File: pattern_net_transform.cc

package info (click to toggle)
pytorch 1.13.1%2Bdfsg-4
  • links: PTS, VCS
  • area: main
  • in suites: bookworm
  • size: 139,252 kB
  • sloc: cpp: 1,100,274; python: 706,454; ansic: 83,052; asm: 7,618; java: 3,273; sh: 2,841; javascript: 612; makefile: 323; xml: 269; ruby: 185; yacc: 144; objc: 68; lex: 44
file content (266 lines) | stat: -rw-r--r-- 8,382 bytes parent folder | download
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
#include "caffe2/transforms/pattern_net_transform.h"

#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/net.h"
#include "caffe2/proto/caffe2_pb.h"

#include <c10/util/irange.h>

namespace caffe2 {

// First, single source traverse through the netdef.
// This ensures all newly ordered are reachable from their prefix subset
// Outputs a permutation of the operators.
std::vector<int> PatternNetTransform::GetPatternTraversalOrder(
    const transform::Graph& graph) {
  std::vector<bool> visited(graph.size(), false);
  std::vector<int> ordered_ops;
  std::queue<int> q;
  if (graph.size() > 0) {
    q.push(0);
    ordered_ops.push_back(0);
    visited[0] = true;
  }
  while (!q.empty()) {
    int idx = q.front();
    q.pop();
    for (const auto& edge : graph.node(idx).children) {
      int x = edge.first;
      if (!visited[x]) {
        q.push(x);
        ordered_ops.push_back(x);
        visited[x] = true;
      }
    }
    for (const auto& edge : graph.node(idx).parents) {
      int x = edge.first;
      if (!visited[x]) {
        q.push(x);
        ordered_ops.push_back(x);
        visited[x] = true;
      }
    }
  }
  CAFFE_ENFORCE(
      ordered_ops.size() == graph.size(), "Pattern graph must be connected.");
  return ordered_ops;
}

bool compare_ops(
    const OperatorDef& p_op,
    const OperatorDef& g_op,
    bool arg_match) {
  // must specify a type for pattern operators
  CAFFE_ENFORCE(
      p_op.has_type(), "Types must be specified for all pattern operators.");
  if (!MatchStrings(p_op.type(), g_op.type())) {
    return false;
  }
  // ensure number of inputs are the same
  if (p_op.input().size() != g_op.input().size()) {
    return false;
  }

  // ensure number of outputs are the same
  if (p_op.output().size() != g_op.output().size()) {
    return false;
  }

  if (p_op.has_device_option()) {
    if (!g_op.has_device_option() ||
        p_op.device_option().device_type() !=
            g_op.device_option().device_type()) {
      return false;
    }
  }

  // make sure engine is the same (if specified in pattern)
  if (p_op.has_engine() && !MatchStrings(p_op.engine(), g_op.engine())) {
    return false;
  }
  // If argument_match is specified, make sure those are the same.
  if (arg_match) {
    if (!MatchArguments(p_op, g_op)) {
      return false;
    }
  }
  return true;
}

// g.node(subgraph[i]) should match p_.node(ordered_ops_[i])
// g.node(g_idx) should match p_.node(p_idx)
bool PatternNetTransform::PatternRule(
    const transform::Graph& g,
    const std::vector<int>& subgraph,
    int g_idx) {
  if (subgraph.size() >= ordered_ops_.size()) {
    return false;
  }
  int p_idx = ordered_ops_[subgraph.size()];

  if (!compare_ops(p_.node(p_idx).op, g.node(g_idx).op, argument_match_)) {
    return false;
  }

  // Let's say ordered_ops_ is [0, 2, 1], with 0 -> 2 being an edge
  // When we try to match onto the second element, let's say our
  // subgraph so far is [4], with it trying to become [4, 5].
  // Then, we need to show that since 0 -> 2 is an edge is ordered_ops_,
  // 4 must be a direct parent of 5 in the subgraph
  // (the indices must match).
  // Similarly, assume there is an edge from 1 -> 2 in p_.
  // When trying to match [4, 5] to [4, 5, 7], we must verify that
  // there exists an edge from 7 -> 5 in G.
  for (const auto& edge : p_.node(p_idx).parents) {
    int parent = edge.first;
    // g_idx doesn't have parent in subgraph that p_[p_idx] has
    // inverse_ops_ gets the index of a p_idx inside of ordered_ops_.
    // NOLINTNEXTLINE(clang-diagnostic-sign-compare)
    if (inverse_ops_[parent] < subgraph.size() &&
        g.node(g_idx).parents.count(subgraph[inverse_ops_[parent]]) == 0) {
      return false;
    }
  }

  for (const auto& edge : p_.node(p_idx).children) {
    int child = edge.first;
    // NOLINTNEXTLINE(clang-diagnostic-sign-compare)
    if (inverse_ops_[child] < subgraph.size() &&
        g.node(g_idx).children.count(subgraph[inverse_ops_[child]]) == 0) {
      return false;
    }
  }
  return true;
}

bool PatternNetTransform::ValidatorRule(
    const transform::Graph& /*g*/,
    const std::vector<int>& subgraph) {
  // Due to strict PatternRule, it suffices to simply check for size
  return subgraph.size() == p_.size();
}

bool PatternNetTransform::ReplaceRule(
    const std::vector<int>& match,
    transform::Graph* g_ptr) {
  CHECK(g_ptr);
  auto& g = *g_ptr;

  ssa_id_++;

  // Map of PatternNet blob name to Matched blob name.
  // Figures out how to rename the pattern_net to make the replacement fit.
  std::unordered_map<string, string> external_renaming;

  // Figure out blob renamings
  for (const auto i : c10::irange(match.size())) {
    int g_idx = match[i];
    int p_idx = ordered_ops_[i];
    for (int j = 0; j < p_.node(p_idx).op.input().size(); j++) {
      string p_blob = p_.node(p_idx).op.input(j);
      string g_blob = g.node(g_idx).op.input(j);
      if (p_.external_input().count(p_blob)) {
        external_renaming[p_blob] = g_blob;
      }
    }
    for (int j = 0; j < p_.node(p_idx).op.output().size(); j++) {
      string p_blob = p_.node(p_idx).op.output(j);
      string g_blob = g.node(g_idx).op.output(j);
      if (p_.external_output().count(p_blob)) {
        external_renaming[p_blob] = g_blob;
      }
    }
  }

  auto input_list = g.GetSubgraphInput(match);
  auto output_list = g.GetSubgraphOutput(match);

  g.DeactivateSubgraph(match);

  int offset = g.size();

  g.resize_nodes(offset + r_.size());

  // Append all the new operators.
  for (const auto i : c10::irange(r_.size())) {
    // NOLINTNEXTLINE(cppcoreguidelines-narrowing-conversions,bugprone-narrowing-conversions)
    int new_node_idx = offset + i;

    OperatorDef new_op = r_.node(i).op;

    new_op.clear_input();
    new_op.clear_output();
    // Stitch Input from external graph into replaced subgraph
    for (const auto& blob : r_.node(i).op.input()) {
      if (external_renaming.count(blob)) {
        string new_blob = external_renaming[blob];
        new_op.add_input(new_blob);

        // binary searches for new_blob amongst input list.
        auto it = std::lower_bound(
            input_list.begin(), input_list.end(), std::make_pair(new_blob, -1));

        // if the input came from the graph (instead of G's external input)
        for (; it < input_list.end() && it->first == new_blob; it++) {
          int parent = it->second;
          g.node(parent).children[new_node_idx].push_back(new_blob);
          g.node(new_node_idx).parents[parent].push_back(new_blob);
        }
      } else {
        new_op.add_input(TransformBlobWrapper(blob));
      }
    }
    // Stitch Output from replaced subgraph to external graph.
    for (const auto& blob : r_.node(i).op.output()) {
      if (external_renaming.count(blob)) {
        string new_blob = external_renaming[blob];
        new_op.add_output(new_blob);

        // binary searches for new_blob amongst input list.
        auto it = std::lower_bound(
            output_list.begin(),
            output_list.end(),
            std::make_pair(new_blob, -1));

        // if the output goes to the graph (instead of G's external output)
        for (; it < output_list.end() && it->first == new_blob; it++) {
          int child = it->second;
          g.node(child).parents[new_node_idx].push_back(new_blob);
          g.node(new_node_idx).children[child].push_back(new_blob);
        }
      } else {
        new_op.add_output(TransformBlobWrapper(blob));
      }
    }

    // Connect all internal edges within replace graph
    for (const auto& edge : r_.node(i).parents) {
      int parent = edge.first;
      int new_node_parent = offset + parent;
      const auto& blobs = edge.second;
      for (const string& blob : blobs) {
        g.node(new_node_idx)
            .parents[new_node_parent]
            .push_back(TransformBlobWrapper(blob));
      }
    }

    for (const auto& edge : r_.node(i).children) {
      int child = edge.first;
      int new_node_child = offset + child;
      const auto& blobs = edge.second;
      for (const string& blob : blobs) {
        g.node(offset + i)
            .children[new_node_child]
            .push_back(TransformBlobWrapper(blob));
      }
    }

    g.node(new_node_idx).op = new_op;
    g.node(new_node_idx).active = true;
  }
  return true;
}

} // namespace caffe2