1 files changed, 221 insertions, 0 deletions
diff --git a/src/cpu/operators/CpuSoftmax.cpp b/src/cpu/operators/CpuSoftmax.cpp
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+++ b/src/cpu/operators/CpuSoftmax.cpp
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+/*
+ * Copyright (c) 2021 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 "src/cpu/operators/CpuSoftmax.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "arm_compute/runtime/NEON/NEScheduler.h"
+#include "src/core/helpers/MemoryHelpers.h"
+#include "src/core/helpers/SoftmaxHelpers.h"
+#include "src/cpu/kernels/CpuSoftmaxKernel.h"
+#include "src/cpu/utils/CpuAuxTensorHandler.h"
+
+using namespace arm_compute::experimental;
+
+namespace arm_compute
+{
+namespace cpu
+{
+template <bool IS_LOG>
+CpuSoftmaxGeneric<IS_LOG>::CpuSoftmaxGeneric()
+    : _permute_input(),
+      _permute_output(),
+      _max_kernel(),
+      _softmax_kernel(),
+      _max(),
+      _tmp(),
+      _input_permuted(),
+      _output_permuted(),
+      _needs_permute(false),
+      _aux_mem(InternalTensorIdx::COUNT)
+{
+}
+
+template <bool IS_LOG>
+void CpuSoftmaxGeneric<IS_LOG>::configure(const ITensorInfo *src, ITensorInfo *dst, float beta, int32_t axis)
+{
+    // Perform validation step
+    ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+    ARM_COMPUTE_ERROR_THROW_ON(CpuSoftmaxGeneric::validate(src, dst, beta, axis));
+
+    const unsigned int actual_axis = static_cast<unsigned int>(wrap_around(axis, static_cast<int32_t>(src->num_dimensions())));
+
+    _needs_permute = actual_axis > 0;
+
+    if(_needs_permute)
+    {
+        _permute_input.configure(src, &_input_permuted, softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis));
+    }
+
+    // We want to deal with a 2D input. Either it is the permuted version of the original input (4D case)
+    // or it is the original input case (2D case)
+    const ITensorInfo *tmp_input = (_needs_permute ? &_input_permuted : src);
+
+    // Create intermediate tensors shapes
+    TensorShape max_sum_shape = tmp_input->tensor_shape();
+    max_sum_shape.set(0, 1);
+    const TensorInfo input_info    = tmp_input->clone()->reset_padding().set_is_resizable(true);
+    DataType         tmp_data_type = is_data_type_quantized_asymmetric(tmp_input->data_type()) ? DataType::F32 : tmp_input->data_type();
+    TensorInfo       tensor_info_tmp(input_info.clone()->set_data_type(tmp_data_type));
+    TensorInfo       max_info(tmp_input->clone()->set_tensor_shape(max_sum_shape));
+
+    // Init intermediate tensors
+    _max = TensorInfo(max_info);
+    _tmp = TensorInfo(tensor_info_tmp);
+
+    // Configure kernels
+    auto mk = std::make_unique<kernels::CpuLogits1DMaxKernel>();
+    mk->configure(tmp_input, &_max);
+    _max_kernel = std::move(mk);
+
+    auto sm = std::make_unique<kernels::CpuLogits1DSoftmaxKernel<IS_LOG>>();
+    if(_needs_permute)
+    {
+        // The normalization kernel stores the result in a permuted output tensor
+        sm->configure(tmp_input, &_max, &_output_permuted, beta, &_tmp);
+
+        // Re-permute the permuted output into the requested (4D) output
+        _permute_output.configure(&_output_permuted, dst, softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis));
+    }
+    else
+    {
+        // Softmax 2D case
+        sm->configure(tmp_input, &_max, dst, beta, &_tmp);
+    }
+    _softmax_kernel = std::move(sm);
+
+    _aux_mem[InternalTensorIdx::MAX] = MemoryInfo(offset_int_vec(InternalTensorIdx::MAX), MemoryLifetime::Temporary, _max.total_size());
+    _aux_mem[InternalTensorIdx::TMP] = MemoryInfo(offset_int_vec(InternalTensorIdx::TMP), MemoryLifetime::Temporary, _tmp.total_size());
+
+    _aux_mem[InternalTensorIdx::PERMUTED_SRC] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), MemoryLifetime::Temporary, _input_permuted.total_size());
+    _aux_mem[InternalTensorIdx::PERMUTED_DST] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_DST), MemoryLifetime::Temporary, _output_permuted.total_size());
+}
+
+template <bool IS_LOG>
+Status CpuSoftmaxGeneric<IS_LOG>::validate(const ITensorInfo *src, const ITensorInfo *dst, float beta, int32_t axis)
+{
+    // Perform validation step
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst);
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(src->num_dimensions() > 4, "Only up to 4 dimensions are supported");
+    ARM_COMPUTE_UNUSED(beta);
+    ARM_COMPUTE_RETURN_ERROR_ON(axis < static_cast<int32_t>(-src->num_dimensions()) || static_cast<int32_t>(src->num_dimensions()) <= axis);
+
+    // Create intermediate tensor info
+    DataType         tmp_data_type = src->data_type();
+    const TensorInfo tensor_info_tmp(src->clone()->set_data_type(tmp_data_type).set_is_resizable(true));
+
+    TensorShape max_sum_shape = src->tensor_shape();
+    max_sum_shape.set(0, 1);
+    const TensorInfo tensor_info_max_sum(src->clone()->set_tensor_shape(max_sum_shape).set_data_type(tmp_data_type).set_quantization_info(src->quantization_info()).set_is_resizable(true));
+    const TensorInfo dont_care;
+
+    const unsigned int actual_axis = static_cast<unsigned int>(wrap_around(axis, static_cast<int32_t>(src->num_dimensions())));
+
+    const bool needs_permute = actual_axis > 0;
+
+    if(needs_permute)
+    {
+        const PermutationVector permutation_vector = softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis);
+        const TensorShape       permuted_shape     = misc::shape_calculator::compute_permutation_output_shape(*src, permutation_vector);
+        TensorInfo              input_permuted(src->clone()->set_tensor_shape(permuted_shape));
+        ARM_COMPUTE_RETURN_ON_ERROR(CpuPermute::validate(src, &input_permuted, permutation_vector));
+        TensorInfo output_permuted(dst->clone()->set_tensor_shape(permuted_shape));
+        ARM_COMPUTE_RETURN_ON_ERROR(CpuPermute::validate(&output_permuted, dst, permutation_vector));
+    }
+
+    ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuLogits1DMaxKernel::validate(src, &tensor_info_max_sum));
+    ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuLogits1DSoftmaxKernel<IS_LOG>::validate(&tensor_info_tmp, &tensor_info_max_sum, dst, beta, &dont_care));
+
+    return Status{};
+}
+
+template <bool IS_LOG>
+void CpuSoftmaxGeneric<IS_LOG>::run(ITensorPack &tensors)
+{
+    ARM_COMPUTE_ERROR_ON_MSG(tensors.empty(), "No inputs provided");
+
+    auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
+    auto dst = tensors.get_tensor(TensorType::ACL_DST);
+
+    CpuAuxTensorHandler tmp(offset_int_vec(InternalTensorIdx::TMP), _tmp, tensors, true);
+    CpuAuxTensorHandler max(offset_int_vec(InternalTensorIdx::MAX), _max, tensors, true);
+
+    CpuAuxTensorHandler input_permuted(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), _input_permuted, tensors, true);
+    CpuAuxTensorHandler output_permuted(offset_int_vec(InternalTensorIdx::PERMUTED_DST), _output_permuted, tensors, true);
+
+    ITensorPack max_pack;
+    ITensorPack softmax_pack;
+
+    if(_needs_permute)
+    {
+        ITensorPack permute_in_pack = { { TensorType::ACL_SRC, src }, { TensorType::ACL_DST, input_permuted.get() } };
+        _permute_input.run(permute_in_pack);
+
+        max_pack = { { TensorType::ACL_SRC, input_permuted.get() }, { TensorType::ACL_DST, max.get() } };
+
+        softmax_pack =
+        {
+            { TensorType::ACL_SRC_0, input_permuted.get() },
+            { TensorType::ACL_SRC_1, max.get() },
+            { TensorType::ACL_DST_0, output_permuted.get() },
+            { TensorType::ACL_DST_1, tmp.get() }
+        };
+    }
+    else
+    {
+        max_pack = { { TensorType::ACL_SRC, src }, { TensorType::ACL_DST, max.get() } };
+
+        softmax_pack =
+        {
+            { TensorType::ACL_SRC_0, src },
+            { TensorType::ACL_SRC_1, max.get() },
+            { TensorType::ACL_DST_0, dst },
+            { TensorType::ACL_DST_1, tmp.get() }
+        };
+    }
+
+    NEScheduler::get().schedule_op(_max_kernel.get(), Window::DimY, _max_kernel->window(), max_pack);
+    NEScheduler::get().schedule_op(_softmax_kernel.get(), Window::DimY, _softmax_kernel->window(), softmax_pack);
+
+    if(_needs_permute)
+    {
+        ITensorPack permute_out_pack;
+        permute_out_pack.add_tensor(TensorType::ACL_SRC, output_permuted.get());
+        permute_out_pack.add_tensor(TensorType::ACL_DST, dst);
+        _permute_output.run(permute_out_pack);
+    }
+}
+
+template <bool                   IS_LOG>
+experimental::MemoryRequirements CpuSoftmaxGeneric<IS_LOG>::workspace() const
+{
+    return _aux_mem;
+}
+
+template class CpuSoftmaxGeneric<false>;
+template class CpuSoftmaxGeneric<true>;
+} // namespace cpu
+} // namespace arm_compute