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[Paddle-Inference] support preln_ernie: add preln_embedding_eltwise_l…
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…ayernorm_fuse_pass, preln_skip_layernorm_fuse_pass (#39508)

* support preln_ernie

* support preln_ernie
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@Wangzheee
Wangzheee authored Feb 15, 2022
1 parent 3e7825f commit 2bc91cc
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Showing 8 changed files with 938 additions and 18 deletions.
2 changes: 2 additions & 0 deletions paddle/fluid/framework/ir/CMakeLists.txt
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Expand Up @@ -103,6 +103,8 @@ target_link_libraries(generate_pass pass_desc_proto)

if(WITH_TENSORRT)
pass_library(trt_map_matmul_to_mul_pass inference)
pass_library(preln_embedding_eltwise_layernorm_fuse_pass inference)
pass_library(preln_skip_layernorm_fuse_pass inference)
endif()

if(WITH_GPU OR WITH_ROCM)
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2 changes: 2 additions & 0 deletions paddle/fluid/framework/ir/pass.h
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Expand Up @@ -47,6 +47,8 @@ constexpr char kPassRecorder[] = "pass_recorder";
constexpr char kEmbEltwiseLayernormPass[] =
"embedding_eltwise_layernorm_fuse_pass_flag";
constexpr char kMultiheadMatmulPass[] = "multihead_matmul_fuse_pass_flag";
constexpr char kPrelnEmbEltwiseLayernormPass[] =
"preln_embedding_eltwise_layernorm_fuse_pass_flag";

class Pass {
public:
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450 changes: 450 additions & 0 deletions paddle/fluid/framework/ir/preln_embedding_eltwise_layernorm_fuse_pass.cc
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166 changes: 166 additions & 0 deletions paddle/fluid/framework/ir/preln_embedding_eltwise_layernorm_fuse_pass.h
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// Copyright (c) 2022 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 <memory>
#include <string>
#include <utility>

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

namespace paddle {
namespace framework {
namespace ir {
class Graph;
} // namespace ir
} // namespace framework
} // namespace paddle

namespace paddle {
namespace framework {
namespace ir {
namespace patterns {

// detect start pattern.
//
// in_var emb in_var emb
// | | | |
// lookup_table lookup_table
// | |
// lkt_var lkt_var
// \ /
// elementwise_add
// |
// elt_out_var
//
struct PrelnEmbedding2Eltwise1Pattern : public PatternBase {
PrelnEmbedding2Eltwise1Pattern(PDPattern* pattern,
const std::string& name_scope)
: PatternBase(pattern, name_scope, "Prelnembedding2_eltwise1") {}

void operator()();

PATTERN_DECL_NODE(lookup_table1_x);
PATTERN_DECL_NODE(lookup_table2_x);
PATTERN_DECL_NODE(lookup_table1_w);
PATTERN_DECL_NODE(lookup_table2_w);
PATTERN_DECL_NODE(lookup_table1);
PATTERN_DECL_NODE(lookup_table2);
PATTERN_DECL_NODE(lookup_table1_out);
PATTERN_DECL_NODE(lookup_table2_out);
PATTERN_DECL_NODE(eltwise_add);
PATTERN_DECL_NODE(eltwise_add_out);
};

// detect repeats inner pattern
//
// elt_out_var in_var emb
// \ | |
// \ lookup_table
// \ |
// \ lkt_var
// \ /
// elementwise_add
// | |
// elementwise_add elt_out_var
//
struct PrelnEmbedding1Eltwise1Pattern : public PatternBase {
PrelnEmbedding1Eltwise1Pattern(PDPattern* pattern,
const std::string& name_scope)
: PatternBase(pattern, name_scope, "Prelnembedding1_eltwise1") {}
void operator()();
PATTERN_DECL_NODE(lookup_table1_x);
PATTERN_DECL_NODE(lookup_table1_w);
PATTERN_DECL_NODE(lookup_table1);
PATTERN_DECL_NODE(lookup_table1_out);
PATTERN_DECL_NODE(eltwise_add_in);
PATTERN_DECL_NODE(eltwise_add);
PATTERN_DECL_NODE(eltwise_add_out);
};

// detect end pattern
//
// elementwise_add
// | |
// | elt_out_var
// | scale | bias
// | \ | /
// elementwise_add layer_norm
//
struct PrelnSkipLayerNorm : public PatternBase {
PrelnSkipLayerNorm(PDPattern* pattern, const std::string& name_scope)
: PatternBase(pattern, name_scope, "Prelnskip_layernorm") {}
void operator()();
PATTERN_DECL_NODE(eltwise_add);
PATTERN_DECL_NODE(eltwise_add_out);
PATTERN_DECL_NODE(layer_norm);
PATTERN_DECL_NODE(layer_norm_bias);
PATTERN_DECL_NODE(layer_norm_scale);
PATTERN_DECL_NODE(layer_norm_out);
// Delete the mean and var nodes in the graph.
PATTERN_DECL_NODE(layer_norm_mean);
PATTERN_DECL_NODE(layer_norm_variance);
};
} // namespace patterns

// The PrelnEmbeddingEltwiseLayerNormFusePass detect the following pattern:
//
// inputs operator output
// --------------------------------------------------------------------
// (word, weights_0) lookup_table -> word_emb
// (pos, weights_1) lookup_table -> pos_emb
// (sent, weights_2) lookup_table -> sent_emb
// (word_emb, pos_emb) elementweise_add -> elementwise_out_0
// (elemtwise_out_0, sent_emb) elementweise_add -> elementwise_out_1
// (elementwise_out_1, scale, bias) layer_norm -> layer_norm_out
//
// and then convert the corresponding subgraph to:
//
// (word, pos, sent, weights_0, weights_1, weights_2,
// scale, baias) Prelnembedding_eltwise_layernorm -> layer_norm_out +
// elementwise_add_out
//
//
// in_var emb_var in_var emb_var in_var emb_var in_var emb_var
// | | | | | | | |
// lookup_table lookup_table lookup_table ... lookup_table
// | | | |
// lkt_var lkt_var lkt_var lkt_var
// \ / | ... |
// elementwise_add | |
// \ / |
// elementwise_add |
// | |
// elt_var /
// \ /
// elementwise_add
// | |
// elementwise_add layer_norm

class PrelnEmbeddingEltwiseLayerNormFusePass : public FusePassBase {
public:
PrelnEmbeddingEltwiseLayerNormFusePass();
virtual ~PrelnEmbeddingEltwiseLayerNormFusePass() {}

protected:
void ApplyImpl(Graph* graph) const;
int BuildFusion(Graph* graph, const std::string& name_scope
/*const Scope* scope*/) const;
const std::string name_scope_{"preln_embedding_eltwise_layernorm_fuse"};
};

} // namespace ir
} // namespace framework
} // namespace paddle
210 changes: 210 additions & 0 deletions paddle/fluid/framework/ir/preln_skip_layernorm_fuse_pass.cc
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/* Copyright (c) 2022 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. */

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

#include <string>

#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
#include "paddle/fluid/framework/op_version_registry.h"

namespace paddle {
namespace framework {
namespace ir {
class Node;
} // namespace ir
} // namespace framework
} // namespace paddle

namespace paddle {
namespace framework {
namespace ir {
namespace patterns {

struct PrelnSkipLayerNorm : public PatternBase {
PrelnSkipLayerNorm(PDPattern *pattern, const std::string &name_scope)
: PatternBase(pattern, name_scope, "preln_skip_layernorm") {}

void operator()(PDNode *x, PDNode *y);

// declare operator node's name
PATTERN_DECL_NODE(fused_skipe_layernorm);
PATTERN_DECL_NODE(elementwise);
PATTERN_DECL_NODE(layer_norm);
// declare variable node's name
PATTERN_DECL_NODE(
elementwise_out); // (elementwise_input_x,elementwise_input_y) ->
// elementwise_out
PATTERN_DECL_NODE(layer_norm_bias);
PATTERN_DECL_NODE(layer_norm_scale);
PATTERN_DECL_NODE(layer_norm_out);
PATTERN_DECL_NODE(layer_norm_mean);
PATTERN_DECL_NODE(layer_norm_variance);
};

void PrelnSkipLayerNorm::operator()(PDNode *x, PDNode *y) {
// Create nodes for elementwise add op.
x->assert_is_op_input("elementwise_add", "X");
y->assert_is_op_input("elementwise_add", "Y");
auto *elementwise =
pattern->NewNode(elementwise_repr())->assert_is_op("elementwise_add");
auto *elementwise_out_var = pattern->NewNode(elementwise_out_repr())
->assert_is_op_output("elementwise_add")
->assert_is_op_input("layer_norm", "X")
->assert_is_op_input("elementwise_add", "Y");

// Add links for elementwise_add op.
elementwise->LinksFrom({x, y}).LinksTo({elementwise_out_var});

// Create nodes for layer_norm op.
auto *layer_norm =
pattern->NewNode(layer_norm_repr())->assert_is_op("layer_norm");
auto *layer_norm_bias_var = pattern->NewNode(layer_norm_bias_repr())
->AsInput()
->assert_is_persistable_var()
->assert_is_op_input("layer_norm", "Bias");
auto *layer_norm_scale_var = pattern->NewNode(layer_norm_scale_repr())
->AsInput()
->assert_is_persistable_var()
->assert_is_op_input("layer_norm", "Scale");

auto *layer_norm_out_var = pattern->NewNode(layer_norm_out_repr())
->AsOutput()
->assert_is_op_output("layer_norm", "Y");
auto *layer_norm_mean_var = pattern->NewNode(layer_norm_mean_repr())
->AsOutput()
->assert_is_op_output("layer_norm", "Mean");
auto *layer_norm_variance_var =
pattern->NewNode(layer_norm_variance_repr())
->AsOutput()
->assert_is_op_output("layer_norm", "Variance");

// Add links for layer_norm op.
layer_norm
->LinksFrom(
{elementwise_out_var, layer_norm_bias_var, layer_norm_scale_var})
.LinksTo(
{layer_norm_out_var, layer_norm_mean_var, layer_norm_variance_var});
}

} // namespace patterns

void PrelnSkipLayerNormFusePass::ApplyImpl(ir::Graph *graph) const {
PADDLE_ENFORCE_NOT_NULL(
graph, platform::errors::PreconditionNotMet("graph should not be null."));
FusePassBase::Init("preln_skip_layernorm_fuse", graph);
int found_subgraph_count = 0;

GraphPatternDetector gpd;
auto *x = gpd.mutable_pattern()
->NewNode("preln_skip_layernorm_fuse/x")
->AsInput()
->assert_is_op_input("elementwise_add", "X")
->assert_var_not_persistable();
auto *y = gpd.mutable_pattern()
->NewNode("preln_skip_layernorm_fuse/y")
->AsInput()
->assert_is_op_input("elementwise_add", "Y")
->assert_var_not_persistable();
patterns::PrelnSkipLayerNorm fused_pattern(gpd.mutable_pattern(),
"preln_skip_layernorm_fuse");
fused_pattern(x, y);

auto handler = [&](const GraphPatternDetector::subgraph_t &subgraph,
Graph *graph) {
if (subgraph.count(x) <= 0 || subgraph.count(y) <= 0) {
LOG(WARNING) << "The subgraph is empty.";
return;
}

if (!IsCompat(subgraph, graph)) {
LOG(WARNING) << "preln_skip_layernorm pass in op compat failed.";
return;
}

VLOG(4) << "handle PrelnSkipLayerNorm fuse";
GET_IR_NODE_FROM_SUBGRAPH(elementwise, elementwise, fused_pattern);
GET_IR_NODE_FROM_SUBGRAPH(elementwise_out, elementwise_out, fused_pattern);
GET_IR_NODE_FROM_SUBGRAPH(layer_norm, layer_norm, fused_pattern);
GET_IR_NODE_FROM_SUBGRAPH(layer_norm_bias, layer_norm_bias, fused_pattern);
GET_IR_NODE_FROM_SUBGRAPH(layer_norm_scale, layer_norm_scale,
fused_pattern);
GET_IR_NODE_FROM_SUBGRAPH(layer_norm_out, layer_norm_out, fused_pattern);
GET_IR_NODE_FROM_SUBGRAPH(layer_norm_mean, layer_norm_mean, fused_pattern);
GET_IR_NODE_FROM_SUBGRAPH(layer_norm_variance, layer_norm_variance,
fused_pattern);

std::unordered_set<const Node *> del_node_set;

// Create an PrelnSkipLayerNorm op node
OpDesc new_desc;
new_desc.SetType("preln_skip_layernorm");

// inputs
new_desc.SetInput("X", {subgraph.at(x)->Name()});
new_desc.SetInput("Y", {subgraph.at(y)->Name()});
new_desc.SetInput("Scale", {layer_norm_scale->Name()});
new_desc.SetInput("Bias", {layer_norm_bias->Name()});

if (elementwise->Op()->HasAttr("out_threshold") &&
layer_norm->Op()->HasAttr("out_threshold")) {
new_desc.SetAttr("enable_int8", true);
new_desc.SetAttr("out_0_threshold",
layer_norm->Op()->GetAttr("out_threshold"));
new_desc.SetAttr("out_1_threshold",
elementwise->Op()->GetAttr("out_threshold"));
}

// outputs
new_desc.SetOutput("Out_0", {layer_norm_out->Name()});
new_desc.SetOutput("Out_1", {elementwise_out->Name()});

// attrs
new_desc.SetAttr("epsilon", layer_norm->Op()->GetAttr("epsilon"));
new_desc.SetAttr("begin_norm_axis",
layer_norm->Op()->GetAttr("begin_norm_axis"));

auto fused_node = graph->CreateOpNode(&new_desc); // OpDesc will be copied.

del_node_set.insert(elementwise);
del_node_set.insert(layer_norm);
del_node_set.insert(layer_norm_mean);
del_node_set.insert(layer_norm_variance);
GraphSafeRemoveNodes(graph, del_node_set);

IR_NODE_LINK_TO(subgraph.at(x), fused_node);
IR_NODE_LINK_TO(subgraph.at(y), fused_node);
IR_NODE_LINK_TO(layer_norm_scale, fused_node);
IR_NODE_LINK_TO(layer_norm_bias, fused_node);
IR_NODE_LINK_TO(fused_node, layer_norm_out);
IR_NODE_LINK_TO(fused_node, elementwise_out);

found_subgraph_count++;
};

gpd(graph, handler);
AddStatis(found_subgraph_count);
}

} // namespace ir
} // namespace framework
} // namespace paddle

REGISTER_PASS(preln_skip_layernorm_fuse_pass,
paddle::framework::ir::PrelnSkipLayerNormFusePass);
REGISTER_PASS_CAPABILITY(preln_skip_layernorm_fuse_pass)
.AddCombination(
paddle::framework::compatible::OpVersionComparatorCombination()
.LE("elementwise_add", 1)
.EQ("layer_norm", 0));
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