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
|
/* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#define EIGEN_USE_THREADS
#include <complex>
#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/kernels/transpose_functor.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/lib/gtl/array_slice.h"
#include "tensorflow/core/lib/gtl/inlined_vector.h"
typedef Eigen::ThreadPoolDevice CPUDevice;
namespace tensorflow {
namespace {
template <typename T, bool conjugate>
void TransposeSimple(const CPUDevice& device, const Tensor& in,
const gtl::ArraySlice<int32> perm, Tensor* out) {
const int ndims = in.dims();
gtl::InlinedVector<int64, 8> in_strides = ComputeStride<int64>(in.shape());
gtl::InlinedVector<int64, 8> out_strides = ComputeStride<int64>(out->shape());
const T* p = reinterpret_cast<const T*>(in.tensor_data().data());
T* q = reinterpret_cast<T*>(const_cast<char*>((out->tensor_data().data())));
auto transpose_fn = [=, &in_strides, &out_strides, &perm](int64 begin,
int64 end) {
for (int64 o_idx = begin; o_idx < end; ++o_idx) {
int64 i_idx = 0;
int64 t = o_idx;
for (int i = 0; i < ndims; ++i) {
const int64 ratio = t / out_strides[i];
t -= ratio * out_strides[i];
i_idx += ratio * in_strides[perm[i]];
}
if (conjugate) {
q[o_idx] = Eigen::numext::conj(p[i_idx]);
} else {
q[o_idx] = p[i_idx];
}
}
};
double cycles_per_element =
(conjugate ? 1 : 0) + ndims * (Eigen::TensorOpCost::DivCost<int64>() +
2 * Eigen::TensorOpCost::MulCost<int64>() +
2 * Eigen::TensorOpCost::AddCost<int64>());
Eigen::TensorOpCost cost(/*bytes_loaded=*/sizeof(T),
/*bytes_stored=*/sizeof(T), cycles_per_element);
device.parallelFor(in.NumElements(), cost, std::move(transpose_fn));
}
} // namespace
template <typename T, bool conjugate>
struct Transpose<CPUDevice, T, conjugate> {
static void run(const CPUDevice& d, const Tensor& in,
const gtl::ArraySlice<int32> perm, Tensor* out) {
switch (in.dims()) {
case 2:
internal::TransposeUsingEigen<CPUDevice, T, 2>(d, in, perm, conjugate,
out);
break;
case 3:
internal::TransposeUsingEigen<CPUDevice, T, 3>(d, in, perm, conjugate,
out);
break;
case 4:
internal::TransposeUsingEigen<CPUDevice, T, 4>(d, in, perm, conjugate,
out);
break;
case 5:
internal::TransposeUsingEigen<CPUDevice, T, 5>(d, in, perm, conjugate,
out);
break;
case 6:
internal::TransposeUsingEigen<CPUDevice, T, 6>(d, in, perm, conjugate,
out);
break;
case 7:
internal::TransposeUsingEigen<CPUDevice, T, 7>(d, in, perm, conjugate,
out);
break;
case 8:
internal::TransposeUsingEigen<CPUDevice, T, 8>(d, in, perm, conjugate,
out);
break;
default:
TransposeSimple<T, conjugate>(d, in, perm, out);
break;
}
}
};
#define INSTANTIATE(DEVICE) \
template <> \
Status DoTranspose(const DEVICE& device, const Tensor& in, \
const gtl::ArraySlice<int32> perm, Tensor* out) { \
return internal::DoTransposeImpl(device, in, perm, /*conjugate=*/false, \
out); \
} \
template <> \
Status DoConjugateTranspose(const DEVICE& device, const Tensor& in, \
const gtl::ArraySlice<int32> perm, \
Tensor* out) { \
return internal::DoTransposeImpl(device, in, perm, /*conjugate=*/true, \
out); \
} \
template <> \
Status DoMatrixTranspose(const DEVICE& device, const Tensor& in, \
Tensor* out) { \
return internal::DoMatrixTransposeImpl(device, in, /*conjugate=*/false, \
out); \
} \
template <> \
Status DoConjugateMatrixTranspose(const DEVICE& device, const Tensor& in, \
Tensor* out) { \
return internal::DoMatrixTransposeImpl(device, in, /*conjugate=*/true, \
out); \
}
INSTANTIATE(CPUDevice)
#ifdef TENSORFLOW_USE_SYCL
typedef Eigen::SyclDevice SYCLDevice;
namespace internal {
template <typename T>
void TransposeSYCL(const SYCLDevice& d, const Tensor& in,
const gtl::ArraySlice<int32> perm, bool conjugate,
Tensor* out) {
switch (in.dims()) {
case 1:
TransposeUsingEigen<SYCLDevice, T, 1>(d, in, perm, conjugate, out);
break;
case 2:
TransposeUsingEigen<SYCLDevice, T, 2>(d, in, perm, conjugate, out);
break;
case 3:
TransposeUsingEigen<SYCLDevice, T, 3>(d, in, perm, conjugate, out);
break;
case 4:
TransposeUsingEigen<SYCLDevice, T, 4>(d, in, perm, conjugate, out);
break;
case 5:
TransposeUsingEigen<SYCLDevice, T, 5>(d, in, perm, conjugate, out);
break;
case 6:
TransposeUsingEigen<SYCLDevice, T, 6>(d, in, perm, conjugate, out);
break;
case 7:
TransposeUsingEigen<SYCLDevice, T, 7>(d, in, perm, conjugate, out);
break;
case 8:
TransposeUsingEigen<SYCLDevice, T, 8>(d, in, perm, conjugate, out);
break;
default:
LOG(FATAL) << "Unsupported TransposeUsingEigen for: " << in.dims();
break;
}
}
} // namespace internal
template <typename T, bool conjugate>
struct Transpose<SYCLDevice, T, conjugate> {
static void run(const SYCLDevice& d, const Tensor& in,
const gtl::ArraySlice<int32> perm, Tensor* out) {
internal::TransposeSycl(d, in, perm, conjugate, out);
}
};
template <bool conjugate>
struct Transpose<SYCLDevice, string, conjugate> {
static void run(const SYCLDevice& d, const Tensor& in,
const gtl::ArraySlice<int32> perm, Tensor* out) {
LOG(FATAL) << "DT_STRING not supported on SYCL device.";
}
};
// Explicit instantiation.
template struct Transpose<SYCLDevice, string, false>;
INSTANTIATE(SYCLDevice)
#undef INSTANTIATE
#endif // TENSORFLOW_USE_SYCL
} // namespace tensorflow
|
