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Results 41 - 50 of 56 for var_handle_op (0.24 sec)
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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) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_globals_to_ml_program.cc
if (auto global = tf_saved_model::LookupBoundInputOfType< tf_saved_model::GlobalTensorOp>(func, i, syms)) { OpBuilder builder(func.getBody()); auto dummy = builder.create<TF::VarHandleOp>( global.getLoc(), func.getArgument(i).getType(), "dummy", "dummy"); func.getArgument(i).replaceAllUsesWith(dummy.getResult()); argsToErase.set(i); } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.6K bytes - Viewed (0) -
tensorflow/c/eager/c_api_test_util.cc
TFE_TensorHandle* TestVariable(TFE_Context* ctx, float value, const tensorflow::string& device_name) { TF_Status* status = TF_NewStatus(); // Create the variable handle. TFE_Op* op = TFE_NewOp(ctx, "VarHandleOp", status); if (TF_GetCode(status) != TF_OK) return nullptr; TFE_OpSetAttrType(op, "dtype", TF_FLOAT); TFE_OpSetAttrShape(op, "shape", {}, 0, status); TFE_OpSetAttrString(op, "container", "localhost", 0);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 22:37:46 UTC 2024 - 23.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/convert_control_to_data_outputs.mlir
// Tests loop with two resource types, one of them being unique per iteration. // // Similar to above test but with one additional resource that is not unique per // iteration (created by `tf.VarHandleOp`). func.func @mixed_unique_resource_chain(%arg0: tensor<i32>, %arg1: tensor<f32>) { tf_executor.graph {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 18:35:00 UTC 2024 - 68.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mark_ops_for_outside_compilation.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 16:22:32 UTC 2024 - 29.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
func.func @infer_var_handle_op_from_assigns() -> tensor<1xi8> { %cst = arith.constant dense<1> : tensor<1xi8> %0 = "tf.VarHandleOp"() {container = "", shared_name = "bar"} : () -> tensor<!tf_type.resource<tensor<*xi8>>> // CHECK: "tf.VarHandleOp"() <{container = "", shared_name = "bar"}> : () -> tensor<!tf_type.resource<tensor<1xi8>>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 17:24:10 UTC 2024 - 167.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/control_flow.mlir
func.return %arg : tensor<!tf_type.resource<tensor<i32>>> } // CHECK-LABEL: func @side_effect_while_test func.func @side_effect_while_test() -> (tensor<i32>) { %0 = "tf.VarHandleOp"() {device = "/device:CPU:0", container = "c", shared_name = "v"} : () -> tensor<!tf_type.resource<tensor<i32>>> // CHECK: [[while_res:%.]]:2 = tfrt.while {{%.*}} @"side_effect_while_body_add2/tfrt_body_1"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 00:40:32 UTC 2024 - 17.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
to input arguments and outputs of the function(s). Two types of resources are supported: (1) A function argument of TF::ResourceType type (this pass). (2) A VarHandleOp in the function (tf-promote-var-handles-to-args). After the pass, . The function will have an input argument for each resource that is
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/transforms/passes.h
// aliasing output arguments. std::unique_ptr<OperationPass<ModuleOp>> CreatePromoteResourcesToArgsPass( llvm::ArrayRef<std::string> functions = {}); // Creates a pass that promotes tf.VarHandleOp to resource arguments for all // functions. std::unique_ptr<OperationPass<ModuleOp>> CreatePromoteVarHandlesToArgsPass(); // Creates a pass that converts readonly reference variables to the
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 31.8K bytes - Viewed (0)