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.github/ISSUE_TEMPLATE/tflite-other.md
TensorFlower Gardener <******@****.***> 1672352909 -0800
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Dec 29 22:28:29 UTC 2022 - 3.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/convert_type.cc
case tflite::TensorType_FLOAT16: return builder.getF16Type(); case tflite::TensorType_BFLOAT16: return builder.getBF16Type(); case tflite::TensorType_FLOAT32: return builder.getF32Type(); case tflite::TensorType_FLOAT64: return builder.getF64Type(); case tflite::TensorType_INT32: return builder.getIntegerType(32); case tflite::TensorType_UINT16:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 07 23:04:40 UTC 2024 - 8.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema_generated.h
tflite::Int32VectorT *AsInt32Vector() { return type == SparseIndexVector_Int32Vector ? reinterpret_cast<tflite::Int32VectorT *>(value) : nullptr; } const tflite::Int32VectorT *AsInt32Vector() const { return type == SparseIndexVector_Int32Vector ? reinterpret_cast<const tflite::Int32VectorT *>(value) : nullptr; } tflite::Uint16VectorT *AsUint16Vector() {
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/flatbuffer_export.cc
} else { return tflite::TensorType_INT4; } case 8: return itype.isUnsigned() ? tflite::TensorType_UINT8 : tflite::TensorType_INT8; case 16: return itype.isUnsigned() ? tflite::TensorType_UINT16 : tflite::TensorType_INT16; case 32: return itype.isUnsigned() ? tflite::TensorType_UINT32
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:41:49 UTC 2024 - 164.5K bytes - Viewed (2) -
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/utils/convert_type.h
namespace mlir { class Builder; } // namespace mlir namespace tflite { // Convert the MLIR type to the corresponding TFLite tensor. tflite::TensorType ConvertTypeToTensorType(mlir::Type type); // Convert the scalar type of a TFlite tensor to the corresponding MLIR type. mlir::Type ConvertElementType(tflite::TensorType type, mlir::Builder builder); // Convert the scalar type of a TFLite tensor to the corresponding // Tensorflow type
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 2.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/python/converter_python_api.cc
} tflite::TensorType FromTocoDataTypeToTflitToTensorType(int inference_type) { switch (inference_type) { case toco::IODataType::QUANTIZED_INT16: return tflite::TensorType_INT16; case toco::IODataType::QUANTIZED_UINT8: return tflite::TensorType_UINT8; case toco::IODataType::UINT8: return tflite::TensorType_UINT8; case toco::IODataType::QUANTIZED_INT8:
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/flatbuffer_operator.cc
.Case("TANH", tflite::ActivationFunctionType_TANH) .Case("SIGN_BIT", tflite::ActivationFunctionType_SIGN_BIT); } static tflite::TensorType ConvertDerivedTFLiteTypeAttrForOptionWriter( tflite::TensorType type, flatbuffers::FlatBufferBuilder* builder) { if (type == tflite::TensorType_INT64) { return tflite::TensorType_INT64; } else if (type == tflite::TensorType_INT32) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 38K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tac_filter.proto
// A list of filters for TAC users to run ops/functions on ML hardwares. The // intuition is that, for ops/functions that can be run on ML hardware (e.g. // EdgeTPU) and TFLite CPU, TAC users give a hint that they're more performant // to run on TFLite CPU. These filters give the TAC users freedom to specify the // parts that they want to use other hardware to accelerate. message TacFilters {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 19 19:32:06 UTC 2023 - 1.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/mlir_tflite_runner.cc
return 1; // Create TFLite interpreter & invoke converted program. std::unique_ptr<tflite::FlatBufferModel> model = tflite::FlatBufferModel::BuildFromBuffer(serialized_flatbuffer.c_str(), serialized_flatbuffer.size()); tflite::ops::builtin::BuiltinOpResolver builtins; std::unique_ptr<tflite::Interpreter> interpreter;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 03 00:14:05 UTC 2023 - 6.3K bytes - Viewed (0)