def _test(self, x, n, p): xtf = tf.constant(x) val_true = stats.nbinom.logpmf(x, n, p) with self.test_session(): self.assertAllClose(nbinom.logpmf(xtf, n, p).eval(), val_true) self.assertAllClose( nbinom.logpmf(xtf, tf.constant(n), tf.constant(p)).eval(), val_true)
def _test(x, n, p): xtf = tf.constant(x) val_true = stats.nbinom.logpmf(x, n, p) _assert_eq(nbinom.logpmf(xtf, n, p), val_true) _assert_eq(nbinom.logpmf(xtf, tf.constant(n), tf.constant(p)), val_true) _assert_eq(nbinom.logpmf(xtf, tf.constant(n), tf.constant([p])), val_true) _assert_eq(nbinom.logpmf(xtf, tf.constant([n]), tf.constant(p)), val_true) _assert_eq(nbinom.logpmf(xtf, tf.constant([n]), tf.constant([p])), val_true)
def _test_logpmf(x, n, p): xtf = tf.constant(x) val_true = stats.nbinom.logpmf(x, n, p) _assert_eq(nbinom.logpmf(xtf, n, p), val_true) _assert_eq(nbinom.logpmf(xtf, tf.constant(n), tf.constant(p)), val_true) _assert_eq(nbinom.logpmf(xtf, tf.constant(n), tf.constant([p])), val_true) _assert_eq(nbinom.logpmf(xtf, tf.constant([n]), tf.constant(p)), val_true) _assert_eq(nbinom.logpmf(xtf, tf.constant([n]), tf.constant([p])), val_true)
def _test(self, x, n, p): xtf = tf.constant(x) val_true = stats.nbinom.logpmf(x, n, p) with self.test_session(): self.assertAllClose(nbinom.logpmf(xtf, n, p).eval(), val_true) self.assertAllClose(nbinom.logpmf(xtf, tf.constant(n), tf.constant(p)).eval(), val_true)
def _test(self, x, n, p): val_true = stats.nbinom.logpmf(x, n, p) with self.test_session(): self.assertAllClose(nbinom.logpmf(x, n=n, p=p).eval(), val_true)