1 /* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
2
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15
16 #include "tensorflow/compiler/tf2xla/side_effect_util.h"
17
18 #include "absl/strings/numbers.h"
19 #include "tensorflow/core/graph/algorithm.h"
20
21 namespace tensorflow {
22
23 const char kXlaTokenInputNodesAttrName[] = "_xla_token_input_nodes";
24
25 const char kXlaTokenArgNodeName[] = "_xla_token_arg_node";
26
27 const char kXlaHasHostTransferAttrName[] = "_xla_has_host_transfer";
28
29 const char kXlaReplicaIdAttrName[] = "_xla_replica_id";
30
31 const char kXlaIsPlaceholderForTailOcAttrName[] =
32 "_xla_is_placeholder_for_tail_oc";
33
34 const char kXlaOriginalOutsideCompilationNodeName[] =
35 "_xla_original_oc_node_name";
36
SetDeviceOrdinalAttributeForNode(Node * node,int device_ordinal)37 Status SetDeviceOrdinalAttributeForNode(Node* node, int device_ordinal) {
38 if (!HasNodeAttr(node->def(), kXlaHasHostTransferAttrName)) {
39 return errors::InvalidArgument("Node ", node->DebugString(),
40 " does not have attribute ",
41 kXlaHasHostTransferAttrName);
42 }
43
44 if (node->type_string() == "_XlaRecvAtHost" ||
45 node->type_string() == "_XlaSendFromHost") {
46 node->ClearAttr("device_ordinal");
47 node->AddAttr("device_ordinal", device_ordinal);
48 } else if (node->IsIfNode()) {
49 AttrValue device_ordinal_value;
50 device_ordinal_value.set_i(device_ordinal);
51 for (const string& attr_name :
52 std::vector<string>{"then_branch", "else_branch"}) {
53 NameAttrList branch_func;
54 TF_RETURN_IF_ERROR(GetNodeAttr(node->attrs(), attr_name, &branch_func));
55 (*branch_func.mutable_attr())["_device_ordinal"] = device_ordinal_value;
56 node->ClearAttr(attr_name);
57 node->AddAttr(attr_name, branch_func);
58 }
59 } else if (node->IsWhileNode()) {
60 AttrValue device_ordinal_value;
61 device_ordinal_value.set_i(device_ordinal);
62 for (const string& attr_name : std::vector<string>{"cond", "body"}) {
63 NameAttrList branch_func;
64 TF_RETURN_IF_ERROR(GetNodeAttr(node->attrs(), attr_name, &branch_func));
65 (*branch_func.mutable_attr())["_device_ordinal"] = device_ordinal_value;
66 node->ClearAttr(attr_name);
67 node->AddAttr(attr_name, branch_func);
68 }
69 } else if (HasNodeAttr(node->def(), "_device_ordinal")) {
70 // Function call node containing outside compilation.
71 node->ClearAttr("_device_ordinal");
72 node->AddAttr("_device_ordinal", device_ordinal);
73 } else {
74 return errors::Internal("Unknown node type to set 'device_ordinal': ",
75 node->DebugString());
76 }
77 return Status::OK();
78 }
79
CalculateTokenInputsForOutputToken(const Graph & g)80 std::set<std::string> CalculateTokenInputsForOutputToken(const Graph& g) {
81 std::set<std::string> results;
82 Node* first_side_effecting_node_on_path = nullptr;
83 ReverseDFS(g,
84 [&](Node* n) {
85 std::vector<string> token_input_nodes;
86 if (!GetNodeAttr(n->attrs(), kXlaTokenInputNodesAttrName,
87 &token_input_nodes)
88 .ok() ||
89 token_input_nodes.empty()) {
90 return;
91 }
92
93 if (first_side_effecting_node_on_path != nullptr) {
94 return;
95 }
96
97 first_side_effecting_node_on_path = n;
98 string original_node_name;
99 TF_CHECK_OK(GetNodeAttr(n->def(),
100 kXlaOriginalOutsideCompilationNodeName,
101 &original_node_name));
102 results.insert(original_node_name);
103 },
104 [&](Node* n) {
105 if (first_side_effecting_node_on_path == n) {
106 first_side_effecting_node_on_path = nullptr;
107 }
108 },
109 NodeComparatorName());
110 return results;
111 }
112
HasSideEffectingNodes(const Graph & g)113 bool HasSideEffectingNodes(const Graph& g) {
114 for (Node* n : g.nodes()) {
115 std::vector<string> token_input_nodes;
116 if (GetNodeAttr(n->attrs(), kXlaTokenInputNodesAttrName, &token_input_nodes)
117 .ok() &&
118 !token_input_nodes.empty()) {
119 return true;
120 }
121 }
122 return false;
123 }
124
ParseHostComputeCoreList(absl::Span<const string> list_from_attr,std::map<string,int> * host_compute_core)125 Status ParseHostComputeCoreList(absl::Span<const string> list_from_attr,
126 std::map<string, int>* host_compute_core) {
127 for (const auto& hc_core : list_from_attr) {
128 std::vector<string> parts = str_util::Split(hc_core, ":");
129 if (parts.size() != 2) {
130 return errors::InvalidArgument(
131 "Malformed host_compute_core entry ", hc_core,
132 " should be <cluster_name>:<core_number>.");
133 }
134 int core;
135 if (!absl::numbers_internal::safe_strto32_base(parts[1], &core, 10)) {
136 return errors::InvalidArgument("Malformed host_compute_core entry ",
137 hc_core,
138 " part after ':' should be an integer.");
139 }
140 if (host_compute_core->find(parts[0]) != host_compute_core->end()) {
141 return errors::InvalidArgument(
142 "Duplicate host_compute_core entry for cluster ", parts[0]);
143 }
144 (*host_compute_core)[parts[0]] = core;
145 }
146 return Status::OK();
147 }
148
149 } // namespace tensorflow
150