Table of Contents

Class GradAvgPool2DOp

Namespace
AiDotNet.JitCompiler.IR.Operations
Assembly
AiDotNet.dll

Backward operation for AvgPool2DOp.

public class GradAvgPool2DOp : BackwardOp
Inheritance
GradAvgPool2DOp
Inherited Members

Remarks

Forward: Average values in each window Backward: Distributes gradient equally to all elements in window

Properties

Padding

public int[] Padding { get; set; }

Property Value

int[]

PoolSize

public int[] PoolSize { get; set; }

Property Value

int[]

Stride

public int[] Stride { get; set; }

Property Value

int[]

Methods

ToString()

Gets a string representation of this operation for debugging.

public override string ToString()

Returns

string

A string describing this operation.

Remarks

The string format is: "tOutput = OpType(tInput1, tInput2, ...) : Type [Shape]"

For Beginners: This creates a readable description of the operation.

Example outputs:

  • "t2 = Add(t0, t1) : Float32 [3, 4]"
  • "t5 = MatMul(t3, t4) : Float32 [128, 256]"
  • "t8 = ReLU(t7) : Float32 [32, 128]"

This is super helpful for debugging - you can see exactly what each operation does and what shape tensors flow through the graph.

Validate()

Validates that this operation is correctly formed.

public override bool Validate()

Returns

bool

True if valid, false otherwise.

Remarks

Basic validation checks that the operation has required information. Derived classes can override to add operation-specific validation.

For Beginners: This checks that the operation makes sense.

Basic checks:

  • Output ID is valid (non-negative)
  • Has the right number of inputs
  • Shapes are compatible

Specific operations add their own checks:

  • MatMul: inner dimensions must match
  • Conv2D: kernel size must be valid
  • Reshape: total elements must be preserved

If validation fails, the operation can't be compiled.