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Results 1 - 6 of 6 for quantizable_input_indices (0.47 sec)
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tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights.h
// Stores information about how to quantize a user-specified custom operation. // CustomOpInfo contains info of its corresponding CustomOp registered in the // CustomOpMap. 'quantizable_input_indices' is used to determine which indices // of the CustomOp are quantizable. 'is_weight_only' is used specify whether the // custom op is quantized only for storage and dequantized at runtime.
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/quantization/lite/quantize_weights.cc
quant_specs.legacy_float_scale = legacy_float_scale; quant_specs.ops_blocklist = denylisted_mlir_op_names; for (const auto& entry : custom_op_map) { quant_specs.custom_map[entry.first].quantizable_input_indices = entry.second.quantizable_input_indices; quant_specs.custom_map[entry.first].is_weight_only = entry.second.is_weight_only; quant_specs.custom_map[entry.first].no_side_effect = entry.second.no_side_effect;
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/quantization/common/quantization_lib/quantization_config.cc
const std::vector<std::string> indices = absl::StrSplit(node_specification, '-'); for (const std::string& cur_index : indices) { custom_op_map[node_name].quantizable_input_indices.push_back( std::stoi(cur_index)); } break; } case CustomOpUpdateOptions::kWeightOnly: custom_op_map[node_name].is_weight_only =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 07:39:40 UTC 2024 - 5.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights_test.cc
LoadCustomOpTestModel(); // The custom op is not hybrid, and the second input is a constant that can // be quantized. CustomOpMap custom_op_map; custom_op_map["CustomTestOp"] = { {1}, // quantizable_input_indices true, // is_weight_only }; flatbuffers::FlatBufferBuilder builder; auto status = QuantizeWeights(&builder, model_, 0, custom_op_map); ASSERT_EQ(status, kTfLiteOk);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 32.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_config.h
namespace mlir { namespace quant { // Stores information about how to quantize a user-specified custom operation. struct CustomOpInfo { std::vector<std::int32_t> quantizable_input_indices; bool is_weight_only = false; bool no_side_effect = true; }; using CustomOpMap = std::unordered_map<std::string, CustomOpInfo>; enum CustomOpUpdateOptions { kInputIndices, kWeightOnly, kNoSideEffect };
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/transforms/prepare_quantize_dynamic_range.cc
auto custom_map_iter = quant_specs_.custom_map.find(op_name); if (custom_map_iter != quant_specs_.custom_map.end()) return isQuantizableIndex( operand_index, custom_map_iter->second.quantizable_input_indices); } else if (auto quantizable_op = llvm::dyn_cast<DynamicRangeQuantizedOpInterface>(op)) { const auto& quantizable_indices = quantizable_op.GetQuantizableOperandIndices();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 20.8K bytes - Viewed (0)