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Results 21 - 30 of 56 for varhandle_op (0.33 sec)
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tensorflow/compiler/jit/shape_inference_test.cc
TEST(ShapeInferenceTest, WhileLoopWithResource) { // Graph: // x = resource_variable_ops.var_handle_op(dtype=dtypes.float32, shape=[2, 3]) // y = control_flow_ops.while_loop(lambda _: true, lambda x: x, [x]) Graph graph(OpRegistry::Global()); { Scope scope = Scope::NewRootScope().ExitOnError(); auto x = ops::VarHandleOp(scope.WithOpName("x"), DT_FLOAT, TensorShape({2, 3})); auto enter =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 00:41:19 UTC 2024 - 10.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/mlrt/rewrite_ifrt_load_variable.mlir
// Variable is used by both CPU and TPU // // CHECK-LABEL: func @serving_default(%arg0: tensor<1x3xf32>) -> tensor<1x1xf32> // CHECK-NEXT: [[HANDLE:%.*]] = "tf.VarHandleOp"() // CHECK-NEXT: [[ARRAYKEY:%.*]], [[FURTURE:%.*]] = "tf_mlrt.tf_ifrt_load_variable"([[HANDLE]]) // CHECK-SAME: <{used_by_host = true}> : (tensor<!tf_type.resource<tensor<3x1xf32>>>) -> (tensor<!tf_type.string>, !mlrt.future)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 21:35:32 UTC 2024 - 1.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/ifrt/tf_restore_pruning.mlir
// CHECK-NOT: tf.RestoreV2 %0 = "tf.RestoreV2"(%cst, %cst_1, %cst_0): (tensor<!tf_type.string>, tensor<1x!tf_type.string>, tensor<1x!tf_type.string>) -> tensor<3x1xf32> %1 = "tf.VarHandleOp"() <{container = "", shared_name = "y"}> : () -> tensor<!tf_type.resource<tensor<3x1xf32>>> return } // CHECK-LABEL: func.func @used_restore_remains func.func @used_restore_remains() {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 25 22:02:06 UTC 2024 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mlprogram.mlir
%0 = tf_executor.graph { %outputs_4, %control_5 = tf_executor.island wraps "tf.VarHandleOp"() {container = "", shared_name = "Variable"} : () -> tensor<!tf_type.resource<tensor<!tf_type.string>>> %outputs_10, %control_11 = tf_executor.island wraps "tf.VarHandleOp"() {container = "", shared_name = "Variable_1"} : () -> tensor<!tf_type.resource<tensor<!tf_type.string>>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 19:27:16 UTC 2024 - 7.4K bytes - Viewed (0) -
tensorflow/compiler/aot/aot_only_var_handle_op.cc
#include "tensorflow/compiler/tf2xla/xla_op_registry.h" #include "tensorflow/core/framework/shape_inference.h" namespace tensorflow { namespace { // Implementation of varhandle that binds a VarHandleOp to an XlaResource of the // same name. It is not safe to use this op in a JIT context. class XlaAotOnlyVarHandleOp : public XlaOpKernel { public: explicit XlaAotOnlyVarHandleOp(OpKernelConstruction* c);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 28 09:57:04 UTC 2024 - 3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/basic.mlir
// CHECK-NOT: "tf_saved_model.session_initializer" "tf_saved_model.session_initializer"() { initializers = [@func_init] } : () -> () // CHECK-LABEL: _tfrt_resource_init // CHECK: tf.VarHandleOp // CHECK: tf.ReadVariableOp // CHECK: tfrt_fallback_async.set_resource // CHECK-SAME: {device = "/device:CPU:0", index = 0 : i64} // CHECK-LABEL: func @init // CHECK-SAME: {tfrt.cost_threshold = 1 : i64}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/tf_to_corert_pipeline_refvar.mlir
// CHECK-NEXT: [[o_chain:%.*]], [[o:%.*]] = tfrt_fallback_async.executeop.seq([[in_chain]]) key(0) cost({{.*}}) device("/job:localhost/replica:0/task:0/device:CPU:0") "tf.VarHandleOp"() // CHECK-NEXT: [[o_chain_0:%.*]], [[o1:%.*]] = tfrt_fallback_async.executeop.seq([[in_chain]]) key(1) cost({{.*}}) device("/job:localhost/replica:0/task:0/device:CPU:0") "tf.ReadVariableOp"([[o]]) {dtype = f32} : 1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_device_passes.td
resource variables directly.. Here is a simple example in TensorFlow where a device doubles the value of a TensorFlow resource variable and returns new value: ```mlir %resource_handle = "tf.VarHandleOp"() %1 = "tf_device.cluster"() ( { %init_value = "tf.ReadVariableOp"(%resource_handle) "tf.AssignAddVariableOp"(%resource_handle, %init_value) %new_value = "tf.ReadVariableOp"(%resource_handle)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 17 18:52:57 UTC 2024 - 12.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/batch_function_lowering.mlir
} // CHECK-LABEL: func @main func.func @main(%arg0: tensor<1x3xf32>) -> tensor<*xf32> attributes {tf.entry_function = {control_outputs = "", inputs = "input:0", outputs = "batch/BatchFunction:0"}} { %0 = "tf.VarHandleOp"() {device = "/device:CPU:0", container = "", shared_name = "variable"} : () -> tensor<!tf_type.resource<tensor<1x3xf32>>> // CHECK: tfrt_fallback_async.batch_function device("/device:CPU:0") @batched_function
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 2K bytes - Viewed (0) -
tensorflow/compiler/jit/mark_for_compilation_pass_test.cc
namespace { Node* MakeRead(const Scope& scope, const string& id, Node** var_handle_op = nullptr) { Output var_handle = ops::VarHandleOp(scope.WithOpName("Var" + id), DT_FLOAT, TensorShape({})); Output read = ops::ReadVariableOp(scope.WithOpName("Read" + id), var_handle, DT_FLOAT); if (var_handle_op) { *var_handle_op = var_handle.node(); } return read.node(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 14 10:11:10 UTC 2024 - 79.6K bytes - Viewed (0)