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/external/tensorflow/tensorflow/python/kernel_tests/
Dsoftplus_op_test.py42 softplus = nn_ops.softplus(np_features)
43 tf_softplus = self.evaluate(softplus)
46 self.assertShapeEqual(np_softplus, softplus)
81 y = nn_ops.softplus(x, name="softplus")
98 y = nn_ops.softplus(x, name="softplus")
116 y = nn_ops.softplus(x, name="softplus")
134 nn_ops.softplus(constant_op.constant(42)).eval()
/external/tensorflow/tensorflow/core/api_def/base_api/
Dapi_def_SoftplusGrad.pbtxt7 The backpropagated gradients to the corresponding softplus operation.
13 The features passed as input to the corresponding softplus operation.
22 summary: "Computes softplus gradients for a softplus operation."
Dapi_def_Softplus.pbtxt3 summary: "Computes softplus: `log(exp(features) + 1)`."
/external/tensorflow/tensorflow/python/ops/distributions/
Dbernoulli.py156 nn.softplus(-self.logits))
184 delta_probs0 = nn.softplus(-b.logits) - nn.softplus(-a.logits)
185 delta_probs1 = nn.softplus(b.logits) - nn.softplus(a.logits)
Dgamma.py305 concentration=nn.softplus(concentration,
307 rate=nn.softplus(rate, name="softplus_rate"),
Dbeta.py368 concentration1=nn.softplus(concentration1,
370 concentration0=nn.softplus(concentration0,
Dexponential.py162 rate=nn.softplus(rate, name="softplus_rate"),
/external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/
Destimator_test.py51 def softplus(x): function
66 return softplus(logits[..., 1] + scale_bias)
71 scale=nn_ops.softplus(logits[..., 1] + scale_bias))
104 expected_stddev = softplus(logits[..., 1] + scale_bias)
/external/tensorflow/tensorflow/core/api_def/python_api/
Dapi_def_Softplus.pbtxt4 name: "math.softplus"
7 name: "nn.softplus"
/external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/
Dsoftplus.py118 return nn_ops.softplus(x)
120 return hinge_softness * nn_ops.softplus(x / hinge_softness)
146 return -nn_ops.softplus(-x)
Dsigmoid.py59 return -nn_ops.softplus(-x) - nn_ops.softplus(x)
Dscale_tril.py24 from tensorflow.contrib.distributions.python.ops.bijectors import softplus
116 diag_bijector = softplus.Softplus(validate_args=validate_args)
Dsoftmax_centered.py170 log_normalization = nn_ops.softplus(
D__init__.py88 from tensorflow.contrib.distributions.python.ops.bijectors.softplus import *
/external/tensorflow/tensorflow/contrib/labeled_tensor/python/ops/
Dnn.py29 softplus = core.define_unary_op('softplus', nn.softplus) variable
Dnn_test.py41 ('softplus', nn_ops.softplus, nn.softplus),
/external/tensorflow/tensorflow/contrib/distributions/python/ops/
Dlogistic.py199 return -nn_ops.softplus(-self._z(x))
205 return -nn_ops.softplus(self._z(x))
212 return - z - 2. * nn_ops.softplus(-z)
Dinverse_gamma.py305 concentration=nn.softplus(concentration,
307 rate=nn.softplus(rate, name="softplus_rate"),
Dmvn_diag.py249 scale_diag=nn.softplus(scale_diag),
/external/tensorflow/tensorflow/python/keras/
Dactivations.py118 def softplus(x): function
127 return nn.softplus(x)
Dactivations_test.py95 def softplus(x): function
99 f = keras.backend.function([x], [keras.activations.softplus(x)])
102 expected = softplus(test_values)
/external/tensorflow/tensorflow/contrib/keras/api/keras/activations/
D__init__.py29 from tensorflow.python.keras.activations import softplus
/external/tensorflow/tensorflow/tools/api/golden/v2/
Dtensorflow.keras.activations.pbtxt48 name: "softplus"
/external/tensorflow/tensorflow/tools/api/golden/v1/
Dtensorflow.keras.activations.pbtxt48 name: "softplus"
/external/tensorflow/tensorflow/contrib/nn/python/ops/
Dscaled_softplus.py66 y = alpha * nn.softplus(x / alpha)

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