rok commented on code in PR #38008: URL: https://github.com/apache/arrow/pull/38008#discussion_r1409318263
########## cpp/src/arrow/extension/variable_shape_tensor.cc: ########## @@ -0,0 +1,263 @@ +// 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. + +#include <sstream> + +#include "arrow/extension/fixed_shape_tensor.h" +#include "arrow/extension/variable_shape_tensor.h" + +#include "arrow/array/array_nested.h" +#include "arrow/array/array_primitive.h" +#include "arrow/json/rapidjson_defs.h" // IWYU pragma: keep +#include "arrow/scalar.h" +#include "arrow/tensor.h" +#include "arrow/util/int_util_overflow.h" +#include "arrow/util/logging.h" +#include "arrow/util/sort.h" + +#include <rapidjson/document.h> +#include <rapidjson/writer.h> + +namespace rj = arrow::rapidjson; + +namespace arrow { +namespace extension { + +const Result<std::shared_ptr<Tensor>> VariableShapeTensorArray::GetTensor( + const int64_t i) const { + auto ext_arr = internal::checked_pointer_cast<StructArray>(this->storage()); + auto ext_type = internal::checked_pointer_cast<VariableShapeTensorType>(this->type()); + auto value_type = ext_type->value_type(); + auto ndim = ext_type->ndim(); + auto dim_names = ext_type->dim_names(); + auto shapes = + std::static_pointer_cast<FixedSizeListArray>(ext_arr->field(0))->value_slice(i); + + std::vector<int64_t> shape; + for (int64_t j = 0; j < ndim; ++j) { + ARROW_ASSIGN_OR_RAISE(auto size, shapes->GetScalar(j)); + shape.push_back( + static_cast<int64_t>(std::static_pointer_cast<UInt32Scalar>(size)->value)); + } + + std::vector<int64_t> strides; + // TODO: optimize ComputeStrides for non-uniform tensors + ARROW_CHECK_OK( + internal::ComputeStrides(value_type, shape, ext_type->permutation(), &strides)); + + auto list_arr = + std::static_pointer_cast<ListArray>(ext_arr->field(1))->value_slice(i)->data(); + auto byte_width = value_type->byte_width(); + auto buffer = SliceBuffer(list_arr->buffers[1], list_arr->offset * byte_width, + list_arr->length * byte_width); + + return Tensor::Make(value_type, buffer, shape, strides, dim_names); +} + +bool VariableShapeTensorType::ExtensionEquals(const ExtensionType& other) const { + if (extension_name() != other.extension_name()) { + return false; + } + const auto& other_ext = static_cast<const VariableShapeTensorType&>(other); + if (this->ndim() != other_ext.ndim()) { + return false; + } + + auto is_permutation_trivial = [](const std::vector<int64_t>& permutation) { + for (size_t i = 1; i < permutation.size(); ++i) { + if (permutation[i - 1] + 1 != permutation[i]) { + return false; + } + } + return true; + }; + const bool permutation_equivalent = + ((permutation_ == other_ext.permutation()) || + (permutation_.empty() && is_permutation_trivial(other_ext.permutation())) || + (is_permutation_trivial(permutation_) && other_ext.permutation().empty())); + + return (storage_type()->Equals(other_ext.storage_type())) && + (dim_names_ == other_ext.dim_names()) && + (uniform_shape_ == other_ext.uniform_shape()) && permutation_equivalent; +} + +std::string VariableShapeTensorType::Serialize() const { + rj::Document document; + document.SetObject(); + rj::Document::AllocatorType& allocator = document.GetAllocator(); + + if (!permutation_.empty()) { + rj::Value permutation(rj::kArrayType); + for (auto v : permutation_) { + permutation.PushBack(v, allocator); + } + document.AddMember(rj::Value("permutation", allocator), permutation, allocator); + } + + if (!dim_names_.empty()) { + rj::Value dim_names(rj::kArrayType); + for (std::string v : dim_names_) { + dim_names.PushBack(rj::Value{}.SetString(v.c_str(), allocator), allocator); + } + document.AddMember(rj::Value("dim_names", allocator), dim_names, allocator); + } + + if (!uniform_shape_.empty()) { + rj::Value uniform_shape(rj::kArrayType); + for (auto v : uniform_shape_) { + if (v.has_value()) { + uniform_shape.PushBack(v.value(), allocator); + } else { + uniform_shape.PushBack(rj::Value{}.SetNull(), allocator); + } + } + document.AddMember(rj::Value("uniform_shape", allocator), uniform_shape, allocator); + } + + rj::StringBuffer buffer; + rj::Writer<rj::StringBuffer> writer(buffer); + document.Accept(writer); + return buffer.GetString(); +} + +Result<std::shared_ptr<DataType>> VariableShapeTensorType::Deserialize( + std::shared_ptr<DataType> storage_type, const std::string& serialized_data) const { + if (storage_type->id() != Type::STRUCT) { + return Status::Invalid("Expected Struct storage type, got ", + storage_type->ToString()); + } + auto value_type = storage_type->field(1)->type()->field(0)->type(); Review Comment: Added DCHECKs below. Do you think anything is missing? ```cpp ARROW_DCHECK_EQ(storage_type->num_fields(), 2); ARROW_DCHECK_EQ(storage_type->field(0)->type()->id(), Type::FIXED_SIZE_LIST); ARROW_DCHECK_EQ( std::static_pointer_cast<FixedSizeListType>(storage_type->field(0)->type()) ->value_type(), int32()); ARROW_DCHECK_EQ(storage_type->field(1)->type()->id(), Type::LIST); ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
