1 files changed, 60 insertions, 21 deletions

diff --git a/src/gpu/cl/kernels/ClScatterKernel.cpp b/src/gpu/cl/kernels/ClScatterKernel.cpp
index 21c0253f91..19adc1ef34 100644
--- a/src/gpu/cl/kernels/ClScatterKernel.cpp
+++ b/src/gpu/cl/kernels/ClScatterKernel.cpp
@@ -66,21 +66,44 @@ Status ClScatterKernel::validate(const ITensorInfo *updates,
     const int32_t upt_dims = upt_shape.num_dimensions();
     const int32_t dst_dims = dst_shape.num_dimensions();
     const int32_t ind_dims = ind_shape.num_dimensions();
+    const int32_t data_dim = upt_dims - (ind_dims - 1); // Number of batch dims is the number of indices dims - 1
 
     const int32_t index_len = ind_shape[0];
+    bool          unsupported_padding_config =
+        (dst_dims == index_len) && index_len > 1 && (dst->has_padding() || updates->has_padding());
 
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(unsupported_padding_config, "Padding is not supported with these shapes.");
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(updates, dst);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(indices, DataType::S32);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(dst, DataType::F32, DataType::F16, DataType::S32, DataType::S16,
                                                  DataType::S8, DataType::U32, DataType::U16, DataType::U8);
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(ind_dims > 2, "Only 2D indices tensors are currently supported.");
+
+    // Check data dims in update tensor and output tensor are equal
+    for (int32_t i = 0; i < data_dim; i++)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MSG(upt_shape[i] != dst_shape[i],
+                                        "Data dims should be same size in both updates and ouput tensor.");
+    }
+
+    // Check if batch dims in indices and updates tensor are equal.
+    for (int32_t i = 0; i < ind_dims - 1; i++)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_MSG(upt_shape[data_dim + i] != ind_shape[i + 1],
+                                        "Batch dimensions should be the same in updates and indices tensor.");
+    }
+
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(ind_shape[1] != upt_shape[data_dim],
+                                    "Height of indices tensor should match size of highest dimension in updates tensor "
+                                    "(Excluding batch dimension)");
+
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(
-        ind_shape[1] != upt_shape[upt_dims - 1],
-        "Height of indices tensor should match size of highest dimension in updates tensor.");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(upt_dims > dst_dims, "Update tensor cannot have more dims than output tensor.");
+        data_dim >= dst_dims, "Update tensor cannot have more dims than output tensor. (Excluding batch dimensions)");
+    ARM_COMPUTE_RETURN_ERROR_ON(index_len != dst_dims - data_dim);
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG((ind_dims < 2), "Shape of Indices tensor must be at least 2D");
 
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(index_len > max_index_length, "Maximum supported index length is 5!");
-    ARM_COMPUTE_RETURN_ERROR_ON(index_len != dst_dims - upt_dims + 1);
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(index_len > dst_dims && dst_dims != 1,
+                                    "Index length should be smaller than or equal to number of output dims");
 
     return Status{};
 }
@@ -95,34 +118,40 @@ void ClScatterKernel::configure(const ClCompileContext &compile_context,
     ARM_COMPUTE_LOG_PARAMS(updates, indices, dst, info);
 
     const TensorShape &dst_shape = dst->tensor_shape();
+    const int          index_len = indices->dimension(0);
 
-    const bool is_scalar_block = updates->num_dimensions() == 1;
-    const int  n0 = adjust_vec_size(16 / updates->element_size(), is_scalar_block ? 1 : updates->dimension(0));
+    // Check for single element data block
+    const bool is_scalar_block = (dst->num_dimensions() == static_cast<uint32_t>(index_len));
 
+    const int n0         = adjust_vec_size(16 / updates->element_size(), is_scalar_block ? 1 : updates->dimension(0));
     const int partial_n0 = updates->dimension(0) % n0;
 
     // The GWS will be 2D [x, y]
     //  x-dimension refers to the x coordinate of the dst tensor
     //  y-dimension refers to the collapsed y-coordinate of the data part of the dst tensor
-    Window    win       = calculate_max_window(dst_shape, Steps(n0));
-    const int index_len = indices->dimension(0);
+    Window win;
 
-    // Collapse the dimensions corresponding to indices in the execution window
-    for (int i = 0; i < index_len; ++i)
+    if (!is_scalar_block)
     {
-        win.set(dst->num_dimensions() - (i + 1), Window::Dimension(0, 1, 1));
-    }
+        win = calculate_max_window(dst_shape, Steps(n0));
+
+        // Collapse the dimensions corresponding to indices in the execution window
+        for (int i = 0; i < index_len; ++i)
+        {
+            win.set(dst->num_dimensions() - (i + 1), Window::Dimension(0, 1, 1));
+        }
 
-    win = win.collapse(win, 1);
+        win = win.collapse(win, 1);
+    }
 
     // Set build options
     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(dst->data_type()));
     build_opts.add_option_if(is_data_type_float(dst->data_type()), "-DIS_FLOAT");
 
-    const int num_dims = dst->num_dimensions();
-
-    build_opts.add_option("-DNUM_INDICES=" + support::cpp11::to_string(indices->dimension(1)));
+    const int   num_dims      = dst->num_dimensions();
+    TensorShape ind_collapsed = indices->tensor_shape().collapsed_from(1);
+    build_opts.add_option("-DNUM_INDICES=" + support::cpp11::to_string(ind_collapsed[1]));
     build_opts.add_option("-DINDEX_LENGTH=" + support::cpp11::to_string(index_len));
 
     // We provide 5 variables to use in a constant array
@@ -185,13 +214,23 @@ void ClScatterKernel::run_op(ITensorPack &tensors, const Window &window, cl::Com
         utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1));
     auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
 
-    const ITensorInfo *dst_info = dst->info();
-    const int          num_dims = dst_info->num_dimensions();
+    const ITensorInfo *dst_info  = dst->info();
+    const ITensorInfo *upd_info  = updates->info();
+    const int          num_dims  = dst_info->num_dimensions();
+    const int          ind_dims  = indices->info()->num_dimensions();
+    const int          index_len = indices->info()->dimension(0);
 
-    const int index_len = indices->info()->dimension(0);
+    bool unsupported_padding_config =
+        num_dims == index_len && index_len > 1 && (dst_info->has_padding() || upd_info->has_padding());
+    if (unsupported_padding_config)
+    {
+        ARM_COMPUTE_ERROR("Unsupported Configuration! Padding not supported with these shapes.");
+    }
 
     // calculate m-dimensional data block strides in updates and destination tensors
-    const int upt_block_stride = updates->info()->strides_in_bytes()[updates->info()->num_dimensions() - 1];
+    const int upt_block_stride =
+        updates->info()->strides_in_bytes()[updates->info()->num_dimensions() - (ind_dims - 1)];
+
     const int out_block_stride = dst_info->strides_in_bytes()[num_dims - index_len];
 
     unsigned int idx = 0;