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#include "tensorflow/core/common_runtime/rendezvous_mgr.h"
#include <unordered_set>
#include "tensorflow/core/common_runtime/device.h"
#include "tensorflow/core/common_runtime/device_mgr.h"
#if (!defined(PLATFORM_POSIX_ANDROID) && !defined(PLATFORM_GOOGLE_ANDROID)) && \
(defined(PLATFORM_GOOGLE) || GOOGLE_CUDA)
#include "tensorflow/core/common_runtime/gpu/gpu_util.h"
#endif
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/core/notification.h"
#include "tensorflow/core/lib/strings/numbers.h"
#include "tensorflow/core/lib/strings/str_util.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/port.h"
namespace tensorflow {
namespace {
void CopyTensorBetweenDevices(const string& id, DeviceContext* send_dev_context,
DeviceContext* recv_dev_context, Device* src,
Device* dst,
const AllocatorAttributes src_alloc_attr,
const AllocatorAttributes dst_alloc_attr,
const Tensor* input, Tensor* output,
std::function<void(const Status&)> done) {
if (src->attributes().device_type() != dst->attributes().device_type()) {
done(errors::Unimplemented(
"Copy between device types not yet implemented: src=", src->name(),
" dst=", dst->name()));
} else if (src->attributes().device_type() != "CPU") {
done(errors::Unimplemented(
"Copy between non-CPU devices not yet implemented"));
}
*output = *input;
done(Status::OK());
}
#if (!defined(PLATFORM_POSIX_ANDROID) && !defined(PLATFORM_GOOGLE_ANDROID)) && \
(defined(PLATFORM_GOOGLE) || GOOGLE_CUDA)
constexpr auto CopyTensorBetweenDevicesFunc = &GPUUtil::CopyViaDMA;
#else
constexpr auto CopyTensorBetweenDevicesFunc = &CopyTensorBetweenDevices;
#endif
} // end namespace
IntraProcessRendezvous::IntraProcessRendezvous(const DeviceMgr* device_mgr)
: device_mgr_(device_mgr), local_(NewLocalRendezvous()) {}
IntraProcessRendezvous::~IntraProcessRendezvous() { local_->Unref(); }
Status IntraProcessRendezvous::Send(const string& key,
const Rendezvous::Args& args,
const Tensor& val, const bool is_dead) {
VLOG(1) << "IntraProcessRendezvous Send " << this << " " << key;
{
mutex_lock l(mu_);
if (!status_.ok()) return status_;
}
Rendezvous::ParsedKey parsed;
TF_RETURN_IF_ERROR(Rendezvous::ParseKey(key, &parsed));
// Buffers "val" and "device_context" in local_.
return local_->Send(key, args, val, is_dead);
}
Status IntraProcessRendezvous::ParseKey(const string& key, bool is_src,
Rendezvous::ParsedKey* parsed) {
{
mutex_lock l(mu_);
if (!status_.ok()) return status_;
}
TF_RETURN_IF_ERROR(Rendezvous::ParseKey(key, parsed));
return Status::OK();
}
void IntraProcessRendezvous::SameWorkerRecvDone(
const Rendezvous::ParsedKey& parsed, const Rendezvous::Args& send_args,
const Rendezvous::Args& recv_args, const Tensor& in, Tensor* out,
StatusCallback done) {
// Do a quick copy (sharing the underlying buffer) if both tensors
// are on host memory.
const bool src_host =
(send_args.alloc_attrs.on_host() || parsed.src.type == "CPU");
const bool dst_host =
(recv_args.alloc_attrs.on_host() || parsed.dst.type == "CPU");
if (src_host && dst_host) {
*out = in;
done(Status::OK());
return;
}
// This copy must involve a non-CPU device. Hence, "in" must support DMA
// (e.g., string tensors do not work on GPU).
if (!DataTypeCanUseMemcpy(in.dtype())) {
done(errors::InvalidArgument("Non-DMA-safe ", DataTypeString(in.dtype()),
" tensor may not be copied from/to a GPU."));
return;
}
Device* src_device;
Status s = device_mgr_->LookupDevice(parsed.src_device, &src_device);
if (!s.ok()) {
done(s);
return;
}
Device* dst_device;
s = device_mgr_->LookupDevice(parsed.dst_device, &dst_device);
if (!s.ok()) {
done(s);
return;
}
AllocatorAttributes attr = recv_args.alloc_attrs;
attr.set_gpu_compatible(send_args.alloc_attrs.gpu_compatible() ||
recv_args.alloc_attrs.gpu_compatible());
Allocator* out_allocator = dst_device->GetAllocator(attr);
Tensor copy(out_allocator, in.dtype(), in.shape());
*out = copy;
CopyTensorBetweenDevicesFunc(parsed.edge_name, send_args.device_context,
recv_args.device_context, src_device, dst_device,
send_args.alloc_attrs, recv_args.alloc_attrs,
&in, out, done);
}
void IntraProcessRendezvous::RecvAsync(const string& key,
const Rendezvous::Args& recv_args,
DoneCallback done) {
VLOG(1) << "IntraProcessRendezvous Recv " << this << " " << key;
Rendezvous::ParsedKey parsed;
Status s = ParseKey(key, false /*!is_src*/, &parsed);
if (!s.ok()) {
done(s, Args(), recv_args, Tensor(), false);
return;
}
// Recv the tensor from local_.
local_->RecvAsync(key, recv_args, [this, parsed, done](
const Status& status,
const Rendezvous::Args& send_args,
const Rendezvous::Args& recv_args,
const Tensor& in, bool is_dead) {
Status s = status;
Tensor* out = new Tensor;
StatusCallback final_callback = [done, send_args, recv_args, out,
is_dead](const Status& s) {
done(s, send_args, recv_args, *out, is_dead);
delete out;
};
if (s.ok()) {
SameWorkerRecvDone(parsed, send_args, recv_args, in, out, final_callback);
} else {
final_callback(s);
}
});
}
void IntraProcessRendezvous::StartAbort(const Status& s) {
CHECK(!s.ok());
local_->StartAbort(s);
}
} // end namespace tensorflow
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