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Small fixes related to BF16 fusion_gru and fusion_lstm #33295

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merged 7 commits into from
Jun 11, 2021
Merged

Small fixes related to BF16 fusion_gru and fusion_lstm #33295

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1ad2478
Small changes related to BF16 fusion_gru and fusion_lstm
wozna Jun 2, 2021
ad5c8b0
Correct to pass arg by value
wozna Jun 2, 2021
419d486
Add conditions to rnn op
wozna Jun 7, 2021
0c1ba3b
Correct the spelling mistake
wozna Jun 9, 2021
e552ac3
Improving the test with checking activation
wozna Jun 10, 2021
5edf125
Merge branch 'develop' into bf16_fusion_rnn
wozna Jun 10, 2021
e731d53
Trigger CI
wozna Jun 10, 2021
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2 changes: 2 additions & 0 deletions paddle/fluid/framework/ir/CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -188,4 +188,6 @@ endif()
cc_test(test_cpu_bfloat16_pass SRCS mkldnn/cpu_bfloat16_pass_tester.cc DEPS cpu_bfloat16_pass)
cc_test(test_multi_gru_fuse_pass SRCS mkldnn/multi_gru_fuse_pass_tester.cc DEPS multi_gru_fuse_pass)
cc_test(test_multi_gru_seq_fuse_pass SRCS mkldnn/multi_gru_seq_fuse_pass_tester.cc DEPS multi_gru_seq_fuse_pass)
set(TEST_FC_RNN_PASS_DEPS fc_gru_fuse_pass fc_lstm_fuse_pass mkldnn_placement_pass)
cc_test(test_fc_rnn_mkldnn_fuse_pass SRCS mkldnn/mkldnn_fc_rnn_fuse_pass_tester.cc DEPS ${TEST_FC_RNN_PASS_DEPS})
endif ()
14 changes: 10 additions & 4 deletions paddle/fluid/framework/ir/fc_gru_fuse_pass.cc
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Expand Up @@ -47,8 +47,9 @@ static int BuildFusion(Graph* graph, const std::string& name_scope,
gru_pattern(fc_out);

// Create New OpDesc
auto gru_creater = [&](Node* gru, Node* x, Node* weight_x, Node* weight_h,
Node* bias, Node* hidden, Node* fc_bias) {
auto gru_creator = [&](Node* gru, Node* x, Node* weight_x, Node* weight_h,
Node* bias, Node* hidden, Node* fc_bias,
const bool use_mkldnn) {
OpDesc op_desc;
op_desc.SetType("fusion_gru");

Expand All @@ -67,6 +68,7 @@ static int BuildFusion(Graph* graph, const std::string& name_scope,
gru->Op()->GetAttrIfExists<bool>("origin_mode"));
// TODO(TJ): This should be a option for infer
op_desc.SetAttr("use_seq", true);
op_desc.SetAttr("use_mkldnn", use_mkldnn);
op_desc.SetAttr("activation", gru->Op()->GetAttr("activation"));
op_desc.SetAttr("gate_activation", gru->Op()->GetAttr("gate_activation"));

Expand Down Expand Up @@ -149,21 +151,25 @@ static int BuildFusion(Graph* graph, const std::string& name_scope,
LOG(INFO) << "fc_gru_fuse_pass not supported when origin_mode=True.";
return;
}
const bool use_mkldnn =
mul->Op()->GetAttrIfExists<bool>("use_mkldnn") &&
gru->Op()->GetAttrIfExists<std::string>("activation") == "tahn" &&
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gru->Op()->GetAttrIfExists<std::string>("gate_activation") == "sigmoid";

if (with_fc_bias) {
GET_IR_NODE_FROM_SUBGRAPH(mul_out, mul_out, fc_pattern);
GET_IR_NODE_FROM_SUBGRAPH(fc_bias, bias, fc_pattern);
GET_IR_NODE_FROM_SUBGRAPH(elementwise_add, elementwise_add, fc_pattern);
GET_IR_NODE_FROM_SUBGRAPH(fc_out, elementwise_add_out, fc_pattern);

gru_creater(gru, x_n, w, Weight, Bias, Hidden, fc_bias);
gru_creator(gru, x_n, w, Weight, Bias, Hidden, fc_bias, use_mkldnn);
// Remove unneeded nodes.
std::unordered_set<const Node*> marked_nodes(
{mul, gru, elementwise_add, fc_out, mul_out, BatchGate,
BatchResetHiddenPrev, BatchHidden});
GraphSafeRemoveNodes(graph, marked_nodes);
} else {
gru_creater(gru, x_n, w, Weight, Bias, Hidden, nullptr);
gru_creator(gru, x_n, w, Weight, Bias, Hidden, nullptr, use_mkldnn);
// Remove unneeded nodes.
std::unordered_set<const Node*> marked_nodes(
{mul, gru, BatchGate, BatchResetHiddenPrev, BatchHidden});
Expand Down
71 changes: 5 additions & 66 deletions paddle/fluid/framework/ir/fc_gru_fuse_pass_tester.cc
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Expand Up @@ -12,77 +12,15 @@
// See the License for the specific language governing permissions and
// limitations under the License.

#include "paddle/fluid/framework/ir/fc_gru_fuse_pass.h"

#include <gtest/gtest.h>
#include "paddle/fluid/framework/ir/pass_tester_helper.h"
#include "paddle/fluid/framework/ir/fc_gru_fuse_pass_tester.h"

namespace paddle {
namespace framework {
namespace ir {

void AddVarToScope(Scope* param_scope, const std::string& name,
const DDim& dims) {
auto* tensor = param_scope->Var(name)->GetMutable<LoDTensor>();
tensor->Resize(dims);
tensor->mutable_data<float>(platform::CPUPlace());
}

Scope* CreateParamScope() {
auto param_scope = new Scope();
AddVarToScope(param_scope, "gru_fc_w", {});
AddVarToScope(param_scope, "gru_fc_b", {});
AddVarToScope(param_scope, "gru_w", {});
AddVarToScope(param_scope, "gru_b", {});
AddVarToScope(param_scope, "gru_batch_gate_0", {});
AddVarToScope(param_scope, "gru_batch_reset_hidden_prev_0", {});
AddVarToScope(param_scope, "gru_batch_hidden_0", {});
AddVarToScope(param_scope, "gru_hidden_0", {});
AddVarToScope(param_scope, "gru_batch_gate_1", {});
AddVarToScope(param_scope, "gru_batch_reset_hidden_prev_1", {});
AddVarToScope(param_scope, "gru_batch_hidden_1", {});
AddVarToScope(param_scope, "gru_hidden_1", {});
return param_scope;
}

TEST(FCFusePass, basic) {
// inputs operator output
// --------------------------------------------------------
// (a, gru_fc_w) mul -> fc_0_tmp_0
// (fc_0_tmp_0, gru_fc_b) elementwise_add -> fc_0_tmp_1
// (fc_0_tmp_1,gru_w,gru_b gru -> gru_out_0

// (b, gru_fc_w) mul -> fc_1_tmp_0
// (fc_1_tmp_0, gru_fc_b) elementwise_add -> fc_1_tmp_1
// (fc_1_tmp_1,gru_w,gru_b) gru -> gru_out_1
Layers layers;
auto* a = layers.data("a");
auto* b = layers.data("b");
auto* fc_w = layers.data("gru_fc_w", {}, true);
auto* fc_b = layers.data("gru_fc_b", {}, true);
auto* gru_w = layers.data("gru_w", {}, true);
auto* gru_b = layers.data("gru_b", {}, true);
auto* fc_0_tmp0 = layers.mul(a, fc_w);
auto* fc_0_tmp1 = layers.elementwise_add(fc_0_tmp0, fc_b);
auto* gru_batch_gate_0 = layers.data("gru_batch_gate_0", {}, false);
auto* gru_batch_reset_hidden_prev_0 =
layers.data("gru_batch_reset_hidden_prev_0", {}, false);
auto* gru_batch_hidden_0 = layers.data("gru_batch_hidden_0", {}, false);
auto* gru_hidden_0 = layers.data("gru_hidden_0", {}, false);
layers.gru(fc_0_tmp1, gru_w, gru_b, gru_batch_gate_0,
gru_batch_reset_hidden_prev_0, gru_batch_hidden_0, gru_hidden_0);

auto* fc_1_tmp0 = layers.mul(b, fc_w);
auto* fc_1_tmp1 = layers.elementwise_add(fc_1_tmp0, fc_b);
auto* gru_batch_gate_1 = layers.data("gru_batch_gate_1", {}, false);
auto* gru_batch_reset_hidden_prev_1 =
layers.data("gru_batch_reset_hidden_prev_1", {}, false);
auto* gru_batch_hidden_1 = layers.data("gru_batch_hidden_1", {}, false);
auto* gru_hidden_1 = layers.data("gru_hidden_1", {}, false);
layers.gru(fc_1_tmp1, gru_w, gru_b, gru_batch_gate_1,
gru_batch_reset_hidden_prev_1, gru_batch_hidden_1, gru_hidden_1);

std::unique_ptr<ir::Graph> graph(new ir::Graph(layers.main_program()));
namespace fc_gru_test {
TEST(FcGruFusePass, basic) {
std::unique_ptr<ir::Graph> graph = PrepareGraph();
auto pass = PassRegistry::Instance().Get("fc_gru_fuse_pass");
pass->Set("use_gpu", new bool(true));
graph->Set("__param_scope__", CreateParamScope());
Expand All @@ -109,6 +47,7 @@ TEST(FCFusePass, basic) {
"expectations after fuse"));
}

} // namespace fc_gru_test
} // namespace ir
} // namespace framework
} // namespace paddle
Expand Down
93 changes: 93 additions & 0 deletions paddle/fluid/framework/ir/fc_gru_fuse_pass_tester.h
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@@ -0,0 +1,93 @@
// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
//
// 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.
#pragma once

#include "paddle/fluid/framework/ir/fc_gru_fuse_pass.h"

#include <gtest/gtest.h>
#include "paddle/fluid/framework/ir/pass_tester_helper.h"

namespace paddle {
namespace framework {
namespace ir {

namespace fc_gru_test {
void AddVarToScope(Scope* param_scope, const std::string& name,
const DDim& dims) {
auto* tensor = param_scope->Var(name)->GetMutable<LoDTensor>();
tensor->Resize(dims);
tensor->mutable_data<float>(platform::CPUPlace());
}

Scope* CreateParamScope() {
auto param_scope = new Scope();
AddVarToScope(param_scope, "gru_fc_w", {});
AddVarToScope(param_scope, "gru_fc_b", {});
AddVarToScope(param_scope, "gru_w", {});
AddVarToScope(param_scope, "gru_b", {});
AddVarToScope(param_scope, "gru_batch_gate_0", {});
AddVarToScope(param_scope, "gru_batch_reset_hidden_prev_0", {});
AddVarToScope(param_scope, "gru_batch_hidden_0", {});
AddVarToScope(param_scope, "gru_hidden_0", {});
AddVarToScope(param_scope, "gru_batch_gate_1", {});
AddVarToScope(param_scope, "gru_batch_reset_hidden_prev_1", {});
AddVarToScope(param_scope, "gru_batch_hidden_1", {});
AddVarToScope(param_scope, "gru_hidden_1", {});
return param_scope;
}

std::unique_ptr<ir::Graph> PrepareGraph() {
// inputs operator output
// --------------------------------------------------------
// (a, gru_fc_w) mul -> fc_0_tmp_0
// (fc_0_tmp_0, gru_fc_b) elementwise_add -> fc_0_tmp_1
// (fc_0_tmp_1,gru_w,gru_b gru -> gru_out_0

// (b, gru_fc_w) mul -> fc_1_tmp_0
// (fc_1_tmp_0, gru_fc_b) elementwise_add -> fc_1_tmp_1
// (fc_1_tmp_1,gru_w,gru_b) gru -> gru_out_1
Layers layers;
auto* a = layers.data("a");
auto* b = layers.data("b");
auto* fc_w = layers.data("gru_fc_w", {}, true);
auto* fc_b = layers.data("gru_fc_b", {}, true);
auto* gru_w = layers.data("gru_w", {}, true);
auto* gru_b = layers.data("gru_b", {}, true);
auto* fc_0_tmp0 = layers.mul(a, fc_w);
auto* fc_0_tmp1 = layers.elementwise_add(fc_0_tmp0, fc_b);
auto* gru_batch_gate_0 = layers.data("gru_batch_gate_0", {}, false);
auto* gru_batch_reset_hidden_prev_0 =
layers.data("gru_batch_reset_hidden_prev_0", {}, false);
auto* gru_batch_hidden_0 = layers.data("gru_batch_hidden_0", {}, false);
auto* gru_hidden_0 = layers.data("gru_hidden_0", {}, false);
layers.gru(fc_0_tmp1, gru_w, gru_b, gru_batch_gate_0,
gru_batch_reset_hidden_prev_0, gru_batch_hidden_0, gru_hidden_0);

auto* fc_1_tmp0 = layers.mul(b, fc_w);
auto* fc_1_tmp1 = layers.elementwise_add(fc_1_tmp0, fc_b);
auto* gru_batch_gate_1 = layers.data("gru_batch_gate_1", {}, false);
auto* gru_batch_reset_hidden_prev_1 =
layers.data("gru_batch_reset_hidden_prev_1", {}, false);
auto* gru_batch_hidden_1 = layers.data("gru_batch_hidden_1", {}, false);
auto* gru_hidden_1 = layers.data("gru_hidden_1", {}, false);
layers.gru(fc_1_tmp1, gru_w, gru_b, gru_batch_gate_1,
gru_batch_reset_hidden_prev_1, gru_batch_hidden_1, gru_hidden_1);

std::unique_ptr<ir::Graph> graph(new ir::Graph(layers.main_program()));
return std::move(graph);
}
} // namespace fc_gru_test
} // namespace ir
} // namespace framework
} // namespace paddle
15 changes: 12 additions & 3 deletions paddle/fluid/framework/ir/fc_lstm_fuse_pass.cc
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Expand Up @@ -47,7 +47,7 @@ int BuildFusion(Graph* graph, const std::string& name_scope, Scope* scope,
// Create New OpDesc
auto lstm_creator = [&](Node* lstm, Node* input, Node* weight_x,
Node* weight_h, Node* bias, Node* hidden, Node* cell,
Node* xx, Node* fc_bias) {
Node* xx, Node* fc_bias, const bool use_mkldnn) {
OpDesc op_desc;
op_desc.SetType("fusion_lstm");
#define SET_IN(Key, node__) op_desc.SetInput(#Key, {node__->Name()});
Expand Down Expand Up @@ -88,6 +88,7 @@ int BuildFusion(Graph* graph, const std::string& name_scope, Scope* scope,
op_desc.SetOutput("XX", {xx->Name()});
op_desc.SetAttr("is_reverse", lstm->Op()->GetAttr("is_reverse"));
op_desc.SetAttr("use_peepholes", lstm->Op()->GetAttr("use_peepholes"));
op_desc.SetAttr("use_mkldnn", use_mkldnn);
// TODO(TJ): get from attr
op_desc.SetAttr("use_seq", true);

Expand Down Expand Up @@ -148,21 +149,29 @@ int BuildFusion(Graph* graph, const std::string& name_scope, Scope* scope,
GET_IR_NODE_FROM_SUBGRAPH(Cell, Cell, lstm_pattern);
GET_IR_NODE_FROM_SUBGRAPH(w, w, fc_pattern);
GET_IR_NODE_FROM_SUBGRAPH(mul, mul, fc_pattern);
const bool use_mkldnn =
mul->Op()->GetAttrIfExists<bool>("use_mkldnn") &&
lstm->Op()->GetAttrIfExists<std::string>("gate_activation") ==
"sigmoid" &&
lstm->Op()->GetAttrIfExists<std::string>("cell_activation") == "tahn" &&
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lstm->Op()->GetAttrIfExists<std::string>("candidate_activation") ==
"tahn";
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if (with_fc_bias) {
GET_IR_NODE_FROM_SUBGRAPH(fc_out, elementwise_add_out, fc_pattern);
GET_IR_NODE_FROM_SUBGRAPH(fc_bias, bias, fc_pattern);
GET_IR_NODE_FROM_SUBGRAPH(mul_out, mul_out, fc_pattern);
GET_IR_NODE_FROM_SUBGRAPH(elementwise_add, elementwise_add, fc_pattern);
lstm_creator(lstm, subgraph.at(x), w, Weight, Bias, Hidden, Cell, fc_out,
fc_bias);
fc_bias, use_mkldnn);
// Remove unneeded nodes.
std::unordered_set<const Node*> marked_nodes(
{mul, lstm, elementwise_add, mul_out, BatchGate, BatchCellPreAct});
GraphSafeRemoveNodes(graph, marked_nodes);
} else {
GET_IR_NODE_FROM_SUBGRAPH(fc_out, mul_out, fc_pattern);
lstm_creator(lstm, subgraph.at(x), w, Weight, Bias, Hidden, Cell, fc_out,
nullptr);
nullptr, use_mkldnn);
// Remove unneeded nodes.
std::unordered_set<const Node*> marked_nodes(
{mul, lstm, BatchGate, BatchCellPreAct});
Expand Down
71 changes: 5 additions & 66 deletions paddle/fluid/framework/ir/fc_lstm_fuse_pass_tester.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -12,77 +12,16 @@
// See the License for the specific language governing permissions and
// limitations under the License.

#include "paddle/fluid/framework/ir/fc_lstm_fuse_pass.h"

#include <gtest/gtest.h>
#include "paddle/fluid/framework/ir/pass_tester_helper.h"
#include "paddle/fluid/framework/ir/fc_lstm_fuse_pass_tester.h"

namespace paddle {
namespace framework {
namespace ir {

void AddVarToScope(Scope* param_scope, const std::string& name,
const DDim& dims) {
auto* tensor = param_scope->Var(name)->GetMutable<LoDTensor>();
tensor->Resize(dims);
tensor->mutable_data<float>(platform::CPUPlace());
}

Scope* CreateParamScope() {
auto param_scope = new Scope();
AddVarToScope(param_scope, "lstm_fc_w", {});
AddVarToScope(param_scope, "lstm_fc_b", {});
AddVarToScope(param_scope, "lstm_w", {});
AddVarToScope(param_scope, "lstm_b", {});
AddVarToScope(param_scope, "lstm_cell_0", {});
AddVarToScope(param_scope, "lstm_batch_gate_0", {});
AddVarToScope(param_scope, "lstm_batch_cell_pre_gate_0", {});
AddVarToScope(param_scope, "lstm_hidden_0", {});
AddVarToScope(param_scope, "lstm_cell_1", {});
AddVarToScope(param_scope, "lstm_batch_gate_1", {});
AddVarToScope(param_scope, "lstm_batch_cell_pre_gate_1", {});
AddVarToScope(param_scope, "lstm_hidden_1", {});
return param_scope;
}

TEST(FCLSTMFusePass, basic) {
// inputs operator output
// --------------------------------------------------------
// (a, lstm_fc_w) mul -> fc_0_tmp_0
// (fc_0_tmp_0, lstm_fc_b) elementwise_add -> fc_0_tmp_1
// fc_0_tmp_1,lstm_w,lstm_b lstm -> lstm_out_0

// (b, lstm_fc_w) mul -> fc_1_tmp_0
// (fc_1_tmp_0, lstm_fc_b) elementwise_add -> fc_1_tmp_1
// (fc_1_tmp_1,lstm_w,lstm_b) lstm -> lstm_out_1
Layers layers;
auto* a = layers.data("a");
auto* b = layers.data("b");
auto* fc_w = layers.data("lstm_fc_w", {}, true);
auto* fc_b = layers.data("lstm_fc_b", {}, true);
auto* lstm_w = layers.data("lstm_w", {}, true);
auto* lstm_b = layers.data("lstm_b", {}, true);
auto* fc_0_tmp0 = layers.mul(a, fc_w);
auto* fc_0_tmp1 = layers.elementwise_add(fc_0_tmp0, fc_b);
auto* lstm_cell_0 = layers.data("lstm_cell_0", {}, false);
auto* lstm_batch_gate_0 = layers.data("lstm_batch_gate_0", {}, false);
auto* lstm_batch_cell_pre_gate_0 =
layers.data("lstm_batch_cell_pre_gate_0", {}, false);
auto* lstm_hidden_0 = layers.data("lstm_hidden_0", {}, false);
layers.lstm(fc_0_tmp1, lstm_w, lstm_b, lstm_cell_0, lstm_batch_gate_0,
lstm_hidden_0, lstm_batch_cell_pre_gate_0);
namespace fc_lstm_test {

auto* fc_1_tmp0 = layers.mul(b, fc_w);
auto* fc_1_tmp1 = layers.elementwise_add(fc_1_tmp0, fc_b);
auto* lstm_cell_1 = layers.data("lstm_cell_1", {}, false);
auto* lstm_batch_gate_1 = layers.data("lstm_batch_gate_1", {}, false);
auto* lstm_batch_cell_pre_gate_1 =
layers.data("lstm_batch_cell_pre_gate_1", {}, false);
auto* lstm_hidden_1 = layers.data("lstm_hidden_1", {}, false);
layers.lstm(fc_1_tmp1, lstm_w, lstm_b, lstm_cell_1, lstm_batch_gate_1,
lstm_hidden_1, lstm_batch_cell_pre_gate_1);

std::unique_ptr<ir::Graph> graph(new ir::Graph(layers.main_program()));
TEST(FcLstmFusePass, basic) {
std::unique_ptr<ir::Graph> graph = PrepareGraph();
auto pass = PassRegistry::Instance().Get("fc_lstm_fuse_pass");
pass->Set("use_gpu", new bool(false));
graph->Set("__param_scope__", CreateParamScope());
Expand All @@ -108,7 +47,7 @@ TEST(FCLSTMFusePass, basic) {
"The number of fusion_gru nodes does "
"not meet expectations after fuse"));
}

} // namespace fc_lstm_test
} // namespace ir
} // namespace framework
} // namespace paddle
Expand Down
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