| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| D | categorical_test.py | 107 dist.logits.dtype, dist.log_prob(np.array(
291 "cat_log_prob": cat.log_prob(disc_event_tf),
295 "norm_log_prob": norm.log_prob(real_event_tf),
317 self.assertAllClose(dist.log_prob([0, 1]), np.log([0.2, 0.4]))
318 self.assertAllClose(dist.log_prob([0.0, 1.0]), np.log([0.2, 0.4]))
438 log_prob = dist.log_prob([0, 1])
439 self.assertEqual(2, log_prob.get_shape().ndims)
440 self.assertAllEqual([1, 2], log_prob.get_shape())
442 log_prob = dist.log_prob([[[1, 1], [1, 0]], [[1, 0], [0, 1]]])
443 self.assertEqual(3, log_prob.get_shape().ndims)
[all …]
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| D | bernoulli_test.py | 122 self.assertEqual(dist.probs.dtype, dist.log_prob(0).dtype)
123 self.assertEqual(dist.probs.dtype, dist.log_prob(0.5).dtype)
152 self.assertAllClose(self.evaluate(dist.log_prob(x)), np.log(expected_pmf))
196 bernoulli.Bernoulli(probs=p, validate_args=False).log_prob(samps)))
203 self.assertAllClose(np.log(0.5), dist.log_prob(1).eval({p: 0.5}))
205 np.log([0.5, 0.5, 0.5]), dist.log_prob([1, 1, 1]).eval({
209 np.log([0.5, 0.5, 0.5]), dist.log_prob(1).eval({
218 self.assertEqual(2, len(dist.log_prob(1).eval({p: [[0.5], [0.5]]}).shape))
221 self.assertEqual(2, len(self.evaluate(dist.log_prob([[1], [1]])).shape))
224 self.assertEqual((), dist.log_prob(1).get_shape())
[all …]
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| D | dirichlet_test.py | 93 log_prob = self.evaluate(dist.log_prob(x))
95 np.ones_like(log_prob, dtype=np.bool), np.isfinite(log_prob))
99 log_prob = self.evaluate(dist.log_prob(x))
101 np.ones_like(log_prob, dtype=np.bool), np.isfinite(log_prob))
284 kl_sample = math_ops.reduce_mean(d1.log_prob(x) - d2.log_prob(x), 0)
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| D | gamma_test.py | 70 log_pdf = gamma.log_prob(x)
85 log_pdf = gamma.log_prob(0.)
96 log_pdf = gamma.log_prob(x)
116 log_pdf = gamma.log_prob(x)
383 kl_sample = math_ops.reduce_mean(g0.log_prob(x) - g1.log_prob(x), 0)
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| D | exponential_test.py | 56 log_pdf = exponential.log_prob(x)
72 log_pdf = exponential.log_prob(0.)
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| D | laplace_test.py | 68 log_pdf = laplace.log_prob(x)
87 log_pdf = laplace.log_prob(x)
108 log_pdf = laplace.log_prob(x)
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| D | student_t_test.py | 63 log_pdf = student.log_prob(t)
91 log_pdf = student.log_prob(t)
261 self.assertEqual(student.log_prob(2.).get_shape(), (3,))
272 self.assertEqual(student.log_prob(arg).get_shape(), shape)
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| D | normal_test.py | 118 log_pdf = normal.log_prob(x)
152 log_pdf = normal.log_prob(x)
256 dist.log_survival_function, dist.log_prob, dist.prob
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| D | uniform_test.py | 82 log_pdf = uniform.log_prob(x)
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | ctc_decoder_ops.cc | 61 Tensor** log_prob, OpOutputList* decoded_indices, in ValidateInputsGenerateOutputs() argument
101 "log_probability", TensorShape({batch_size, top_paths_}), log_prob); in ValidateInputsGenerateOutputs()
192 Tensor* log_prob = nullptr; in Compute() local
197 ctx, &inputs, &seq_len, &log_prob, &decoded_indices, in Compute()
219 auto log_prob_t = log_prob->matrix<T>(); in Compute()
290 Tensor* log_prob = nullptr; in Compute() local
295 ctx, &inputs, &seq_len, &log_prob, &decoded_indices, in Compute()
300 auto log_prob_t = log_prob->matrix<T>(); in Compute()
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| /external/tensorflow/tensorflow/python/ops/distributions/ |
| D | transformed_distribution.py | 442 log_prob = self.distribution.log_prob(x)
444 log_prob = math_ops.reduce_sum(log_prob, self._reduce_event_indices)
445 log_prob += math_ops.cast(ildj, log_prob.dtype)
447 log_prob.set_shape(
451 return log_prob
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.distributions.-distribution.pbtxt | 87 name: "log_prob"
88 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-multinomial.pbtxt | 100 name: "log_prob"
101 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-dirichlet.pbtxt | 96 name: "log_prob"
97 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-exponential.pbtxt | 97 name: "log_prob"
98 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-categorical.pbtxt | 100 name: "log_prob"
101 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-laplace.pbtxt | 96 name: "log_prob"
97 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-student-t.pbtxt | 100 name: "log_prob"
101 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-normal.pbtxt | 96 name: "log_prob"
97 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-dirichlet-multinomial.pbtxt | 100 name: "log_prob"
101 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-bernoulli.pbtxt | 96 name: "log_prob"
97 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-uniform.pbtxt | 96 name: "log_prob"
97 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-gamma.pbtxt | 96 name: "log_prob"
97 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| D | tensorflow.distributions.-beta.pbtxt | 100 name: "log_prob"
101 …pec: "args=[\'self\', \'value\', \'name\'], varargs=None, keywords=None, defaults=[\'log_prob\'], "
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | special_math_test.py | 69 log_prob = math_ops.xlogy(a - 1., x) - math_ops.lgamma(a) - x
70 prob = math_ops.exp(log_prob)
|