Remove denoise module and thirdparty OIDN.

This is replaced by a much lighter weight and faster JNLM denoiser. OIDN is still much more accurate, and may be provided as an optional backend in the future, but the JNLM denoiser seems good enough for most use cases and removing OIDN reduces the build system complexity, binary size, and build times very significantly.

1 files changed, 0 insertions, 199 deletions

diff --git a/thirdparty/oidn/mkl-dnn/src/cpu/ref_deconvolution.cpp b/thirdparty/oidn/mkl-dnn/src/cpu/ref_deconvolution.cpp
deleted file mode 100644
index 541a303aab..0000000000
--- a/thirdparty/oidn/mkl-dnn/src/cpu/ref_deconvolution.cpp
+++ /dev/null
@@ -1,199 +0,0 @@
-/*******************************************************************************
-* Copyright 2018 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 "c_types_map.hpp"
-#include "type_helpers.hpp"
-#include "mkldnn_thread.hpp"
-#include "mkldnn_traits.hpp"
-#include "math_utils.hpp"
-
-#include "ref_deconvolution.hpp"
-
-namespace mkldnn {
-namespace impl {
-namespace cpu {
-
-void ref_deconvolution_fwd_t::compute_fwd_bias(const data_t *bias,
-        data_t *dst) const {
-    const memory_desc_wrapper dst_d(pd()->dst_md());
-
-    const int G = pd()->G();
-    const int MB = pd()->MB();
-    const int OH = pd()->OH();
-    const int OW = pd()->OW();
-    const int OD = pd()->OD();
-    const int OC = pd()->OC() / G;
-    const int ndims = pd()->desc()->src_desc.ndims;
-
-    parallel_nd(MB, G, OC, OD, OH, OW,
-        [&](int mb, int g, int oc, int od, int oh, int ow) {
-            auto b = bias[g * OC + oc];
-            switch (ndims) {
-            case 5: dst[dst_d.off(mb, g * OC + oc, od, oh, ow)] += b; break;
-            case 4: dst[dst_d.off(mb, g * OC + oc, oh, ow)] += b; break;
-            case 3: dst[dst_d.off(mb, g * OC + oc, ow)] += b; break;
-            default: assert(!"invalid dimension size");
-            }
-    });
-}
-
-void ref_deconvolution_fwd_t::compute_fwd_bias_ncdhw(const data_t *bias,
-        data_t *dst) const {
-    const memory_desc_wrapper dst_d(pd()->dst_md());
-
-    const int MB = pd()->MB();
-    const int OC = pd()->OC();
-    const int SP = pd()->OW()*pd()->OH()*pd()->OD();
-
-    parallel_nd(MB, OC, [&](int mb, int oc) {
-        PRAGMA_OMP_SIMD()
-        for (int sp = 0; sp < SP; ++sp) {
-            auto offset = (size_t)(mb * OC + oc) * SP + sp;
-            dst[offset] += bias[oc];
-        }
-    });
-}
-
-template <int blksize>
-void ref_deconvolution_fwd_t::compute_fwd_bias_nCdhwXc(const data_t *bias,
-        data_t *dst) const {
-    const memory_desc_wrapper dst_d(pd()->dst_md());
-
-    const int MB = pd()->MB();
-    const int OC = pd()->OC();
-    const int SP = pd()->OW() * pd()->OH() * pd()->OD();
-
-    const ptrdiff_t stride_mb = dst_d.blocking_desc().strides[0];
-
-    parallel_nd(MB, utils::div_up(OC, blksize), SP,
-        [&](int mb, int oc_blk, int sp) {
-        int oc = oc_blk * blksize;
-        auto offset = mb * stride_mb + oc * SP + sp * blksize;
-        const int blk = nstl::min(blksize, OC - oc);
-
-        PRAGMA_OMP_SIMD()
-        for (int i = 0; i < blk; ++i)
-            dst[offset + i] += bias[oc + i];
-    });
-}
-
-void ref_deconvolution_bwd_weights_t::compute_bwd_bias(const data_t *diff_dst,
-        data_t *diff_bias) const {
-    const memory_desc_wrapper diff_dst_d(pd()->diff_dst_md());
-
-    const int G = pd()->G();
-    const int MB = pd()->MB();
-    const int OH = pd()->OH();
-    const int OW = pd()->OW();
-    const int OC = pd()->OC() / G;
-    const int OD = pd()->OD();
-    const int ndims = pd()->desc()->src_desc.ndims;
-
-    parallel_nd(G, OC, [&](int g, int oc) {
-        data_t db = 0;
-        for (int mb = 0; mb < MB; ++mb) {
-            for (int od = 0; od < OD; ++od) {
-                for (int oh = 0; oh < OH; ++oh) {
-                    for (int ow = 0; ow < OW; ++ow) {
-                        switch (ndims) {
-                        case 5:
-                            db += diff_dst[diff_dst_d.off(
-                                    mb, g * OC + oc, od, oh, ow)];
-                            break;
-                        case 4:
-                            db += diff_dst[diff_dst_d.off(
-                                    mb, g * OC + oc, oh, ow)];
-                            break;
-                        case 3:
-                            db += diff_dst[diff_dst_d.off(mb, g * OC + oc, ow)];
-                            break;
-                        default: assert(!"invalid dimension size");
-                        }
-                    }
-                }
-            }
-        }
-        diff_bias[g * OC + oc] = db;
-    });
-}
-
-void ref_deconvolution_bwd_weights_t::compute_bwd_bias_ncdhw(
-        const data_t *diff_dst, data_t *diff_bias) const {
-    const memory_desc_wrapper diff_dst_d(pd()->diff_dst_md());
-
-    const int OC = pd()->OC();
-    const int MB = pd()->MB();
-    const int SP = pd()->OH()*pd()->OW()*pd()->OD();
-
-    parallel_nd(OC, [&](int oc) {
-        data_t db = 0;
-        for (int mb = 0; mb < MB; ++mb) {
-            PRAGMA_OMP_SIMD()
-            for (int sp = 0; sp < SP; ++sp) {
-                auto offset = (size_t)(mb * OC + oc) * SP + sp;
-                db += diff_dst[offset];
-            }
-        }
-        diff_bias[oc] = db;
-    });
-}
-
-template <int blksize>
-void ref_deconvolution_bwd_weights_t::compute_bwd_bias_nCdhwXc(
-        const data_t *diff_dst, data_t *diff_bias) const {
-    const memory_desc_wrapper diff_dst_d(pd()->diff_dst_md());
-
-    const int OC = pd()->OC();
-    const int MB = pd()->MB();
-    const int SP = pd()->OH() * pd()->OW() * pd()->OD();
-
-    const ptrdiff_t stride_mb = diff_dst_d.blocking_desc().strides[0];
-
-    parallel_nd(utils::div_up(OC, blksize), [&](int ocb) {
-        data_t db[blksize] = {0};
-
-        for (int mb = 0; mb < MB; ++mb) {
-            for (int sp = 0; sp < SP; ++sp) {
-                auto offset = mb * stride_mb + (ocb * SP + sp) * blksize;
-
-                PRAGMA_OMP_SIMD()
-                for (int i = 0; i < blksize; ++i)
-                    db[i] += diff_dst[offset+i];
-            }
-        }
-
-        const int blk = nstl::min(blksize, OC - ocb * blksize);
-
-        PRAGMA_OMP_SIMD()
-        for (int i = 0; i < blk; ++i)
-            diff_bias[ocb * blksize + i] = db[i];
-    });
-}
-
-template void ref_deconvolution_fwd_t::compute_fwd_bias_nCdhwXc<8>(
-        const data_t *diff_dst, data_t *diff_bias) const;
-template void ref_deconvolution_fwd_t::compute_fwd_bias_nCdhwXc<16>(
-        const data_t *diff_dst, data_t *diff_bias) const;
-template void ref_deconvolution_bwd_weights_t::compute_bwd_bias_nCdhwXc<8>(
-        const data_t *diff_dst, data_t *diff_bias) const;
-template void ref_deconvolution_bwd_weights_t::compute_bwd_bias_nCdhwXc<16>(
-        const data_t *diff_dst, data_t *diff_bias) const;
-
-}
-}
-}
-
-// vim: et ts=4 sw=4 cindent cino^=l0,\:0,N-s