gpu: generic: deconvolution: move implementation from ocl folder

src/gpu/generic/convolution_deconvolution.hpp

@@ -0,0 +1,376 @@
+/*******************************************************************************
+* Copyright 2024 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 GPU_GENERIC_CONVOLUTION_DECONVOLUTION_HPP
+#define GPU_GENERIC_CONVOLUTION_DECONVOLUTION_HPP
+
+#include "common/c_types_map.hpp"
+#include "common/primitive.hpp"
+#include "common/primitive_desc_iterator.hpp"
+#include "common/type_helpers.hpp"
+#include "common/utils.hpp"
+#include "gpu/gpu_deconvolution_pd.hpp"
+#include "gpu/gpu_primitive.hpp"
+
+namespace dnnl {
+namespace impl {
+namespace gpu {
+namespace generic {
+
+static status_t weights_axes_permutation(
+ memory_desc_t *o_md, const memory_desc_t *i_md, bool with_groups) {
+ int perm[DNNL_MAX_NDIMS] {}; // deconv to conv weight permutation
+ for (int d = 0; d < DNNL_MAX_NDIMS; ++d)
+ perm[d] = d;
+ nstl::swap(perm[0 + with_groups], perm[1 + with_groups]);
+
+ return memory_desc_permute_axes(*o_md, *i_md, perm);
+}
+
+static status_t conv_descr_create(
+ const deconvolution_desc_t *dd, convolution_desc_t *cd) {
+ using namespace prop_kind;
+ alg_kind_t alg_kind = alg_kind::convolution_direct;
+
+ const memory_desc_t *src_md, *dst_md, *d_weights_d;
+ prop_kind_t prop_kind;
+
+ switch (dd->prop_kind) {
+ case forward:
+ case forward_inference:
+ prop_kind = backward_data;
+ src_md = &dd->dst_desc;
+ dst_md = &dd->src_desc;
+ d_weights_d = &dd->weights_desc;
+ break;
+ case backward_data:
+ prop_kind = forward_training;
+ src_md = &dd->diff_dst_desc;
+ dst_md = &dd->diff_src_desc;
+ d_weights_d = &dd->weights_desc;
+ break;
+ case backward_weights:
+ prop_kind = dd->prop_kind;
+ src_md = &dd->diff_dst_desc;
+ dst_md = &dd->src_desc;
+ d_weights_d = &dd->diff_weights_desc;
+ break;
+ default: assert(!"unknown prop kind"); return status::invalid_arguments;
+ }
+
+ // Create weights desc for convolution
+ memory_desc_t c_weights_d;
+ const bool with_groups = d_weights_d->ndims == src_md->ndims + 1;
+ CHECK(weights_axes_permutation(&c_weights_d, d_weights_d, with_groups));
+
+ return conv_desc_init(cd, prop_kind, alg_kind, src_md, &c_weights_d,
+ prop_kind != backward_weights ? &dd->bias_desc : nullptr, dst_md,
+ dd->strides, dd->dilates, dd->padding[0], dd->padding[1]);
+}
+
+struct convolution_deconvolution_fwd_t : public gpu::primitive_t {
+ using gpu::primitive_t::primitive_t;
+ struct pd_t : public gpu_deconvolution_fwd_pd_t {
+ pd_t(const deconvolution_desc_t *adesc, const primitive_attr_t *attr,
+ const deconvolution_fwd_pd_t *hint_fwd_pd)
+ : gpu_deconvolution_fwd_pd_t(adesc, attr, hint_fwd_pd) {}
+
+ pd_t(const pd_t &other) = default;
+
+ ~pd_t() = default;
+
+ DECLARE_COMMON_PD_T(name_.c_str(), convolution_deconvolution_fwd_t);
+ status_t init_convolution(impl::engine_t *engine) {
+ convolution_desc_t cd;
+ CHECK(conv_descr_create(desc(), &cd));
+ primitive_attr_t conv_attr(*attr());
+ if (!conv_attr.is_initialized()) return status::out_of_memory;
+ primitive_desc_iterator_t it(
+ engine, (op_desc_t *)&cd, &conv_attr, nullptr);
+ if (!it.is_initialized()) return status::out_of_memory;
+ conv_pd_ = *(++it);
+
+ return (conv_pd_) ? status::success : status::unimplemented;
+ }
+
+ status_t init(impl::engine_t *engine) {
+ using namespace format_tag;
+ using sm = primitive_attr_t::skip_mask_t;
+
+ const auto attr_skip_mask = sm::post_ops | sm::zero_points_runtime
+ | sm::scales_runtime;
+
+ VDISPATCH_DECONVOLUTION(is_fwd(), VERBOSE_BAD_PROPKIND);
+ VDISPATCH_DECONVOLUTION(
+ desc()->alg_kind == alg_kind::deconvolution_direct,
+ VERBOSE_BAD_ALGORITHM);
+ VDISPATCH_DECONVOLUTION(attr()->has_default_values(attr_skip_mask),
+ VERBOSE_UNSUPPORTED_ATTR);
+ VDISPATCH_DECONVOLUTION(
+ (utils::everyone_is(data_type::f32,
+ desc()->src_desc.data_type,
+ desc()->weights_desc.data_type,
+ desc()->dst_desc.data_type)
+ || (utils::everyone_is(data_type::f64,
+ desc()->src_desc.data_type,
+ desc()->weights_desc.data_type,
+ desc()->dst_desc.data_type))
+ || ((utils::everyone_is(data_type::f16,
+ desc()->src_desc.data_type,
+ desc()->weights_desc.data_type)
+ || utils::everyone_is(data_type::f32,
+ desc()->src_desc.data_type,
+ desc()->weights_desc.data_type)
+ || utils::everyone_is(data_type::bf16,
+ desc()->src_desc.data_type,
+ desc()->weights_desc.data_type))
+ && utils::one_of(desc()->dst_desc.data_type,
+ data_type::f16, data_type::u8,
+ data_type::s8))
+ || (utils::everyone_is(data_type::bf16,
+ desc()->src_desc.data_type,
+ desc()->weights_desc.data_type)
+ && utils::one_of(desc()->dst_desc.data_type,
+ data_type::f32, data_type::bf16))
+ || (utils::everyone_is(data_type::f16,
+ desc()->src_desc.data_type,
+ desc()->weights_desc.data_type)
+ && utils::one_of(desc()->dst_desc.data_type,
+ data_type::f32, data_type::f16))
+ || (desc()->weights_desc.data_type == data_type::s8
+ && utils::one_of(desc()->src_desc.data_type,
+ data_type::u8, data_type::s8)
+ && desc()->dst_desc.data_type
+ != data_type::f64)),
+ VERBOSE_UNSUPPORTED_DT);
+
+ VDISPATCH_DECONVOLUTION_SC(
+ init_convolution(engine), "init_convolution()");
+ if (weights_md_.format_kind == format_kind::any) {
+ VDISPATCH_DECONVOLUTION_SC(
+ weights_axes_permutation(&weights_md_,
+ conv_pd_->weights_md(), with_groups()),
+ "weights_axes_permutation()");
+ }
+ if (src_md_.format_kind == format_kind::any)
+ src_md_ = *conv_pd_->diff_dst_md();
+ if (dst_md_.format_kind == format_kind::any)
+ dst_md_ = *conv_pd_->diff_src_md();
+ if (bias_md_.format_kind == format_kind::any) {
+ VDISPATCH_DECONVOLUTION_SC(memory_desc_init_by_tag(bias_md_, x),
+ VERBOSE_UNSUPPORTED_TAG);
+ }
+ init_name();
+ init_scratchpad();
+ VDISPATCH_DECONVOLUTION_SC(attr_.set_default_formats(dst_md(0)),
+ VERBOSE_UNSUPPORTED_ATTR);
+
+ return status::success;
+ }
+
+ std::shared_ptr<primitive_desc_t> conv_pd_;
+
+ private:
+ std::string name_ = "conv:any";
+
+ void init_name() {
+ name_.append("+");
+ name_.append(conv_pd_->name());
+ }
+
+ void init_scratchpad() {
+ auto scratchpad = scratchpad_registry().registrar();
+ scratchpad.book(memory_tracking::names::key_nested,
+ conv_pd_->scratchpad_registry());
+ }
+ };
+
+ status_t init(impl::engine_t *engine) override {
+ return create_nested_primitive(conv_p_, pd()->conv_pd_, engine);
+ }
+
+ status_t execute(const exec_ctx_t &ctx) const override {
+ using namespace memory_tracking::names;
+ const auto &args = ctx.args();
+ exec_args_t conv_args;
+ conv_args[DNNL_ARG_DIFF_DST] = args.at(DNNL_ARG_SRC);
+ conv_args[DNNL_ARG_WEIGHTS] = args.at(DNNL_ARG_WEIGHTS);
+ conv_args[DNNL_ARG_DIFF_SRC] = args.at(DNNL_ARG_DST);
+ if (pd()->with_bias())
+ conv_args[DNNL_ARG_BIAS] = args.at(DNNL_ARG_BIAS);
+
+ for (int idx = 0; idx < pd()->attr()->post_ops_.len(); ++idx) {
+ if (pd()->attr()->post_ops_.entry_[idx].is_binary()) {
+ conv_args[DNNL_ARG_ATTR_MULTIPLE_POST_OP(idx) | DNNL_ARG_SRC_1]
+ = args.at(DNNL_ARG_ATTR_MULTIPLE_POST_OP(idx)
+ | DNNL_ARG_SRC_1);
+ } else if (pd()->attr()->post_ops_.entry_[idx].is_prelu()) {
+ conv_args[DNNL_ARG_ATTR_MULTIPLE_POST_OP(idx)
+ | DNNL_ARG_WEIGHTS]
+ = args.at(DNNL_ARG_ATTR_MULTIPLE_POST_OP(idx)
+ | DNNL_ARG_WEIGHTS);
+ }
+ }
+ const auto z_src = DNNL_ARG_ATTR_ZERO_POINTS | DNNL_ARG_SRC;
+ const auto z_dst = DNNL_ARG_ATTR_ZERO_POINTS | DNNL_ARG_DST;
+ if (args.find(z_src) != args.end()) conv_args[z_src] = args.at(z_src);
+ if (args.find(z_dst) != args.end()) conv_args[z_dst] = args.at(z_dst);
+
+ for (int arg : {DNNL_ARG_SRC, DNNL_ARG_WEIGHTS, DNNL_ARG_DST}) {
+ int key = DNNL_ARG_ATTR_SCALES | arg;
+ if (args.find(key) != args.end()) conv_args[key] = args.at(key);
+ }
+
+ exec_ctx_t conv_ctx(ctx, std::move(conv_args));
+
+ nested_scratchpad_t ns(ctx, key_nested, conv_p_);
+ conv_ctx.set_scratchpad_grantor(ns.grantor());
+ // Executing the convolution kernel
+ return conv_p_->execute(conv_ctx);
+ }
+
+private:
+ const pd_t *pd() const { return (const pd_t *)primitive_t::pd().get(); }
+ std::shared_ptr<impl::primitive_t> conv_p_;
+};
+
+struct convolution_deconvolution_bwd_data_t : public gpu::primitive_t {
+ using gpu::primitive_t::primitive_t;
+ struct pd_t : public gpu_deconvolution_bwd_data_pd_t {
+ pd_t(const deconvolution_desc_t *adesc, const primitive_attr_t *attr,
+ const deconvolution_fwd_pd_t *hint_fwd_pd)
+ : gpu_deconvolution_bwd_data_pd_t(adesc, attr, hint_fwd_pd)
+ , conv_pd_(nullptr) {}
+
+ pd_t(const pd_t &other) = default;
+
+ ~pd_t() = default;
+
+ DECLARE_COMMON_PD_T(
+ name_.c_str(), convolution_deconvolution_bwd_data_t);
+
+ status_t init_convolution(impl::engine_t *engine) {
+ convolution_desc_t cd;
+ CHECK(conv_descr_create(desc(), &cd));
+ primitive_attr_t conv_attr(*attr());
+ if (!conv_attr.is_initialized()) return status::out_of_memory;
+ primitive_desc_iterator_t it(
+ engine, (op_desc_t *)&cd, &conv_attr, nullptr);
+ if (!it.is_initialized()) return status::out_of_memory;
+ conv_pd_ = *(++it);
+ return (conv_pd_) ? status::success : status::unimplemented;
+ }
+
+ status_t init(impl::engine_t *engine) {
+ VDISPATCH_DECONVOLUTION(
+ desc()->prop_kind == prop_kind::backward_data,
+ VERBOSE_BAD_PROPKIND);
+
+ VDISPATCH_DECONVOLUTION(
+ (utils::everyone_is(data_type::f32,
+ desc()->diff_src_desc.data_type,
+ desc()->weights_desc.data_type,
+ desc()->diff_dst_desc.data_type)
+ || (utils::everyone_is(data_type::f64,
+ desc()->diff_src_desc.data_type,
+ desc()->weights_desc.data_type,
+ desc()->diff_dst_desc.data_type))
+ || utils::everyone_is(data_type::f16,
+ desc()->weights_desc.data_type,
+ desc()->diff_dst_desc.data_type)
+ || utils::everyone_is(data_type::bf16,
+ desc()->weights_desc.data_type,
+ desc()->diff_dst_desc.data_type)),
+ VERBOSE_UNSUPPORTED_DT);
+
+ VDISPATCH_DECONVOLUTION(
+ utils::one_of(desc()->diff_src_desc.data_type,
+ data_type::bf16, data_type::f16, data_type::f32,
+ data_type::f64),
+ VERBOSE_UNSUPPORTED_DT);
+ VDISPATCH_DECONVOLUTION(
+ desc()->alg_kind == alg_kind::deconvolution_direct,
+ VERBOSE_BAD_ALGORITHM);
+ VDISPATCH_DECONVOLUTION(
+ attr()->has_default_values(), VERBOSE_UNSUPPORTED_ATTR);
+
+ VDISPATCH_DECONVOLUTION_SC(
+ init_convolution(engine), "init_convolution()");
+ if (weights_md_.format_kind == format_kind::any)
+ VDISPATCH_DECONVOLUTION_SC(
+ weights_axes_permutation(&weights_md_,
+ conv_pd_->weights_md(), with_groups()),
+ "weights_axes_permutation()");
+ if (diff_src_md_.format_kind == format_kind::any)
+ diff_src_md_ = *conv_pd_->dst_md();
+ if (diff_dst_md_.format_kind == format_kind::any)
+ diff_dst_md_ = *conv_pd_->src_md();
+
+ init_name();
+ init_scratchpad();
+
+ return status::success;
+ }
+
+ std::shared_ptr<primitive_desc_t> conv_pd_;
+
+ private:
+ std::string name_ = "conv:any";
+
+ void init_name() {
+ name_.append("+");
+ name_.append(conv_pd_->name());
+ }
+
+ void init_scratchpad() {
+ auto scratchpad = scratchpad_registry().registrar();
+ scratchpad.book(memory_tracking::names::key_nested,
+ conv_pd_->scratchpad_registry());
+ }
+ };
+
+ status_t init(impl::engine_t *engine) override {
+ return create_nested_primitive(conv_p_, pd()->conv_pd_, engine);
+ }
+
+ status_t execute(const exec_ctx_t &ctx) const override {
+ using namespace memory_tracking::names;
+ const auto &args = ctx.args();
+ exec_args_t conv_args;
+ conv_args[DNNL_ARG_SRC] = args.at(DNNL_ARG_DIFF_DST);
+ conv_args[DNNL_ARG_WEIGHTS] = args.at(DNNL_ARG_WEIGHTS);
+ conv_args[DNNL_ARG_DST] = args.at(DNNL_ARG_DIFF_SRC);
+ if (!types::is_zero_md(pd()->scratchpad_md()))
+ conv_args[DNNL_ARG_SCRATCHPAD] = args.at(DNNL_ARG_SCRATCHPAD);
+ exec_ctx_t conv_ctx(ctx, std::move(conv_args));
+
+ nested_scratchpad_t ns(ctx, key_nested, conv_p_);
+ conv_ctx.set_scratchpad_grantor(ns.grantor());
+ // Executing the convolution kernel
+ return conv_p_->execute(conv_ctx);
+ }
+
+private:
+ const pd_t *pd() const { return (const pd_t *)primitive_t::pd().get(); }
+ std::shared_ptr<impl::primitive_t> conv_p_;
+};
+
+} // namespace generic
+} // namespace gpu
+} // namespace impl
+} // namespace dnnl
+
+#endif