Reject zero-length sequences in LSTM/GRU with a clear message

src/nn/rnn.rs

@@ -185,7 +185,13 @@ fn check_sequence(input: &Tensor, input_size: usize, layer: &str) -> (usize, usi
         "{layer} expects {input_size} features, got {:?}",
         input.shape()
     );
-    (input.dim(0), input.dim(1))
+    let (batch, steps) = (input.dim(0), input.dim(1));
+    assert!(
+        steps > 0,
+        "{layer}: sequence length is 0 in shape {:?}",
+        input.shape()
+    );
+    (batch, steps)
 }
 
 /// Timestep `t` as `[batch, features]`.

src/tensor/ops/view.rs

@@ -200,6 +200,7 @@ impl Tensor {
 
     /// Join tensors along a new dimension inserted at `axis`.
     pub fn stack(parts: &[&Tensor], axis: usize) -> Tensor {
+        assert!(!parts.is_empty(), "stack: needs at least one tensor");
         let lifted: Vec<Tensor> = parts.iter().map(|t| t.unsqueeze(axis)).collect();
         Tensor::cat(&lifted.iter().collect::<Vec<_>>(), axis)
     }

tests/rnn.rs

@@ -0,0 +1,21 @@
+use fastnn::prelude::*;
+
+#[test]
+#[should_panic(expected = "sequence length is 0")]
+fn lstm_zero_length_sequence_panics() {
+    let lstm = LSTM::new(2, 3);
+    lstm.forward(&Tensor::zeros(&[1, 0, 2]));
+}
+
+#[test]
+#[should_panic(expected = "sequence length is 0")]
+fn gru_zero_length_sequence_panics() {
+    let gru = GRU::new(2, 3);
+    gru.forward(&Tensor::zeros(&[1, 0, 2]));
+}
+
+#[test]
+#[should_panic(expected = "stack: needs at least one tensor")]
+fn stack_empty_panics() {
+    Tensor::stack(&[], 0);
+}