| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| D | cauchy_test.py | 96 self.assertAllEqual(cauchy.batch_shape_tensor().eval(), log_pdf.shape)
97 self.assertAllEqual(cauchy.batch_shape_tensor().eval(),
103 self.assertAllEqual(cauchy.batch_shape_tensor().eval(), pdf.shape)
104 self.assertAllEqual(cauchy.batch_shape_tensor().eval(), pdf.eval().shape)
126 self.assertAllEqual(cauchy.batch_shape_tensor().eval(), log_pdf.shape)
127 self.assertAllEqual(cauchy.batch_shape_tensor().eval(),
135 self.assertAllEqual(cauchy.batch_shape_tensor().eval(), pdf.shape)
136 self.assertAllEqual(cauchy.batch_shape_tensor().eval(), pdf_values.shape)
155 self.assertAllEqual(cauchy.batch_shape_tensor().eval(), cdf.shape)
156 self.assertAllEqual(cauchy.batch_shape_tensor().eval(), cdf.eval().shape)
[all …]
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| D | mixture_test.py | 126 use_static_graph, batch_shape_tensor=None): argument
127 if batch_shape_tensor is None:
128 batch_shape_tensor = batch_shape
129 batch_shape_tensor = ops.convert_to_tensor(batch_shape_tensor, dtypes.int32)
131 array_ops.concat((batch_shape_tensor, [num_components]), 0),
138 batch_and_event_shape = array_ops.concat((batch_shape_tensor, event_shape), 0)
160 self.assertAllEqual(batch_shape, dist.batch_shape_tensor().eval())
169 self.assertAllEqual(batch_shape, dist.batch_shape_tensor().eval())
627 batch_shape_tensor = [2, 3]
630 batch_shape_tensor = array_ops.placeholder(dtype=dtypes.int32)
[all …]
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| D | half_normal_test.py | 73 self.assertAllEqual(dist.batch_shape_tensor().eval(), tensor.shape)
74 self.assertAllEqual(dist.batch_shape_tensor().eval(), tensor.eval().shape)
256 tensor_shape.TensorShape(halfnorm.batch_shape_tensor().eval()))
280 tensor_shape.TensorShape(halfnorm.batch_shape_tensor().eval()))
300 self.assertEqual(halfnorm.batch_shape_tensor().eval(), [5])
315 sess.run(halfnorm.batch_shape_tensor(),
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| D | wishart_test.py | 279 self.assertAllEqual([], w.batch_shape_tensor().eval())
284 self.assertAllEqual([2], w.batch_shape_tensor().eval())
289 [], sess.run(w.batch_shape_tensor(),
293 sess.run(w.batch_shape_tensor(),
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| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| D | normal_test.py | 120 self.evaluate(normal.batch_shape_tensor()), log_pdf.get_shape())
122 self.evaluate(normal.batch_shape_tensor()),
129 self.evaluate(normal.batch_shape_tensor()), pdf.get_shape())
131 self.evaluate(normal.batch_shape_tensor()),
156 self.evaluate(normal.batch_shape_tensor()), log_pdf.get_shape())
158 self.evaluate(normal.batch_shape_tensor()),
167 self.evaluate(normal.batch_shape_tensor()), pdf.get_shape())
169 self.evaluate(normal.batch_shape_tensor()), pdf_values.shape)
190 self.evaluate(normal.batch_shape_tensor()), cdf.get_shape())
192 self.evaluate(normal.batch_shape_tensor()),
[all …]
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| /external/tensorflow/tensorflow/python/ops/distributions/ |
| D | student_t.py | 253 shape = array_ops.concat([[n], self.batch_shape_tensor()], 0)
255 df = self.df * array_ops.ones(self.batch_shape_tensor(), dtype=self.dtype)
287 v = array_ops.ones(self.batch_shape_tensor(),
303 mean = self.loc * array_ops.ones(self.batch_shape_tensor(),
310 array_ops.ones(self.batch_shape_tensor(), dtype=self.dtype)),
312 array_ops.fill(self.batch_shape_tensor(), nan, name="nan"))
339 var = (array_ops.ones(self.batch_shape_tensor(), dtype=self.dtype) *
344 self.df > array_ops.fill(self.batch_shape_tensor(), 2.),
346 array_ops.fill(self.batch_shape_tensor(), inf, name="inf"))
353 array_ops.ones(self.batch_shape_tensor(), dtype=self.dtype)),
[all …]
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| D | uniform.py | 171 shape = array_ops.concat([[n], self.batch_shape_tensor()], 0)
179 self.batch_shape_tensor(), dtype=x.dtype)
191 array_ops.shape(x), self.batch_shape_tensor())
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| D | transformed_distribution.py | 366 self.distribution.batch_shape_tensor())
553 self.distribution.batch_shape_tensor()
558 _ones_like(self.distribution.batch_shape_tensor())
563 [self.batch_shape_tensor(), self.event_shape_tensor()],
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| D | vector_diffeomixture.py | 179 ndims = array_ops.shape(dist.batch_shape_tensor())[0]
572 self.batch_shape_tensor(),
581 batch_size = array_ops.reduce_prod(self.batch_shape_tensor())
585 self.mixture_distribution.batch_shape_tensor())
624 ([-1], self.batch_shape_tensor(), [1]), axis=0)
782 single_draw_shape = concat_vectors(self.batch_shape_tensor(),
801 self.mixture_distribution.batch_shape_tensor(),
865 batch_shape_tensor = array_ops.shape(grid)[:-2]
880 batch_shape_tensor = array_ops.broadcast_dynamic_shape(
881 batch_shape_tensor, array_ops.shape(aff.shift)[:-1])
[all …]
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| D | independent.py | 168 batch_shape = self.distribution.batch_shape_tensor()
186 batch_shape = self.distribution.batch_shape_tensor()
245 batch_shape = distribution.batch_shape_tensor()
270 ndims = array_ops.shape(distribution.batch_shape_tensor())[0]
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| D | cauchy.py | 179 shape = array_ops.concat([[n], self.batch_shape_tensor()], 0)
221 return array_ops.fill(self.batch_shape_tensor(),
228 return array_ops.fill(self.batch_shape_tensor(),
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| D | mixture_same_family.py | 180 mdbs = mixture_distribution.batch_shape_tensor()
181 cdbs = components_distribution.batch_shape_tensor()[:-1]
201 kc = components_distribution.batch_shape_tensor()[-1]
234 return self.components_distribution.batch_shape_tensor()[:-1]
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| D | poisson_lognormal.py | 138 batch_ndims = array_ops.shape(dist.batch_shape_tensor())[0]
349 self.distribution.batch_shape_tensor(),
365 batch_size = math_ops.reduce_prod(self.batch_shape_tensor())
397 rate, shape=concat_vectors([n], self.batch_shape_tensor()))
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| D | test_util.py | 88 batch_size = math_ops.reduce_prod(dist.batch_shape_tensor())
89 batch_dims = array_ops.shape(dist.batch_shape_tensor())[0]
303 batch_shape = dist.batch_shape_tensor()
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| D | half_normal.py | 156 shape = array_ops.concat([[n], self.batch_shape_tensor()], 0)
180 return array_ops.zeros(self.batch_shape_tensor())
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| D | mixture.py | 172 cat_batch_shape = cat.batch_shape_tensor()
175 batch_shapes = [d.batch_shape_tensor() for d in components]
230 return self._cat.batch_shape_tensor()
359 batch_shape = self.batch_shape_tensor()
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| D | wishart.py | 217 return self.scale_operator.batch_shape_tensor()
223 batch_shape = self.batch_shape_tensor()
241 self.scale_operator.batch_shape_tensor(),
290 batch_shape = self.batch_shape_tensor()
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| D | batch_reshape.py | 123 distribution.batch_shape_tensor(), self._batch_shape_unexpanded,
244 self.distribution.batch_shape_tensor(),
320 self.batch_shape_tensor(),
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| /external/tensorflow/tensorflow/python/ops/linalg/ |
| D | linear_operator_identity.py | 95 [self.batch_shape_tensor(),
344 special_shape = array_ops.concat((self.batch_shape_tensor(), [1, 1]), 0)
357 return array_ops.ones(shape=self.batch_shape_tensor(), dtype=self.dtype)
360 return array_ops.zeros(shape=self.batch_shape_tensor(), dtype=self.dtype)
371 shape=self.batch_shape_tensor(), dtype=self.dtype)
690 shape=self.batch_shape_tensor(), dtype=self.dtype)
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| D | linear_operator_zeros.py | 288 special_shape = array_ops.concat((self.batch_shape_tensor(), [1, 1]), 0)
322 return array_ops.zeros(shape=self.batch_shape_tensor(), dtype=self.dtype)
329 return array_ops.zeros(shape=self.batch_shape_tensor(), dtype=self.dtype)
449 [self.batch_shape_tensor(),
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| D | linear_operator_kronecker.py | 270 batch_shape = self.operators[0].batch_shape_tensor()
273 batch_shape, operator.batch_shape_tensor())
320 [array_ops.ones_like(self.batch_shape_tensor()), [1, 1]], 0)
436 [array_ops.ones_like(self.batch_shape_tensor()), [1, 1]], 0)
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| D | linear_operator_composition.py | 226 zeros = array_ops.zeros(shape=self.operators[0].batch_shape_tensor())
228 zeros += array_ops.zeros(shape=operator.batch_shape_tensor())
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.distributions.-distribution.pbtxt | 43 name: "batch_shape_tensor"
44 …spec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'batch_shape_tensor\'], "
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| D | tensorflow.distributions.-exponential.pbtxt | 53 name: "batch_shape_tensor"
54 …spec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'batch_shape_tensor\'], "
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| D | tensorflow.distributions.-normal.pbtxt | 52 name: "batch_shape_tensor"
53 …spec: "args=[\'self\', \'name\'], varargs=None, keywords=None, defaults=[\'batch_shape_tensor\'], "
|