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Results 61 - 70 of 108 for input_type (0.12 sec)
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pkg/test/echo/proto/echo.pb.go
7, // 9: proto.EchoTestService.ForwardEcho:output_type -> proto.ForwardEchoResponse 8, // [8:10] is the sub-list for method output_type 6, // [6:8] is the sub-list for method input_type 6, // [6:6] is the sub-list for extension type_name 6, // [6:6] is the sub-list for extension extendee 0, // [0:6] is the sub-list for field type_name } func init() { file_test_echo_proto_echo_proto_init() }
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Fri May 31 02:27:10 UTC 2024 - 33.3K bytes - Viewed (0) -
pkg/workloadapi/workload.pb.go
11, // 20: istio.workload.Workload.ServicesEntry.value:type_name -> istio.workload.PortList 21, // [21:21] is the sub-list for method output_type 21, // [21:21] is the sub-list for method input_type 21, // [21:21] is the sub-list for extension type_name 21, // [21:21] is the sub-list for extension extendee 0, // [0:21] is the sub-list for field type_name }
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Wed Jun 12 18:02:35 UTC 2024 - 65.9K bytes - Viewed (0) -
tensorflow/c/c_api.cc
} int TF_OperationNumInputs(TF_Operation* oper) { return oper->node.num_inputs(); } TF_DataType TF_OperationInputType(TF_Input oper_in) { return static_cast<TF_DataType>(oper_in.oper->node.input_type(oper_in.index)); } int TF_OperationInputListLength(TF_Operation* oper, const char* arg_name, TF_Status* status) { NameRangeMap name_ranges; status->status =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tpu_annotate_dynamic_shape_inputs.cc
for (int index : dynamic_shape_arg_index) { BlockArgument arg = func.getArgument(index); auto inputType = mlir::dyn_cast<RankedTensorType>(arg.getType()); // Only rank 1 tensor is supported for now. if (!inputType || inputType.getRank() != 1) continue; auto shape = llvm::to_vector<4>(inputType.getShape()); llvm::SmallVector<int64_t, 4> bounds(shape.begin(), shape.end()); // Mark the dim as dynamic dim.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/passes/raise_to_tf.cc
const llvm::SmallVectorImpl<Attribute>& input_types, llvm::SmallVectorImpl<Value>& input_values) const { if (input_types.size() <= 1) return; Type target_input_type = mlir::cast<TypeAttr>(input_types[0]).getValue(); auto result_type = UnrankedTensorType::get(target_input_type); for (auto i = 1; i < input_types.size(); ++i) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 21.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.cc
ArrayRef<int64_t> shape = arg_shapes[i]; Type element_type; if (auto input_ty = mlir::dyn_cast<RankedTensorType>(func_type.getInput(i))) { if (input_ty.getRank() != shape.size()) { return failure(); } element_type = input_ty.getElementType(); } else { auto unranked_input_ty =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 08 07:28:49 UTC 2024 - 134.1K bytes - Viewed (0) -
subprojects/core/src/main/java/org/gradle/api/internal/initialization/transform/ExternalDependencyInstrumentingArtifactTransform.java
File input = getInput().get().getAsFile(); InstrumentationInputType inputType = getInputType(input); switch (inputType) { case DEPENDENCY_ANALYSIS_DATA: doOutputTransformedFile(input, outputs); return; case ORIGINAL_ARTIFACT:
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu Apr 18 15:08:33 UTC 2024 - 4.4K bytes - Viewed (0) -
subprojects/core/src/main/java/org/gradle/api/internal/initialization/transform/MergeInstrumentationAnalysisTransform.java
File input = getInput().get().getAsFile(); InstrumentationInputType inputType = getInputType(input); switch (inputType) { case DEPENDENCY_ANALYSIS_DATA: doMergeAndOutputAnalysis(input, outputs); return; case ORIGINAL_ARTIFACT:
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu Apr 18 15:08:33 UTC 2024 - 6.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/ir/QuantOps.cc
for (auto input : llvm::zip(getOperandTypes(), getInputSpecs())) { Type inputType = std::get<0>(input); Attribute inputSpec = std::get<1>(input); if (!isValidQuantizationSpec(inputSpec, inputType)) { return emitOpError() << "has incompatible specification " << inputSpec << " and input type " << inputType; } } for (auto result : llvm::zip(getResultTypes(), getOutputSpecs())) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/ir/QuantOps.cc
for (auto input : llvm::zip(getOperandTypes(), getInputSpecs())) { Type inputType = std::get<0>(input); Attribute inputSpec = std::get<1>(input); if (!isValidQuantizationSpec(inputSpec, inputType)) { return emitOpError() << "has incompatible specification " << inputSpec << " and input type " << inputType; } } for (auto result : llvm::zip(getResultTypes(), getOutputSpecs())) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.3K bytes - Viewed (0)