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| // Copyright 2019 The TensorFlow Authors. All Rights Reserved. | |
| // | |
| // Licensed 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. | |
| // ============================================================================= | |
| import Accelerate | |
| import CoreImage | |
| import Foundation | |
| import TensorFlowLite | |
| // MARK: - Data | |
| extension Data { | |
| /// Creates a new buffer by copying the buffer pointer of the given array. | |
| /// | |
| /// - Warning: The given array's element type `T` must be trivial in that it can be copied bit | |
| /// for bit with no indirection or reference-counting operations; otherwise, reinterpreting | |
| /// data from the resulting buffer has undefined behavior. | |
| /// - Parameter array: An array with elements of type `T`. | |
| init<T>(copyingBufferOf array: [T]) { | |
| self = array.withUnsafeBufferPointer(Data.init) | |
| } | |
| /// Convert a Data instance to Array representation. | |
| func toArray<T>(type: T.Type) -> [T] where T: AdditiveArithmetic { | |
| var array = [T](repeating: T.zero, count: self.count / MemoryLayout<T>.stride) | |
| _ = array.withUnsafeMutableBytes { self.copyBytes(to: $0) } | |
| return array | |
| } | |
| } | |
| // MARK: - Wrappers | |
| /// Struct for handling multidimension `Data` in flat `Array`. | |
| struct FlatArray<Element: AdditiveArithmetic> { | |
| private var array: [Element] | |
| var dimensions: [Int] | |
| init(tensor: Tensor) { | |
| dimensions = tensor.shape.dimensions | |
| array = tensor.data.toArray(type: Element.self) | |
| } | |
| private func flatIndex(_ index: [Int]) -> Int { | |
| guard index.count == dimensions.count else { | |
| fatalError("Invalid index: got \(index.count) index(es) for \(dimensions.count) index(es).") | |
| } | |
| var result = 0 | |
| for i in 0..<dimensions.count { | |
| guard dimensions[i] > index[i] else { | |
| fatalError("Invalid index: \(index[i]) is bigger than \(dimensions[i])") | |
| } | |
| result = dimensions[i] * result + index[i] | |
| } | |
| return result | |
| } | |
| subscript(_ index: Int...) -> Element { | |
| get { | |
| return array[flatIndex(index)] | |
| } | |
| set(newValue) { | |
| array[flatIndex(index)] = newValue | |
| } | |
| } | |
| } | |