onednn-src 0.1.13

Source of oneAPI Deep Neural Network Library (oneDNN)
Documentation
/*******************************************************************************
* Copyright 2017 Intel Corporation
*
* 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.
*******************************************************************************/

#ifndef CPU_X64_JIT_UNI_BATCH_NORMALIZATION_HPP
#define CPU_X64_JIT_UNI_BATCH_NORMALIZATION_HPP

#include <assert.h>

#include "common/c_types_map.hpp"
#include "common/primitive.hpp"
#include "common/type_helpers.hpp"
#include "common/utils.hpp"

#include "cpu/cpu_batch_normalization_pd.hpp"
#include "cpu/x64/cpu_isa_traits.hpp"
#include "cpu/x64/jit_avx512_core_bf16cvt.hpp"

namespace dnnl {
namespace impl {
namespace cpu {
namespace x64 {

namespace bnorm_impl {
template <cpu_isa_t isa>
struct driver_t;
}

template <cpu_isa_t isa>
struct jit_uni_batch_normalization_fwd_t : public primitive_t {
    struct pd_t : public cpu_batch_normalization_fwd_pd_t {
        using cpu_batch_normalization_fwd_pd_t::
                cpu_batch_normalization_fwd_pd_t;

        DECLARE_COMMON_PD_T(
                JIT_IMPL_NAME_HELPER("bnorm_jit:",
                        (src_md()->data_type == data_type::bf16)
                                ? (mayiuse(avx512_core_bf16) ? avx512_core_bf16
                                                  : mayiuse(avx512_core)
                                                  ? bf16_emulation_t::get_isa()
                                                  : avx2_vnni_2)
                                : (src_md()->data_type == data_type::f16)
                                ? (mayiuse(avx512_core_fp16) ? avx512_core_fp16
                                                             : avx2_vnni_2)
                                : isa,
                        ""),
                jit_uni_batch_normalization_fwd_t);

        status_t init(engine_t *engine);
        int nthr_; // To not exceed the limit in execute used for set up.
    };

    jit_uni_batch_normalization_fwd_t(const pd_t *apd);

    ~jit_uni_batch_normalization_fwd_t() override;

    status_t init(engine_t *engine) override;

    status_t execute(const exec_ctx_t &ctx) const override;

private:
    const pd_t *pd() const { return (const pd_t *)primitive_t::pd().get(); }

    bnorm_impl::driver_t<isa> *bnorm_driver_;
};

template <cpu_isa_t isa>
struct jit_uni_batch_normalization_bwd_t : public primitive_t {
    struct pd_t : public cpu_batch_normalization_bwd_pd_t {
        using cpu_batch_normalization_bwd_pd_t::
                cpu_batch_normalization_bwd_pd_t;

        DECLARE_COMMON_PD_T(
                JIT_IMPL_NAME_HELPER("bnorm_jit:",
                        (src_md()->data_type == data_type::bf16)
                                ? (mayiuse(avx512_core_bf16)
                                                  ? avx512_core_bf16
                                                  : bf16_emulation_t::get_isa())
                                : (src_md()->data_type == data_type::f16)
                                ? avx512_core_fp16
                                : isa,
                        ""),
                jit_uni_batch_normalization_bwd_t);

        status_t init(engine_t *engine);
        int nthr_; // To not exceed the limit in execute used for set up.
    };

    jit_uni_batch_normalization_bwd_t(const pd_t *apd);

    ~jit_uni_batch_normalization_bwd_t() override;

    status_t init(engine_t *engine) override;

    status_t execute(const exec_ctx_t &ctx) const override;

private:
    const pd_t *pd() const { return (const pd_t *)primitive_t::pd().get(); }

    bnorm_impl::driver_t<isa> *bnorm_driver_;
};

} // namespace x64
} // namespace cpu
} // namespace impl
} // namespace dnnl

#endif

// vim: et ts=4 sw=4 cindent cino+=l0,\:4,N-s