/*******************************************************************************
* Copyright 2020-2023, 2025 Arm Ltd. and affiliates
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*     http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*******************************************************************************/

#include "cpu/aarch64/acl_winograd_convolution.hpp"

namespace dnnl {
namespace impl {
namespace cpu {
namespace aarch64 {
using data_t = prec_traits_t<data_type::f32>::type;

status_t acl_wino_convolution_fwd_t::execute_forward(
        const exec_ctx_t &ctx) const {
    // Lock here is needed because resource_mapper does not support
    // concurrent multithreaded access.
    std::lock_guard<std::mutex> _lock {this->mtx};
    // Retrieve primitive resource and configured Compute Library objects
    auto *acl_resource
            = ctx.get_resource_mapper()->get<acl_wino_resource_t>(this);
    acl_obj_t<arm_compute::NEWinogradConvolutionLayer> &acl_wino_obj
            = acl_resource->get_acl_obj();

    return execute_forward_conv_acl<
            acl_obj_t<arm_compute::NEWinogradConvolutionLayer>, pd_t, data_t>(
            ctx, acl_wino_obj, pd());
}

} // namespace aarch64
} // namespace cpu
} // namespace impl
} // namespace dnnl
