Searched refs:concentration1_a (Results 1 – 3 of 3) sorted by relevance
| /third_party/mindspore/mindspore/nn/probability/distribution/ |
| D | beta.py | 264 …def _cross_entropy(self, dist, concentration1_b, concentration0_b, concentration1_a=None, concentr… argument
276 return self._entropy(concentration1_a, concentration0_a) \
277 … + self._kl_loss(dist, concentration1_b, concentration0_b, concentration1_a, concentration0_a)
298 …def _kl_loss(self, dist, concentration1_b, concentration0_b, concentration1_a=None, concentration0… argument
320 … concentration1_a, concentration0_a = self._check_param_type(concentration1_a, concentration0_a)
321 total_concentration_a = concentration1_a + concentration0_a
323 log_normalization_a = self.lbeta(concentration1_a, concentration0_a)
326 - (self.digamma(concentration1_a) * (concentration1_b - concentration1_a)) \
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| /third_party/mindspore/tests/st/probability/distribution/ |
| D | test_beta.py | 86 concentration1_a = np.array([3.0]).astype(np.float32)
92 total_concentration_a = concentration1_a + concentration0_a
94 log_normalization_a = np.log(special.beta(concentration1_a, concentration0_a))
97 - (special.digamma(concentration1_a) * (concentration1_b - concentration1_a)) \
226 concentration1_a = np.array([3.0]).astype(np.float32)
232 total_concentration_a = concentration1_a + concentration0_a
234 log_normalization_a = np.log(special.beta(concentration1_a, concentration0_a))
237 - (special.digamma(concentration1_a) * (concentration1_b - concentration1_a)) \
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| /third_party/mindspore/tests/ut/python/nn/probability/distribution/ |
| D | test_beta.py | 129 def construct(self, concentration1_b, concentration0_b, concentration1_a, concentration0_a): argument
131 …kl2 = self.g2.kl_loss('Gamma', concentration1_b, concentration0_b, concentration1_a, concentration…
141 concentration1_a = Tensor(np.array([2.0]).astype(np.float32), dtype=dtype.float32)
143 ans = net(concentration1_b, concentration0_b, concentration1_a, concentration0_a)
155 def construct(self, concentration1_b, concentration0_b, concentration1_a, concentration0_a): argument
157 …h2 = self.g2.cross_entropy('Gamma', concentration1_b, concentration0_b, concentration1_a, concentr…
167 concentration1_a = Tensor(np.array([2.0]).astype(np.float32), dtype=dtype.float32)
169 ans = net(concentration1_b, concentration0_b, concentration1_a, concentration0_a)
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