foundation

tests/integration_test.rs

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+// Copyright (C) 2025 Bellande Artificial Intelligence Computer Vision Research Innovation Center, Ronaldson Bellande
+
+// This program is free software: you can redistribute it and/or modify
+// it under the terms of the GNU General Public License as published by
+// the Free Software Foundation, either version 3 of the License, or
+// (at your option) any later version.
+
+// This program is distributed in the hope that it will be useful,
+// but WITHOUT ANY WARRANTY; without even the implied warranty of
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+// GNU General Public License for more details.
+
+// You should have received a copy of the GNU General Public License
+// along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+use std::error::Error;
+
+use bellande_artificial_intelligence_training_framework::{
+    core::tensor::Tensor,
+    layer::{activation::ReLU, conv::Conv2d, linear::Linear, pooling::MaxPool2d},
+    models::sequential::Sequential,
+};
+
+#[test]
+fn test_single_layer() -> Result<(), Box<dyn Error>> {
+    // Create the simplest possible model
+    let mut model = Sequential::new();
+
+    // Add just one conv layer
+    model.add(Box::new(Conv2d::new(
+        3,            // in_channels
+        4,            // out_channels (reduced)
+        (3, 3),       // kernel_size
+        Some((1, 1)), // stride
+        Some((1, 1)), // padding
+        true,         // bias
+    )));
+
+    // Create tiny input
+    let input = Tensor::zeros(&[1, 3, 8, 8]); // Minimal size
+
+    // Test forward pass
+    let output = model.forward(&input)?;
+
+    // Verify output
+    assert_eq!(output.shape()[1], 4); // Check output channels
+
+    Ok(())
+}
+
+// Test tensor operations separately
+#[test]
+fn test_tensor_ops() -> Result<(), Box<dyn Error>> {
+    let tensor = Tensor::zeros(&[1, 3, 8, 8]);
+    assert_eq!(tensor.shape(), &[1, 3, 8, 8]);
+    Ok(())
+}