LHS broadcasting addition for dynamic fusion

* Binary elementwise operator now can have broadcasting in either
  X dimension, Y+Z dimension, or both, in either LHS or RHS
  operand.
* Fix bug in CL code to support batching.

Resolves: COMPMID-5704
Signed-off-by: Viet-Hoa Do <viet-hoa.do@arm.com>
Change-Id: I51b04986d30861f255ca9f754adffa0e6c85a26b
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8898
Reviewed-by: SiCong Li <sicong.li@arm.com>
Reviewed-by: Ramy Elgammal <ramy.elgammal@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Dynamic-Fusion: Ramy Elgammal <ramy.elgammal@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 25 insertions, 7 deletions

diff --git a/src/dynamic_fusion/sketch/gpu/components/cl/ClComponentElementwiseBinary.cpp b/src/dynamic_fusion/sketch/gpu/components/cl/ClComponentElementwiseBinary.cpp
index a17d835ac6..9b006b13ce 100644
--- a/src/dynamic_fusion/sketch/gpu/components/cl/ClComponentElementwiseBinary.cpp
+++ b/src/dynamic_fusion/sketch/gpu/components/cl/ClComponentElementwiseBinary.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2022 Arm Limited.
+ * Copyright (c) 2022-2023 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -66,8 +66,30 @@ Status ClComponentElementwiseBinary::validate(const ArgumentPack<ITensorInfo> &t
     const TensorShape out_shape = TensorShape::broadcast_shape(lhs->tensor_shape(), rhs->tensor_shape());
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible");
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst->tensor_shape(), 0), "Wrong shape for dst.");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG((!rhs_in_place && !lhs_in_place) && detail::have_different_dimensions(lhs->tensor_shape(), dst->tensor_shape(), 0),
-                                    "Only the rhs operand can be broadcast to match the accumulator's (lhs) shape");
+
+    const auto &lhs_shape = lhs->tensor_shape();
+    const auto &rhs_shape = rhs->tensor_shape();
+    const auto &dst_shape = dst->tensor_shape();
+
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(
+        detail::have_different_dimensions(lhs_shape, dst_shape, 0) && detail::have_different_dimensions(rhs_shape, dst_shape, 0),
+        "Only LHS or RHS can be broadcasting, not both.");
+
+    // Dimension Y and Z are collapsed together in the current kernel implementation,
+    // hence they cannot be independently broadcast or non-broadcast.
+    // See: ClTemplateElementwiseBinary::get_window
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(
+        (lhs_shape[1] != dst_shape[1] || rhs_shape[1] != dst_shape[1]) != (lhs_shape[2] != dst_shape[2] || rhs_shape[2] != dst_shape[2]),
+        "Dimension Y and Z must both be either broadcast or non-broadcast.");
+
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(
+        detail::have_different_dimensions(lhs_shape, dst_shape, 3),
+        "LHS broadcast in dimension 3 or higher is not supported.");
+
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(
+        detail::have_different_dimensions(rhs_shape, dst_shape, 3),
+        "RHS broadcast in dimension 3 or higher is not supported.");
+
     // Matching data type
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, rhs);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst);
@@ -76,10 +98,6 @@ Status ClComponentElementwiseBinary::validate(const ArgumentPack<ITensorInfo> &t
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(lhs, rhs);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(lhs, dst);
 
-    // Batching case not supported yet
-    const size_t idx_batch = get_data_layout_dimension_index(lhs->data_layout(), DataLayoutDimension::BATCHES);
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG((lhs->tensor_shape()[idx_batch] != 1) || (rhs->tensor_shape()[idx_batch] != 1) || (dst->tensor_shape()[idx_batch] != 1), "Batching case not supported yet");
-
     // All tensor infos are initialized
     ARM_COMPUTE_RETURN_ERROR_ON(lhs->tensor_shape().total_size() == 0);
     ARM_COMPUTE_RETURN_ERROR_ON(rhs->tensor_shape().total_size() == 0);