - map from new blob name to blob name in parent's
   * workspace skip_defined_blob - if set skips blobs with names that already
   * exist in the workspace, otherwise throws exception
   */
  void AddBlobMapping(
      const Workspace* parent,
      const std::unordered_map<string, string>& forwarded_blobs,
      bool skip_defined_blobs = false);

/**
   * Converts previously mapped tensor blobs to local blobs, copies values from
   * parent workspace blobs into new local blobs. Ignores undefined blobs.
   */
  template <class Context>
  void CopyForwardedTensors(const std::unordered_set<std::string>& blobs) {
    for (const auto& blob : blobs) {
      auto it = forwarded_blobs_.find(blob);
      if (it == forwarded_blobs_.end()) {
        continue;
      }
      const auto& ws_blob = it->second;
      const auto* parent_ws = ws_blob.first;
      auto* from_blob = parent_ws->GetBlob(ws_blob.second);
      CAFFE_ENFORCE(from_blob);
      CAFFE_ENFORCE(
          from_blob->template IsType<Tensor>(),
          "Expected blob with tensor value",
          ws_blob.second);
      forwarded_blobs_.erase(blob);
      auto* to_blob = CreateBlob(blob);
      CAFFE_ENFORCE(to_blob);
      const auto& from_tensor = from_blob->template Get<Tensor>();
      auto* to_tensor = BlobGetMutableTensor(to_blob, Context::GetDeviceType());
      to_tensor->CopyFrom(from_tensor);
    }
  }

/**
   * Return list of blobs owned by this Workspace, not including blobs
   * shared from parent workspace.
   */
  vector<string> LocalBlobs() const;

/**
   * Return a list of blob names. This may be a bit slow since it will involve
   * creation of multiple temp variables. For best performance, simply use
   * HasBlob() and GetBlob().
   */
  vector<string> Blobs() const;

/**
   * Return the root folder of the workspace.
   */
  const string& RootFolder() { return root_folder_; }
  /**
   * Checks if a blob with the given name is present in the current workspace.
   */
  inline bool HasBlob(const string& name) const {
    // First, check the local workspace,
    // Then, check the forwarding map, then the parent workspace
    if (blob_map_.count(name)) {
      return true;
    }

auto it = forwarded_blobs_.find(name);
    if (it != forwarded_blobs_.end()) {
      const auto parent_ws = it->second.first;
      const auto& parent_name = it->second.second;
      return parent_ws->HasBlob(parent_name);
    }

if (shared_) {
      return shared_->HasBlob(name);
    }

return false;
  }

void PrintBlobSizes();

/**
   * Creates a blob of the given name. The pointer to the blob is returned, but
   * the workspace keeps ownership of the pointer. If a blob of the given name
   * already exists, the creation is skipped and the existing blob is returned.
   */
  Blob* CreateBlob(const string& name);
  /**
   * Similar to CreateBlob(), but it creates a blob in the local workspace even
   * if another blob with the same name already exists in the parent workspace
   * -- in such case the new blob hides the blob in parent workspace. If a blob
   * of the given name already exists in the local workspace, the creation is
   * skipped and the existing blob is returned.
   */
  Blob* CreateLocalBlob(const string& name);
  /**
   * Remove the blob of the given name. Return true if removed and false if
   * not exist.
   * Will NOT remove from the shared workspace.
   */
  bool RemoveBlob(const string& name);
  /**
   * Gets the blob with the given name as a const pointer. If the blob does not
   * exist, a nullptr is returned.
   */
  const Blob* GetBlob(const string& name) const;
  /**
   * Gets the blob with the given name as a mutable pointer. If the blob does
   * not exist, a nullptr is returned.
   */
  Blob* GetBlob(const string& name);

/**
   * Renames a local workspace blob. If blob is not found in the local blob list
   * or if the target name is already present in local or any parent blob list
   * the function will throw.
   */
  Blob* RenameBlob(const string& old_name, const string& new_name);

/**
   * Creates a network with the given NetDef, and returns the pointer to the
   * network. If there is anything wrong during the creation of the network, a
   * nullptr is returned. The Workspace keeps ownership of the pointer.
   *
   * If there is already a net created in the workspace with the given name,
   * CreateNet will overwrite it if overwrite=true is specified. Otherwise, an
   * exception is thrown.
   */
  NetBase* CreateNet(const NetDef& net_def, bool overwrite = false);
  NetBase* CreateNet(
      const std::shared_ptr<const NetDef>& net_def,
      bool overwrite = false);
  /**
   * Gets the pointer to a created net. The workspace keeps ownership of the
   * network.
   */
  NetBase* GetNet(const string& net_name);
  /**
   * Deletes the instantiated network with the given name.
   */
  void DeleteNet(const string& net_name);
  /**
   * Finds and runs the instantiated network with the given name. If the network
   * does not exist or there are errors running the network, the function
   * returns false.
   */
  bool RunNet(const string& net_name);

/**
   * Returns a list of names of the currently instantiated networks.
   */
  vector<string> Nets() const {
    vector<string> names;
    for (auto& entry : net_map_) {
      names.push_back(entry.first);
    }
    return names;
  }

/**
   * Runs a plan that has multiple nets and execution steps.
   */
  bool RunPlan(const PlanDef& plan_def,
               ShouldContinue should_continue = StopOnSignal{});

/*
   * Returns a CPU threadpool instance for parallel execution of
   * work. The threadpool is created lazily; if no operators use it,
   * then no threadpool will be created.
   */
  ThreadPool* GetThreadPool();

// RunOperatorOnce and RunNetOnce runs an operator or net once. The difference
  // between RunNet and RunNetOnce lies in the fact that RunNet allows you to
  // have a persistent net object, while RunNetOnce creates a net and discards
  // it on the fly - this may make things like database read and random number
  // generators repeat the same thing over multiple calls.
  bool RunOperatorOnce(const OperatorDef& op_def);
  bool RunNetOnce(const NetDef& net_def);

/**
   * Applies a function f on each workspace that currently exists.
   *
   * This function is thread safe and there is no race condition between
   * workspaces being passed to f in this thread and destroyed in another.
   */
  template <typename F>
  static void ForEach(F f) {
    auto bk = bookkeeper();
    std::lock_guard<std::mutex> guard(bk->wsmutex);
    for (Workspace* ws : bk->workspaces) {
      f(ws);
    }
  }

public:
  std::atomic<int> last_failed_op_net_position{};

private:
  struct Bookkeeper {
    std::mutex wsmutex;
    std::unordered_set<Workspace*> workspaces;
  };

static std::shared_ptr<Bookkeeper> bookkeeper();

std::unordered_map<string, unique_ptr<Blob>> blob_map_;
  const string root_folder_;
  const Workspace* shared_;
  std::unordered_map<string, std::pair<const Workspace*, string>>
      forwarded_blobs_;
  std::unique_ptr<ThreadPool> thread_pool_;
  std::mutex thread_pool_creation_mutex_;
  std::shared_ptr<Bookkeeper> bookkeeper_;
  std::unordered_map<string, unique_ptr<NetBase>> net_map_;

C10_DISABLE_COPY_AND_ASSIGN(Workspace);
};

}  // namespace caffe2

#endif  // CAFFE2_CORE_WORKSPACE_H_

cmd: