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tensorflow/compiler/mlir/tensorflow/tests/region-control-flow-to-functional.mlir
// RUN: tf-opt %s -tf-region-control-flow-to-functional -split-input-file | FileCheck %s // Simple IfRegion // CHECK: func private @test_else_name(%arg0: tensor<*xf32>) -> tensor<*xf32> // CHECK-NEXT: "tf.Neg" // CHECK: func private @test_then_name(%arg0: tensor<*xf32>) -> tensor<*xf32> // CHECK-NEXT: "tf.Abs" func.func @testSimple(%arg0: tensor<i1>, %arg1: tensor<*xf32>) -> tensor<*xf32> { // CHECK: "tf.If" // CHECK-NOT: attr1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Feb 02 11:15:34 UTC 2024 - 44.3K bytes - Viewed (0) -
src/main/webapp/WEB-INF/view/admin/plugin/admin_plugin_installplugin.jsp
Registered: Wed Jun 12 13:08:18 UTC 2024 - Last Modified: Fri Feb 14 12:15:45 UTC 2020 - 5.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/graphdef2mlir/target.pbtxt
# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -tf-prune-unused-nodes -tf-control-output-arrays=AssignAdd -o - | FileCheck --check-prefix=PRUNE %s
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 10 19:53:21 UTC 2020 - 4.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/g3doc/_includes/tf_passes.md
run on TPU instead of CPU while still being compiled on host. ### `-tf-functional-control-flow-to-cfg` _Transform functional control flow Ops to MLIR Control Form Graph (CFG) form_ ### `-tf-functional-control-flow-to-regions` _Transforms functional control flow operations to their region-based counterparts_ This pass transforms functional control flow operations in the TensorFlow
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 02 02:26:39 UTC 2023 - 96.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
} def ExecutorConvertControlToDataOutputsPass : Pass<"tf-executor-convert-control-to-data-outputs", "ModuleOp"> { let summary = "Chain control outputs of while loop body"; let description = [{ This pass converts the control outputs of a while loop body function to data outputs. Thus, inter iteration control dependencies are transformed to data dependencies. Since data dependencies can express which particular
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 99.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_executor_ops_invalid.mlir
func.func @invalid_yield(%arg0: tensor<*xf32>, %ctl: !tf_executor.control) { tf_executor.graph { "tf_executor.island"() ({ "tf_executor.yield"(%arg0, %ctl) : (tensor<*xf32>, !tf_executor.control) -> () // expected-error@-1 {{'tf_executor.yield' op unexpected control type for operand #1}} }) : () -> (tensor<*xf32>, !tf_executor.control, !tf_executor.control) } func.return
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Oct 19 01:12:10 UTC 2023 - 28.2K bytes - Viewed (0) -
cmd/kubeadm/app/cmd/cmd.go
Create a two-machine cluster with one control-plane node (which controls the cluster), and one worker node (where your workloads, like Pods and Deployments run). ┌──────────────────────────────────────────────────────────┐ │ On the first machine: │ ├──────────────────────────────────────────────────────────┤ │ control-plane# kubeadm init │
Registered: Sat Jun 15 01:39:40 UTC 2024 - Last Modified: Tue Aug 17 14:40:46 UTC 2021 - 4.3K bytes - Viewed (0) -
src/cmd/compile/internal/ssa/fuse_branchredirect.go
for _, v := range child.Values { if v.Op != OpPhi { continue } v.AddArg(v.Args[ai]) } if b.Func.pass.debug > 0 { b.Func.Warnl(b.Controls[0].Pos, "Redirect %s based on %s", b.Controls[0].Op, p.Controls[0].Op) } changed = true k-- break } ft.restore() } if len(b.Preds) == 0 && b != f.Entry { // Block is now dead. b.Kind = BlockInvalid
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue May 16 21:40:11 UTC 2023 - 3.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/func_attr.mlir
module attributes {tf.versions = {bad_consumers = [], min_consumer = 12 : i32, producer = 458 : i32}} { func.func @main() { tf_executor.graph { %control = tf_executor.island wraps "tf.NoOp"() {_f = #tf_type.func<@callee, {attr2 = true, attr3 = 8.0 : f32}>} : () -> () %control_1 = tf_executor.island(%control) wraps "tf.LegacyCall"() {f = @callee} : () -> () tf_executor.fetch } func.return }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 11 16:41:06 UTC 2023 - 1.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v2/testdata/outside_compilation.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Oct 19 20:19:45 UTC 2023 - 21.9K bytes - Viewed (0)