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tensorflow/compiler/mlir/lite/utils/string_utils.cc
if (len > max_length_ || data_.size() >= max_length_ - len) return absl::ResourceExhaustedError("Buffer overflow"); data_.resize(data_.size() + len); memcpy(data_.data() + offset_.back(), str, len); offset_.push_back(offset_.back() + len); return absl::OkStatus(); } int MiniDynamicBuffer::WriteToBuffer(char** buffer) { // Allocate sufficient memory to tensor buffer. int32_t num_strings = offset_.size() - 1;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:41:49 UTC 2024 - 2.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_model_test.cc
output->quantization = std::make_unique<QuantizationParametersT>(); input->quantization->min.push_back(0.0); output->quantization->min.push_back(0.0); input->quantization->max.push_back(6.0); output->quantization->max.push_back(6.0); } TensorType tensor_type_; }; INSTANTIATE_TEST_SUITE_P(QuantizeConvModelTestInst, QuantizeConvModelTest,
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/mlir_graph_optimization_pass.cc
for (const auto& pass_registration : registry_->passes()) { MlirOptimizationPassState pass_state = pass_registration.pass->GetPassState( &device_set, config_proto, **graph, *flib_def); per_pass_state.push_back(pass_state); switch (pass_state) { case MlirOptimizationPassState::FallbackEnabled: { if (overall_state != MlirOptimizationPassState::Enabled)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 22:19:26 UTC 2024 - 18.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights_test.cc
// different between float and quantized tensors. So do those tests // separately in the test body without checking them here. used_tensors.push_back(i); return float_tensor; } else { // Otherwise, do additional checks for data type and buffer contents. const std::vector<uint8_t> quantized_buffer =
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/lite/python/converter_python_api.cc
mlir::TFL::ErrorCollector* collector = mlir::TFL::ErrorCollector::GetErrorCollector(); std::vector<std::string> collected_errors; for (const auto& error_data : collector->CollectedErrors()) { collected_errors.push_back(error_data.SerializeAsString()); } collector->Clear(); return collected_errors; } std::string FlatBufferFileToMlir(const std::string& model, bool input_is_filepath) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 19.2K bytes - Viewed (0)