Improve error messages for tensor size errors

runtime/core/exec_aten/util/dim_order_util.h

@@ -9,6 +9,8 @@
 #pragma once
 
 #include <cstdint>
+#include <cstdio>
+#include <cstring>
 
 #include <executorch/runtime/core/error.h>
 #include <executorch/runtime/platform/assert.h>
@@ -257,6 +259,36 @@ ET_NODISCARD inline Error stride_to_dim_order(
   }
   return Error::Ok;
 }
+
+/**
+ * Print a string representation of an ArrayRef of tensor sizes into a
+ * user-provided string buffer. If the user buffer is too small, the string
+ * will be truncated. The output is of the format (1,2,3,4).
+ *
+ * Note that we cannot use ArrayRef here due to a circular dependency (see
+ * above comments).
+ */
+template <class SizesType>
+inline void sizes_to_string(
+    char* output,
+    size_t output_size,
+    SizesType* sizes,
+    size_t rank) {
+  auto remaining_size = output_size;
+  for (auto i = 0; remaining_size > 0 && i < rank; i++) {
+    snprintf(
+        output,
+        remaining_size,
+        "%s%zd",
+        i == 0 ? "(" : ",",
+        static_cast<size_t>(sizes[i]));
+    auto len = strlen(output);
+    output += len;
+    remaining_size -= len;
+  }
+  snprintf(output, remaining_size, ")");
+}
+
 } // namespace runtime
 } // namespace executorch
 

runtime/core/portable_type/tensor_impl.cpp

@@ -90,24 +90,46 @@ Error TensorImpl::internal_resize_contiguous(ArrayRef<SizesType> new_sizes) {
   if (dim_ == 0) {
     return Error::Ok;
   }
+
   switch (shape_dynamism_) {
     case TensorShapeDynamism::STATIC:
-      ET_CHECK_OR_RETURN_ERROR(
-          std::equal(sizes_, sizes_ + dim_, new_sizes.begin()),
-          NotSupported,
-          "Attempted to resize a static tensor");
+      if (!std::equal(sizes_, sizes_ + dim_, new_sizes.begin())) {
+#ifdef ET_LOG_ENABLED
+        std::array<char, 5> old_sizes_str, new_sizes_str;
+
+        executorch::runtime::sizes_to_string(
+            old_sizes_str.data(),
+            old_sizes_str.size(),
+            sizes().data(),
+            sizes().size());
+        executorch::runtime::sizes_to_string(
+            new_sizes_str.data(),
+            new_sizes_str.size(),
+            new_sizes.data(),
+            new_sizes.size());
+#endif
+
+        ET_CHECK_OR_RETURN_ERROR(
+            false,
+            NotSupported,
+            "Attempted to resize a static tensor. Expected shape %s, but received %s.",
+            old_sizes_str.data(),
+            new_sizes_str.data())
+      }
+
       break;
     case TensorShapeDynamism::DYNAMIC_BOUND:
       // TODO(T175194371): Unbounded dynamic tensor resizing is not yet
       // supported: treat them as upper-bounded.
     case TensorShapeDynamism::DYNAMIC_UNBOUND: {
       const auto new_numel = compute_numel(new_sizes.data(), dim_);
+
       ET_CHECK_OR_RETURN_ERROR(
           new_numel <= numel_bound_,
           NotSupported,
-          "Attempted to resize a bounded tensor with capacity of %zu elements to %zu elements.",
-          new_numel,
-          numel_bound_);
+          "Attempted to resize a bounded tensor with a maximum capacity of %zu elements to %zu elements.",
+          numel_bound_,
+          new_numel);
 
       if (strides_ && dim_order_) {
         auto error =

runtime/executor/method.cpp

@@ -1061,7 +1061,7 @@ Error Method::execute_instruction() {
         // We know that instr_args_as_KernelCall is non-null because it was
         // checked at init time.
         auto op_index = instruction->instr_args_as_KernelCall()->op_index();
-        auto op = serialization_plan_->operators()->Get(op_index);
+        ET_UNUSED auto op = serialization_plan_->operators()->Get(op_index);
         ET_LOG(
             Error,
             "KernelCall failed at instruction %zu:%zu in operator %s.%s: 0x%x",

runtime/kernel/operator_registry.cpp

@@ -74,7 +74,8 @@ Error register_kernels_internal(const Span<const Kernel> kernels) {
     return Error::Internal;
   }
   // for debugging purpose
-  const char* lib_name = et_pal_get_shared_library_name(kernels.data());
+  ET_UNUSED const char* lib_name =
+      et_pal_get_shared_library_name(kernels.data());
 
   for (const auto& kernel : kernels) {
     // Linear search. This is fine if the number of kernels is small.