| /external/tensorflow/tensorflow/core/kernels/ |
| cwise_op_gpu_sigmoid.cu.cc | 23 DEFINE_UNARY3(sigmoid, Eigen::half, float, double);
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| cwise_op_sigmoid.cc | 20 REGISTER5(UnaryOp, CPU, "Sigmoid", functor::sigmoid, float, Eigen::half, double,
23 REGISTER3(UnaryOp, GPU, "Sigmoid", functor::sigmoid, float, Eigen::half,
27 REGISTER(UnaryOp, SYCL, "Sigmoid", functor::sigmoid, float);
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| /external/libopus/src/ |
| mlp.h | 41 int sigmoid; member in struct:__anon29285
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| mlp.c | 88 if (layer->sigmoid) {
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| /external/tensorflow/tensorflow/contrib/model_pruning/python/layers/ |
| rnn_cells.py | 139 sigmoid = math_ops.sigmoid
161 multiply(c, sigmoid(add(f, forget_bias_tensor))),
162 multiply(sigmoid(i), self._activation(j)))
163 new_h = multiply(self._activation(new_c), sigmoid(o))
299 sigmoid = math_ops.sigmoid
321 sigmoid(f + self._forget_bias + self._w_f_diag * c_prev) * c_prev +
322 sigmoid(i + self._w_i_diag * c_prev) * self._activation(j))
325 sigmoid(f + self._forget_bias) * c_prev
[all...] |
| /external/eigen/unsupported/test/ |
| cxx11_tensor_math.cpp | 34 Tensor<float, 1> vec2 = vec1.sigmoid();
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| /external/tensorflow/tensorflow/contrib/rnn/python/ops/ |
| rnn_cell.py | 244 sigmoid = math_ops.sigmoid
294 f_act = sigmoid(f + self._forget_bias + w_f_diag * c_prev)
296 f_act = sigmoid(f + self._forget_bias)
304 m = sigmoid(o + w_o_diag * c) * self._activation(c)
306 m = sigmoid(o) * self._activation(c)
407 sigmoid = math_ops.sigmoid
450 sigmoid(f + self._forget_bias + w_f_diag * c_prev) * c_prev +
451 sigmoid(i + w_i_diag * c_prev) * tanh(j)
[all...] |
| /external/tensorflow/tensorflow/compiler/tests/ |
| lstm.py | 72 in_gate = math_ops.sigmoid(in_gate)
73 forget_gate = math_ops.sigmoid(forget_gate)
74 out_gate = math_ops.sigmoid(out_gate)
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| /external/tensorflow/tensorflow/contrib/keras/api/keras/activations/ |
| __init__.py | 27 from tensorflow.python.keras.activations import sigmoid
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| /external/tensorflow/tensorflow/python/keras/ |
| activations.py | 180 @keras_export('keras.activations.sigmoid')
181 def sigmoid(x): function
182 """Sigmoid activation function.
188 The sigmoid activation: `(1.0 / (1.0 + exp(-x)))`.
190 return nn.sigmoid(x)
208 """Hard sigmoid activation function.
210 Faster to compute than sigmoid activation.
216 Hard sigmoid activation:
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| activations_test.py | 40 'sigmoid', 'hard_sigmoid', 'linear',
123 sigmoid = np.vectorize(ref_sigmoid)
126 f = keras.backend.function([x], [keras.activations.sigmoid(x)])
129 expected = sigmoid(test_values)
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| /external/tensorflow/tensorflow/python/ops/ |
| nn.py | 32 from tensorflow.python.ops.math_ops import sigmoid
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| rnn_cell_impl.py | 584 value = math_ops.sigmoid(gate_inputs)
758 sigmoid = math_ops.sigmoid
779 new_c = add(multiply(c, sigmoid(add(f, forget_bias_tensor))),
780 multiply(sigmoid(i), self._activation(j)))
781 new_h = multiply(self._activation(new_c), sigmoid(o))
[all...] |
| /external/tensorflow/tensorflow/contrib/boosted_trees/estimator_batch/ |
| distillation_loss.py | 43 return math_ops.sigmoid(logits)
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| sigmoid.py | 15 """Sigmoid bijector."""
28 "Sigmoid",
32 class Sigmoid(bijector.Bijector):
43 def __init__(self, validate_args=False, name="sigmoid"):
44 super(Sigmoid, self).__init__(
50 return math_ops.sigmoid(x)
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| /external/tensorflow/tensorflow/lite/experimental/examples/lstm/ |
| rnn_cell.py | 416 sigmoid = math_ops.sigmoid
479 sigmoid(f + self._w_f_diag * c_prev) * c_prev +
480 sigmoid(i + self._w_i_diag * c_prev) * self._activation(j))
482 c = (sigmoid(f) * c_prev + sigmoid(i) * self._activation(j))
489 m = sigmoid(o + self._w_o_diag * c) * self._activation(c)
491 m = sigmoid(o) * self._activation(c)
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| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ |
| sigmoid_test.py | 15 """Sigmoid Tests."""
24 from tensorflow.contrib.distributions.python.ops.bijectors.sigmoid import Sigmoid
35 self.assertEqual("sigmoid", Sigmoid().name)
39 bijector = Sigmoid()
49 assert_scalar_congruency(Sigmoid(), lower_x=-7., upper_x=7.)
57 Sigmoid(), x, y, event_ndims=0, atol=0., rtol=1e-4)
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| /external/tensorflow/tensorflow/contrib/specs/python/ |
| specs_ops.py | 81 Cs = Fun(layers.conv2d, activation_fn=math_ops.sigmoid)
90 Fs = Fun(layers.fully_connected, activation_fn=math_ops.sigmoid)
119 Sig = Fun(math_ops.sigmoid)
125 """Depth-wise convolution + sigmoid (used after LSTM)."""
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| /external/tensorflow/tensorflow/python/ops/distributions/ |
| bernoulli.py | 63 where the probability of an event is sigmoid(logits). Only one of
155 return (-self.logits * (math_ops.sigmoid(self.logits) - 1) +
186 return (math_ops.sigmoid(a.logits) * delta_probs0
187 + math_ops.sigmoid(-a.logits) * delta_probs1)
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| relaxed_bernoulli.py | 22 from tensorflow.contrib.distributions.python.ops.bijectors.sigmoid import Sigmoid
57 random variable followed by a `tf.sigmoid` op, one solution is to treat
58 the Logistic as the random variable and `tf.sigmoid` as downstream. The
59 KL divergences of two Logistics, which are always followed by a `tf.sigmoid`
92 Creates three continuous distributions, whose sigmoid approximate 3 Bernoullis
100 sigmoid_samples = tf.sigmoid(samples)
159 event is sigmoid(logits). Only one of `logits` or `probs` should be
191 bijector=Sigmoid(validate_args=validate_args),
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| logistic.py | 202 return math_ops.sigmoid(self._z(x))
208 return math_ops.sigmoid(-self._z(x))
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| negative_binomial.py | 170 math_ops.sigmoid(-self.logits))
200 return self._mean() / math_ops.sigmoid(-self.logits)
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| /external/tensorflow/tensorflow/contrib/boosted_trees/python/utils/ |
| losses.py | 185 modified_predictions are 1 if sigmoid is >= 0.5+eps (eg we predict positive
186 class), -1 if sigmoid < 0.5-eps (e.g. we predict negative class) and ax+b in
205 modified_predictions are 1 if sigmoid is >= 0.5+eps (eg we predict positive
206 class), -1 if sigmoid < 0.5-eps (e.g. we predict negative class) and ax+b in
246 probs = math_ops.sigmoid(logits)
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| /external/tensorflow/tensorflow/contrib/labeled_tensor/ |
| __init__.py | 76 sigmoid = _core.sigmoid variable
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| dnn.py | 68 "sigmoid": nn.sigmoid
107 "sigmoid".
340 name of the op may also be provided, e.g., "relu", "tanh", or "sigmoid".
624 the op may also be provided, e.g., "relu", "tanh", or "sigmoid".
[all...] |
