- Sort Score
- Result 10 results
- Languages All
Results 1 - 10 of 39 for tflite (0.13 sec)
-
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/importer_test_min_max.cc
#include "llvm/Support/raw_ostream.h" #include "tensorflow/compiler/mlir/lite/schema/schema_generated.h" #include "tensorflow/compiler/mlir/lite/schema/schema_utils.h" #include "tensorflow/lite/model.h" using llvm::cl::opt; // RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s.mlir -o - \ // RUN: | %p/importer_test_min_max - \ // RUN: | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - \ // RUN: | FileCheck %s
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 6.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights.cc
const tflite::Model* input_model, BufferType quant_type, bool use_updated_hybrid_scheme) { tflite::TensorType inference_type; switch (quant_type) { case BufferType::QUANTIZED_FLOAT16: inference_type = tflite::TensorType_FLOAT16; break; default: inference_type = tflite::TensorType_INT8; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/sparsity/sparsify_model.cc
flatbuffers::Offset<tflite::Model> input_model_location = tflite::Model::Pack(input_builder, &input_model); tflite::FinishModelBuffer(input_builder, input_model_location); std::string serialized_model( reinterpret_cast<const char*>(input_builder.GetBufferPointer()), input_builder.GetSize()); OwningOpRef<mlir::ModuleOp> module = tflite::FlatBufferToMlir(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Jun 10 20:16:40 UTC 2024 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_model.cc
<< ", input_inference_type: " << tflite::EnumNameTensorType(input_type) << ", output_inference_type: " << tflite::EnumNameTensorType(output_type) << "\n"; mlir::Builder mlir_builder(&context); mlir::Type input_mlir_type = tflite::ConvertElementType(input_type, mlir_builder); mlir::Type output_mlir_type = tflite::ConvertElementType(output_type, mlir_builder);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/python/converter_python_api_wrapper.cc
return tensorflow::PyoOrThrow( tflite::MlirSparsifyModel(input_contents_txt_raw.ptr())); }, py::arg("input_contents_txt_raw"), R"pbdoc( Returns a sparsified model. )pbdoc"); m.def( "RegisterCustomOpdefs", [](py::object custom_opdefs_txt_raw) { return tensorflow::PyoOrThrow( tflite::RegisterCustomOpdefs(custom_opdefs_txt_raw.ptr())); },
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 18:18:30 UTC 2024 - 5.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/sparsity/sparsify_model_test.cc
// Load input model auto input_fbm = tflite::FlatBufferModel::BuildFromFile( "tensorflow/lite/testdata/sparse_tensor.bin"); tflite::ModelT input_model; input_fbm->GetModel()->UnPackTo(&input_model); // Populate input metadata auto model_metadata_buffer = std::make_unique<tflite::BufferT>(); model_metadata_buffer->data = std::vector<uint8_t>(expected_value.begin(), expected_value.end());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Jun 10 20:16:40 UTC 2024 - 2.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/execution_metadata_exporter.cc
#include "mlir/Support/LLVM.h" // from @llvm-project #include "tensorflow/compiler/mlir/lite/experimental/tac/common/targets.h" #include "tensorflow/compiler/mlir/lite/experimental/tac/hardwares/target_hardware.h" #include "tensorflow/compiler/mlir/lite/experimental/tac/runtime_metadata_generated.h" #include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h" #include "tensorflow/compiler/mlir/lite/quantization/ir/QuantOps.h"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 06:11:34 UTC 2024 - 7.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights.h
// quantization, specifically for // third_party/tensorflow/lite/tools/optimize/quantize_weights.h. // TODO(b/202468183): Selective quantization + quant debugger support for // 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,
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
#include "flatbuffers/flatbuffers.h" // from @flatbuffers #include "flatbuffers/minireflect.h" // from @flatbuffers #include "tensorflow/compiler/mlir/lite/schema/reflection/schema_generated.h" #if FLATBUFFERS_LITTLEENDIAN == 0 #include "tensorflow/lite/core/model_builder.h" #endif namespace tflite { namespace { // Reads a model from a provided file path and verifies if it is a valid
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 15:52:23 UTC 2024 - 4.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_model.h
// of double, and call TOCO's quantization routines to maintain bit-exactness of // the values with the TOCO quantizer. TfLiteStatus QuantizeModel( absl::string_view model_buffer, const tflite::TensorType &input_type, const tflite::TensorType &output_type, const tflite::TensorType &inference_type, const std::unordered_set<std::string> &operator_names, bool disable_per_channel, bool fully_quantize, std::string &output_buffer,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 2.8K bytes - Viewed (0)