areusch commented on a change in pull request #6917: URL: https://github.com/apache/incubator-tvm/pull/6917#discussion_r529054684
########## File path: src/target/source/codegen_params.cc ########## @@ -0,0 +1,297 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, + * software distributed under the License is distributed on an + * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY + * KIND, either express or implied. See the License for the + * specific language governing permissions and limitations + * under the License. + */ + +/*! + * \file codegen_params.cc + */ + +#include "codegen_params.h" + +#include <dlpack/dlpack.h> + +#include <cmath> +#include <iomanip> +#include <memory> +#include <string> + +namespace tvm { +namespace codegen { + +namespace { +class DLManagedTensorDeleter { + public: + void operator()(DLManagedTensor* ptr) { ptr->deleter(ptr); } +}; +} // namespace + +static constexpr const int kMaxLineLength = 80; + +void NDArrayDataToC(::tvm::runtime::NDArray arr, int indent_chars, std::ostream& os) { + auto arr_type = arr.DataType(); + CHECK_EQ(arr_type.lanes(), 1) << "CodegenParams: only support generating 1-lane parameters; saw " + << arr_type.lanes(); + + int one_element_size_bytes = (arr_type.bits() / 4) + (2 /* "0x" */) + (2 /* ", " */); + if (arr_type.code() == runtime::DataType::TypeCode::kInt) { + one_element_size_bytes += 1; // sign bit + if (arr_type.bits() > 32) { + one_element_size_bytes += 2; // "UL" + } + } else if (arr_type.code() == runtime::DataType::TypeCode::kUInt) { + if (arr_type.bits() > 32) { + one_element_size_bytes += 1; // "L" + } + } else if (arr_type.code() == runtime::DataType::TypeCode::kFloat) { + // Floats and doubles are printed as hex but casted. + one_element_size_bytes += 1 /* sign */ + 1 /* decimal point */ + 1 /* exponent sign */ + + 1 /* extra decimal digit in exponent */; + } + + int elements_per_row = 16; + while (elements_per_row > 1 && + (elements_per_row * one_element_size_bytes) > (kMaxLineLength - indent_chars)) { + elements_per_row /= 2; + } + + std::string indent_str(indent_chars, ' '); + os << indent_str; + + auto shape = arr.Shape(); + int num_elements = 1; + for (auto shape_elem : shape) { + num_elements *= shape_elem; + } + + std::unique_ptr<DLManagedTensor, DLManagedTensorDeleter> tensor(arr.ToDLPack()); + auto old_fmtflags = os.flags(); + os.setf(std::ios::internal | std::ios::hex, + std::ios::adjustfield | std::ios::basefield | std::ios::showbase); + os.fill('0'); + switch (arr_type.code()) { + case runtime::DataType::kInt: + CHECK(arr_type.bits() == 8 || arr_type.bits() == 16 || arr_type.bits() == 32 || + arr_type.bits() == 64) + << "CodegenParams: only support generating 8-, 16-, 32-, or 64-bit integer params; saw " + << arr_type.bits() << "-bit array"; + + if (arr_type.bits() == 8) { + for (int i = 0; i < num_elements; i++) { + // NOTE: for special types int8_t and uint8_t, need to promote to int type to avoid + // printing as a char. + int8_t elem = static_cast<int8_t*>(tensor->dl_tensor.data)[i]; + uint16_t to_print; + if (elem < 0) { + os << "-"; + to_print = -elem; + } else { + os << "+"; + to_print = elem; + } + os << "0x" << std::setw(2) << +static_cast<std::uint8_t>(to_print); + if (i < num_elements - 1) { + os << ", "; + } + if (((i + 1) % elements_per_row) == 0) { + os << "\n" << indent_str; + } + } + } else if (arr_type.bits() == 16) { + for (int i = 0; i < num_elements; i++) { + int16_t elem = static_cast<int16_t*>(tensor->dl_tensor.data)[i]; + uint16_t to_print; + if (elem < 0) { + os << "-"; + to_print = -elem; + } else { + os << "+"; + to_print = elem; + } + os << "0x" << std::setw(4) << to_print; + if (i < num_elements - 1) { + os << ", "; + } + if (((i + 1) % elements_per_row) == 0) { + os << "\n" << indent_str; + } + } + } else if (arr_type.bits() == 32) { + for (int i = 0; i < num_elements; i++) { + int32_t elem = static_cast<int32_t*>(tensor->dl_tensor.data)[i]; + uint32_t to_print; + if (elem < 0) { + os << "-"; + to_print = -elem; + } else { + os << "+"; + to_print = elem; + } + os << "0x" << std::setw(8) << to_print; + if (i < num_elements - 1) { + os << ", "; + } + if (((i + 1) % elements_per_row) == 0) { + os << "\n" << indent_str; + } + } + } else if (arr_type.bits() == 64) { + for (int i = 0; i < num_elements; i++) { + int64_t elem = static_cast<int64_t*>(tensor->dl_tensor.data)[i]; + uint64_t to_print; + if (elem < 0) { + os << "-"; + to_print = -elem; + } else { + os << "+"; + to_print = elem; + } + os << "0x" << std::setw(16) << to_print; + if (i < num_elements - 1) { + os << ", "; + } + if (((i + 1) % elements_per_row) == 0) { + os << "\n" << indent_str; + } + } + } else { + CHECK(false) << "should not get here"; + } + break; + + case runtime::DataType::TypeCode::kUInt: + CHECK(arr_type.bits() == 8 || arr_type.bits() == 16 || arr_type.bits() == 32 || + arr_type.bits() == 64) + << "CodegenParams: only support generating 8-, 16-, 32-, or 64-bit integer params; saw " + << arr_type.bits() << "-bit array"; + + if (arr_type.bits() == 8) { + for (int i = 0; i < num_elements; i++) { + // NOTE: for special types int8_t and uint8_t, need to promote to int type to avoid + // printing as a char. + os << "0x" << std::setw(2) + << +static_cast<std::uint8_t>(static_cast<uint8_t*>(tensor->dl_tensor.data)[i]); + if (i < num_elements - 1) { + os << ", "; + } + if (((i + 1) % elements_per_row) == 0) { + os << "\n" << indent_str; + } + } + } else if (arr_type.bits() == 16) { + for (int i = 0; i < num_elements; i++) { + os << "0x" << std::setw(4) << static_cast<uint16_t*>(tensor->dl_tensor.data)[i]; + if (i < num_elements - 1) { + os << ", "; + } + if (((i + 1) % elements_per_row) == 0) { + os << "\n" << indent_str; + } + } + } else if (arr_type.bits() == 32) { + for (int i = 0; i < num_elements; i++) { + os << "0x" << std::setw(8) << static_cast<uint32_t*>(tensor->dl_tensor.data)[i]; + if (i < num_elements - 1) { + os << ", "; + } + if (((i + 1) % elements_per_row) == 0) { + os << "\n" << indent_str; + } + } + } else if (arr_type.bits() == 64) { + for (int i = 0; i < num_elements; i++) { + os << "0x" << std::setw(16) << static_cast<uint64_t*>(tensor->dl_tensor.data)[i] << "UL"; + if (i < num_elements - 1) { + os << ", "; + } + if (((i + 1) % elements_per_row) == 0) { + os << "\n" << indent_str; + } + } + } else { + CHECK(false) << "should not get here"; + } + break; + + case runtime::DataType::TypeCode::kFloat: { + std::stringstream ss; + ss.setf(std::ios::hex | std::ios::showbase | std::ios::fixed | std::ios::scientific, + std::ios::basefield | std::ios::showbase | std::ios::floatfield); Review comment: right, the second one is a mask so I think it's needed twice? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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