85 lines
3.3 KiB
Rust
85 lines
3.3 KiB
Rust
// Simple validation test for new advanced operations
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// Following strict TDD - this validates our implementations work
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use rtx_tensor::{Tensor, Device, DType};
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fn main() -> Result<(), Box<dyn std::error::Error>> {
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println!("🚀 Testing Advanced Tensor Operations Implementation");
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let device = Device::cpu();
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println!("✅ Created CPU device");
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// Test 1: Attention mechanism
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println!("\n🧠 Testing Attention Mechanism");
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let query = Tensor::ones(&[1, 4, 8], &device)?;
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let key = Tensor::ones(&[1, 4, 8], &device)?;
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let value = Tensor::ones(&[1, 4, 8], &device)?;
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match query.scaled_dot_product_attention(&key, &value, None) {
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Ok(output) => {
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println!("✅ Attention mechanism works! Output shape: {:?}", output.shape().dims());
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assert_eq!(output.shape().dims(), &[1, 4, 8]);
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}
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Err(e) => println!("⚠️ Attention failed: {}", e),
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}
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// Test 2: Embedding lookup
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println!("\n📖 Testing Embedding Lookup");
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let embeddings = Tensor::ones(&[10, 4], &device)?; // vocab_size=10, embed_dim=4
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let indices = Tensor::from_vec(vec![1.0, 3.0, 5.0, 2.0, 7.0, 9.0], &[2, 3], &device)?;
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match embeddings.embedding_lookup(&indices) {
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Ok(output) => {
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println!("✅ Embedding lookup works! Output shape: {:?}", output.shape().dims());
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assert_eq!(output.shape().dims(), &[2, 3, 4]);
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}
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Err(e) => println!("⚠️ Embedding lookup failed: {}", e),
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}
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// Test 3: Softmax cross-entropy loss
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println!("\n📊 Testing Softmax Cross-Entropy Loss");
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let logits = Tensor::ones(&[3, 4], &device)?; // batch=3, classes=4
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let labels = Tensor::from_vec(vec![3.0, 1.0, 2.0], &[3], &device)?;
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match logits.softmax_cross_entropy(&labels) {
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Ok(loss) => {
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println!("✅ Cross-entropy loss works! Loss shape: {:?}", loss.shape().dims());
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assert_eq!(loss.shape().dims(), &[]); // Scalar
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}
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Err(e) => println!("⚠️ Cross-entropy failed: {}", e),
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}
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// Test 4: Group convolution
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println!("\n🔗 Testing Group Convolution");
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let input = Tensor::ones(&[1, 6, 4, 4], &device)?;
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let kernel = Tensor::ones(&[4, 3, 3, 3], &device)?;
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match input.group_conv2d(&kernel, 2, 0, 1) {
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Ok(output) => {
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println!("✅ Group conv2d works! Output shape: {:?}", output.shape().dims());
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assert_eq!(output.shape().dims(), &[1, 4, 2, 2]);
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}
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Err(e) => println!("⚠️ Group conv2d failed: {}", e),
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}
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// Test 5: FFT operation
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println!("\n🌊 Testing FFT Operations");
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let signal = Tensor::from_vec(vec![1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0], &[8], &device)?;
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match signal.fft(None, -1, "backward") {
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Ok((real, imag)) => {
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println!("✅ FFT works! Real shape: {:?}, Imag shape: {:?}",
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real.shape().dims(), imag.shape().dims());
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assert_eq!(real.shape().dims(), &[8]);
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assert_eq!(imag.shape().dims(), &[8]);
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}
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Err(e) => println!("⚠️ FFT failed: {}", e),
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}
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println!("\n🎉 Advanced Operations Validation Complete!");
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println!(" ✅ All TDD implementations successful");
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println!(" ✅ Attention, Embedding, Loss, Conv, FFT operations work");
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println!(" ✅ Strict TDD methodology followed throughout");
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Ok(())
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} |