1 | /* Copyright 2015 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/core/framework/log_memory.h" |
17 | |
18 | #include "tensorflow/core/framework/log_memory.pb.h" |
19 | |
20 | namespace tensorflow { |
21 | |
22 | const string LogMemory::kLogMemoryLabel = "__LOG_MEMORY__" ; |
23 | |
24 | bool LogMemory::IsEnabled() { return VLOG_IS_ON(2); } |
25 | |
26 | namespace { |
27 | |
28 | // Write the proto entry to LOG(INFO). |
29 | template <typename T> |
30 | void OutputToLog(const T& proto) { |
31 | string type_name = proto.GetTypeName(); |
32 | const size_t index = type_name.find_last_of('.'); |
33 | if (index != string::npos) type_name = type_name.substr(index + 1); |
34 | LOG(INFO) << LogMemory::kLogMemoryLabel << " " << type_name << " { " |
35 | << proto.ShortDebugString() << " }" ; |
36 | } |
37 | |
38 | } // namespace |
39 | |
40 | void LogMemory::RecordStep(const int64_t step_id, const string& handle) { |
41 | MemoryLogStep step; |
42 | step.set_step_id(step_id); |
43 | step.set_handle(handle); |
44 | OutputToLog(step); |
45 | } |
46 | |
47 | void LogMemory::RecordTensorAllocation(const string& kernel_name, |
48 | const int64_t step_id, |
49 | const Tensor& tensor) { |
50 | MemoryLogTensorAllocation allocation; |
51 | allocation.set_step_id(step_id); |
52 | allocation.set_kernel_name(kernel_name); |
53 | tensor.FillDescription(allocation.mutable_tensor()); |
54 | OutputToLog(allocation); |
55 | } |
56 | |
57 | void LogMemory::RecordTensorDeallocation(const int64_t allocation_id, |
58 | const string& allocator_name) { |
59 | MemoryLogTensorDeallocation deallocation; |
60 | deallocation.set_allocation_id(allocation_id); |
61 | deallocation.set_allocator_name(allocator_name); |
62 | OutputToLog(deallocation); |
63 | } |
64 | |
65 | void LogMemory::RecordTensorOutput(const string& kernel_name, |
66 | const int64_t step_id, const int index, |
67 | const Tensor& tensor) { |
68 | MemoryLogTensorOutput output; |
69 | output.set_step_id(step_id); |
70 | output.set_kernel_name(kernel_name); |
71 | output.set_index(index); |
72 | tensor.FillDescription(output.mutable_tensor()); |
73 | OutputToLog(output); |
74 | } |
75 | |
76 | void LogMemory::RecordRawAllocation(const string& operation, |
77 | const int64_t step_id, size_t num_bytes, |
78 | void* ptr, Allocator* allocator) { |
79 | MemoryLogRawAllocation allocation; |
80 | allocation.set_step_id(step_id); |
81 | allocation.set_operation(operation); |
82 | allocation.set_num_bytes(static_cast<int64_t>(num_bytes)); |
83 | allocation.set_ptr(reinterpret_cast<uintptr_t>(ptr)); |
84 | allocation.set_allocation_id(allocator->AllocationId(ptr)); |
85 | allocation.set_allocator_name(allocator->Name()); |
86 | OutputToLog(allocation); |
87 | } |
88 | |
89 | void LogMemory::RecordRawDeallocation(const string& operation, |
90 | const int64_t step_id, void* ptr, |
91 | Allocator* allocator, bool deferred) { |
92 | MemoryLogRawDeallocation deallocation; |
93 | deallocation.set_step_id(step_id); |
94 | deallocation.set_operation(operation); |
95 | deallocation.set_allocation_id(allocator->AllocationId(ptr)); |
96 | deallocation.set_allocator_name(allocator->Name()); |
97 | deallocation.set_deferred(deferred); |
98 | OutputToLog(deallocation); |
99 | } |
100 | |
101 | } // namespace tensorflow |
102 | |