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Results 31 - 40 of 268 for r2devices (0.25 sec)
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tensorflow/compiler/jit/xla_device.h
// If padded_shape_fn is empty, a default implementation that returns // the logical on-device shape without padding is used. PaddedShapeFn padded_shape_fn; // Set of devices to use. This controls which of the devices on the given // platform will have resources allocated. For GPUs this will be // filled from visible_gpu_devices list from session configuration. std::optional<std::set<int>> allowed_devices;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 09:53:30 UTC 2024 - 13.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_colocate_composite_resource_ops.mlir
// CHECK-SAME: (%[[ARG0]] as %[[RI_0:[a-z0-9]*]]: tensor<*x!tf_type.resource<tensor<4xf32>>>) tf_device.replicate(%arg0 as %arg1: tensor<*x!tf_type.resource<tensor<4xf32>>>) { _mirrored_variable_indices = [0], devices = {TPU_REPLICATED_CORE_0 = ["/job:worker/replica:0/task:0/device:TPU:0", "/job:worker/replica:0/task:0/device:TPU:1"]}, n = 2 : i32} { // CHECK: %[[RESOURCE_OUT:.*]] = "tf_device.launch"()
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:59:10 UTC 2023 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/host_runtime/lower_cluster_to_runtime_ops.h
// // Input: // Tensorflow Dialect MLIR with tf_device.cluster ops and virtual devices. // xla_device_type - The device type that is being targeted. // Output: // Tensorflow Dialect MLIR with Runtime specific ops. All tf_device.cluster // ops are removed. Physical devices are assigned to ops instead of virtual // devices. tensorflow::Status RunLowerClusterToRuntimeOpsPassPipeline(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 21:47:17 UTC 2023 - 2.3K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_platform_info.h
// configuring the persistor used in the DeviceCompiler. Please note that // non-XLA devices aren't supported yet. This is because: // 1. PjRtClient doesn't support data transfer for non-XLA devices yet // 2. Fetching the PjRtClient for non-XLA devices is also not supported yet Status GetOrCreatePjRtDeviceCompilerAndProfiler( const OpKernelContext& ctx, const XlaPlatformInfo& platform_info,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 09:53:30 UTC 2024 - 7.2K bytes - Viewed (0) -
tensorflow/compiler/jit/device_context_test.cc
auto device_factory = DeviceFactory::GetFactory(device_type); SessionOptions options; std::vector<std::unique_ptr<Device>> devices; Status s = device_factory->CreateDevices( options, "/job:worker/replica:0/task:0", &devices); device_ = std::move(devices[0]); tensorflow::AllocatorAttributes host_alloc_attr; host_alloc_attr.set_on_host(true);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 06 19:12:29 UTC 2023 - 3.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/runtime_lowering_tpu.mlir
// RUN: tf-tfrt-opt -tfrt-lower-cluster-to-runtime-ops-tpu -split-input-file -verify-diagnostics %s | FileCheck %s module attributes {tf.versions = {producer = 888 : i32}, tf.devices = ["/job:worker/replica:0/task:0/device:CPU:0", "/job:worker/replica:0/task:0/device:TPU_SYSTEM:0", "/job:worker/replica:0/task:0/device:TPU:0"]} { // CHECK-LABEL: @converts_cluster func.func @converts_cluster() { // CHECK: %0:2 = "tf_device.launch"() <{{.*}}> ({
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:59:10 UTC 2023 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/host_runtime/tpu_rewrite_pass.cc
return tensorflow::WrapOpInLaunch(builder, compile_op.getLoc(), compile_op, compilation_device); } // Assigns explicit devices to replicate op. An aliased device is created per // core, and all replica devices per core are grouped together. void AssignDevicesToReplicate( tf_device::ReplicateOp replicate, llvm::ArrayRef<llvm::SmallVector<tensorflow::TPUDeviceAndHost, 8>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 21:25:12 UTC 2024 - 29.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/host_runtime/testdata/spmd.mlir
module attributes {tf.versions = {producer = 888 : i32}, tf.devices = ["/job:localhost/replica:0/task:0/device:CPU:0", "/job:localhost/replica:0/task:0/device:TPU_SYSTEM:0", "/job:localhost/replica:0/task:0/device:TPU:0", "/job:localhost/replica:0/task:0/device:TPU:1", "/job:localhost/replica:0/task:0/device:TPU:2", "/job:localhost/replica:0/task:0/device:TPU:3", "/job:localhost/replica:0/task:0/device:TPU:4", "/job:localhost/replica:0/task:0/device:TPU:5", "/job:localhost/replica:0/task:0/device:TPU:6",...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Dec 12 04:22:33 UTC 2023 - 1.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/passes/extract_head_tail_outside_compilation.cc
auto& side_effect_analysis = getAnalysis<mlir::TF::SideEffectAnalysis>(); // Get runtime devices information from the closest parent module. auto module = getOperation(); mlir::TF::RuntimeDevices devices; if (failed(tensorflow::GetDevicesFromOp(module, &devices))) return signalPassFailure(); OpBuilder builder(&getContext()); llvm::SmallVector<mlir::tf_device::ClusterOp, 4> clusters;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 20.6K bytes - Viewed (0) -
tensorflow/compiler/jit/test_util.cc
for (const auto& device_name : device_names) { device_count->insert({device_name, 1}); } std::vector<std::unique_ptr<Device>> devices; TF_CHECK_OK(DeviceFactory::AddDevices( options, "/job:localhost/replica:0/task:0", &devices)); device_mgr_ = std::make_unique<StaticDeviceMgr>(std::move(devices)); OptimizerOptions opts; lib_def_ = std::make_unique<FunctionLibraryDefinition>(OpRegistry::Global(),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Feb 09 11:36:41 UTC 2024 - 3.7K bytes - Viewed (0)