[fix] check for histogramdd when bins is int[]

aten/src/ATen/native/Histogram.cpp

@@ -299,6 +299,10 @@ std::vector<Tensor>& histogramdd_bin_edges_out_cpu(const Tensor& self, IntArrayR
 
     auto outer_bin_edges = select_outer_bin_edges(reshaped_self, range);
 
+    const int64_t bin_size = bin_ct.size();
+    TORCH_CHECK(
+        N == bin_size,
+        "histogramdd: The size of bins must be equal to the innermost dimension of the input.");
     for (const auto dim : c10::irange(N)) {
         linspace_out(outer_bin_edges.first[dim], outer_bin_edges.second[dim],
                 bin_ct[dim] + 1, bin_edges_out[dim]);

torch/testing/_internal/common_methods_invocations.py

@@ -2748,6 +2748,12 @@ def sample_inputs_histogramdd(op_info, device, dtype, requires_grad, **kwargs):
         yield SampleInput(input_tensor, bins_tensor,
                           weight=weight_tensor, density=density)
 
+def error_inputs_histogramdd(opinfo, device, **kwargs):
+    invalid_bins = [1, 1, 1, 1, 1]
+    make_arg = partial(make_tensor, dtype=torch.float, device=device, requires_grad=False)
+    msg = "histogramdd: The size of bins must be equal to the innermost dimension of the input."
+    yield ErrorInput(SampleInput(make_arg(5, 6), invalid_bins), error_regex=msg)
+
 def sample_inputs_histc(op_info, device, dtype, requires_grad, **kwargs):
     make_arg = partial(make_tensor, dtype=dtype, device=device, requires_grad=requires_grad)
 
@@ -16024,8 +16030,11 @@ def reference_flatten(input, start_dim=0, end_dim=-1):
            dtypes=floating_types(),
            dtypesIfCUDA=_dispatch_dtypes(),  # histogramdd is only implemented on CPU
            sample_inputs_func=sample_inputs_histogramdd,
+           error_inputs_func=error_inputs_histogramdd,
            supports_autograd=False,
            skips=(
+               # Not implemented on CUDA
+               DecorateInfo(unittest.expectedFailure, 'TestCommon', 'test_errors', device_type='cuda'),
                DecorateInfo(unittest.expectedFailure, 'TestNormalizeOperators', 'test_normalize_operator_exhaustive'),
                # JIT tests don't work with Tensor keyword arguments
                # https://github.com/pytorch/pytorch/issues/58507