| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | ragged_reduce_op_test.py | 80 ragged_reduce_op=ragged_math_ops.reduce_prod,
86 ragged_reduce_op=ragged_math_ops.reduce_prod,
159 ragged_reduce_op=ragged_math_ops.reduce_prod,
185 ragged_reduce_op=ragged_math_ops.reduce_prod,
214 ragged_reduce_op=ragged_math_ops.reduce_prod,
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| D | ragged_math_ops.py | 508 def reduce_prod(input_tensor, axis=None, keepdims=None, name=None): function
510 return _ragged_reduce_aggregate(math_ops.reduce_prod,
556 reduce_prod(_cast(input_tensor, dtypes.int32), axis, keepdims),
578 _set_ragged_reduce_docstring(reduce_prod, 'product', 'multiplied', '1',
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| D | ragged_dispatch.py | 397 math_ops.reduce_prod,
456 (math_ops.reduce_prod, ragged_math_ops.reduce_prod, ['input_tensor']),
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| /external/tensorflow/tensorflow/tools/compatibility/testdata/ |
| D | test_file_v0_11.py | 63 tf.reduce_prod(
66 tf.reduce_prod(
68 self.assertAllEqual(tf.reduce_prod(a, [0, 1]).eval(), 720.0)
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| /external/tensorflow/tensorflow/contrib/labeled_tensor/ |
| D | __init__.py | 130 reduce_prod = _ops.reduce_prod variable
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| D | batch_reshape.py | 379 original_size = math_ops.reduce_prod(original_shape)
382 original_size // math_ops.maximum(1, -math_ops.reduce_prod(new_shape)))
398 math_ops.reduce_prod(expanded_new_shape),
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| D | vector_diffeomixture.py | 581 batch_size = array_ops.reduce_prod(self.batch_shape_tensor())
584 mix_batch_size = math_ops.reduce_prod(
608 stride = array_ops.reduce_prod(
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| D | test_util.py | 88 batch_size = math_ops.reduce_prod(dist.batch_shape_tensor())
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| D | conditional_transformed_distribution.py | 149 prob = math_ops.reduce_prod(prob, self._reduce_event_indices)
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| D | poisson_lognormal.py | 365 batch_size = math_ops.reduce_prod(self.batch_shape_tensor())
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| /external/tensorflow/tensorflow/python/ops/linalg/ |
| D | linear_operator_circulant.py | 257 (vec_leading_shape, [math_ops.reduce_prod(vec_block_shape)]), 0)
332 n = math_ops.reduce_prod(trailing_dims)
422 det = math_ops.reduce_prod(self.spectrum, axis=axis)
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| D | linear_operator_lower_triangular.py | 198 return math_ops.reduce_prod(self._diag, axis=[-1])
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| D | linear_operator_diag.py | 231 return math_ops.reduce_prod(self._diag, axis=[-1])
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| /external/tensorflow/tensorflow/contrib/learn/python/learn/ops/ |
| D | embeddings_ops.py | 64 ids, math_ops.reduce_prod(shape, keepdims=True))
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| /external/tensorflow/tensorflow/python/ops/ |
| D | math_grad_test.py | 153 outputs = math_ops.reduce_prod(inputs)
164 outputs = math_ops.reduce_prod(inputs, -1)
176 outputs = math_ops.reduce_prod(inputs)
188 outputs = math_ops.reduce_prod(inputs, -1)
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| D | data_flow_grad.py | 39 math_ops.range(math_ops.reduce_prod(prefix_shape)), prefix_shape)
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| D | math_ops.py | 1816 def reduce_prod(input_tensor, axis=None, keepdims=False, name=None): function
1890 return reduce_prod(input_tensor, axis, keepdims, name)
2966 array_is_nonempty = reduce_prod(array_ops.shape(arr)) > 0
3656 prod_free_dims = reduce_prod(free_dims)
3657 prod_axes_dims = reduce_prod(axes_dims)
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| D | math_grad.py | 136 math_ops.reduce_prod(input_shape), math_ops.reduce_prod(output_shape))
169 reduced_num = math_ops.reduce_prod(array_ops.gather(input_shape, reduced))
170 other_num = math_ops.reduce_prod(array_ops.gather(input_shape, other))
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| /external/tensorflow/tensorflow/compiler/tests/ |
| D | reduce_ops_test.py | 105 self._testReduction(math_ops.reduce_prod, np.prod, np.float32,
109 self._testReduction(math_ops.reduce_prod, np.prod, np.complex64,
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| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | local.py | 726 in_size = K.math_ops.reduce_prod(in_dims)
727 out_size = K.math_ops.reduce_prod(out_dims)
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| /external/tensorflow/tensorflow/python/ops/distributions/ |
| D | transformed_distribution.py | 470 prob = math_ops.reduce_prod(prob, self._reduce_event_indices)
548 entropy *= math_ops.cast(math_ops.reduce_prod(self._override_event_shape),
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | reduction_ops_test.py | 106 math_ops.reduce_prod, math_ops.reduce_max,
567 return math_ops.reduce_prod(x, reduction_axes, keepdims)
578 v = math_ops.reduce_prod([0, 0], constant_op.constant(0, dtype=dtype))
650 y = math_ops.reduce_prod(x, [1])
660 y = math_ops.reduce_prod(x, [0])
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| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | embedding_ops.py | 134 math_ops.reduce_prod(
490 ids, math_ops.reduce_prod(shape, keepdims=True))
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| /external/tensorflow/tensorflow/contrib/bayesflow/python/kernel_tests/ |
| D | monte_carlo_test.py | 84 x1_times_x2 = math_ops.reduce_prod(x, axis=[-1])
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| /external/tensorflow/tensorflow/contrib/slim/python/slim/data/ |
| D | tfexample_decoder.py | 276 pred=math_ops.equal(math_ops.reduce_prod(array_ops.shape(item)), 0),
|