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src/main/resources/fess_indices/fess/lv/stopwords.txt
ja ka lai tomēr tikko turpretī arī kaut gan tādēļ tā ne tikvien vien kā ir te vai kamēr # Particles ar diezin droši diemžēl nebūt ik it taču nu pat tiklab iekšpus nedz tik nevis turpretim jeb iekam iekām iekāms kolīdz līdzko tiklīdz jebšu tālab tāpēc nekā itin jā jau jel nē nezin
Registered: Wed Jun 12 13:08:18 UTC 2024 - Last Modified: Thu Jul 19 06:31:02 UTC 2018 - 1.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tf_to_tfl_flatbuffer.cc
mlir::StatusScopedDiagnosticHandler& status_handler, const toco::TocoFlags& toco_flags, const mlir::TFL::PassConfig& pass_config, std::optional<Session*> session, std::string* result, const std::unordered_set<std::string>& saved_model_tags) { // Currently, TF quantization only support dynamic range quant, as such // when toco flag post training quantization is specified with converting to
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 23.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/transforms/device_transform_patterns.h
#include "mlir/Support/LogicalResult.h" // from @llvm-project #include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h" #include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h" namespace mlir { namespace TFL { namespace tac { // TODO(renjieliu): add more patterns. // This basically: // Pack => (Concat -> Reshape) struct LowerPackIntoConcatReshape : public OpRewritePattern<TFL::PackOp> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 03 16:37:16 UTC 2022 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/e2e/device-transform-nnapi.mlir
// RUN: tac-translate -input-mlir -output-mlir -device-specs=NNAPI %s -o - 2>&1 | FileCheck %s module { // CHECK-LABEL: main func.func @main(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>) -> tensor<4xf32> { %0 = "tfl.squared_difference"(%arg0, %arg1) : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32> func.return %0 : tensor<4xf32> // CHECK: [[VAL_0:%.*]] = tfl.sub %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_model.h
// ops. // // When `legacy_float_scale` is true, the quantizer will use float scale instead // 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,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 2.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/python/converter_python_api.h
// of the converted model and some statistics like arithmetic ops count. // `debug_info_str` contains the `GraphDebugInfo` proto. When // `enable_mlir_converter` is True, use MLIR-based conversion instead of // TOCO conversion. PyObject* Convert(PyObject* model_flags_proto_txt_raw, PyObject* toco_flags_proto_txt_raw, PyObject* input_contents_txt_raw, bool extended_return = false,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 18:18:30 UTC 2024 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/py_wrapper/tac_wrapper_pybind11.cc
#include <pybind11/stl.h> #include <string> #include <vector> #include "pybind11/pybind11.h" // from @pybind11 #include "tensorflow/compiler/mlir/lite/experimental/tac/py_wrapper/tac_wrapper.h" // Warning: The API is experimental and subject to change. PYBIND11_MODULE(_pywrap_tac_wrapper, m) { m.def( "run_tac", [](const std::string& model_file_path,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 06 03:08:33 UTC 2023 - 1.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/hardwares/BUILD
"//tensorflow/compiler/mlir/lite/experimental/tac:common", "//tensorflow/compiler/mlir/lite/experimental/tac:device_transform_patterns", "//tensorflow/compiler/mlir/lite/experimental/tac/hardwares:simple_hardware", ], alwayslink = 1, ) cc_library( name = "target_hardware", srcs = ["target_hardware.cc"], hdrs = ["target_hardware.h"], deps = [
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 17 08:24:48 UTC 2023 - 2.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_config.h
// This option only targets `DT_HALF` and `DT_QINT8` inference type. bool weight_quantization = false; // Whether to use the MLIR dynamic range quantizer instead of TOCO. bool enable_mlir_dynamic_range_quantizer = false; // Whether to allow weight-only quantization. This scheme quantizes // weights but will dequantize them back at runtime which is useful for
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 13 10:16:19 UTC 2024 - 10.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/device-transform-gpu.mlir
// RUN: tac-opt-all-backends -tfl-device-transform-gpu %s -split-input-file -verify-diagnostics | FileCheck %s func.func @pack(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>) -> tensor<2x1xf32> { %0 = "tfl.pack"(%arg0, %arg1) {axis = 0 : i32, values_count = 2 : i32} : (tensor<1xf32>, tensor<1xf32>) -> tensor<2x1xf32> func.return %0 : tensor<2x1xf32> } // CHECK: func @pack(%[[VAL_0:.*]]: tensor<1xf32>, %[[VAL_1:.*]]: tensor<1xf32>) -> tensor<2x1xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 15.6K bytes - Viewed (0)