| /external/tensorflow/tensorflow/core/api_def/python_api/ |
| api_def_Sigmoid.pbtxt | 2 graph_op_name: "Sigmoid"
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| api_def_Sigmoid.pbtxt | 2 graph_op_name: "Sigmoid"
3 summary: "Computes sigmoid of `x` element-wise."
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| api_def_SigmoidGrad.pbtxt | 4 summary: "Computes the gradient of the sigmoid of `x` wrt its input."
6 Specifically, `grad = dy * y * (1 - y)`, where `y = sigmoid(x)`, and
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| sigmoid.py | 15 """Sigmoid bijector."""
27 "Sigmoid",
31 class Sigmoid(bijector.Bijector):
34 def __init__(self, validate_args=False, name="sigmoid"):
35 super(Sigmoid, self).__init__(
39 return math_ops.sigmoid(x)
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| __init__.py | 34 @@Sigmoid
67 from tensorflow.contrib.distributions.python.ops.bijectors.sigmoid import *
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| /external/tensorflow/tensorflow/core/kernels/ |
| 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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| cwise_op_gpu_sigmoid.cu.cc | 23 DEFINE_UNARY3(sigmoid, Eigen::half, float, double);
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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 self.assertAllClose(y, Sigmoid().forward(x).eval(), atol=0., rtol=1e-2)
40 self.assertAllClose(x, Sigmoid().inverse(y).eval(), atol=0., rtol=1e-4)
41 self.assertAllClose(ildj, Sigmoid().inverse_log_det_jacobian(y).eval(),
43 self.assertAllClose(-ildj, Sigmoid().forward_log_det_jacobian(x).eval(),
48 assert_scalar_congruency(Sigmoid(), lower_x=-7., upper_x=7.
[all...] |
| sigmoid_centered_test.py | 32 sigmoid = SigmoidCentered()
33 self.assertEqual("sigmoid_centered", sigmoid.name)
42 self.assertAllClose(y, sigmoid.forward(x).eval())
43 self.assertAllClose(x, sigmoid.inverse(y).eval())
46 sigmoid.inverse_log_det_jacobian(y).eval(),
50 -sigmoid.inverse_log_det_jacobian(y).eval(),
51 sigmoid.forward_log_det_jacobian(x).eval(),
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| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| target_column_test.py | 65 # z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
79 # z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
104 # z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
116 # z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
139 # z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x)
[all...] |
| /external/tensorflow/tensorflow/core/util/ |
| activation_mode.cc | 27 } else if (str_value == "Sigmoid") {
28 *value = SIGMOID;
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| activation_mode.h | 32 SIGMOID = 1,
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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/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| relaxed_bernoulli.py | 24 from tensorflow.contrib.distributions.python.ops.bijectors.sigmoid import Sigmoid
56 random variable followed by a `tf.sigmoid` op, one solution is to treat
57 the Logistic as the random variable and `tf.sigmoid` as downstream. The
58 KL divergences of two Logistics, which are always followed by a `tf.sigmoid`
91 Creates three continuous distributions, whose sigmoid approximate 3 Bernoullis
99 sigmoid_samples = tf.sigmoid(samples)
150 event is sigmoid(logits). Only one of `logits` or `probs` should be
182 bijector=Sigmoid(validate_args=validate_args),
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| /frameworks/rs/tests/java_api/VrDemo/src/com/example/android/rs/vr/engine/ |
| bugdroid.rs | 25 static float sigmoid(float f) {
38 return (short) (max * sigmoid(pillDistance(p1, p2, img) - rad));
45 * sigmoid(pillDistance(p1, p2, img) - rad * (1 + angle / 2)));
58 return (short) (max * sigmoid(cylinderDistance(p1, p2, img) - rad));
65 * sigmoid(cylinderDistance(p1, p2, img) - rad * (1 + angle / 5)));
80 * sigmoid(distanceCircle(center, circleRadius, normal, img) - rad));
99 * sigmoid(distanceDisk(center, circleRadius, normal, img) - rad));
108 * sigmoid(
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| /external/eigen/unsupported/test/ |
| cxx11_tensor_math.cpp | 34 Tensor<float, 1> vec2 = vec1.sigmoid();
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| /external/tensorflow/tensorflow/tools/api/golden/ |
| tensorflow.keras.activations.pbtxt | 36 name: "sigmoid"
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| /external/webrtc/webrtc/modules/video_coding/ |
| nack_fec_tables.h | 17 // Table values are built as a sigmoid function, ranging from 0 to 100, based on
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
| head_test.py | 504 # z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
764 # z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
788 # z * -log(sigmoid(x)) + (1 - z) * -log(1 - sigmoid(x))
[all...] |
| /external/tensorflow/tensorflow/contrib/rnn/python/ops/ |
| rnn_cell.py | 239 sigmoid = math_ops.sigmoid
287 f_act = sigmoid(f + self._forget_bias + w_f_diag * c_prev)
289 f_act = sigmoid(f + self._forget_bias)
297 m = sigmoid(o + w_o_diag * c) * self._activation(c)
299 m = sigmoid(o) * self._activation(c)
400 sigmoid = math_ops.sigmoid
443 sigmoid(f + self._forget_bias + w_f_diag * c_prev) * c_prev +
444 sigmoid(i + w_i_diag * c_prev) * tanh(j)
[all...] |
| /external/tensorflow/tensorflow/contrib/estimator/python/estimator/ |
| head_test.py | 85 """Returns sigmoid cross entropy averaged over classes."""
274 # loss = labels * -log(sigmoid(logits)) +
275 # (1 - labels) * -log(1 - sigmoid(logits))
295 # loss = labels * -log(sigmoid(logits)) +
296 # (1 - labels) * -log(1 - sigmoid(logits))
438 # loss = labels * -log(sigmoid(logits)) +
439 # (1 - labels) * -log(1 - sigmoid(logits))
468 # loss = labels * -log(sigmoid(logits)) +
469 # (1 - labels) * -log(1 - sigmoid(logits))
499 # labels * -log(sigmoid(logits))
[all...] |
| /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/keras/_impl/keras/ |
| activations_test.py | 37 'sigmoid', 'hard_sigmoid', 'linear',
117 sigmoid = np.vectorize(ref_sigmoid)
121 f = keras.backend.function([x], [keras.activations.sigmoid(x)])
124 expected = sigmoid(test_values)
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| /external/tensorflow/tensorflow/python/ops/distributions/ |
| bernoulli.py | 54 where the probability of an event is sigmoid(logits). Only one of
146 return (-self.logits * (math_ops.sigmoid(self.logits) - 1) +
177 return (math_ops.sigmoid(a.logits) * delta_probs0
178 + math_ops.sigmoid(-a.logits) * delta_probs1)
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| /external/webrtc/webrtc/modules/audio_processing/ns/ |
| defines.h | 39 #define WIDTH_PR_MAP (float)4.0 // width parameter in sigmoid map for prior model
|
