1 files changed, 118 insertions, 0 deletions
diff --git a/src/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.cpp b/src/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.cpp
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+++ b/src/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.cpp
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+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+
+#include "arm_compute/core/NEON/kernels/assembly/NEGEMMInterleavedTransformAWrapper.h"
+
+#include "NEGEMMInterleavedStrategies.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/ITensor.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/WindowIterator.h"
+
+#include "utils/TypePrinter.h"
+
+namespace arm_compute
+{
+template <typename To, bool use_dot>
+void NEGEMMInterleavedTransformAWrapperTemplate<To, use_dot>::configure(const ITensor *a, ITensor *transformed_a, bool transpose_a, const Window &block_walker,
+                                                                        const INEGEMMWrapperKernel::Params &params)
+{
+    _a              = a;
+    _transformed_a  = transformed_a;
+    _transpose_a    = transpose_a;
+    _Ksize          = params.K;
+    _Msize          = params.M;
+    _k_multi_window = block_walker.shift_dimensions(1); // block_walker contains (M,K,Multi) --> shift by 1 to get rid of the "M" dimension
+}
+
+template <typename To, bool use_dot>
+void NEGEMMInterleavedTransformAWrapperTemplate<To, use_dot>::transform(const TransformAWorkload &wl, const ThreadInfo &info, const Window &batch_window, const Coordinates &start_offset,
+                                                                        const Coordinates &end_offset)
+{
+    using strategy = typename Kernel<To, use_dot>::strategy;
+
+    strategy           strat(info.cpu_info);
+    TensorAccessor<To> a(*_a);
+    TensorAccessor<To> transformed_a(*_transformed_a);
+
+    if(_a->info()->data_layout() == DataLayout::NHWC)
+    {
+        // In the case of NHWC we want to interpret the output shape as 3D. Thus, the batch stride for A is
+        // the relevant multiple of the row stride.
+        const size_t nhwc_batch_stride = _a->info()->strides_in_bytes().y() * _Msize;
+        a.set_stride(2, nhwc_batch_stride);
+    }
+
+    unsigned int last_m = 0;
+    //TODO: Create a new iterate_1D( DimY);
+    int  last_y          = -1;
+    auto window_iterator = arm_compute::create_window_iterator(batch_window, start_offset, end_offset, [&](const Coordinates & id)
+    {
+        if(id.y() != last_y)
+        {
+            last_y               = id.y();
+            unsigned int batch   = id.y();
+            unsigned int first_m = id.x();
+
+            if(first_m >= last_m)
+                return;
+
+            strat.transforms.PrepareA(transformed_a(0, first_m, batch),
+                                      a(0, 0, batch, wl._multi),
+                                      a.stride(1), first_m, last_m, wl._k0, wl._kmax, _transpose_a);
+        }
+    });
+    auto on_new_row_size = [&](unsigned int start, unsigned int end)
+    {
+        last_m = std::min(end, _Msize);
+    };
+    window_iterator.iterate_2D(on_new_row_size);
+}
+
+template <typename To, bool use_dot>
+void NEGEMMInterleavedTransformAWrapperTemplate<To, use_dot>::create_workloads(std::vector<TransformAWorkload> &workloads)
+{
+    execute_window_loop(_k_multi_window, [&](const Coordinates & id)
+    {
+        const unsigned int k0    = id.x();
+        const unsigned int multi = id.y();
+        const unsigned int kmax  = std::min(k0 + _k_multi_window.x().step(), _Ksize);
+
+        workloads.push_back(TransformAWorkload(k0, kmax, multi));
+    });
+}
+
+template class NEGEMMInterleavedTransformAWrapperTemplate<float>;
+#ifdef __aarch64__
+template class NEGEMMInterleavedTransformAWrapperTemplate<uint8_t>;
+template class NEGEMMInterleavedTransformAWrapperTemplate<int8_t>;
+template class NEGEMMInterleavedTransformAWrapperTemplate<uint8_t, true>;
+template class NEGEMMInterleavedTransformAWrapperTemplate<int8_t, true>;
+#endif /* __aarch64__ */
+
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+template class NEGEMMInterleavedTransformAWrapperTemplate<float16_t>;
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+} // namespace arm_compute