1/*******************************************************************************
2* Copyright 2022 Intel Corporation
3*
4* Licensed under the Apache License, Version 2.0 (the "License");
5* you may not use this file except in compliance with the License.
6* You may obtain a copy of the License at
7*
8* http://www.apache.org/licenses/LICENSE-2.0
9*
10* Unless required by applicable law or agreed to in writing, software
11* distributed under the License is distributed on an "AS IS" BASIS,
12* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13* See the License for the specific language governing permissions and
14* limitations under the License.
15*******************************************************************************/
16
17#ifndef CPU_X64_JIT_BRGEMM_DECONV_HPP
18#define CPU_X64_JIT_BRGEMM_DECONV_HPP
19
20#include "common/c_types_map.hpp"
21#include "common/dnnl_thread.hpp"
22#include "common/memory_tracking.hpp"
23#include "common/primitive.hpp"
24#include "common/utils.hpp"
25
26#include "cpu/cpu_deconvolution_pd.hpp"
27
28#include "cpu/x64/jit_brgemm_1x1_conv.hpp"
29#include "cpu/x64/jit_brgemm_conv.hpp"
30#include "cpu/x64/jit_brgemm_conv_bwd_strided.hpp"
31
32namespace dnnl {
33namespace impl {
34namespace cpu {
35namespace x64 {
36
37template <cpu_isa_t isa>
38struct brgemm_deconvolution_fwd_t : public primitive_t {
39
40 struct pd_t : public cpu_deconvolution_fwd_pd_t {
41 pd_t(const deconvolution_desc_t *adesc, const primitive_attr_t *attr,
42 const typename pd_t::hint_class *hint_fwd_pd)
43 : cpu_deconvolution_fwd_pd_t(adesc, attr, hint_fwd_pd) {}
44
45 ~pd_t() = default;
46
47 DECLARE_COMMON_PD_T(conv_pd_->name(), brgemm_deconvolution_fwd_t);
48
49 status_t init(engine_t *engine);
50
51 bool output_scales_mask_ok() const {
52 using namespace data_type;
53 const auto &mask = attr()->output_scales_.mask_;
54 return IMPLICATION(!utils::one_of(src_md()->data_type, s8, u8),
55 attr()->output_scales_.has_default_values())
56 && (mask == 0 || mask == 1 << 1);
57 }
58
59 bool post_ops_ok() const {
60 return attr()->post_ops_.find(primitive_kind::convolution) == -1;
61 }
62
63 bool zero_points_ok() const {
64 using namespace data_type;
65 int mask_src = 0, mask_dst = 0;
66 attr()->zero_points_.get(DNNL_ARG_SRC, &mask_src);
67 attr()->zero_points_.get(DNNL_ARG_DST, &mask_dst);
68
69 return IMPLICATION(!utils::one_of(src_md()->data_type, s8, u8),
70 attr()->zero_points_.has_default_values())
71 && attr()->zero_points_.has_default_values(DNNL_ARG_WEIGHTS)
72 && (mask_src == 0 || mask_src == 1 << 1)
73 && (mask_dst == 0 || mask_dst == 1 << 1);
74 }
75
76 std::shared_ptr<primitive_desc_t> conv_pd_;
77 bool has_strides_ = false;
78 };
79
80 brgemm_deconvolution_fwd_t(const pd_t *apd) : primitive_t(apd) {};
81
82 ~brgemm_deconvolution_fwd_t() = default;
83
84 status_t init(engine_t *engine) override;
85
86 status_t execute(const exec_ctx_t &ctx) const override;
87
88private:
89 const pd_t *pd() const {
90 return static_cast<const pd_t *>(primitive_t::pd().get());
91 }
92
93 std::shared_ptr<primitive_t> conv_p_;
94};
95
96} // namespace x64
97} // namespace cpu
98} // namespace impl
99} // namespace dnnl
100
101#endif
102
103// vim: et ts=4 sw=4 cindent cino+=l0,\:4,N-s
104