1// This file is MACHINE GENERATED! Do not edit.
2
3
4#include "tensorflow/cc/ops/const_op.h"
5#include "tensorflow/cc/ops/random_ops.h"
6
7namespace tensorflow {
8namespace ops {
9
10Multinomial::Multinomial(const ::tensorflow::Scope& scope, ::tensorflow::Input
11 logits, ::tensorflow::Input num_samples, const
12 Multinomial::Attrs& attrs) {
13 if (!scope.ok()) return;
14 auto _logits = ::tensorflow::ops::AsNodeOut(scope, logits);
15 if (!scope.ok()) return;
16 auto _num_samples = ::tensorflow::ops::AsNodeOut(scope, num_samples);
17 if (!scope.ok()) return;
18 ::tensorflow::Node* ret;
19 const auto unique_name = scope.GetUniqueNameForOp("Multinomial");
20 auto builder = ::tensorflow::NodeBuilder(unique_name, "Multinomial")
21 .Input(_logits)
22 .Input(_num_samples)
23 .Attr("seed", attrs.seed_)
24 .Attr("seed2", attrs.seed2_)
25 .Attr("output_dtype", attrs.output_dtype_)
26 ;
27 scope.UpdateBuilder(&builder);
28 scope.UpdateStatus(builder.Finalize(scope.graph(), &ret));
29 if (!scope.ok()) return;
30 scope.UpdateStatus(scope.DoShapeInference(ret));
31 this->operation = Operation(ret);
32 this->output = Output(ret, 0);
33}
34
35Multinomial::Multinomial(const ::tensorflow::Scope& scope, ::tensorflow::Input
36 logits, ::tensorflow::Input num_samples)
37 : Multinomial(scope, logits, num_samples, Multinomial::Attrs()) {}
38
39ParameterizedTruncatedNormal::ParameterizedTruncatedNormal(const
40 ::tensorflow::Scope&
41 scope,
42 ::tensorflow::Input
43 shape,
44 ::tensorflow::Input
45 means,
46 ::tensorflow::Input
47 stdevs,
48 ::tensorflow::Input
49 minvals,
50 ::tensorflow::Input
51 maxvals, const
52 ParameterizedTruncatedNormal::Attrs&
53 attrs) {
54 if (!scope.ok()) return;
55 auto _shape = ::tensorflow::ops::AsNodeOut(scope, shape);
56 if (!scope.ok()) return;
57 auto _means = ::tensorflow::ops::AsNodeOut(scope, means);
58 if (!scope.ok()) return;
59 auto _stdevs = ::tensorflow::ops::AsNodeOut(scope, stdevs);
60 if (!scope.ok()) return;
61 auto _minvals = ::tensorflow::ops::AsNodeOut(scope, minvals);
62 if (!scope.ok()) return;
63 auto _maxvals = ::tensorflow::ops::AsNodeOut(scope, maxvals);
64 if (!scope.ok()) return;
65 ::tensorflow::Node* ret;
66 const auto unique_name = scope.GetUniqueNameForOp("ParameterizedTruncatedNormal");
67 auto builder = ::tensorflow::NodeBuilder(unique_name, "ParameterizedTruncatedNormal")
68 .Input(_shape)
69 .Input(_means)
70 .Input(_stdevs)
71 .Input(_minvals)
72 .Input(_maxvals)
73 .Attr("seed", attrs.seed_)
74 .Attr("seed2", attrs.seed2_)
75 ;
76 scope.UpdateBuilder(&builder);
77 scope.UpdateStatus(builder.Finalize(scope.graph(), &ret));
78 if (!scope.ok()) return;
79 scope.UpdateStatus(scope.DoShapeInference(ret));
80 this->operation = Operation(ret);
81 this->output = Output(ret, 0);
82}
83
84ParameterizedTruncatedNormal::ParameterizedTruncatedNormal(const
85 ::tensorflow::Scope&
86 scope,
87 ::tensorflow::Input
88 shape,
89 ::tensorflow::Input
90 means,
91 ::tensorflow::Input
92 stdevs,
93 ::tensorflow::Input
94 minvals,
95 ::tensorflow::Input
96 maxvals)
97 : ParameterizedTruncatedNormal(scope, shape, means, stdevs, minvals, maxvals, ParameterizedTruncatedNormal::Attrs()) {}
98
99RandomGamma::RandomGamma(const ::tensorflow::Scope& scope, ::tensorflow::Input
100 shape, ::tensorflow::Input alpha, const
101 RandomGamma::Attrs& attrs) {
102 if (!scope.ok()) return;
103 auto _shape = ::tensorflow::ops::AsNodeOut(scope, shape);
104 if (!scope.ok()) return;
105 auto _alpha = ::tensorflow::ops::AsNodeOut(scope, alpha);
106 if (!scope.ok()) return;
107 ::tensorflow::Node* ret;
108 const auto unique_name = scope.GetUniqueNameForOp("RandomGamma");
109 auto builder = ::tensorflow::NodeBuilder(unique_name, "RandomGamma")
110 .Input(_shape)
111 .Input(_alpha)
112 .Attr("seed", attrs.seed_)
113 .Attr("seed2", attrs.seed2_)
114 ;
115 scope.UpdateBuilder(&builder);
116 scope.UpdateStatus(builder.Finalize(scope.graph(), &ret));
117 if (!scope.ok()) return;
118 scope.UpdateStatus(scope.DoShapeInference(ret));
119 this->operation = Operation(ret);
120 this->output = Output(ret, 0);
121}
122
123RandomGamma::RandomGamma(const ::tensorflow::Scope& scope, ::tensorflow::Input
124 shape, ::tensorflow::Input alpha)
125 : RandomGamma(scope, shape, alpha, RandomGamma::Attrs()) {}
126
127RandomPoissonV2::RandomPoissonV2(const ::tensorflow::Scope& scope,
128 ::tensorflow::Input shape, ::tensorflow::Input
129 rate, const RandomPoissonV2::Attrs& attrs) {
130 if (!scope.ok()) return;
131 auto _shape = ::tensorflow::ops::AsNodeOut(scope, shape);
132 if (!scope.ok()) return;
133 auto _rate = ::tensorflow::ops::AsNodeOut(scope, rate);
134 if (!scope.ok()) return;
135 ::tensorflow::Node* ret;
136 const auto unique_name = scope.GetUniqueNameForOp("RandomPoissonV2");
137 auto builder = ::tensorflow::NodeBuilder(unique_name, "RandomPoissonV2")
138 .Input(_shape)
139 .Input(_rate)
140 .Attr("seed", attrs.seed_)
141 .Attr("seed2", attrs.seed2_)
142 .Attr("dtype", attrs.dtype_)
143 ;
144 scope.UpdateBuilder(&builder);
145 scope.UpdateStatus(builder.Finalize(scope.graph(), &ret));
146 if (!scope.ok()) return;
147 scope.UpdateStatus(scope.DoShapeInference(ret));
148 this->operation = Operation(ret);
149 this->output = Output(ret, 0);
150}
151
152RandomPoissonV2::RandomPoissonV2(const ::tensorflow::Scope& scope,
153 ::tensorflow::Input shape, ::tensorflow::Input
154 rate)
155 : RandomPoissonV2(scope, shape, rate, RandomPoissonV2::Attrs()) {}
156
157RandomShuffle::RandomShuffle(const ::tensorflow::Scope& scope,
158 ::tensorflow::Input value, const
159 RandomShuffle::Attrs& attrs) {
160 if (!scope.ok()) return;
161 auto _value = ::tensorflow::ops::AsNodeOut(scope, value);
162 if (!scope.ok()) return;
163 ::tensorflow::Node* ret;
164 const auto unique_name = scope.GetUniqueNameForOp("RandomShuffle");
165 auto builder = ::tensorflow::NodeBuilder(unique_name, "RandomShuffle")
166 .Input(_value)
167 .Attr("seed", attrs.seed_)
168 .Attr("seed2", attrs.seed2_)
169 ;
170 scope.UpdateBuilder(&builder);
171 scope.UpdateStatus(builder.Finalize(scope.graph(), &ret));
172 if (!scope.ok()) return;
173 scope.UpdateStatus(scope.DoShapeInference(ret));
174 this->operation = Operation(ret);
175 this->output = Output(ret, 0);
176}
177
178RandomShuffle::RandomShuffle(const ::tensorflow::Scope& scope,
179 ::tensorflow::Input value)
180 : RandomShuffle(scope, value, RandomShuffle::Attrs()) {}
181
182RandomNormal::RandomNormal(const ::tensorflow::Scope& scope,
183 ::tensorflow::Input shape, DataType dtype, const
184 RandomNormal::Attrs& attrs) {
185 if (!scope.ok()) return;
186 auto _shape = ::tensorflow::ops::AsNodeOut(scope, shape);
187 if (!scope.ok()) return;
188 ::tensorflow::Node* ret;
189 const auto unique_name = scope.GetUniqueNameForOp("RandomNormal");
190 auto builder = ::tensorflow::NodeBuilder(unique_name, "RandomStandardNormal")
191 .Input(_shape)
192 .Attr("seed", attrs.seed_)
193 .Attr("seed2", attrs.seed2_)
194 .Attr("dtype", dtype)
195 ;
196 scope.UpdateBuilder(&builder);
197 scope.UpdateStatus(builder.Finalize(scope.graph(), &ret));
198 if (!scope.ok()) return;
199 scope.UpdateStatus(scope.DoShapeInference(ret));
200 this->operation = Operation(ret);
201 this->output = Output(ret, 0);
202}
203
204RandomNormal::RandomNormal(const ::tensorflow::Scope& scope,
205 ::tensorflow::Input shape, DataType dtype)
206 : RandomNormal(scope, shape, dtype, RandomNormal::Attrs()) {}
207
208RandomUniform::RandomUniform(const ::tensorflow::Scope& scope,
209 ::tensorflow::Input shape, DataType dtype, const
210 RandomUniform::Attrs& attrs) {
211 if (!scope.ok()) return;
212 auto _shape = ::tensorflow::ops::AsNodeOut(scope, shape);
213 if (!scope.ok()) return;
214 ::tensorflow::Node* ret;
215 const auto unique_name = scope.GetUniqueNameForOp("RandomUniform");
216 auto builder = ::tensorflow::NodeBuilder(unique_name, "RandomUniform")
217 .Input(_shape)
218 .Attr("seed", attrs.seed_)
219 .Attr("seed2", attrs.seed2_)
220 .Attr("dtype", dtype)
221 ;
222 scope.UpdateBuilder(&builder);
223 scope.UpdateStatus(builder.Finalize(scope.graph(), &ret));
224 if (!scope.ok()) return;
225 scope.UpdateStatus(scope.DoShapeInference(ret));
226 this->operation = Operation(ret);
227 this->output = Output(ret, 0);
228}
229
230RandomUniform::RandomUniform(const ::tensorflow::Scope& scope,
231 ::tensorflow::Input shape, DataType dtype)
232 : RandomUniform(scope, shape, dtype, RandomUniform::Attrs()) {}
233
234RandomUniformInt::RandomUniformInt(const ::tensorflow::Scope& scope,
235 ::tensorflow::Input shape,
236 ::tensorflow::Input minval,
237 ::tensorflow::Input maxval, const
238 RandomUniformInt::Attrs& attrs) {
239 if (!scope.ok()) return;
240 auto _shape = ::tensorflow::ops::AsNodeOut(scope, shape);
241 if (!scope.ok()) return;
242 auto _minval = ::tensorflow::ops::AsNodeOut(scope, minval);
243 if (!scope.ok()) return;
244 auto _maxval = ::tensorflow::ops::AsNodeOut(scope, maxval);
245 if (!scope.ok()) return;
246 ::tensorflow::Node* ret;
247 const auto unique_name = scope.GetUniqueNameForOp("RandomUniformInt");
248 auto builder = ::tensorflow::NodeBuilder(unique_name, "RandomUniformInt")
249 .Input(_shape)
250 .Input(_minval)
251 .Input(_maxval)
252 .Attr("seed", attrs.seed_)
253 .Attr("seed2", attrs.seed2_)
254 ;
255 scope.UpdateBuilder(&builder);
256 scope.UpdateStatus(builder.Finalize(scope.graph(), &ret));
257 if (!scope.ok()) return;
258 scope.UpdateStatus(scope.DoShapeInference(ret));
259 this->operation = Operation(ret);
260 this->output = Output(ret, 0);
261}
262
263RandomUniformInt::RandomUniformInt(const ::tensorflow::Scope& scope,
264 ::tensorflow::Input shape,
265 ::tensorflow::Input minval,
266 ::tensorflow::Input maxval)
267 : RandomUniformInt(scope, shape, minval, maxval, RandomUniformInt::Attrs()) {}
268
269TruncatedNormal::TruncatedNormal(const ::tensorflow::Scope& scope,
270 ::tensorflow::Input shape, DataType dtype,
271 const TruncatedNormal::Attrs& attrs) {
272 if (!scope.ok()) return;
273 auto _shape = ::tensorflow::ops::AsNodeOut(scope, shape);
274 if (!scope.ok()) return;
275 ::tensorflow::Node* ret;
276 const auto unique_name = scope.GetUniqueNameForOp("TruncatedNormal");
277 auto builder = ::tensorflow::NodeBuilder(unique_name, "TruncatedNormal")
278 .Input(_shape)
279 .Attr("seed", attrs.seed_)
280 .Attr("seed2", attrs.seed2_)
281 .Attr("dtype", dtype)
282 ;
283 scope.UpdateBuilder(&builder);
284 scope.UpdateStatus(builder.Finalize(scope.graph(), &ret));
285 if (!scope.ok()) return;
286 scope.UpdateStatus(scope.DoShapeInference(ret));
287 this->operation = Operation(ret);
288 this->output = Output(ret, 0);
289}
290
291TruncatedNormal::TruncatedNormal(const ::tensorflow::Scope& scope,
292 ::tensorflow::Input shape, DataType dtype)
293 : TruncatedNormal(scope, shape, dtype, TruncatedNormal::Attrs()) {}
294
295/// @}
296
297} // namespace ops
298} // namespace tensorflow
299