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Results 41 - 50 of 68 for StatefulPartitionedCall (0.51 sec)
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tensorflow/compiler/mlir/tensorflow/tests/tensor_array_ops_decomposition.mlir
// CHECK: %[[GVAR2:.*]] = "tf.MlirLocalVarOp"() : () -> tensor<!tf_type.resource<tensor<5x3xf32>>> // CHECK: "tf.StatefulPartitionedCall"(%[[VAR]], %[[GVAR1]], %[[GVAR2]]) // CHECK-SAME: f = @callee_tensorarray_decomposed %call = "tf.StatefulPartitionedCall"(%ta#0) {f = @callee, config = "", config_proto = "", executor_type = ""} : (tensor<!tf_type.resource>) -> tensor<!tf_type.resource>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 49K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_device_passes.td
let summary = "Rewrites partition calls into Xla launch ops to make the attached function run on XLA."; let description = [{ This pass rewrites `tf.PartitionedCall` and `tf.StatefulPartitionedCall` operations with `_xla_compile_device_type` attribute in a `tf_device.cluster` into `tf.XlaLaunch` operations. This makes the attached function execute with XLA. `tf.XlaLaunch` requires resource-type arguments
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/tensorflow/tests/resource_op_lifting.mlir
// CHECK: %[[CLUSTER:.*]] = "tf_device.cluster"() "tf_device.cluster"() ({ // CHECK: %[[PC0:.*]] = "tf.StatefulPartitionedCall"(%[[READ0]], %[[READ1]], %[[CONST]]) // CHECK-SAME: f = @callee_resource_lifted %3 = "tf.StatefulPartitionedCall"(%0, %1, %2) {f = @callee, config = "", config_proto = "", executor_type = ""}
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/tf2xla/internal/mlir_bridge_pass_util.cc
bool IsNonReplicatedGraph(const Graph& graph, const FunctionLibraryDefinition* function_library) { auto predicate = [](const Graph& graph) { const std::string kStatefulPartitionedCallOp = "StatefulPartitionedCall"; for (const Node* node : graph.nodes()) { auto node_op = node->type_string(); if (node_op == kStatefulPartitionedCallOp) { // Functions called by StatefulfulPartitionedCall ops with
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 07 12:22:33 UTC 2024 - 8.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/quantize_preprocess.cc
pm.addNestedPass<mlir::func::FuncOp>( mlir::quant::stablehlo::CreateConvertTFQuantOpsToMHLOPass()); pm.addPass(mlir::createCanonicalizerPass()); // TF -> StableHLO legalization. // Skip StatefulPartitionedCall to preserve aliased functions. mlir::odml::AddLegalizeTFToStablehloPasses(pm, /*skip_quantization_ops=*/true, /*skip_resize=*/false,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 12:49:45 UTC 2024 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/replace_stablehlo_ops_in_main_function_with_xla_call_module_ops.mlir
// CHECK: return %[[SUBGRAPH_1]] : tensor<1024x3xf32> // CHECK: } } // ----- // main function contains PartitionedCall and StatefulPartitionedCall ops which // is used to preserve aliased functions. This test make sure stablehlo ops in // each PartitionedCall functions are lifted.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 01:09:50 UTC 2024 - 39.8K bytes - Viewed (0) -
tensorflow/compiler/jit/build_xla_ops_pass.cc
// we don't have any evidence that choosing a stateless partitioned call helps // for performance. ops::StatefulPartitionedCall call( root.WithOpName("stateful_partitioned_call"), args, n->output_types(), func, ops::StatefulPartitionedCall::Attrs{}.ConfigProto(config_string)); for (const Edge* e : n->in_edges()) { if (e->IsControlEdge()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 06:33:33 UTC 2024 - 24.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model_optimize_global_tensors_interprocedural.mlir
func.func @f(%arg0: tensor<!tf_type.resource<tensor<f32>>> {tf_saved_model.bound_input = @v}) -> (tensor<f32> {tf_saved_model.index_path = []}) attributes {tf_saved_model.exported_names = ["f"]} { %val = "tf.StatefulPartitionedCall"(%arg0) {config = "", config_proto = "", executor_type = "", f = @f_callee} : (tensor<!tf_type.resource<tensor<f32>>>) -> (tensor<f32>) func.return %val : tensor<f32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:49:35 UTC 2023 - 10.8K bytes - Viewed (0) -
tensorflow/c/experimental/saved_model/internal/saved_model_api_test.cc
// dtype: DT_FLOAT // tensor_shape: { // } // } // } // outputs: { // key : "output_0" // value: { // name : "StatefulPartitionedCall:0" // dtype: DT_FLOAT // tensor_shape: { // } // } // } // method_name: "tensorflow/serving/predict" // } // }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 23 08:08:45 UTC 2024 - 21.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/sparsecore/embedding_sequencing.cc
} } TF::StatefulPartitionedCallOp MakeFuncCaller( mlir::OpBuilder& builder, const Location& loc, func::FuncOp func, const llvm::SetVector<Value>& operands) { // Constructs a tf.StatefulPartitionedCall to the function provided in 'func' // using the operands in 'operands'. Assumes the insertion point on builder is // already set. auto symbol =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 39.4K bytes - Viewed (0)