forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
test_utils.cc
137 lines (122 loc) · 3.83 KB
/
test_utils.cc
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
#include "caffe2/core/tensor.h"
#include "caffe2/core/workspace.h"
#include "test_utils.h"
namespace {
template <typename T>
void assertTensorEqualsWithType(
const caffe2::TensorCPU& tensor1,
const caffe2::TensorCPU& tensor2,
float /* unused */) {
CAFFE_ENFORCE_EQ(tensor1.sizes(), tensor2.sizes());
for (auto idx = 0; idx < tensor1.numel(); ++idx) {
CAFFE_ENFORCE_EQ(tensor1.data<T>()[idx], tensor2.data<T>()[idx]);
}
}
template <>
void assertTensorEqualsWithType<float>(
const caffe2::TensorCPU& tensor1,
const caffe2::TensorCPU& tensor2,
float eps) {
CAFFE_ENFORCE_EQ(tensor1.sizes(), tensor2.sizes());
for (auto idx = 0; idx < tensor1.numel(); ++idx) {
CAFFE_ENFORCE_LT(
fabs(tensor1.data<float>()[idx] - tensor2.data<float>()[idx]),
eps,
"Mismatch at index ",
idx,
" exceeds threshold of ",
eps);
}
}
} // namespace
namespace caffe2 {
namespace testing {
// Asserts that two float values are close within epsilon.
void assertNear(float value1, float value2, float epsilon) {
// These two enforces will give good debug messages.
CAFFE_ENFORCE_LE(value1, value2 + epsilon);
CAFFE_ENFORCE_GE(value1, value2 - epsilon);
}
void assertTensorEquals(
const TensorCPU& tensor1,
const TensorCPU& tensor2,
float eps) {
CAFFE_ENFORCE_EQ(tensor1.sizes(), tensor2.sizes());
if (tensor1.IsType<float>()) {
CAFFE_ENFORCE(tensor2.IsType<float>());
assertTensorEqualsWithType<float>(tensor1, tensor2, eps);
} else if (tensor1.IsType<int>()) {
CAFFE_ENFORCE(tensor2.IsType<int>());
assertTensorEqualsWithType<int>(tensor1, tensor2, eps);
} else if (tensor1.IsType<int64_t>()) {
CAFFE_ENFORCE(tensor2.IsType<int64_t>());
assertTensorEqualsWithType<int64_t>(tensor1, tensor2, eps);
}
// Add more types if needed.
}
void assertTensorListEquals(
const std::vector<std::string>& tensorNames,
const Workspace& workspace1,
const Workspace& workspace2) {
for (const std::string& tensorName : tensorNames) {
CAFFE_ENFORCE(workspace1.HasBlob(tensorName));
CAFFE_ENFORCE(workspace2.HasBlob(tensorName));
auto& tensor1 = getTensor(workspace1, tensorName);
auto& tensor2 = getTensor(workspace2, tensorName);
assertTensorEquals(tensor1, tensor2);
}
}
const caffe2::Tensor& getTensor(
const caffe2::Workspace& workspace,
const std::string& name) {
CAFFE_ENFORCE(workspace.HasBlob(name));
return workspace.GetBlob(name)->Get<caffe2::Tensor>();
}
caffe2::Tensor* createTensor(
const std::string& name,
caffe2::Workspace* workspace) {
return BlobGetMutableTensor(workspace->CreateBlob(name), caffe2::CPU);
}
caffe2::OperatorDef* createOperator(
const std::string& type,
const std::vector<std::string>& inputs,
const std::vector<std::string>& outputs,
caffe2::NetDef* net) {
auto* op = net->add_op();
op->set_type(type);
for (const auto& in : inputs) {
op->add_input(in);
}
for (const auto& out : outputs) {
op->add_output(out);
}
return op;
}
NetMutator& NetMutator::newOp(
const std::string& type,
const std::vector<std::string>& inputs,
const std::vector<std::string>& outputs) {
lastCreatedOp_ = createOperator(type, inputs, outputs, net_);
return *this;
}
NetMutator& NetMutator::externalInputs(
const std::vector<std::string>& externalInputs) {
for (auto& blob : externalInputs) {
net_->add_external_input(blob);
}
return *this;
}
NetMutator& NetMutator::externalOutputs(
const std::vector<std::string>& externalOutputs) {
for (auto& blob : externalOutputs) {
net_->add_external_output(blob);
}
return *this;
}
NetMutator& NetMutator::setDeviceOptionName(const std::string& name) {
CAFFE_ENFORCE(lastCreatedOp_ != nullptr);
lastCreatedOp_->mutable_device_option()->set_node_name(name);
return *this;
}
} // namespace testing
} // namespace caffe2