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tensorflow/compiler/mlir/tensorflow/transforms/resource_op_lifting.cc
} // Clone the callee before making changes. SmallString<64> name_base = callee.getName(); auto module = callee->getParentOfType<ModuleOp>(); name_base += "_resource_lifted"; auto name = name_base; callee = callee.clone(); callee.setPrivate(); callee.setName(mlir::StringAttr::get(callee->getContext(), name)); SymbolTable(module).insert(callee); result->lifted_callee = callee;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 55.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tensor_array_ops_decomposition.mlir
// CHECK-SAME: f = @callee %call = "tf.StatefulPartitionedCall"(%ta#0) {f = @callee, config = "", config_proto = "", executor_type = ""} : (tensor<!tf_type.resource>) -> tensor<!tf_type.resource> // CHECK: "tf.PartitionedCall"(%[[VAR]], %[[GVAR1]], %[[GVAR2]]) // CHECK-SAME: f = @callee %call2 = "tf.PartitionedCall"(%call) {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 - 49K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/resource_op_lifting.mlir
func.return %0 : tensor<*x!tf_type.resource<tensor<4xf32>>> } // ----- // Tests that the pass lifts resources on two partitioned call ops sharing the // same callee. The lifting should clone the callee then modify the clone. // CHECK-LABEL: @cluster_with_partitioned_call func.func @cluster_with_partitioned_call() -> tensor<f32> { // CHECK: %[[VH:.*]] = "tf.VarHandleOp"()
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/ir/tf_ops.td
return getArgsMutable(); } // Returns the callee of this operation. CallInterfaceCallable getCallableForCallee() { return getFAttr(); } // Sets the callee from the callable void setCalleeFromCallable(::mlir::CallInterfaceCallable callee); // Returns the resolved callee function of this operation. // Prefer passing in SymbolTableCollection to reduce lookup costs by
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 04:08:35 UTC 2024 - 90.5K bytes - Viewed (0) -
analysis/analysis-api-fir/src/org/jetbrains/kotlin/analysis/api/fir/components/KaFirResolver.kt
// If a function call is resolved to an implicit invoke call, the FirImplicitInvokeCall will have the `invoke()` function as the // callee and the variable as the explicit receiver. To correctly get all candidates, we need to get the original function // call's explicit receiver (if there is any) and callee (i.e., the variable). val unwrappedExplicitReceiver = explicitReceiver?.unwrapSmartcastExpression()
Registered: Wed Jun 12 09:53:16 UTC 2024 - Last Modified: Tue Jun 11 15:45:42 UTC 2024 - 73K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/sparsecore/embedding_pipelining.cc
if (!llvm::isa<func::FuncOp>(symbol)) { func.emitError() << "Invalid callee: " << caller.getF(); return LogicalResult::failure(); } auto callee = llvm::dyn_cast<func::FuncOp>(symbol_table.lookup(caller.getF())); auto& src_region = callee.getRegion(); auto result = inlineCall(*this, caller, callee, &src_region, true); if (failed(result)) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 92.9K bytes - Viewed (0) -
src/cmd/link/internal/ppc64/asm.go
su.SetRelocType(rIdx, objabi.R_CALLPOWER) // This is a local call, so the caller isn't setting // up r12 and r2 is the same for the caller and // callee. Hence, we need to go to the local entry // point. (If we don't do this, the callee will try // to use r12 to compute r2.) localEoffset := int64(ldr.SymLocalentry(targ)) if localEoffset == 1 { ldr.Errorf(s, "Unsupported NOTOC call to %s", targ) }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue Mar 19 20:54:08 UTC 2024 - 63.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/flatbuffer_import.cc
} if (op_name == "tfl.while") { // Adds two empty regions for "tfl.while". We will fill the regions after // creating the callee functions because the "tfl.while" input/output types // may be different with the callee functions, and the call ops need to sync // with callee function types. op_state.addRegion(); op_state.addRegion(); } if (op_name == "tfl.unidirectional_sequence_lstm") {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 66.8K bytes - Viewed (0) -
src/cmd/asm/internal/asm/testdata/arm64.s
TLBI ALLE1IS // 9f830cd5 TLBI VMALLS12E1IS // df830cd5 TLBI ALLE2 // 1f870cd5 TLBI ALLE1 // 9f870cd5 TLBI VMALLS12E1 // df870cd5 TLBI ALLE3IS // 1f830ed5 TLBI ALLE3 // 1f870ed5 TLBI VMALLE1OS // 1f8108d5
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Fri Dec 08 03:28:17 UTC 2023 - 94.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/compose_uniform_quantized_type_pass.cc
} // Matches the following pattern that represents uniform quantization: // // `call @uniform_quantize(%input, %inverse_scale, %zero_point)` // // Provides helper functions to access the operands and the callee. class UniformQuantizeFunctionCallPattern { public: // Returns Failure if it doesn't match. Returns the "wrapper" for the uniform // dequantization function call pattern when matched.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 64.6K bytes - Viewed (0)