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s4nnc support swift package (#28)
* s4nnc support swift package * remove comments and update package setup to ccv unstable * resolve comments * adding target for TensorBoard * update imports * remove fix
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‎Package.swift‎

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// swift-tools-version:5.9
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import PackageDescription
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let package = Package(
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name: "s4nnc",
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platforms: [
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.macOS(.v13),
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.iOS(.v16),
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.tvOS(.v16),
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.visionOS(.v1)
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],
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products: [
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.library(
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name: "NNC",
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targets: ["NNC"]),
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.library(
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name: "NNCCoreMLConversion",
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targets: ["NNCCoreMLConversion"]),
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.library(
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name: "TensorBoard",
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targets: ["TensorBoard"]),
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],
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dependencies: [
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.package(url: "https://github.com/liuliu/ccv.git", revision: "70be3804a44c760a591858a2ac8261f3267fe85b"),
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.package(url: "https://github.com/weiyanlin117/swift-fpzip-support.git", revision: "0ec6d4668c9c83bc3da0f8b2d6dfc46da0b98609"),
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.package(url: "https://github.com/apple/swift-protobuf.git", revision: "d57a5aecf24a25b32ec4a74be2f5d0a995a47c4b"),
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.package(url: "https://github.com/apple/swift-system.git", revision: "fbd61a676d79cbde05cd4fda3cc46e94d6b8f0eb"),
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],
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targets: [
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// C_zlib - System zlib wrapper
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.target(
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name: "C_zlib",
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path: "nnc/C_zlib",
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publicHeadersPath: ".",
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cSettings: [
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.define("_GNU_SOURCE"),
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],
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linkerSettings: [
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.linkedLibrary("z"),
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]
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),
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// NNC - Main Swift library
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.target(
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name: "NNC",
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dependencies: [
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.product(name: "nnc", package: "ccv"),
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.product(name: "sfmt", package: "ccv"),
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.product(name: "lib_nnc_mps_compat", package: "ccv"),
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.product(name: "C_fpzip", package: "swift-fpzip-support"),
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"C_zlib",
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],
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path: "nnc",
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exclude: [
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"C_ccv",
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"C_nnc",
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"C_sfmt",
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"C_zlib",
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"C_sqlite3",
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"BUILD.bazel",
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"CoreMLConversion.swift",
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"PythonConversion.swift",
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"MuJoCoConversion.swift",
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],
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sources: [
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"AnyModel.swift",
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"AutoGrad.swift",
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"DataFrame.swift",
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"DataFrameAddons.swift",
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"DataFrameCore.swift",
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"DynamicGraph.swift",
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"Functional.swift",
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"FunctionalAddons.swift",
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"GradScaler.swift",
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"Group.swift",
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"Hint.swift",
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"Loss.swift",
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"Model.swift",
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"ModelAddons.swift",
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"ModelBuilder.swift",
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"ModelCore.swift",
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"ModelIOAddons.swift",
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"Operators.swift",
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"Optimizer.swift",
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"OptimizerAddons.swift",
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"Store.swift",
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"StreamContext.swift",
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"Tensor.swift",
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"TensorGroup.swift",
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"Wrapped.swift",
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]
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),
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// NNCCoreMLConversion - CoreML conversion utilities
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.target(
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name: "NNCCoreMLConversion",
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dependencies: ["NNC",
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.product(name: "lib_nnc_mps_compat", package: "ccv"),
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.product(name: "sfmt", package: "ccv"),
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],
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path: "nnc",
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sources: ["CoreMLConversion.swift"]
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),
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// TensorBoard - TensorBoard logging support
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.target(
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name: "TensorBoard",
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dependencies: [
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"NNC",
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.product(name: "SwiftProtobuf", package: "swift-protobuf"),
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.product(name: "SystemPackage", package: "swift-system"),
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],
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path: "tensorboard",
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exclude: ["BUILD.bazel"]
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),
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// Test targets
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.testTarget(
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name: "NNCTests",
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dependencies: ["NNC"],
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path: "test",
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exclude: [
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"coreml",
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"python",
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"BUILD.bazel",
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],
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sources: [
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"dataframe.swift",
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"graph.swift",
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"loss.swift",
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"model.swift",
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"ops.swift",
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"optimizer.swift",
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"store.swift",
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"tensor.swift",
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],
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resources: [
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.copy("scaled_data.csv"),
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.copy("some_variables.db"),
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]
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),
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.testTarget(
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name: "NNCCoreMLTests",
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dependencies: ["NNCCoreMLConversion"],
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path: "test/coreml",
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sources: [
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"mlshapedarray.swift",
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]
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),
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]
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)

‎gym/http/HTTP.swift‎

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#if canImport(C_ccv)
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import C_ccv
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#elseif canImport(C_swiftpm_ccv)
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import C_swiftpm_ccv
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#endif
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import Foundation
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import MuJoCo
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import NIOCore

‎gym/renders/MuJoCoVideo.swift‎

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#if canImport(C_ccv)
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import C_ccv
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#elseif canImport(C_swiftpm_ccv)
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import C_swiftpm_ccv
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#endif
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import C_ffmpeg
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import Foundation
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import Gym

‎nnc/AutoGrad.swift‎

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#if canImport(C_nnc)
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import C_nnc
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#elseif canImport(C_swiftpm_nnc)
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import C_swiftpm_nnc
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#endif
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extension DynamicGraph.AnyTensor {
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/**

‎nnc/CoreMLConversion.swift‎

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#if canImport(C_nnc)
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import C_nnc
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#elseif canImport(C_swiftpm_nnc)
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import C_swiftpm_nnc
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#endif
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import NNC
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#if canImport(lib_nnc_mps_compat) && canImport(CoreML)
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import lib_nnc_mps_compat

‎nnc/DataFrame.swift‎

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#if canImport(C_nnc)
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import C_nnc
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#elseif canImport(C_swiftpm_nnc)
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import C_swiftpm_nnc
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#endif
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public protocol DataSeries: Sequence {
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func prefetch(_ i: Int, streamContext: StreamContext?)

‎nnc/DataFrameAddons.swift‎

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#if canImport(C_nnc)
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import C_nnc
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#elseif canImport(C_swiftpm_nnc)
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import C_swiftpm_nnc
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#endif
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// MARK - Load CSV
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‎nnc/DataFrameCore.swift‎

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#if canImport(C_nnc)
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import C_nnc
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#elseif canImport(C_swiftpm_nnc)
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import C_swiftpm_nnc
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#endif
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// MARK - Sampling
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‎nnc/DynamicGraph.swift‎

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#if canImport(C_nnc)
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import C_nnc
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#elseif canImport(C_swiftpm_nnc)
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import C_swiftpm_nnc
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#endif
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/// A dynamic graph is a workspace for computations. All tensor variables can be tracked
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/// from a dynamic graph.

‎nnc/Functional.swift‎

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#if canImport(C_nnc)
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import C_nnc
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#elseif canImport(C_swiftpm_nnc)
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import C_swiftpm_nnc
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#endif
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/// This protocol defines a generic constructs such that we can use DynamicGraph.AnyTensorGroup
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/// to represent either a collection of tensors from multiple GPUs or one tensor.

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