torch::nn::AdaptiveLogSoftmaxWithLoss: check length of cutoffs (#106777)

Sehun0819 · pytorchmergebot · commit c36b31d5302d · 2023-10-05T05:35:47.000Z
Fixes #106698 Also added a check for python API, because current error message ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/sehoon/pytorch-latest/torch/nn/modules/adaptive.py", line 128, in __init__ or (min(cutoffs) <= 0) \ ValueError: min() arg is an empty sequence ``` is not very comprehensible. Pull Request resolved: #106777 Approved by: https://github.com/albanD
diff --git a/torch/csrc/api/src/nn/modules/adaptive.cpp b/torch/csrc/api/src/nn/modules/adaptive.cpp
@@ -24,6 +24,9 @@ AdaptiveLogSoftmaxWithLossImpl::AdaptiveLogSoftmaxWithLossImpl(
 }
 
 void AdaptiveLogSoftmaxWithLossImpl::reset() {
+  TORCH_CHECK(
+      options.cutoffs().size() > 0,
+      "cutoffs should be a sequence of length larger than 0");
   TORCH_CHECK(
       std::is_sorted(options.cutoffs().begin(), options.cutoffs().end()) &&
           *std::min_element(
diff --git a/torch/nn/modules/adaptive.py b/torch/nn/modules/adaptive.py
@@ -124,6 +124,9 @@ def __init__(
 
         cutoffs = list(cutoffs)
 
+        if (len(cutoffs) == 0):
+            raise ValueError("cutoffs should be a sequence of length larger than 0")
+
         if (cutoffs != sorted(cutoffs)) \
                 or (min(cutoffs) <= 0) \
                 or (max(cutoffs) > (n_classes - 1)) \
