Add broadcasting support in NEPixelWiseMultiplicationKernel for FP16

* FP16 kernel missed the broadcast path

* Resolves: COMPMID-4113

Change-Id: I8fd79030f2ae9c268dfeed672a57c6d0f64f58f4
Signed-off-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4926
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sheri Zhang <sheri.zhang@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

diff --git a/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp b/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp
index 39517f6ff697b897b3afad9dd04aa51bcabd5e92..6661326ea84676d31bd22130d1eefeda1baece6f 100644 (file)
--- a/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp
+++ b/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp
@@ -1157,68 +1157,122 @@ void c_mul_F32_F32_F32_n(const ITensor *in1, const ITensor *in2, ITensor *out, c
 void mul_F16_F16_F16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window, float scale)
 {
     // Create input windows
-    Window win        = window;
     Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape());
     Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape());
 
     // Clear X Dimension on execution window as we handle manually
+    Window win = window;
     win.set(Window::DimX, Window::Dimension(0, 1, 1));
-    input1_win.set(Window::DimX, Window::Dimension(0, 1, 1));
-    input2_win.set(Window::DimX, Window::Dimension(0, 1, 1));
-
-    Iterator input1(in1, input1_win);
-    Iterator input2(in2, input2_win);
-    Iterator output(out, win);
-
-    const int  window_step_x  = 16;
-    const auto window_start_x = static_cast<int>(window.x().start());
-    const auto window_end_x   = static_cast<int>(window.x().end());
-
-    execute_window_loop(win, [&](const Coordinates &)
+    constexpr int window_step_x         = 16;
+    const auto    window_start_x        = static_cast<int>(window.x().start());
+    const auto    window_end_x          = static_cast<int>(window.x().end());
+    const bool    is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
+    if(is_broadcast_across_x)
     {
-        const auto input1_ptr = reinterpret_cast<const float16_t *>(input1.ptr());
-        const auto input2_ptr = reinterpret_cast<const float16_t *>(input2.ptr());
-        const auto output_ptr = reinterpret_cast<float16_t *>(output.ptr());
-
-        // Compute window_step_x elements per iteration
-        int x = window_start_x;
-        for(; x <= (window_end_x - window_step_x); x += window_step_x)
+        const bool     is_broadcast_input_2 = input2_win.x().step() == 0;
+        Window         broadcast_win        = is_broadcast_input_2 ? input2_win : input1_win;
+        Window         non_broadcast_win    = !is_broadcast_input_2 ? input2_win : input1_win;
+        const ITensor *broadcast_tensor     = is_broadcast_input_2 ? in2 : in1;
+        const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1;
+        // Clear X Dimension on execution window as we handle manually
+        non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1));
+        Iterator broadcast_input(broadcast_tensor, broadcast_win);
+        Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win);
+        Iterator output(out, win);
+        execute_window_loop(win, [&](const Coordinates &)
         {
-            const float16x8x2_t ta1 =
+            const auto          non_broadcast_input_ptr = reinterpret_cast<const float16_t *>(non_broadcast_input.ptr());
+            const auto          output_ptr              = reinterpret_cast<float16_t *>(output.ptr());
+            const auto          broadcast_value         = *reinterpret_cast<const float16_t *>(broadcast_input.ptr());
+            const float16x8x2_t broadcast_value_vec =
             {
                 {
-                    vld1q_f16(input1_ptr + x),
-                    vld1q_f16(input1_ptr + x + 8),
+                    vdupq_n_f16(broadcast_value),
+                    vdupq_n_f16(broadcast_value),
                 }
             };
-            const float16x8x2_t ta2 =
+            const auto scale_vec = vdupq_n_f16(scale);
+            // Compute window_step_x elements per iteration
+            int x = window_start_x;
+            for(; x <= (window_end_x - window_step_x); x += window_step_x)
             {
+                const float16x8x2_t non_broadcast_v =
                 {
-                    vld1q_f16(input2_ptr + x),
-                    vld1q_f16(input2_ptr + x + 8),
-                }
-            };
-            const float16x8_t   scale_vec = vdupq_n_f16(scale);
-            const float16x8x2_t result =
-            {
+                    {
+                        vld1q_f16(non_broadcast_input_ptr + x),
+                        vld1q_f16(non_broadcast_input_ptr + x + 8),
+                    }
+                };
+                const float16x8x2_t result =
                 {
-                    vmulq_f16(vmulq_f16(ta1.val[0], ta2.val[0]), scale_vec),
-                    vmulq_f16(vmulq_f16(ta1.val[1], ta2.val[1]), scale_vec),
-                }
-            };
-            vst1q_f16(output_ptr + x, result.val[0]);
-            vst1q_f16(output_ptr + x + 8, result.val[1]);
-        }
-
-        // Compute left-over elements
-        for(; x < window_end_x; ++x)
+                    {
+                        vmulq_f16(vmulq_f16(broadcast_value_vec.val[0], non_broadcast_v.val[0]), scale_vec),
+                        vmulq_f16(vmulq_f16(broadcast_value_vec.val[1], non_broadcast_v.val[1]), scale_vec),
+                    }
+                };
+                vst1q_f16(output_ptr + x, result.val[0]);
+                vst1q_f16(output_ptr + x + 8, result.val[1]);
+            }
+            // Compute left-over elements
+            for(; x < window_end_x; ++x)
+            {
+                const auto non_broadcast_v = *(non_broadcast_input_ptr + x);
+                *(output_ptr + x)          = broadcast_value * non_broadcast_v * scale;
+            }
+        },
+        broadcast_input, non_broadcast_input, output);
+    }
+    else
+    {
+        input1_win.set(Window::DimX, Window::Dimension(0, 1, 1));
+        input2_win.set(Window::DimX, Window::Dimension(0, 1, 1));
+        Iterator input1(in1, input1_win);
+        Iterator input2(in2, input2_win);
+        Iterator output(out, win);
+        execute_window_loop(win, [&](const Coordinates &)
         {
-            const auto ta1    = *(input1_ptr + x);
-            const auto ta2    = *(input2_ptr + x);
-            *(output_ptr + x) = ta1 * ta2 * scale;
-        }
-    },
-    input1, input2, output);
+            const auto input1_ptr = reinterpret_cast<const float16_t *>(input1.ptr());
+            const auto input2_ptr = reinterpret_cast<const float16_t *>(input2.ptr());
+            const auto output_ptr = reinterpret_cast<float16_t *>(output.ptr());
+            // Compute window_step_x elements per iteration
+            int x = window_start_x;
+            for(; x <= (window_end_x - window_step_x); x += window_step_x)
+            {
+                const float16x8x2_t ta1 =
+                {
+                    {
+                        vld1q_f16(input1_ptr + x),
+                        vld1q_f16(input1_ptr + x + 8),
+                    }
+                };
+                const float16x8x2_t ta2 =
+                {
+                    {
+                        vld1q_f16(input2_ptr + x),
+                        vld1q_f16(input2_ptr + x + 8),
+                    }
+                };
+                const float16x8_t   scale_vec = vdupq_n_f16(scale);
+                const float16x8x2_t result =
+                {
+                    {
+                        vmulq_f16(vmulq_f16(ta1.val[0], ta2.val[0]), scale_vec),
+                        vmulq_f16(vmulq_f16(ta1.val[1], ta2.val[1]), scale_vec),
+                    }
+                };
+                vst1q_f16(output_ptr + x, result.val[0]);
+                vst1q_f16(output_ptr + x + 8, result.val[1]);
+            }
+            // Compute left-over elements
+            for(; x < window_end_x; ++x)
+            {
+                const auto ta1    = *(input1_ptr + x);
+                const auto ta2    = *(input2_ptr + x);
+                *(output_ptr + x) = ta1 * ta2 * scale;
+            }
+        },
+        input1, input2, output);
+    }
 }
 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */