chickadee » nanograd » make-dense-layer

Creates a fully-connected (dense) layer with Xavier/Glorot initialization. Supports both single vectors and batches.

input-size

number of input features

output-size

number of output features

activation

activation function object (default identity)

use-bias

whether to include bias term (default #t)

dtype

'f32 or 'f64 (default 'f32)

name

layer name for debugging

Input shapes:

• 1D: (input_size,) → output: (output_size,)
• 2D: (batch_size, input_size) → output: (batch_size, output_size)

For 2D inputs, uses BLAS GEMM for efficient batch processing.

(define layer (make-dense-layer 784 128 
                                activation: (make-relu)
                                name: "Hidden1"))

; Single input
(define x (make-tensor32 (make-f32vector 784) '(784)))
(define output (forward layer x))  ; Shape: (128,)

; Batch input
(define batch-x (make-tensor32 (make-f32vector (* 32 784)) '(32 784)))
(define batch-output (forward layer batch-x))  ; Shape: (32, 128)