Class ScalarConstantOp
- Namespace
- AiDotNet.JitCompiler.IR.Operations
- Assembly
- AiDotNet.dll
Represents a scalar constant in the IR (single value).
public class ScalarConstantOp : IROp
- Inheritance
-
ScalarConstantOp
- Inherited Members
Remarks
ScalarConstantOp is a specialized version of ConstantOp for single values. It's more efficient for storing scalar values used in operations.
For Beginners: A ScalarConstantOp holds a single number.
Examples:
- Learning rate: 0.001
- Epsilon for numerical stability: 1e-7
- Scale factor: 2.0
These are used in operations like:
- result = input * 0.001 (scaling by learning rate)
- result = input + 1e-7 (adding epsilon)
Properties
Value
Gets or sets the scalar value.
public double Value { get; set; }
Property Value
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.