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Results 1 - 10 of 10 for var_handle_op (0.17 sec)
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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) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td
shared_name: the name by which this variable is referred to. dtype and shape: attributes representing the data type and shape held in the variable. Example: resource_variable_ops.var_handle_op( dtype=dtypes.int32, shape=[8, 16], container="foo", shared_name="bar") returns a handle for a variable with name "bar" in container "foo", and the variable holds a tensor of shape [8, 16] and dtype int32. }];
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 04:08:35 UTC 2024 - 90.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/decompose_resource_ops.mlir
// CHECK-DAG: [[VAR_HANDLE:%.*]] = "tf.VarHandleOp" // CHECK-DAG: [[MG_HANDLE:%.*]] = "tf.VarHandleOp" // CHECK-DAG: [[MS_HANDLE:%.*]] = "tf.VarHandleOp" // CHECK-DAG: [[MOM_HANDLE:%.*]] = "tf.VarHandleOp" %0 = "tf.VarHandleOp"() {container = "c", shared_name = "v"} : () -> tensor<*x!tf_type.resource<tensor<f32>>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 19:47:48 UTC 2024 - 51.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/resource_op_lifting.mlir
// CHECK-LABEL: func @cluster_with_nested_loop func.func @cluster_with_nested_loop() -> () { // CHECK: %[[VH:.*]] = "tf.VarHandleOp"() %0 = "tf.VarHandleOp"() {container = "c", shared_name = "v"} : () -> tensor<*x!tf_type.resource<tensor<f32>>> // CHECK: %[[VH_UNUSED:.*]] = "tf.VarHandleOp"() %1 = "tf.VarHandleOp"() {container = "c", shared_name = "v2"} : () -> tensor<*x!tf_type.resource<tensor<f32>>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 74K 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/c/eager/c_api_test.cc
TFE_DeleteContextOptions(opts); TFE_Op* var_op = TFE_NewOp(ctx, "VarHandleOp", status); TFE_OpSetAttrType(var_op, "dtype", TF_INT64); TFE_OpSetAttrShape(var_op, "shape", {}, 0, status); const TFE_OpAttrs* attributes = TFE_OpGetAttrs(var_op); TFE_Op* copy_op = TFE_NewOp(ctx, "VarHandleOp", status); TFE_OpSetAttrType(copy_op, "dtype", TF_FLOAT); TFE_OpAddAttrs(copy_op, attributes);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Aug 03 20:50:20 UTC 2023 - 94.6K 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/g3doc/_includes/tf_passes.md
if the variable is read only. For example, the following pseudo MLIR code (types are left out for brevity) ```mlir func.func @hoist_loop_invariant(%arg0, %arg1) { %var = "tf.VarHandleOp"() {container="", shared_name="var_name", device = "/device:CPU:0"} %results:2 = "tf.WhileRegion"(%arg0, %arg1) ({ ^bb0(%arg2, %arg3): %0 = "tf.OpA"() {is_stateless = true} "tf.Yield"(%0)
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/tfrt/tests/mlrt/while_to_map_fn.mlir
%outputs_8 = "tf.Const"() {device = "/job:localhost/replica:0/task:0/device:CPU:0", value = dense<1> : tensor<i32>} : () -> tensor<i32> // CHECK: [[elems:%.*]] = "tf.VarHandleOp" %outputs_10 = "tf.VarHandleOp"() {_xla_inferred_shapes = [#tf_type.shape<>], allowed_devices = [], container = "", device = "/job:localhost/replica:0/task:0/device:CPU:0", shared_name = "w"} : () -> tensor<!tf_type.resource<tensor<3x1xf32>>>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 23 06:40:22 UTC 2024 - 68.6K bytes - Viewed (0) -
tensorflow/compiler/jit/mark_for_compilation_pass.cc
if (std::optional<absl::string_view> cluster_name = GetXlaClusterForNode(*n)) { n->set_name(absl::StrCat(*cluster_name, "/", n->name())); } else if (n->type_string() == "VarHandleOp") { n->set_name(absl::StrCat("varhandle/", n->name())); } else { // There is room for improvement here. In particular, it may help to
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 12:19:41 UTC 2024 - 85.3K bytes - Viewed (0)