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Results 1 - 9 of 9 for UNIFORM_QUANTIZED (0.22 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/passes/preprocess_op.cc
*this, "target-opset", llvm::cl::init(OpSet::UNIFORM_QUANTIZED), llvm::cl::desc("Choose target opset."), llvm::cl::values( clEnumValN(OpSet::TF, "TF", "Uses TF ops that mimic quantization behavior"), clEnumValN(OpSet::XLA, "XLA", "Uses TF XLA ops"), clEnumValN(OpSet::UNIFORM_QUANTIZED, "UNIFORM_QUANTIZED", "Uses TF Uniform Quantized ops"))};
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_drq.mlir
// RUN: tf-quant-opt %s -split-input-file -quant-insert-quantized-functions='quantization-method=drq target-opset=UNIFORM_QUANTIZED' -quant-quantize-composite-functions='quantization-method=drq target-opset=UNIFORM_QUANTIZED' -symbol-dce | FileCheck %s module { // TODO(b/260020937): Support transpose_a, transpose_b for matmul. func.func @matmul(%arg0: tensor<2x12xf32>) -> (tensor<*xf32>) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/quantize_passes.cc
std::optional<const absl::string_view> mlir_dump_file_prefix) { pm.addNestedPass<mlir::func::FuncOp>( mlir::quant::CreateConvertFakeQuantToQdqPass()); if (quantization_options.op_set() == OpSet::UNIFORM_QUANTIZED) { pm.addNestedPass<mlir::func::FuncOp>( mlir::TF::CreateUnrollBatchMatMulPassPass()); } pm.addPass(mlir::TF::CreateTFShapeInferencePass());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 9.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.cc
clEnumValN(OpSet::TF, "TF", "Uses TF ops that mimic quantization behavior"), clEnumValN(OpSet::XLA, "XLA", "Uses TF XLA ops"), clEnumValN(OpSet::UNIFORM_QUANTIZED, "UNIFORM_QUANTIZED", "Uses TF Uniform Quantized ops"))}; }; // Check if given indices in `val1` has same number of elements as given // indices in `val2`.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 13.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/lift_quantizable_spots_as_functions.cc
clEnumValN(OpSet::TF, "TF", "Uses TF ops that mimic quantization behavior"), clEnumValN(OpSet::XLA, "XLA", "Uses TF XLA ops"), clEnumValN(OpSet::UNIFORM_QUANTIZED, "UNIFORM_QUANTIZED", "Uses TF Uniform Quantized ops"))}; // Initialize for tests. void initializeForTest() { if (!test_mode_) return;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 16.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantize.cc
clEnumValN(OpSet::TF, "TF", "Uses TF ops that mimic quantization behavior"), clEnumValN(OpSet::XLA, "XLA", "Uses TF XLA ops"), clEnumValN(OpSet::UNIFORM_QUANTIZED, "UNIFORM_QUANTIZED", "Uses TF Uniform Quantized ops"))}; }; bool QuantizePass::shouldKeepUnusedQdqPattern() { return target_opset_ == OpSet::XLA &&
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 05:52:39 UTC 2024 - 23.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_quantize_drq.cc
// Constructor used by the PassRegistration and enforce int8 quantization. // This is only used by test. explicit PrepareQuantizeDRQPass() : op_set_(OpSet::UNIFORM_QUANTIZED) { quant_specs_.inference_type = tensorflow::DT_QINT8; } // Constructor used by manually creating the pass. explicit PrepareQuantizeDRQPass(const QuantizationSpecs& quant_specs,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/quantize_model.py
quantization_options.enable_per_channel_quantization = False if quantization_options.enable_per_channel_quantization and not ( ( quantization_options.op_set == quant_opts_pb2.OpSet.UNIFORM_QUANTIZED or quantization_options.quantization_method.preset_method == _PresetMethod.METHOD_STATIC_RANGE_WEIGHT_ONLY_INT8 ) or ( quantization_options.op_set
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 34.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tf_to_tfl_flatbuffer.cc
quantization_options.mutable_quantization_method()->set_preset_method( quantization::QuantizationMethod::METHOD_DYNAMIC_RANGE_INT8); quantization_options.set_op_set(quantization::UNIFORM_QUANTIZED); quantization_options.set_min_num_elements_for_weights( kWeightsMinNumElementsDefault); quantization::AddQuantizePtqDynamicRangePasses(pass_manager,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 23.8K bytes - Viewed (0)