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Results 11 - 20 of 204 for r2devices (0.17 sec)
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tensorflow/compiler/mlir/tensorflow/utils/tpu_rewrite_device_util_test.cc
std::vector<std::string> devices{ "/job:localhost/replica:0/task:0/device:CPU:0"}; devices.reserve(num_tasks * num_devices_per_task + num_tasks + 1); for (int task = 0; task < num_tasks; ++task) { devices.push_back( llvm::formatv("/job:worker/replica:0/task:{0}/device:CPU:0", task) .str()); devices.push_back(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Apr 26 09:37:10 UTC 2024 - 46.8K bytes - Viewed (0) -
tensorflow/compiler/jit/device_util.h
// same type. // - GPU is preferred over CPU. // - If `allow_mixing_unknown_and_cpu` is true then unknown devices are // preferred over CPU. // - XLA devices count as "unrecognized devices". // // This set of rules above implicitly assume that XLA:GPU can compile all // operations in the cluster that XLA:CPU can compile, and if
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 15 17:18:31 UTC 2024 - 7.1K bytes - Viewed (0) -
pkg/kubelet/apis/podresources/server_v1_test.go
{ Name: containerName, Devices: []*podresourcesapi.ContainerDevices{}, DynamicResources: []*podresourcesapi.DynamicResource{}, }, }, }, }, }, }, { desc: "pod with devices", pods: pods, devices: devs, cpus: cpus, memory: memory,
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Wed Apr 24 18:25:29 UTC 2024 - 45.9K bytes - Viewed (0) -
pkg/kubelet/cm/devicemanager/checkpoint/checkpoint.go
func New(devEntries []PodDevicesEntry, devices map[string][]string) DeviceManagerCheckpoint { return newV2(devEntries, devices) } func newV2(devEntries []PodDevicesEntry, devices map[string][]string) DeviceManagerCheckpoint { return &Data{ Data: checkpointData{ PodDeviceEntries: devEntries, RegisteredDevices: devices, }, } } // MarshalCheckpoint returns marshalled data
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Mon Apr 15 12:01:56 UTC 2024 - 3.2K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_gpu_device.cc
public: Status ListPhysicalDevices(std::vector<string>* devices) override; Status CreateDevices(const SessionOptions& options, const string& name_prefix, std::vector<std::unique_ptr<Device>>* devices) override; }; Status XlaGpuDeviceFactory::ListPhysicalDevices(std::vector<string>* devices) { XlaDeviceFlags* flags = GetXlaDeviceFlags();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 08:47:20 UTC 2024 - 6.6K bytes - Viewed (0) -
pkg/kubelet/cm/devicemanager/pod_devices_test.go
for devID, plugInfo := range contDevices { nodes := plugInfo.GetTopology().GetNodes() require.Equal(t, len(nodes), len(devices), "Incorrect container devices: %v - %v (nodes %v)", devices, contDevices, nodes) for _, node := range plugInfo.GetTopology().GetNodes() { dev, ok := devices[node.ID] require.True(t, ok, "NUMA id %v doesn't exist in result", node.ID)
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Wed Apr 24 18:25:29 UTC 2024 - 10.3K bytes - Viewed (0) -
pkg/kubelet/cm/devicemanager/topology_hints.go
// Only consider devices that actually contain topology information. if aligned := m.deviceHasTopologyAlignment(resource); !aligned { klog.InfoS("Resource does not have a topology preference", "resource", resource) deviceHints[resource] = nil continue } // Short circuit to regenerate the same hints if there are already // devices allocated to the Container. This might happen after a
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Sat Jan 27 02:10:25 UTC 2024 - 9.9K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_tpu_device.cc
public: Status ListPhysicalDevices(std::vector<string>* devices) override; Status CreateDevices(const SessionOptions& options, const string& name_prefix, std::vector<std::unique_ptr<Device>>* devices) override; }; Status TpuNodeDeviceFactory::ListPhysicalDevices(std::vector<string>* devices) { tpu::TpuPlatformInterface* platform =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 22:53:47 UTC 2024 - 20.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_device_ops.td
The region held by this operation represents a computation that is replicated across multiple devices. The number of replications is based on the `n` attribute. Explicit devices can be populated in the `devices` attribute, and it must be a mapping of device alias to list of explicit or aliased device names from the outer scope. The device name map specifies devices on which replicated ops inside tf_device.replicate will be executed.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 23:53:20 UTC 2024 - 14.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/ifrt/rewrite_cluster_to_ifrt_call.mlir
// CHECK-SAME: tfrt_ifrt_serving.program_id = [[PROGRAM_ID]] : i64 // CHECK: return
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Feb 17 07:28:40 UTC 2024 - 9K bytes - Viewed (0)