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Results 21 - 30 of 59 for StatefulPartitionedCall (0.27 sec)
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tensorflow/compiler/mlir/tfrt/tests/ifrt/sink_variable_as_named_array.mlir
// // CHECK-LABEL: func.func @serving_default // CHECK-NOT: IfrtLoadVariable // CHECK: "tf.VarHandleOp" // CHECK-NEXT: "tf.AssignVariableOp" // CHECK-NEXT: "tf.ReadVariableOp" // CHECK-NEXT: "tf.StatefulPartitionedCall" // CHECK-NEXT: return // module { func.func @serving_default() -> tensor<*xi32> { %cst = "tf.Const"() <{value = dense<"some_test.txt"> : tensor<!tf_type.string>}> : () -> tensor<!tf_type.string>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 15:33:17 UTC 2024 - 5.3K bytes - Viewed (0) -
tensorflow/compiler/jit/build_xla_ops_pass_test.cc
NodeWith(Op("Switch"), Inputs(Out(0, xla_compile), Out(1, xla_compile))); auto xla_run = NodeWith(Op("_XlaRun"), Inputs(Out(1, predicated_compilation_key))); auto tf_call = NodeWith(Op("StatefulPartitionedCall"), CtrlDeps(NodeWith(Op("Identity"), Inputs(Out(0, predicated_compilation_key))))); auto merge = NodeWith(Op("_XlaMerge"), Inputs(Out(tf_call), Out(xla_run)));
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/tensorflow/tests/stack_ops_decomposition.mlir
// ----- // Tests PartitionedCall/StatefulPartitionedCall. // CHECK-LABEL: func @main func.func @main(%arg0: tensor<i1>) -> () { %max_size = "tf.Const"() {value = dense<10> : tensor<i32>} : () -> tensor<i32> // CHECK-NOT: tf.Stack %stack = "tf.StackV2"(%max_size) {elem_type = f32, stack_name = "s"} : (tensor<i32>) -> tensor<!tf_type.resource> // CHECK: "tf.StatefulPartitionedCall" // CHECK-SAME: f = @callee_stack_decomposed
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 25.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/sink_in_invariant_ops.mlir
// CHECK: [[handle:%.*]] = "tf.VarHandleOp"() %handle = "tf.VarHandleOp"() {container = "", shared_name = "x"} : () -> tensor<!tf_type.resource<tensor<i32>>> // CHECK: "tf.StatefulPartitionedCall"([[handle]]) %x = "tf.StatefulPartitionedCall"(%handle) {device = "/CPU:0", config = "", config_proto = "", executor_type = "", f = @some_func} : (tensor<!tf_type.resource<tensor<i32>>>) -> (tensor<i32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 21K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/hoist_invariant_ops.mlir
// CHECK-NOT: tf.VarHandleOp // CHECK: "tf._TfrtGetResource"() %handle = "tf.VarHandleOp"() {container = "", shared_name = "x"} : () -> tensor<!tf_type.resource<tensor<i32>>> // CHECK: tf.StatefulPartitionedCall %x = "tf.StatefulPartitionedCall"(%handle) {device = "/CPU:0", config = "", config_proto = "", executor_type = "", f = @some_func} : (tensor<!tf_type.resource<tensor<i32>>>) -> (tensor<i32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 01 23:54:14 UTC 2024 - 18.3K bytes - Viewed (0) -
tensorflow/compiler/jit/encapsulate_xla_computations_pass.h
// When add_edges_to_output_of_downstream_nodes is true, the output edges of // the xla_launch_node's immediate downstream nodes would be attached to the // generated xla node. For example, if the original graph is // StatefulPartitionedCall{_xla_compile_id=1} -> XlaClusterOutput -> NodeA // The output graph of this function would look like the following when // add_edges_to_output_of_downstream_nodes is true: // XlaLaunch -> NodeA
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 06:59:07 UTC 2024 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/end-to-end-tpu-reshard-variables.mlir
tf_executor.graph { %control = tf_executor.island { "tf.StatefulPartitionedCall"(%arg0) <{config = "", config_proto = "", executor_type = "", f = @partitioned}> : (tensor<*x!tf_type.resource>) -> () tf_executor.yield } tf_executor.fetch %control : !tf_executor.control }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 13 21:23:47 UTC 2024 - 4.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/components/tf_to_stablehlo.mlir
// ----- // This test makes sure functions with tf._noinline=true is not inlined. module { func.func @stateful_partitioned_call(%arg0: tensor<1x2x2x3xf32>) -> (tensor<1x2x2x3xf32>) { %0 = "tf.StatefulPartitionedCall"(%arg0) <{ config = "", config_proto = "", executor_type = "", f = @some_func }> { _collective_manager_ids = [], device = "" } : (tensor<1x2x2x3xf32>) -> tensor<1x2x2x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 08 20:05:12 UTC 2024 - 13.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model_freeze_assets.mlir
// CHECK: func @f(%arg0 func.func @f(%arg0: tensor<!tf_type.string> {tf_saved_model.bound_input = @v}) attributes {tf_saved_model.exported_names = ["f"]} { "tf.StatefulPartitionedCall"(%arg0) {config = "", config_proto = "", executor_type = "", f = @f_callee} : (tensor<!tf_type.string>) -> () func.return } func.func private @f_callee(%arg0: tensor<!tf_type.string>) { func.return
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/passes/clustering_passes.td
def XlaClusterFormationPass : Pass<"tf-xla-cluster-formation", "ModuleOp"> { let summary = "Encapsulate partitioned calls within a Cluster op"; let description = [{ This pass clusters `tf.PartitionedCall` and `tf.StatefulPartitionedCall` with `_xla_compile_device_type` attribute into a `tf_device.cluster`. Notice this pass will only rewrite the outermost call if there are nested
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 02:01:13 UTC 2024 - 19.8K bytes - Viewed (0)