refactor(mgb/dnn): rocm pooling rebase algochooser

GitOrigin-RevId: 95be9298415636583c9737362568b59e2d38580d

dnn/src/rocm/miopen_wrapper.cpp

@@ -96,34 +96,6 @@ void ConvDesc::set(const param::Convolution& param, const size_t nr_group,
     //! not supported
 }
 
-PoolingDesc::PoolingDesc() {
-    miopen_check(miopenCreatePoolingDescriptor(&desc));
-}
-
-PoolingDesc::~PoolingDesc() {
-    miopen_check(miopenDestroyPoolingDescriptor(desc));
-}
-
-void PoolingDesc::set(const param::Pooling& param) {
-    miopenPoolingMode_t mode;
-    switch (param.mode) {
-        case param::Pooling::Mode::MAX:
-            mode = miopenPoolingMax;
-            break;
-        case param::Pooling::Mode::AVERAGE_COUNT_EXCLUDE_PADDING:
-            mode = miopenPoolingAverage;
-            break;
-        case param::Pooling::Mode::AVERAGE:
-            mode = miopenPoolingAverageInclusive;
-            break;
-        default:
-            megdnn_throw("Unsupported pooling mode for miopen");
-    }
-    miopen_check(miopenSet2dPoolingDescriptor(
-            desc, mode, param.window_h, param.window_w, param.pad_h,
-            param.pad_w, param.stride_h, param.stride_w));
-}
-
 LRNDesc::LRNDesc() {
     miopen_check(miopenCreateLRNDescriptor(&desc));
 }

dnn/src/rocm/miopen_wrapper.h

@@ -38,14 +38,6 @@ public:
     miopenConvolutionDescriptor_t desc;
 };
 
-class PoolingDesc {
-public:
-    PoolingDesc();
-    void set(const param::Pooling& param);
-    ~PoolingDesc();
-    miopenPoolingDescriptor_t desc;
-};
-
 class LRNDesc {
 public:
     LRNDesc();

dnn/src/rocm/pooling/algo.cpp

+/**
+ * \file dnn/src/rocm/pooling/algos.cpp
+ * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
+ *
+ * Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or
+ * implied.
+ */
+
+#include "./algo.h"
+#include "hcc_detail/hcc_defs_prologue.h"
+#include "src/rocm/utils.h"
+
+using namespace megdnn;
+using namespace rocm;
+
+PoolingForwardImpl::AlgoPack::AlgoPack() {
+    all_algos.push_back(&algo_miopen);
+
+    for (auto&& algo : all_algos) {
+        m_all_algos_map.emplace(algo->info().desc, algo);
+    }
+}
+
+PoolingForwardImpl::AlgoPack PoolingForwardImpl::sm_algo_pack;
+MEGDNN_DEF_GET_ALGO_FROM_DESC(PoolingForwardImpl)
+
+PoolingForwardImpl::AlgoBase::SizeArgs::SizeArgs(PoolingForwardImpl* o,
+                                                 const TensorLayout& src,
+                                                 const TensorLayout& dst)
+        : handle{concrete_handle(o->handle())},
+          opr{o},
+          layout_src{&src},
+          layout_dst{&dst} {}
+
+PoolingForwardImpl::AlgoBase::ExecArgs::ExecArgs(PoolingForwardImpl* opr,
+                                                 _megdnn_tensor_in src,
+                                                 _megdnn_tensor_out dst,
+                                                 _megdnn_workspace workspace)
+        : SizeArgs(opr, src.layout, dst.layout),
+          src_tensor{&src},
+          dst_tensor{&dst},
+          workspace{workspace} {}
+
+std::string PoolingForwardImpl::AlgoBase::SizeArgs::to_string() const {
+    return ssprintf("src=%s, dst=%s", layout_src->to_string().c_str(),
+                    layout_dst->to_string().c_str());
+}
+
+bool PoolingForwardImpl::AlgoMIOpen::is_available(const SizeArgs& args) const {
+    return true;
+}
+
+void PoolingForwardImpl::AlgoMIOpen::init_mode(
+        const ExecArgs& args, miopenPoolingMode_t& mode) const {
+    switch (args.opr->param().mode) {
+        case param::Pooling::Mode::MAX:
+            mode = miopenPoolingMax;
+            break;
+        case param::Pooling::Mode::AVERAGE:
+            mode = miopenPoolingAverage;
+            break;
+        case param::Pooling::Mode::AVERAGE_COUNT_EXCLUDE_PADDING:
+            mode = miopenPoolingAverageInclusive;
+            break;
+        default:
+            megdnn_throw(ssprintf("Unspport pooling mode : {%d}",
+                                  static_cast<int>(args.opr->param().mode)));
+    }
+}
+
+size_t PoolingForwardImpl::AlgoMIOpen::get_workspace_in_bytes(
+        const SizeArgs& args) const {
+    return 0;
+}
+
+void PoolingForwardImpl::AlgoMIOpen::exec(const ExecArgs& args) const {
+    auto handle = miopen_handle(args.handle);
+    TensorDesc src_desc, dst_desc;
+    args.init_desc(src_desc, dst_desc);
+    miopenPoolingMode_t mode;
+    init_mode(args, mode);
+
+    miopenPoolingDescriptor_t miopen_desc;
+    miopen_check(miopenCreatePoolingDescriptor(&miopen_desc));
+    miopen_check(miopenSet2dPoolingDescriptor(
+            miopen_desc, mode, args.opr->param().window_h,
+            args.opr->param().window_w, args.opr->param().pad_h,
+            args.opr->param().pad_w, args.opr->param().stride_h,
+            args.opr->param().stride_w));
+
+    dt_float32 alpha = 1.0f, beta = 0.0f;
+    miopen_check(miopenPoolingForward(
+            handle, miopen_desc, &alpha, src_desc.desc,
+            args.src_tensor->raw_ptr, &beta, dst_desc.desc,
+            args.src_tensor->raw_ptr, false, nullptr, 0_z));
+    miopen_check(miopenDestroyPoolingDescriptor(miopen_desc));
+}
+
+PoolingBackwardImpl::AlgoPack::AlgoPack() {
+    all_algos.push_back(&algo_miopen);
+
+    for (auto&& algo : all_algos) {
+        m_all_algos_map.emplace(algo->info().desc, algo);
+    }
+}
+
+PoolingBackwardImpl::AlgoPack PoolingBackwardImpl::sm_algo_pack;
+MEGDNN_DEF_GET_ALGO_FROM_DESC(PoolingBackwardImpl)
+
+PoolingBackwardImpl::AlgoBase::SizeArgs::SizeArgs(PoolingBackwardImpl* o,
+                                                  const TensorLayout& src,
+                                                  const TensorLayout& dst,
+                                                  const TensorLayout& diff,
+                                                  const TensorLayout& grad)
+        : handle{concrete_handle(o->handle())},
+          opr{o},
+          layout_src{&src},
+          layout_dst{&dst},
+          layout_diff{&diff},
+          layout_grad{&grad} {}
+
+PoolingBackwardImpl::AlgoBase::ExecArgs::ExecArgs(PoolingBackwardImpl* opr,
+                                                  _megdnn_tensor_in src,
+                                                  _megdnn_tensor_in dst,
+                                                  _megdnn_tensor_in diff,
+                                                  _megdnn_tensor_out grad,
+                                                  _megdnn_workspace workspace)
+        : SizeArgs(opr, src.layout, dst.layout, diff.layout, grad.layout),
+          src_tensor{&src},
+          dst_tensor{&dst},
+          diff_tensor{&diff},
+          grad_tensor{&grad},
+          workspace{workspace} {}
+
+std::string PoolingBackwardImpl::AlgoBase::SizeArgs::to_string() const {
+    return ssprintf(
+            "src=%s, dst=%s, diff=%s, grad=%s", layout_src->to_string().c_str(),
+            layout_dst->to_string().c_str(), layout_diff->to_string().c_str(),
+            layout_grad->to_string().c_str());
+}
+
+bool PoolingBackwardImpl::AlgoMIOpen::is_available(const SizeArgs&) const {
+    return true;
+}
+
+size_t PoolingBackwardImpl::AlgoMIOpen::get_workspace_in_bytes(
+        const SizeArgs& args) const {
+    TensorDesc dst_desc;
+    dst_desc.set(*args.layout_dst);
+
+    size_t ws_size = 0_z;
+    miopenPoolingGetWorkSpaceSize(dst_desc.desc, &ws_size);
+    return ws_size;
+}
+
+void PoolingBackwardImpl::AlgoMIOpen::init_mode(const ExecArgs& args,
+                                               miopenPoolingMode_t& mode) const {
+    switch (args.opr->param().mode) {
+        case param::Pooling::Mode::MAX:
+            mode = miopenPoolingMax;
+            break;
+        case param::Pooling::Mode::AVERAGE:
+            mode = miopenPoolingAverage;
+            break;
+        case param::Pooling::Mode::AVERAGE_COUNT_EXCLUDE_PADDING:
+            mode = miopenPoolingAverageInclusive;
+            break;
+        default:
+            megdnn_throw(ssprintf("Unspport pooling mode : {%d}",
+                                  static_cast<int>(args.opr->param().mode)));
+    }
+}
+
+void PoolingBackwardImpl::AlgoMIOpen::exec(const ExecArgs& args) const {
+    auto handle = miopen_handle(args.handle);
+    TensorDesc src_desc, dst_desc, diff_desc, grad_desc;
+    args.init_desc(src_desc, dst_desc, diff_desc, grad_desc);
+    miopenPoolingMode_t mode;
+    init_mode(args, mode);
+
+    miopenPoolingDescriptor_t miopen_desc;
+    miopen_check(miopenCreatePoolingDescriptor(&miopen_desc));
+    miopen_check(miopenSet2dPoolingDescriptor(
+            miopen_desc, mode, args.opr->param().window_h,
+            args.opr->param().window_w, args.opr->param().pad_h,
+            args.opr->param().pad_w, args.opr->param().stride_h,
+            args.opr->param().stride_w));
+
+    float alpha = 1.0f, beta = 0.0f;
+    if (args.opr->param().mode == param::Pooling::Mode::MAX) {
+        //! FIXME: when using max pooling opr, the backward opr need the indices
+        //! of the forward opr which stored in workspace. We have to recompute
+        //! the indices by calling miopenPoolingForward again.
+        miopen_check(miopenPoolingForward(
+                handle, miopen_desc, &alpha, src_desc.desc,
+                args.src_tensor->raw_ptr, &beta, dst_desc.desc,
+                args.dst_tensor->raw_ptr, true, args.workspace.raw_ptr,
+                args.workspace.size));
+    }
+    miopen_check(miopenPoolingBackward(
+            handle, miopen_desc, &alpha, dst_desc.desc,
+            args.dst_tensor->raw_ptr, diff_desc.desc, args.diff_tensor->raw_ptr,
+            src_desc.desc, args.src_tensor->raw_ptr, &beta, grad_desc.desc,
+            args.grad_tensor->raw_ptr, args.workspace.raw_ptr));
+}
\ No newline at end of file

dnn/src/rocm/pooling/algo.h

+/**
+ * \file dnn/src/rocm/pooling/algo.h
+ * MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
+ *
+ * Copyright (c) 2014-2021 Megvii Inc. All rights reserved.
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or
+ * implied.
+ */
+
+#pragma once
+
+#include <unordered_map>
+#include "src/common/algo_base.h"
+#include "src/common/metahelper.h"
+#include "src/rocm/miopen_wrapper.h"
+#include "src/rocm/pooling/opr_impl.h"
+#include "src/rocm/handle.h"
+
+namespace megdnn {
+namespace rocm {
+
+class PoolingForwardImpl::AlgoBase : public Algorithm {
+public:
+    enum class AlgoType : uint32_t { ROCM_MIOPEN };
+    using Mapper = std::unordered_map<AlgorithmDesc, AlgoBase*>;
+
+    AlgoBase() : Algorithm() { m_handle_type = Handle::HandleType::ROCM; }
+    struct SizeArgs {
+        HandleImpl* handle;
+        PoolingForwardImpl* opr;
+        const TensorLayout *layout_src, *layout_dst;
+
+        std::string to_string() const;
+        void init_desc(TensorDesc& src_desc, TensorDesc& dst_desc) const {
+            src_desc.set(*layout_src, opr->param().format);
+            dst_desc.set(*layout_dst, opr->param().format);
+        }
+
+        SizeArgs(PoolingForwardImpl* opr, const TensorLayout& src,
+                 const TensorLayout& dst);
+    };
+    struct ExecArgs : public SizeArgs {
+        const TensorND *src_tensor, *dst_tensor;
+        Workspace workspace;
+
+        ExecArgs(PoolingForwardImpl* opr, _megdnn_tensor_in src,
+                 _megdnn_tensor_out dst, _megdnn_workspace workspace);
+    };
+
+    virtual bool is_available(const SizeArgs& args) const = 0;
+    virtual size_t get_workspace_in_bytes(const SizeArgs& args) const = 0;
+    virtual void exec(const ExecArgs& args) const = 0;
+
+    bool is_available_attribute(
+            const SizeArgs& args,
+            const AlgoAttribute& positive_attr = AlgoAttribute::REPRODUCIBLE,
+            const AlgoAttribute& negative_attr = AlgoAttribute::DEFAULT) {
+        return contain_attribute_all(positive_attr) &&
+               !contain_attribute_any(negative_attr) && is_available(args);
+    }
+
+protected:
+    ~AlgoBase() = default;
+};
+
+class PoolingForwardImpl::AlgoMIOpen final : public AlgoBase {
+    std::string m_algo_name;
+    AlgoAttribute m_algo_attribute;
+
+public:
+    AlgoMIOpen(AlgoAttribute attr)
+            : m_algo_name("MIOpenPoolingForward"), m_algo_attribute(attr) {}
+
+    bool is_available(const SizeArgs& args) const override;
+    size_t get_workspace_in_bytes(const SizeArgs& args) const override;
+    void init_mode(const ExecArgs& args, miopenPoolingMode_t& mode) const;
+    void exec(const ExecArgs& args) const override;
+
+    const char* name() const override { return m_algo_name.c_str(); }
+    AlgoAttribute attribute() const override { return m_algo_attribute; }
+
+    MEGDNN_DECL_ALGO_TYPE(ROCM_MIOPEN)
+
+    std::string param() const override {
+        std::string ret;
+        serialize_write_pod(m_algo_attribute, ret);
+        return ret;
+    }
+};
+
+class PoolingForwardImpl::AlgoPack : NonCopyableObj {
+private:
+    AlgoBase::Mapper m_all_algos_map;
+
+public:
+    AlgoPack();
+    AlgoMIOpen algo_miopen{AlgoAttribute::REPRODUCIBLE};
+
+    std::vector<AlgoBase*> all_algos;
+
+    const AlgoBase::Mapper& all_algos_map() const { return m_all_algos_map; }
+};
+
+class PoolingBackwardImpl::AlgoBase : public Algorithm {
+public:
+    enum class AlgoType : uint32_t { ROCM_MIOPEN };
+    using Mapper = std::unordered_map<AlgorithmDesc, AlgoBase*>;
+
+    AlgoBase() : Algorithm() { m_handle_type = Handle::HandleType::ROCM; }
+    struct SizeArgs {
+        HandleImpl* handle;
+        PoolingBackwardImpl* opr;
+        const TensorLayout *layout_src, *layout_dst, *layout_diff, *layout_grad;
+
+        std::string to_string() const;
+        void init_desc(TensorDesc& src_desc, TensorDesc& dst_desc,
+                       TensorDesc& diff_desc, TensorDesc& grad_desc) const {
+            src_desc.set(*layout_src);
+            dst_desc.set(*layout_dst);
+            diff_desc.set(*layout_diff);
+            grad_desc.set(*layout_grad);
+        }
+        SizeArgs(PoolingBackwardImpl* opr, const TensorLayout& src,
+                 const TensorLayout& dst, const TensorLayout& diff,
+                 const TensorLayout& grad);
+    };
+    struct ExecArgs : public SizeArgs {
+        const TensorND *src_tensor, *dst_tensor, *diff_tensor, *grad_tensor;
+        Workspace workspace;
+
+        ExecArgs(PoolingBackwardImpl* opr, _megdnn_tensor_in src,
+                 _megdnn_tensor_in dst, _megdnn_tensor_in diff,
+                 _megdnn_tensor_out grad, _megdnn_workspace workspace);
+    };
+
+    virtual bool is_available(const SizeArgs& args) const = 0;
+    virtual size_t get_workspace_in_bytes(const SizeArgs& args) const = 0;
+    virtual void exec(const ExecArgs& args) const = 0;
+
+    bool is_available_attribute(
+            const SizeArgs& args,
+            const AlgoAttribute& positive_attr = AlgoAttribute::REPRODUCIBLE,
+            const AlgoAttribute& negative_attr = AlgoAttribute::DEFAULT) {
+        return contain_attribute_all(positive_attr) &&
+               !contain_attribute_any(negative_attr) && is_available(args);
+    }
+
+protected:
+    ~AlgoBase() = default;
+};
+
+class PoolingBackwardImpl::AlgoMIOpen final : public AlgoBase {
+    std::string m_algo_name;
+    AlgoAttribute m_algo_attribute;
+
+public:
+    AlgoMIOpen(AlgoAttribute attr)
+            : m_algo_name("MIOpenPoolingBackward"), m_algo_attribute(attr) {}
+
+    bool is_available(const SizeArgs& args) const override;
+    size_t get_workspace_in_bytes(const SizeArgs& args) const override;
+    void init_mode(const ExecArgs& args, miopenPoolingMode_t& mode) const;
+    void exec(const ExecArgs& args) const override;
+
+    const char* name() const override { return m_algo_name.c_str(); }
+    AlgoAttribute attribute() const override {
+        return m_algo_attribute;
+    }
+
+    MEGDNN_DECL_ALGO_TYPE(ROCM_MIOPEN)
+
+    std::string param() const override {
+        std::string ret;
+        serialize_write_pod(m_algo_attribute, ret);
+        return ret;
+    }
+};
+
+class PoolingBackwardImpl::AlgoPack : NonCopyableObj {
+private:
+    AlgoBase::Mapper m_all_algos_map;
+
+public:
+    AlgoPack();
+    AlgoMIOpen algo_miopen{AlgoAttribute::REPRODUCIBLE};
+    std::vector<AlgoBase*> all_algos;
+
+    const AlgoBase::Mapper& all_algos_map() const { return m_all_algos_map; }
+};
+
+}  // namespace rocm
+}  // namespace megdnn

dnn/src/rocm/pooling/opr_impl.cpp

@@ -10,18 +10,47 @@
  */
 #include "hcc_detail/hcc_defs_prologue.h"
 #include "src/rocm/pooling/opr_impl.h"
-
 #include "src/rocm/utils.h"
+#include "./algo.h"
+#include "src/common/algo_chooser.h"
 
 namespace megdnn {
 namespace rocm {
 
-void PoolingForwardImpl::setup_descs(const TensorLayout &src,
-        const TensorLayout &dst)
-{
-    src_desc.set(src, param().format);
-    dst_desc.set(dst, param().format);
-    pooling_desc.set(this->param());
+size_t PoolingForwardImpl::get_workspace_in_bytes(const TensorLayout& src,
+                              const TensorLayout& dst) {
+    AlgoBase::SizeArgs args(this, src, dst);
+    return get_algorithm(this, src, dst)->get_workspace_in_bytes(args);
+}
+
+const char* PoolingForwardImpl::get_algorithm_set_name() const {
+    return "ROCM_POOLING_FORWARD";
+}
+
+std::vector<PoolingForwardImpl::Algorithm*>
+PoolingForwardImpl::get_all_algorithms(const TensorLayout& src,
+                                       const TensorLayout& dst) {
+    return megdnn::get_all_algorithms<PoolingForwardImpl>({this, src, dst});
+}
+
+PoolingForwardImpl::Algorithm* PoolingForwardImpl::get_algorithm_heuristic(
+        const TensorLayout& src, const TensorLayout& dst,
+        size_t workspace_limit_in_bytes, const AlgoAttribute& positive_attr,
+        const AlgoAttribute& negative_attr) {
+    MEGDNN_MARK_USED_VAR(workspace_limit_in_bytes);
+
+    AlgoBase::SizeArgs args(this, src, dst);
+    for (auto&& iter : sm_algo_pack.all_algos) {
+        if (iter->is_available_attribute(args, positive_attr, negative_attr)) {
+            return iter;
+        }
+    }
+    megdnn_throw(
+            ssprintf("require algorithm with attribute(%s) and without "
+                     "attribute(%s), but can't get suitable algo.\n",
+                     Algorithm::attribute_str(positive_attr).c_str(),
+                     Algorithm::attribute_str(negative_attr).c_str()));
+    return nullptr;
 }
 
 void PoolingForwardImpl::exec(_megdnn_tensor_in src,
@@ -29,24 +58,52 @@ void PoolingForwardImpl::exec(_megdnn_tensor_in src,
         _megdnn_workspace workspace)
 {
     check_exec(src.layout, dst.layout, workspace.size);
-    auto handle = miopen_handle(this->handle());
-    setup_descs(src.layout, dst.layout);
-    dt_float32 alpha = 1.0f, beta = 0.0f;
-    miopen_check(miopenPoolingForward(handle, pooling_desc.desc, &alpha,
-                                      src_desc.desc, src.raw_ptr, &beta,
-                                      dst_desc.desc, dst.raw_ptr, false,
-                                      nullptr, 0_z));
+    {
+        AlgoBase::ExecArgs args(this, src, dst, workspace);
+        auto algo = get_algorithm(this, src.layout, dst.layout);
+        algo->exec(args);
+    }
 }
 
-void PoolingBackwardImpl::setup_descs(const TensorLayout& src,
-                                      const TensorLayout& dst,
-                                      const TensorLayout& diff,
-                                      const TensorLayout& grad) {
-    src_desc.set(src);
-    dst_desc.set(dst);
-    diff_desc.set(diff);
-    grad_desc.set(grad);
-    pooling_desc.set(this->param());
+size_t PoolingBackwardImpl::get_workspace_in_bytes(const TensorLayout& src,
+                const TensorLayout& dst,
+                const TensorLayout& diff,
+                const TensorLayout& grad) {
+    AlgoBase::SizeArgs args(this, src, dst, diff, grad);
+    return get_algorithm(this, src, dst, diff, grad)
+            ->get_workspace_in_bytes(args);
+};
+
+const char* PoolingBackwardImpl::get_algorithm_set_name() const {
+    return "ROCM_POOLING_BACKWARD";
+}
+
+std::vector<Algorithm*> PoolingBackwardImpl::get_all_algorithms(
+        const TensorLayout& src, const TensorLayout& dst,
+        const TensorLayout& diff, const TensorLayout& grad) {
+    return megdnn::get_all_algorithms<PoolingBackwardImpl>(
+            {this, src, dst, diff, grad});
+}
+
+Algorithm* PoolingBackwardImpl::get_algorithm_heuristic(
+        const TensorLayout& src, const TensorLayout& dst,
+        const TensorLayout& diff, const TensorLayout& grad,
+        size_t workspace_limit_in_bytes, const AlgoAttribute& positive_attr,
+        const AlgoAttribute& negative_attr) {
+    MEGDNN_MARK_USED_VAR(workspace_limit_in_bytes);
+
+    AlgoBase::SizeArgs args(this, src, dst, diff, grad);
+    for (auto iter : sm_algo_pack.all_algos) {
+        if (iter->is_available_attribute(args, positive_attr, negative_attr)) {
+            return iter;
+        }
+    }
+    megdnn_throw(
+            ssprintf("require algorithm with attribute(%s) and without "
+                     "attribute(%s), but can't get suitable algo.\n",
+                     Algorithm::attribute_str(positive_attr).c_str(),
+                     Algorithm::attribute_str(negative_attr).c_str()));
+    return nullptr;
 }
 
 void PoolingBackwardImpl::exec(_megdnn_tensor_in src,
@@ -55,35 +112,16 @@ void PoolingBackwardImpl::exec(_megdnn_tensor_in src,
         _megdnn_tensor_out grad,
         _megdnn_workspace workspace)
 {
-    check_exec(src.layout, dst.layout, diff.layout, grad.layout, workspace.size);
-    auto handle = miopen_handle(this->handle());
-    setup_descs(src.layout, dst.layout, diff.layout, grad.layout);
-    float alpha = 1.0f, beta = 0.0f;
-    if (param().mode == param::Pooling::Mode::MAX) {
-        //! FIXME: when using max pooling opr, the backward opr need the indices
-        //! of the forward opr which stored in workspace. We have to recompute
-        //! the indices by calling miopenPoolingForward again.
-        miopen_check(miopenPoolingForward(handle, pooling_desc.desc, &alpha,
-                                          src_desc.desc, src.raw_ptr, &beta,
-                                          dst_desc.desc, dst.raw_ptr, true,
-                                          workspace.raw_ptr, workspace.size));
+    check_exec(src.layout, dst.layout, diff.layout, grad.layout,
+               workspace.size);
+    {
+        AlgoBase::ExecArgs args(this, src, dst, diff, grad, workspace);
+        auto algo = get_algorithm(this, src.layout, dst.layout, diff.layout,
+                                  grad.layout);
+        algo->exec(args);
     }
-    miopen_check(miopenPoolingBackward(
-            handle, pooling_desc.desc, &alpha, dst_desc.desc, dst.raw_ptr,
-            diff_desc.desc, diff.raw_ptr, src_desc.desc, src.raw_ptr, &beta,
-            grad_desc.desc, grad.raw_ptr, workspace.raw_ptr));
 }
 
-size_t PoolingBackwardImpl::get_workspace_in_bytes(const TensorLayout& src,
-                const TensorLayout& dst,
-                const TensorLayout& diff,
-                const TensorLayout& grad) {
-    setup_descs(src, dst, diff, grad);
-    size_t ws_size = 0_z;
-    miopenPoolingGetWorkSpaceSize(dst_desc.desc, &ws_size); 
-    return ws_size;
-};
-
 } // namespace rocm
 } // namespace megdnn
 

dnn/src/rocm/pooling/opr_impl.h

@@ -22,13 +22,37 @@ class PoolingForwardImpl final: public PoolingForward {
         void exec(_megdnn_tensor_in src, _megdnn_tensor_out dst,
                 _megdnn_workspace workspace) override;
         size_t get_workspace_in_bytes(const TensorLayout &,
-                const TensorLayout &) override {
-            return 0;
+                const TensorLayout &) override;
+
+        const char* get_algorithm_set_name() const override;
+        Algorithm* get_algorithm_from_desc(const AlgorithmDesc& desc) override;
+
+        AlgorithmInfo get_algorithm_info_heuristic(
+                const TensorLayout& src, const TensorLayout& dst,
+                size_t workspace_limit_in_bytes,
+                const AlgoAttribute& positive_attr,
+                const AlgoAttribute& negative_attr) {
+            return get_algorithm_heuristic(src, dst, workspace_limit_in_bytes,
+                                           positive_attr, negative_attr)
+                    ->info();
         }
+
+        class AlgoBase;
+        class AlgoMIOpen;
+        class AlgoPack;
+
+        static const AlgoPack& algo_pack() { return sm_algo_pack; }
+    
+    protected:
+        std::vector<Algorithm*> get_all_algorithms(
+            const TensorLayout& src, const TensorLayout& dst) override;
+        Algorithm* get_algorithm_heuristic(
+                const TensorLayout& src, const TensorLayout& dst,
+                size_t workspace_limit_in_bytes, const AlgoAttribute& positive_attr,
+                const AlgoAttribute& negative_attr) override;
+
     private:
-        TensorDesc src_desc, dst_desc;
-        PoolingDesc pooling_desc;
-        void setup_descs(const TensorLayout &src, const TensorLayout &dst);
+        static AlgoPack sm_algo_pack;
 };
 
 class PoolingBackwardImpl final: public PoolingBackward {
@@ -43,14 +67,41 @@ class PoolingBackwardImpl final: public PoolingBackward {
                 const TensorLayout& dst,
                 const TensorLayout& diff,
                 const TensorLayout& grad) override;
-    private:
-        TensorDesc src_desc, dst_desc, diff_desc, grad_desc;
-        PoolingDesc pooling_desc;
-        void setup_descs(const TensorLayout &src,
-                const TensorLayout &dst,
-                const TensorLayout &diff,
-                const TensorLayout &grad);
 
+        const char* get_algorithm_set_name() const override;
+        Algorithm* get_algorithm_from_desc(const AlgorithmDesc& desc) override;
+
+        AlgorithmInfo get_algorithm_info_heuristic(
+                const TensorLayout& src, const TensorLayout& dst,
+                const TensorLayout& diff, const TensorLayout& grad,
+                size_t workspace_limit_in_bytes,
+                const AlgoAttribute& positive_attr,
+                const AlgoAttribute& negative_attr) {
+            return get_algorithm_heuristic(src, dst, diff, grad,
+                                           workspace_limit_in_bytes,
+                                           positive_attr, negative_attr)
+                    ->info();
+        }
+
+        class AlgoBase;
+        class AlgoMIOpen;
+        class AlgoPack;
+
+        static const AlgoPack& algo_pack() { return sm_algo_pack; }
+
+    protected:
+        std::vector<Algorithm*> get_all_algorithms(
+                const TensorLayout& src, const TensorLayout& dst,
+                const TensorLayout& diff, const TensorLayout& grad) override;
+        Algorithm* get_algorithm_heuristic(
+                const TensorLayout& src, const TensorLayout& dst,
+                const TensorLayout& diff, const TensorLayout& grad,
+                size_t workspace_limit_in_bytes,
+                const AlgoAttribute& positive_attr,
+                const AlgoAttribute& negative_attr) override;
+
+    private:
+        static AlgoPack sm_algo_pack;
 };
 
 } // namespace rocm