onednn-src 0.1.13

Source of oneAPI Deep Neural Network Library (oneDNN)
Documentation 
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/*******************************************************************************
* Copyright 2020 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.
*******************************************************************************/

#include <assert.h>
#include "dnnl.h"

#include "common/c_types_map.hpp"
#include "opdesc.hpp"
#include "primitive_desc_iface.hpp"
#include "type_helpers.hpp"
#include "utils.hpp"

#include "common/broadcast_strategy.hpp"

using namespace dnnl::impl;
using namespace dnnl::impl::utils;
using namespace dnnl::impl::status;
using namespace dnnl::impl::prop_kind;
using namespace dnnl::impl::types;

#define VCHECK_PRELU(cond, msg, ...) \
    VCONDCHECK(primitive, create, check, prelu, (cond), \
            status::invalid_arguments, msg, ##__VA_ARGS__)

#define VCHECK_PRELU_UNIMPL(cond, msg, ...) \
    VCONDCHECK(primitive, create, check, prelu, (cond), status::unimplemented, \
            msg, ##__VA_ARGS__)

namespace {
status_t prelu_desc_init(prelu_desc_t *prelu_desc, prop_kind_t prop_kind,
        const memory_desc_t *src_desc, const memory_desc_t *weights_desc,
        const memory_desc_t *dst_desc, const memory_desc_t *diff_src_desc,
        const memory_desc_t *diff_weights_desc,
        const memory_desc_t *diff_dst_desc) {
    const bool is_fwd = one_of(prop_kind, forward_training, forward_inference);
    VCHECK_PRELU(
            !any_null(prelu_desc, src_desc, weights_desc), VERBOSE_NULL_ARG);
    VCHECK_PRELU(
            one_of(prop_kind, forward_training, forward_inference, backward),
            VERBOSE_BAD_PROPKIND);
    VCHECK_PRELU(IMPLICATION(is_fwd, dst_desc != nullptr), VERBOSE_NULL_ARG);
    VCHECK_PRELU(
            IMPLICATION(!is_fwd,
                    !any_null(diff_src_desc, diff_weights_desc, diff_dst_desc)),
            VERBOSE_NULL_ARG);
    VCHECK_PRELU(
            IMPLICATION(is_fwd, !memory_desc_wrapper(src_desc).format_any()),
            VERBOSE_UNSUPPORTED_TAG_S, "src");
    VCHECK_PRELU(!any_memory_desc_host_scalar(src_desc, weights_desc, dst_desc,
                         diff_src_desc, diff_weights_desc, diff_dst_desc),
            VERBOSE_UNSUPPORTED_FORMAT_KIND);

    bool runtime_dims_or_strides
            = memory_desc_wrapper(src_desc).has_runtime_dims_or_strides()
            || memory_desc_wrapper(weights_desc).has_runtime_dims_or_strides();
    if (!is_fwd)
        runtime_dims_or_strides = runtime_dims_or_strides
                || (memory_desc_wrapper(diff_src_desc)
                                .has_runtime_dims_or_strides()
                        || memory_desc_wrapper(diff_weights_desc)
                                   .has_runtime_dims_or_strides());
    VCHECK_PRELU_UNIMPL(
            !runtime_dims_or_strides, VERBOSE_RUNTIMEDIM_UNSUPPORTED);

    auto pd = prelu_desc_t();
    pd.primitive_kind = primitive_kind::prelu;
    pd.prop_kind = prop_kind;
    pd.src_desc = *src_desc;
    pd.weights_desc = *weights_desc;
    if (is_fwd) {
        pd.dst_desc = *dst_desc;
    } else {
        pd.diff_src_desc = *diff_src_desc;
        pd.diff_weights_desc = *diff_weights_desc;
        pd.diff_dst_desc = *diff_dst_desc;
    }

    const memory_desc_wrapper src_mdw(*src_desc);
    VCHECK_PRELU(get_rhs_arg_broadcasting_strategy(pd.weights_desc, src_mdw)
                    != broadcasting_strategy_t::unsupported,
            VERBOSE_INCONSISTENT_MDS, "src", "wei");

    static constexpr int max_supported_ndims = 5;
    bool consistency = src_desc->ndims <= max_supported_ndims
            && src_desc->ndims == weights_desc->ndims;
    if (consistency && is_fwd) {
        consistency = pd.dst_desc.ndims == pd.src_desc.ndims
                && array_cmp(
                        pd.dst_desc.dims, pd.src_desc.dims, pd.src_desc.ndims);
    }
    if (consistency && !is_fwd) {
        consistency = pd.diff_dst_desc.ndims == pd.src_desc.ndims
                && pd.diff_dst_desc.ndims == pd.diff_src_desc.ndims
                && array_cmp(pd.diff_dst_desc.dims, pd.src_desc.dims,
                        pd.src_desc.ndims)
                && array_cmp(pd.diff_src_desc.dims, pd.diff_dst_desc.dims,
                        pd.diff_dst_desc.ndims);
    }
    VCHECK_PRELU(consistency, VERBOSE_INCONSISTENT_MDS, "src", "dst");

    *prelu_desc = pd;
    return success;
}

status_t prelu_attr_check(const prelu_desc_t &desc, const engine_t *engine,
        const primitive_attr_t *attr) {

    if (attr == nullptr) return status::success;

    // Check attributes
    VCHECK_PRELU_UNIMPL(attr->has_default_values(), VERBOSE_UNSUPPORTED_ATTR);

    return status::success;
}

} // namespace

status_t dnnl_prelu_forward_primitive_desc_create(
        primitive_desc_iface_t **primitive_desc_iface, engine_t *engine,
        prop_kind_t prop_kind, const memory_desc_t *src_desc,
        const memory_desc_t *weights_desc, const memory_desc_t *dst_desc,
        const primitive_attr_t *attr) {

    if (!one_of(prop_kind, forward_training, forward_inference))
        return invalid_arguments;

    auto prelu_desc = prelu_desc_t();
    CHECK(prelu_desc_init(&prelu_desc, prop_kind, src_desc, weights_desc,
            dst_desc, nullptr, nullptr, nullptr));
    CHECK(prelu_attr_check(prelu_desc, engine, attr));
    return primitive_desc_create(primitive_desc_iface, engine,
            (const op_desc_t *)&prelu_desc, nullptr, attr);
}

status_t dnnl_prelu_backward_primitive_desc_create(
        primitive_desc_iface_t **primitive_desc_iface, engine_t *engine,
        const memory_desc_t *src_desc, const memory_desc_t *weights_desc,
        const memory_desc_t *diff_src_desc,
        const memory_desc_t *diff_weights_desc,
        const memory_desc_t *diff_dst_desc,
        const primitive_desc_iface_t *hint_fwd_pd,
        const primitive_attr_t *attr) {

    auto prelu_desc = prelu_desc_t();
    CHECK(prelu_desc_init(&prelu_desc, backward, src_desc, weights_desc,
            nullptr, diff_src_desc, diff_weights_desc, diff_dst_desc));
    CHECK(prelu_attr_check(prelu_desc, engine, attr));
    return primitive_desc_create(primitive_desc_iface, engine,
            (const op_desc_t *)&prelu_desc, hint_fwd_pd, attr);
}

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