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Results 21 - 30 of 286 for TfLite (0.21 sec)
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tensorflow/compiler/mlir/lite/flatbuffer_translate.cc
bool use_buffer_offset; bool emit_stablehlo_ops; bool disable_vhlo_to_stablehlo; // NOLINTNEXTLINE static opt<bool, true> emit_builtin_tflite_ops_flag( "emit-builtin-tflite-ops", llvm::cl::desc( "Emit TFLite built in operations in the generated TFLite model"), llvm::cl::location(emit_builtin_tflite_ops), llvm::cl::init(true)); // NOLINTNEXTLINE static opt<bool, true> emit_select_tf_ops_flag(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 14 19:15:40 UTC 2024 - 9.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/metrics/types_util.cc
[&]() {}); }); } }; } // namespace tflite::metrics::ConverterErrorData NewConverterErrorData( const std ::string& pass_name, const std::string& error_message, tflite::metrics::ConverterErrorData::ErrorCode error_code, const std::string& op_name, const Location& location) { using tflite::metrics::ConverterErrorData; ConverterErrorData error; if (!pass_name.empty()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 4.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tflite_import_export.h
namespace mlir { namespace TFL { namespace tac { // TAC Importer for TFLite. // This import to MLIR from tflite file or MLIR class TfLiteImporter : public mlir::TFL::tac::TacImporter { public: // Options for configuring the importer. struct Options { std::string file_name; // Whether the input file is an MLIR not tflite file. bool input_mlir = false; };
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 08 01:19:25 UTC 2023 - 2.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/metrics/types_util.h
struct ConverterErrorDataComparison { std::size_t operator()( const tflite::metrics::ConverterErrorData& a, const tflite::metrics::ConverterErrorData& b) const noexcept { return ConverterErrorDataHash()(a) == ConverterErrorDataHash()(b); } }; // Helper function to create a new ConverterErrorData. tflite::metrics::ConverterErrorData NewConverterErrorData(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Sep 01 16:09:28 UTC 2022 - 2.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/disable_builtin.mlir
// RUN: not flatbuffer_translate -mlir-to-tflite-flatbuffer -emit-builtin-tflite-ops=false %s 2>&1 | FileCheck %s // CHECK: 'tfl.add' op is a TFLite builtin op but builtin emission is not enabled func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32> { ^bb0(%arg0: tensor<3x2xi32>): %0 = "arith.constant"() {name = "Const2", value = dense<10> : tensor<i32>} : () -> tensor<i32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 24 07:31:32 UTC 2022 - 547 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/analyze_variables.cc
// Attribute name to be added on the module to identify whether // variables should be legalized to TFLite or not. const char kLegalizeTflVariables[] = "tfl._legalize_tfl_variables"; // Returns true if 'op' is TF op that accepts resource type, but is // supported by TFLite. bool IsSupportedTFLiteResourceOp(Operation* op) { return llvm::isa<TF::ReadVariableOp, TF::AssignVariableOp, TF::VarHandleOp,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/flatbuffer_import.cc
using mlir::func::FuncOp; using tflite::OperatorT; using tflite::TensorT; namespace errors = tensorflow::errors; namespace tfl = mlir::TFL; namespace { constexpr char kScatterRegionFuncName[] = "update_computation_func_name"; using ::mlir::tf_saved_model::kTfSavedModelExportedNamesAttr; using ::mlir::tf_saved_model::kTfSavedModelIndexPathAttr; using ::tflite::IsValidBufferOffset;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 66.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tac.py
"""Target aware conversion for TFLite model.""" from tensorflow.compiler.mlir.lite.experimental.tac.py_wrapper import _pywrap_tac_wrapper def run_tac(model_path, targets, output_path): """Run target aware conversion for the given tflite model file. Args: model_path: Path to the tflite model file. targets: A list of string of the desired targets. E.g., ['GPU', 'CPU'].
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jul 21 01:22:53 UTC 2021 - 1.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights.h
// dynamic range quantization for verify_numeric and whole_model_verify flags. TfLiteStatus QuantizeWeights( flatbuffers::FlatBufferBuilder* builder, const tflite::Model* input_model, const tflite::TensorType& inference_type, const absl::flat_hash_set<std::string>& denylisted_ops, const CustomOpMap& custom_op_map, int64_t minimum_elements_for_weights = 1024,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 4.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/flatbuffer_to_string.cc
return 1; } std::string serialized_model; if (tflite::ReadAndVerify(argv[1], &serialized_model)) return 1; #if FLATBUFFERS_LITTLEENDIAN == 0 // If the flatbuffer model comes from stdin, convert its tensor content from // BE to LE to ensure the output text string is the same as on LE platforms. if (std::string(argv[1]) == "-") tflite::FlatBufferModel::ByteSwapSerializedModel(&serialized_model, true); #endif
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 15:52:23 UTC 2024 - 4.8K bytes - Viewed (0)