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
SetDeviceOrdinalAttributeForNode(Node * node,int device_ordinal)29 Status SetDeviceOrdinalAttributeForNode(Node* node, int device_ordinal) {
30 if (!HasNodeAttr(node->def(), kXlaHasHostTransferAttrName)) {
31 return errors::InvalidArgument("Node ", node->DebugString(),
32 " does not have attribute ",
33 kXlaHasHostTransferAttrName);
34 }
35
36 if (node->type_string() == "_XlaRecvAtHost" ||
37 node->type_string() == "_XlaSendFromHost") {
38 node->ClearAttr("device_ordinal");
39 node->AddAttr("device_ordinal", device_ordinal);
40 } else if (node->type_string() == "If") {
41 AttrValue device_ordinal_value;
42 device_ordinal_value.set_i(device_ordinal);
43 for (const string& attr_name :
44 std::vector<string>{"then_branch", "else_branch"}) {
45 NameAttrList branch_func;
46 TF_RETURN_IF_ERROR(GetNodeAttr(node->attrs(), attr_name, &branch_func));
47 (*branch_func.mutable_attr())["device_ordinal"] = device_ordinal_value;
48 node->ClearAttr(attr_name);
49 node->AddAttr(attr_name, branch_func);
50 }
51 } else if (node->type_string() == "While") {
52 AttrValue device_ordinal_value;
53 device_ordinal_value.set_i(device_ordinal);
54 for (const string& attr_name : std::vector<string>{"cond", "body"}) {
55 NameAttrList branch_func;
56 TF_RETURN_IF_ERROR(GetNodeAttr(node->attrs(), attr_name, &branch_func));
57 (*branch_func.mutable_attr())["device_ordinal"] = device_ordinal_value;
58 node->ClearAttr(attr_name);
59 node->AddAttr(attr_name, branch_func);
60 }
61 } else if (HasNodeAttr(node->def(), "device_ordinal")) {
62 // Function call node containing outside compilation.
63 node->ClearAttr("device_ordinal");
64 node->AddAttr("device_ordinal", device_ordinal);
65 } else {
66 return errors::Internal("Unknown node type to set 'device_ordinal': ",
67 node->DebugString());
68 }
69 return Status::OK();
70 }
71
CalculateTokenInputsForOutputToken(const Graph & g)72 std::set<std::string> CalculateTokenInputsForOutputToken(const Graph& g) {
73 std::set<std::string> results;
74 Node* first_side_effecting_node_on_path = nullptr;
75 ReverseDFS(g,
76 [&](Node* n) {
77 std::vector<string> token_input_nodes;
78 if (!GetNodeAttr(n->attrs(), kXlaTokenInputNodesAttrName,
79 &token_input_nodes)
80 .ok() ||
81 token_input_nodes.empty()) {
82 return;
83 }
84
85 if (first_side_effecting_node_on_path != nullptr) {
86 return;
87 }
88
89 first_side_effecting_node_on_path = n;
90 results.insert(n->name());
91 },
92 [&](Node* n) {
93 if (first_side_effecting_node_on_path == n) {
94 first_side_effecting_node_on_path = nullptr;
95 }
96 },
97 NodeComparatorName());
98 return results;
99 }
100
HasSideEffectingNodes(const Graph & g)101 bool HasSideEffectingNodes(const Graph& g) {
102 for (Node* n : g.nodes()) {
103 std::vector<string> token_input_nodes;
104 if (GetNodeAttr(n->attrs(), kXlaTokenInputNodesAttrName, &token_input_nodes)
105 .ok() &&
106 !token_input_nodes.empty()) {
107 return true;
108 }
109 }
110 return false;
111 }
112
ParseHostComputeCoreList(absl::Span<const string> list_from_attr,std::map<string,int> * host_compute_core)113 Status ParseHostComputeCoreList(absl::Span<const string> list_from_attr,
114 std::map<string, int>* host_compute_core) {
115 for (const auto& hc_core : list_from_attr) {
116 std::vector<string> parts = str_util::Split(hc_core, ":");
117 if (parts.size() != 2) {
118 return errors::InvalidArgument(
119 "Malformed host_compute_core entry ", hc_core,
120 " should be <cluster_name>:<core_number>.");
121 }
122 int core;
123 if (!absl::numbers_internal::safe_strto32_base(parts[1], &core, 10)) {
124 return errors::InvalidArgument("Malformed host_compute_core entry ",
125 hc_core,
126 " part after ':' should be an integer.");
127 }
128 if (host_compute_core->find(parts[0]) != host_compute_core->end()) {
129 return errors::InvalidArgument(
130 "Duplicate host_compute_core entry for cluster ", parts[0]);
131 }
132 (*host_compute_core)[parts[0]] = core;
133 }
134 return Status::OK();
135 }
136
137 } // namespace tensorflow
138