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Results 1 - 6 of 6 for XlaClusterOutput (0.27 sec)
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tensorflow/compiler/jit/encapsulate_xla_computations_pass_test.cc
scope.graph()->AddEdge(w.node(), 0, launch, 6); auto out0 = ops::XlaClusterOutput(scope.WithOpName("Out0"), Output(launch, 0)); auto out1 = ops::XlaClusterOutput(scope.WithOpName("Out1"), Output(launch, 1)); auto out2 = ops::XlaClusterOutput(scope.WithOpName("Out2"), Output(launch, 2)); auto out3 = ops::XlaClusterOutput(scope.WithOpName("Out3"), Output(launch, 3));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 16 18:03:15 UTC 2023 - 14.7K bytes - Viewed (0) -
tensorflow/compiler/jit/encapsulate_xla_computations_pass.h
// XlaLaunch nodes. // // xla.compile() does two main things: // a) marks operators that make up an XLA computation with the attribute // _xla_compile_id=XYZ, where XYZ is a unique key. // b) adds XlaClusterOutput nodes to represent outputs of the computation. // These nodes are not marked with the _xla_compile_id attribute. #ifndef TENSORFLOW_COMPILER_JIT_ENCAPSULATE_XLA_COMPUTATIONS_PASS_H_
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 06:59:07 UTC 2024 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/jit/ops/xla_ops_grad.py
# limitations under the License. # ============================================================================== from tensorflow.python.framework import ops @ops.RegisterGradient("XlaClusterOutput") def _XlaClusterOutputGrad(_, grad): del grad # unused raise RuntimeError("Gradient computation of graph in xla.compile() is " "prohibited because it can cause performance degradation."
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Sep 28 21:37:05 UTC 2021 - 1.1K bytes - Viewed (0) -
tensorflow/compiler/jit/ops/xla_ops.cc
.Attr("Tresults: list(type) >= 0") .Attr("constants: list(int) >= 0") .Attr("resources: list(int) >= 0") .Attr("function: func") .Doc("XLA Launch Op. For use by the XLA JIT only."); REGISTER_OP("XlaClusterOutput") .Input("input: T") // Note: when replication is supported, this op will have N outputs. .Output("outputs: T") .Attr("T: type") .SetShapeFn([](InferenceContext* c) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 09:08:06 UTC 2024 - 4.5K bytes - Viewed (0) -
tensorflow/compiler/jit/encapsulate_xla_computations_pass.cc
#include "tensorflow/core/platform/statusor.h" #include "tensorflow/core/util/dump_graph.h" namespace tensorflow { namespace { const char* const kXlaClusterOutput = "XlaClusterOutput"; bool IsCpuGpuCompile(const Graph* graph) { for (Node* n : graph->nodes()) { string name; // Only consider nodes being compiled. if (!TryGetNodeAttr(n->attrs(), kXlaClusterIdAttr, &name)) continue;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 06:33:33 UTC 2024 - 15.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
); TF_DerivedOperandTypeListAttr Tin = TF_DerivedOperandTypeListAttr<0>; TF_DerivedResultTypeListAttr Tout = TF_DerivedResultTypeListAttr<0>; } def TF_XlaClusterOutputOp : TF_Op<"XlaClusterOutput", [Pure, TF_NoConstantFold]> { let summary = [{ Operator that connects the output of an XLA computation to other consumer graph nodes. }]; let arguments = (ins TF_Tensor:$input
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)