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Results 31 - 40 of 56 for varhandle_op (0.33 sec)
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tensorflow/compiler/mlir/tensorflow/analysis/resource_value_typed_analyzer.cc
auto* operation = resource.getDefiningOp(); if (operation && isa<TF::VarHandleOp>(operation)) { mutable_variables_.insert(GetResourceKey(operation)); } } bool ResourceAnalyzer::IsPotentiallyWritten(Value resource) const { assert(IsResource(resource)); auto* operation = resource.getDefiningOp(); if (operation && isa<TF::VarHandleOp>(operation)) return mutable_variables_.contains(GetResourceKey(operation));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 15 09:04:13 UTC 2024 - 8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/freeze_global_tensors.cc
Operation *op = *latticeElement->getValue().ops.begin(); GlobalTensorOp globalTensor = llvm::dyn_cast<GlobalTensorOp>(op); if (!globalTensor) continue; // happens if the name is e.g. in a VarHandleOp. if (globalTensor.getIsMutable()) { freezeable[val] = false; continue; } freezeable[val] = true; // Verify users are supported kind.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 7.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/host_runtime/tpu_variable_runtime_reformatting.cc
// Creates the per-device variables that represent the formatting state of each // device. llvm::SmallVector<TF::VarHandleOp, 4> CreateStateVars( const llvm::SmallDenseMap<llvm::StringRef, llvm::SmallVector<StringRef, 4>>& devices, Location loc, RankedTensorType key_type, OpBuilder* builder) { llvm::SmallVector<TF::VarHandleOp, 4> state_vars; // TODO(b/148913020): Remove this constraint once model parallelism is // supported.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 21.9K bytes - Viewed (0) -
tensorflow/compiler/jit/build_xla_ops_pass_test.cc
result); } Node* MakeWrite(const Scope& scope, Output value_to_write, const string& id) { Output var_handle = ops::VarHandleOp(scope.WithOpName("Var_" + id), DT_FLOAT, TensorShape({})); ops::AssignVariableOp assign_op(scope.WithOpName("Assignee_" + id),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 08:47:20 UTC 2024 - 12.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/integration/node_expansion_pass.cc
static const char* kOpsToSkip[] = { "IdentityOp", "NoOp", // b/174596063 "OptionalHasValue", // b/173136483 "OptionalGetValue", // b/173136483 "VarHandleOp", // b/176819198 }; for (const char* skip : kOpsToSkip) { if (absl::StartsWith(orig_op->op_name(), skip)) return absl::OkStatus(); } tf_core_op_expansion_node_counter->GetCell()->IncrementBy(1);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Feb 25 16:22:36 UTC 2024 - 3.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/analysis/resource_dataflow.cc
symbol_table); ResourceConstructingOps result(global_tensor); return result; } } else if (auto vh = dyn_cast<TF::VarHandleOp>(value.getDefiningOp())) { return ResourceConstructingOps(vh); } else if (auto it = dyn_cast<TF::IteratorOp>(value.getDefiningOp())) { return ResourceConstructingOps(it); } return ResourceConstructingOps();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/cc/saved_model_import.h
// SavedModelBundle complements the imported ModuleOp by providing access to // `tensorflow::Session` which may be useful when reading values from resources // (e.g. `TF::VarHandleOp`s). using ImportedMlirModuleOp = std::pair<OwningOpRef<ModuleOp>, std::unique_ptr<::tensorflow::SavedModelBundle>>; // Loads a SavedModel at `saved_model_path` and converts it to `mlir::ModuleOp`. //
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 12:49:45 UTC 2024 - 4.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/mlrt/tf_to_mlrt.mlir
// Test lowering of IfrtLoadVariableOp // CHECK-LABEL: func @ifrt_load_variable_test func.func @ifrt_load_variable_test() -> () { // CHECK: [[HANDLE:%.*]] = tf_mlrt.executeop() // CHECK-SAME: VarHandleOp %0 = "tf.VarHandleOp"() {__op_key = 1: i32, device = "/device:CPU:0", container = "", shared_name = "variable"} : () -> tensor<!tf_type.resource<tensor<1x3xf32>>> // CHECK-NEXT: "tf_mlrt.ifrt_load_variable"([[HANDLE]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 20:44:15 UTC 2024 - 24.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/analyze_variables.cc
// Returns true if 'op' is TF op that accepts resource type, but is // supported by TFLite. bool IsSupportedTFLiteResourceOp(Operation* op) { return llvm::isa<TF::ReadVariableOp, TF::AssignVariableOp, TF::VarHandleOp, TF::LookupTableFindV2Op, TF::LookupTableImportV2Op, TF::LookupTableSizeV2Op>(op); } // Returns true if 'op' is TF/TFLite control flow op that can accept resource
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_cluster_formation.mlir
func.func @resource_before_cluster() { // CHECK-NEXT: [[CONST:%.*]] = "tf.Const" %0 = "tf.Const"() {value = dense<1.000000e+00> : tensor<f32>} : () -> tensor<f32> // CHECK-NEXT: [[UNUSED_RESOURCE:%.*]] = "tf.VarHandleOp" // CHECK-NEXT: "tf.AssignAddVariableOp"([[UNUSED_RESOURCE]], [[CONST]]) // CHECK: "tf_device.cluster" // CHECK-NEXT: "tf.NoOp" // CHECK-NEXT: tf_device.return
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 22:03:30 UTC 2024 - 53.9K bytes - Viewed (0)