| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | relu_op_test.py | 50 def _npRelu(self, np_features): argument
51 return np.maximum(np_features, np.zeros(np_features.shape))
60 def _testRelu(self, np_features): argument
61 np_relu = self._npRelu(np_features)
62 tf_relu = nn_ops.relu(np_features)
222 def _npRelu6(self, np_features): argument
223 sixes = np.copy(np_features)
226 np.maximum(np_features, np.zeros(np_features.shape)), sixes)
235 def _testRelu6(self, np_features): argument
236 np_relu6 = self._npRelu6(np_features)
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| D | softplus_op_test.py | 34 def _npSoftplus(self, np_features): argument
35 np_features = np.asarray(np_features)
36 zero = np.asarray(0).astype(np_features.dtype)
37 return np.logaddexp(zero, np_features)
39 def _testSoftplus(self, np_features, use_gpu=False): argument
40 np_softplus = self._npSoftplus(np_features)
42 softplus = nn_ops.softplus(np_features)
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| D | softsign_op_test.py | 33 def _npSoftsign(self, np_features): argument
34 return np_features / (1 + np.abs(np_features))
36 def _testSoftsign(self, np_features, use_gpu=False): argument
37 np_softsign = self._npSoftsign(np_features)
39 softsign = nn_ops.softsign(np_features)
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| D | xent_op_test.py | 55 def _testXent(self, np_features, np_labels, use_gpu=False): argument
56 np_loss, np_backprop = self._npXent(np_features, np_labels)
59 np_features, np_labels)
64 def _testXentWrapper(self, np_features, np_labels, dim=-1, use_gpu=False): argument
65 np_loss, _ = self._npXent(np_features, np_labels, dim=dim)
68 labels=np_labels, logits=np_features, dim=dim)
95 np_features = np.array([[[1., 1., 1., 1.]], [[1., 2., 3.,
101 np_features, np_labels)
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| D | softmax_op_test.py | 57 def _testSoftmax(self, np_features, dim=-1, log=False, use_gpu=False): argument
62 np_softmax = self._npSoftmax(np_features, dim=dim, log=log)
65 tf_softmax = nn_ops.log_softmax(np_features, axis=dim, name=name)
67 tf_softmax = nn_ops.softmax(np_features, axis=dim, name=name)
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| D | sparse_xent_op_test.py | 65 def _testXent(self, np_features, np_labels): argument
66 np_loss, np_backprop = self._npXent(np_features, np_labels)
69 np_features, np_labels)
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| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| D | util_test.py | 918 def _npSoftplus(self, np_features): argument
919 np_features = np.asarray(np_features)
920 zero = np.asarray(0).astype(np_features.dtype)
921 return np.logaddexp(zero, np_features)
923 def _testSoftplus(self, np_features, use_gpu=False): argument
924 np_features = np.asarray(np_features)
925 np_softplus = self._npSoftplus(np_features)
927 softplus = nn_ops.softplus(np_features)
933 str(np_features.dtype), 1e-6)
937 np_features, tf_softplus_inverse,
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| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | layers_test.py | 3596 np_features = np.zeros(batch_shape, dtype=np.float32)
3600 feed_dict = {features: np_features}
3607 np_features = np.zeros(batch_shape, dtype=np.float32)
3611 feed_dict = {features: np_features}
3622 np_features = np.zeros(batch_shape, dtype=np.float32)
3627 np_features[:, x0, y0, :] = 100.
3628 np_features[:, x1, y1, :] = 100.
3638 feed_dict = {features: np_features}
3649 np_features = np.zeros(batch_shape, dtype=np.float32)
3654 np_features[:, x_loc[c], y_loc[c], c] = 100.
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