Lines Matching refs:constant_op
23 from tensorflow.python.framework import constant_op
44 self._predictions = constant_op.constant([4, 8, 12, 8, 1, 3], shape=(2, 3))
45 self._labels = constant_op.constant([1, 9, 2, -5, -2, 6], shape=(2, 3))
72 constant_op.constant(weights))
77 weights = constant_op.constant((1.2, 0.0), shape=(2, 1))
83 weights = constant_op.constant([1.2, 0.0], shape=[2, 1])
89 weights = constant_op.constant([3, 6, 5, 0, 4, 2], shape=[2, 3])
95 weights = constant_op.constant([0, 0, 0, 0, 0, 2], shape=[2, 3])
110 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
112 labels = constant_op.constant([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
119 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
121 labels = constant_op.constant([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
127 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
129 labels = constant_op.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
137 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
139 labels = constant_op.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
146 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
148 labels = constant_op.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
152 constant_op.constant(weights))
156 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
158 labels = constant_op.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
159 weights = constant_op.constant((1.2, 3.4, 5.6))
165 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
167 labels = constant_op.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
168 weights = constant_op.constant([0, 0, 0], shape=[3])
174 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
176 labels = constant_op.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
177 weights = constant_op.constant([1.2, 0, 0], shape=[3])
184 logits = constant_op.constant([[100.0, -100.0, -100.0],
187 labels = constant_op.constant([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
188 weights = constant_op.constant([[3, 4, 5], [2, 6, 0], [8, 0, 1]])
205 logits = constant_op.constant([[100.0, -100.0, -100.0]])
206 labels = constant_op.constant([[1, 0, 0]])
218 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
220 labels = constant_op.constant([[0], [1], [2]])
227 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
229 labels = constant_op.constant([[0], [1], [2]], dtype=dtypes.int32)
236 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
238 labels = constant_op.constant([[0], [1], [2]], dtype=dtypes.int64)
245 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
247 labels = constant_op.constant([0, 1, 2])
253 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
255 labels = constant_op.constant([[2], [0], [1]], dtype=dtypes.int32)
263 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
265 labels = constant_op.constant([[2], [0], [1]], dtype=dtypes.int64)
273 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
275 labels = constant_op.constant([2, 0, 1])
283 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
285 labels = constant_op.constant([[2], [0], [1]])
292 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
294 labels = constant_op.constant([[2], [0], [1]])
298 constant_op.constant(weights))
302 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
304 labels = constant_op.constant([[2], [0], [1]])
308 labels, logits, constant_op.constant((weights,)))
312 logits = constant_op.constant([[10.0, 0.0, 0.0],
315 labels = constant_op.constant([[2], [0], [1]])
355 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
357 labels = constant_op.constant([[2], [0], [1]])
358 constant_op.constant([1.2, 3.4, 5.6], shape=(3, 1))
364 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
366 labels = constant_op.constant([[2], [0], [1]])
367 weights = constant_op.constant([[1.2], [3.4], [5.6]])
373 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
375 labels = constant_op.constant([[2], [0], [1]])
376 weights = constant_op.constant([0, 0, 0], shape=(3, 1))
382 logits = constant_op.constant([[10.0, 0.0, 0.0], [0.0, 10.0, 0.0],
384 labels = constant_op.constant([[2], [0], [1]])
385 weights = constant_op.constant([1.2, 0, 0], shape=(3, 1))
392 logits = constant_op.constant([[100.0, -100.0, -100.0],
395 labels = constant_op.constant([[0], [1], [2]])
396 weights = constant_op.constant([[3, 4, 5], [2, 6, 0], [8, 0, 1]])
405 logits = constant_op.constant([[100.0, -100.0, -100.0],
408 labels = constant_op.constant([[0], [1], [2]])
409 weights = constant_op.constant([1.2, 3.4, 5.6, 7.8])
418 logits = constant_op.constant([[100.0, -100.0, -100.0],
421 labels = constant_op.constant([[0], [1], [2], [3]])
422 weights = constant_op.constant([1.2, 3.4, 5.6])
431 logits = constant_op.constant([[100.0, -100.0, -100.0, -100.0],
435 labels = constant_op.constant([[0], [1], [2], [3]])
436 weights = constant_op.constant([[1.2, 3.4], [5.6, 7.8]])
445 logits = constant_op.constant([[100.0, -100.0, -100.0, -100.0],
449 labels = constant_op.constant([[0, 1], [2, 3]])
450 weights = constant_op.constant(1.2)
461 logits = constant_op.constant([[100.0, -100.0, -100.0],
464 labels = constant_op.constant([[1, 0, 0], [0, 1, 0], [0, 0, 1]])
504 logits = constant_op.constant([[100.0, -100.0, -100.0],
507 labels = constant_op.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
515 logits = constant_op.constant([[100.0, -100.0, -100.0],
518 labels = constant_op.constant([[0, 0, 1], [1, 0, 0], [0, 1, 0]])
519 weights = constant_op.constant([[3, 4, 5], [2, 6, 0], [8, 0, 1]])
526 logits = constant_op.constant([[100.0, -100.0, 100.0],
529 labels = constant_op.constant([[1, 0, 1], [1, 1, 0], [0, 1, 1]])
538 logits = constant_op.constant((
543 labels = constant_op.constant((
553 logits = constant_op.constant((
557 labels = constant_op.constant(((1, 0, 1), (1, 1, 0), (0, 1, 1)))
571 logits = constant_op.constant([[100.0, -100.0, -100.0]])
572 labels = constant_op.constant([[1, 0, 1]])
595 sigmoid_logits = constant_op.constant([[100.0, -100.0, -100.0]])
596 sigmoid_labels = constant_op.constant([[1, 0, 1]])
601 softmax_logits = constant_op.constant(
603 softmax_labels = constant_op.constant([[0, 1], [1, 0], [0, 1]])
624 self._predictions = constant_op.constant(predictions)
625 self._labels = constant_op.constant(labels)
661 constant_op.constant(weights))
671 constant_op.constant(weights))
681 constant_op.constant(weights))
688 weights = constant_op.constant((1.2, 3.4), shape=(2, 1))
697 weights = constant_op.constant((1.2, 0), shape=(2, 1))
706 weights = constant_op.constant([1.2, 0], shape=[2, 1])
715 weights = constant_op.constant(np.random.normal(size=(2, 4)), shape=[2, 4])
727 constant_op.constant(
740 constant_op.constant(
754 constant_op.constant(
764 tf_weights = constant_op.constant(weights, shape=(2, 3))
782 logits = constant_op.constant([[-1.0], [2.1]])
783 labels = constant_op.constant([0.0, 1.0])
789 logits = constant_op.constant([1.2, -1.4, -1.0, 2.1])
790 labels = constant_op.constant([1.0, 0.0, 0.0, 1.0])
796 logits = constant_op.constant([[-0.7], [-1.4], [1.4], [0.6]])
797 labels = constant_op.constant([[0.0], [0.0], [1.0], [1.0]])
805 logits = constant_op.constant([[[1.2], [0.4], [-1.0], [-1.1]]])
806 labels = constant_op.constant([[[1.0], [0.0], [0.0], [1.0]]])
817 predictions = constant_op.constant([[-1.0], [2.1]])
818 labels = constant_op.constant([0.0, 1.0])
824 predictions = constant_op.constant([1.5, -1.4, -1.0, 0.0])
825 labels = constant_op.constant([1.0, -1.0, 0.0, 0.5])
832 predictions = constant_op.constant([1.5, -1.4, -1.0, 0.0])
833 labels = constant_op.constant([0.0, 1.0, 0.0, 1.5])
840 predictions = constant_op.constant([[1.5, -1.4, -1.0, 0.0],
842 labels = constant_op.constant([[1.0, -1.0, 0.0, 0.5],
853 predictions = constant_op.constant([1.5, -1.4, -0.5, 0.0])
854 labels = constant_op.constant([1.0, -1.0, 0.0, 0.5])
861 predictions = constant_op.constant([1.5, -1.4, -1.0, 0.0])
862 labels = constant_op.constant([0.0, 1.0, 0.0, 1.5])
874 self._predictions = constant_op.constant([4, 8, 12, 8, 1, 3], shape=(2, 3))
875 self._labels = constant_op.constant([1, 9, 2, -5, -2, 6], shape=(2, 3))
887 losses.mean_squared_error(predictions=constant_op.constant(0),
888 labels=constant_op.constant(0)).eval())
909 constant_op.constant(weights))
914 weights = constant_op.constant([1.2, 3.4], shape=(2, 1))
920 weights = constant_op.constant([1.2, 3.4], shape=[2, 1])
926 weights = constant_op.constant([3, 6, 5, 0, 4, 2], shape=[2, 3])
932 weights = constant_op.constant([0, 0, 0, 0, 0, 2], shape=[2, 3])
969 predictions=constant_op.constant(self._labels),
970 labels=constant_op.constant(self._labels),
1042 predictions=constant_op.constant(self._predictions),
1043 labels=constant_op.constant(self._labels),
1044 weights=constant_op.constant(weights))
1191 predictions=constant_op.constant(self._labels),
1192 labels=constant_op.constant(self._labels),
1198 predictions=constant_op.constant(self._labels),
1199 labels=constant_op.constant(self._labels),
1206 predictions=constant_op.constant(self._predictions),
1207 labels=constant_op.constant(self._labels),
1221 tf_preds = constant_op.constant(
1223 tf_labels = constant_op.constant(
1232 predictions=constant_op.constant(self._predictions),
1233 labels=constant_op.constant(self._labels),
1241 predictions=constant_op.constant(self._predictions),
1242 labels=constant_op.constant(self._labels),
1244 weights=constant_op.constant(
1254 labels=constant_op.constant(self._labels),
1256 weights=constant_op.constant(
1264 predictions=constant_op.constant(self._predictions),
1265 labels=constant_op.constant(self._labels),
1273 predictions=constant_op.constant(self._predictions),
1274 labels=constant_op.constant(self._labels),
1284 logits = constant_op.constant([[1.2, 0.4, -1.0, -1.1]] * 2)
1285 labels = constant_op.constant([[1.0, 0.0, 0.0, 1.0]] * 2)
