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Results 1 - 7 of 7 for unpackInto (0.29 sec)
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platforms/core-runtime/base-services/src/main/java/org/gradle/internal/ImmutableActionSet.java
if (action instanceof ImmutableActionSet) { ImmutableActionSet<T> immutableSet = Cast.uncheckedNonnullCast(action); immutableSet.unpackInto(builder); } else { builder.add(action); } } protected abstract void unpackInto(ImmutableSet.Builder<Action<? super T>> builder); /** * Creates a new set that runs the actions of this set plus the given action. */
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Fri Sep 22 08:48:02 UTC 2023 - 11K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema_generated.h
auto _o = std::unique_ptr<CustomQuantizationT>(new CustomQuantizationT()); UnPackTo(_o.get(), _resolver); return _o.release(); } inline void CustomQuantization::UnPackTo(CustomQuantizationT *_o, const ::flatbuffers::resolver_function_t *_resolver) const { (void)_o; (void)_resolver;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 1M 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/quantization/lite/quantize_model_test.cc
// // This helper is useful as UnPackTo requires the input to not have any existing // state so directly calling UnPackTo could lead to memory leaks if the model // already had some state. Instead, the returned object from here can be used to // overwrite existing model. ModelT UnPackFlatBufferModel(const Model& flatbuffer_model) { ModelT model; flatbuffer_model.UnPackTo(&model); return model; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 73.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/python/converter_python_api.cc
if (!model) { PyErr_Format(PyExc_ValueError, "Invalid model"); return nullptr; } auto tflite_model = std::make_unique<tflite::ModelT>(); model->GetModel()->UnPackTo(tflite_model.get(), nullptr); const tflite::TensorType inference_tensor_type = FromTocoDataTypeToTflitToTensorType(inference_type); const tflite::TensorType input_type =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 19.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights.cc
return op_name.lower(); } std::unique_ptr<tflite::ModelT> CreateMutableModelFromFile( const tflite::Model* input_model) { auto copied_model = std::make_unique<tflite::ModelT>(); input_model->UnPackTo(copied_model.get(), nullptr); return copied_model; } } // namespace // TODO(b/214314076): Support MLIR model as an input for the C++ dynamic range // quantization API TfLiteStatus QuantizeWeights(
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/quantization/lite/quantize_weights_test.cc
constexpr bool kUseUpdatedHybridSchemeDefault = true; std::unique_ptr<ModelT> CreateMutableModelFromFile(const Model* input_model) { auto copied_model = std::make_unique<ModelT>(); input_model->UnPackTo(copied_model.get(), nullptr); return copied_model; } std::unique_ptr<FlatBufferModel> ReadTestModel() { auto model_path = tensorflow::io::JoinPath( *g_test_model_dir, internal::kConvModelWith0Plus10Weights);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 32.3K bytes - Viewed (0)