Package spidr - Namespaces

• BayesianOptimization.Acquisition

  Acquisition functionality for Bayesian optimization. Acquisition functions quantify the usefulness of points in a search domain, towards the task of finding a function optimum.
• Compiler.Enzyme.MLIR.Dialect.Dialect

  For internal spidr use only.
• Compiler.Enzyme.MLIR.Dialect.Ops

  For internal spidr use only.
• Compiler.Enzyme.MLIR.Implementations.CoreDialectsAutoDiffImplementations

  For internal spidr use only.
• Compiler.Enzyme.MLIR.Passes.Passes

  For internal spidr use only.
• Compiler.EnzymeJAX.Src.EnzymeAD.JAX.Implementations.XLADerivatives

  For internal spidr use only.
• Compiler.EnzymeJAX.Src.EnzymeAD.JAX.Passes.Passes

  For internal spidr use only.
• Compiler.LLVM.ADT.APFloat

  For internal spidr use only.
• Compiler.LLVM.ADT.APInt

  For internal spidr use only.
• Compiler.LLVM.Support.RawOStream

  For internal spidr use only.
• Compiler.MLIR.Dialect.Func.IR.FuncOps

  For internal spidr use only.
• Compiler.MLIR.IR.Block

  For internal spidr use only.
• Compiler.MLIR.IR.Builders

  For internal spidr use only.
• Compiler.MLIR.IR.BuiltinAttributes

  For internal spidr use only.
• Compiler.MLIR.IR.BuiltinLocationAttributes

  For internal spidr use only.
• Compiler.MLIR.IR.BuiltinOps

  For internal spidr use only.
• Compiler.MLIR.IR.BuiltinTypeInterfaces

  For internal spidr use only.
• Compiler.MLIR.IR.BuiltinTypes

  For internal spidr use only.
• Compiler.MLIR.IR.DialectRegistry

  For internal spidr use only.
• Compiler.MLIR.IR.Location

  For internal spidr use only.
• Compiler.MLIR.IR.MLIRContext

  For internal spidr use only.
• Compiler.MLIR.IR.OpDefinition

  For internal spidr use only.
• Compiler.MLIR.IR.Operation

  For internal spidr use only.
• Compiler.MLIR.IR.Region

  For internal spidr use only.
• Compiler.MLIR.IR.TypeRange

  For internal spidr use only.
• Compiler.MLIR.IR.Types

  For internal spidr use only.
• Compiler.MLIR.IR.Value

  For internal spidr use only.
• Compiler.MLIR.IR.ValueRange

  For internal spidr use only.
• Compiler.MLIR.Pass.PassManager

  For internal spidr use only.
• Compiler.MLIR.Transforms.Passes

  For internal spidr use only.
• Compiler.MLIR.IR

  For internal spidr use only.
• Compiler.Stablehlo.Dialect.ChloOps

  For internal spidr use only.
• Compiler.Stablehlo.Dialect.Serialization

  For internal spidr use only.
• Compiler.Stablehlo.Dialect.StablehloAttrs

  For internal spidr use only.
• Compiler.Stablehlo.Dialect.StablehloEnums

  For internal spidr use only.
• Compiler.Stablehlo.Dialect.StablehloOps

  For internal spidr use only.
• Compiler.Stablehlo.Dialect.Version

  For internal spidr use only.
• Compiler.Stablehlo.Transforms.Passes

  For internal spidr use only.
• Compiler.Xla.Client.ExecutableBuildOptions

  For internal spidr use only.
• Compiler.Xla.HLO.Translate.HloToMhlo.HloUtils

  For internal spidr use only.
• Compiler.Xla.PJRT.C.PjrtCApi

  For internal spidr use, and use by plugin developers.
• Compiler.Xla.PJRT.PjrtExecutable

  For internal spidr use only.
• Compiler.Xla.Literal

  For internal spidr use only.
• Compiler.Xla.Shape

  For internal spidr use only.
• Compiler.Xla.ShapeUtil

  For internal spidr use only.
• Compiler.Xla.XlaData

  For internal spidr use only.
• Compiler.Eval

  For internal spidr use only.
• Compiler.FFI

  For internal spidr use only.
• Compiler.IR

  For internal spidr use only.
• Compiler.LiteralRW

  For internal spidr use only.
• Model.GaussianProcess

  Gaussian process inference.
• Model.Kernel

  Kernel functions, particularly for use in Gaussian processes.
• Model.MeanFunction

  Mean functions, particularly for use in Gaussian processes.
• BayesianOptimization

  Functionality for Bayesian optimization, the data-efficient optimization of objective functions. Bayesian optimization recommends new points at which to query your objective by placing a probabilistic model over historic data then, typically, optimizing an _acquisition function_ which quantifies how useful it would be to evaluate the objective at any given set of points.
• Constants

  Common tensor constants.
• Data

  Definitions and utilities for datasets.
• Device

  `Device` management. A `Device` encapsulates the graph compiler and hardware support.
• Distribution

  Probability distributions.
• Literal

  Defines `Literal`, a single value or array of values with a specified shape. `Literal` is similar to `Tensor`, but differs in a number of important ways:
• Model

  Functionality for probabilistic models.
• Optimize

  Function optimizers.
• Primitive

  Primitive backend data types, and their interaction with Idris.
• Tensor

  Defines `Tensor`, an array of numbers or booleans, along with a number of functions operating on `Tensor`s. `Tensor` operations typically leverage hardware acceleration and graph compilation. spidr tracks tensor shape and data type in the types, so you can be sure that if your tensor code compiles, these are consistent.
• Types

  Common library types.
• Util

  Generic library utilities.