| /external/tensorflow/tensorflow/python/ops/ragged/ |
| D | ragged_reduce_op_test.py | 104 ragged_reduce_op=ragged_math_ops.reduce_max,
110 ragged_reduce_op=ragged_math_ops.reduce_max,
169 ragged_reduce_op=ragged_math_ops.reduce_max,
195 ragged_reduce_op=ragged_math_ops.reduce_max,
226 ragged_reduce_op=ragged_math_ops.reduce_max,
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| D | ragged_math_ops.py | 482 num_segments = math_ops.maximum(math_ops.reduce_max(row_lengths), 0)
522 def reduce_max(input_tensor, axis=None, keepdims=None, name=None): function
524 return _ragged_reduce_aggregate(math_ops.reduce_max,
583 _set_ragged_reduce_docstring(reduce_max, 'maximum', 'maximized',
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| D | ragged_dispatch.py | 399 math_ops.reduce_max,
458 (math_ops.reduce_max, ragged_math_ops.reduce_max, ['input_tensor']),
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| D | ragged_tensor.py | 977 return math_ops.maximum(math_ops.reduce_max(self.row_lengths()), 0)
983 math_ops.maximum(math_ops.reduce_max(splits[1:] - splits[:-1]), 0)
1179 lengths = math_ops.reduce_max(length_for_nondefault_value, axis=1)
1271 ncols = math_ops.maximum(math_ops.reduce_max(rt_row_lengths), 0)
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| /external/tensorflow/tensorflow/contrib/quantize/python/ |
| D | quant_ops.py | 149 batch_max = math_ops.reduce_max(
154 batch_max = math_ops.reduce_max(inputs, name='BatchMax')
274 batch_max = math_ops.reduce_max(
279 batch_max = math_ops.reduce_max(inputs, name='BatchMax')
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| /external/tensorflow/tensorflow/tools/compatibility/testdata/ |
| D | test_file_v0_11.py | 84 tf.reduce_max(
87 tf.reduce_max(
89 self.assertAllEqual(tf.reduce_max(a, [0, 1]).eval(), 6.0)
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| /external/tensorflow/tensorflow/python/ops/ |
| D | confusion_matrix.py | 170 num_classes = math_ops.maximum(math_ops.reduce_max(predictions),
171 math_ops.reduce_max(labels)) + 1
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| D | linalg_ops.py | 612 math_ops.reduce_max(
630 result = math_ops.reduce_max(result, axis[-1], keepdims=True)
635 result = math_ops.reduce_max(result, max_axis, keepdims=True)
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| /external/tensorflow/tensorflow/contrib/labeled_tensor/ |
| D | __init__.py | 127 reduce_max = _ops.reduce_max variable
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | stage_op_test.py | 42 y = math_ops.reduce_max(math_ops.matmul(y, y))
62 y = math_ops.reduce_max(z * math_ops.matmul(y, y))
88 y = math_ops.reduce_max(z * math_ops.matmul(y, y))
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| D | reduction_ops_test.py | 106 math_ops.reduce_prod, math_ops.reduce_max,
795 tf_ans = math_ops.reduce_max(x, reduction_axes, keepdims)
809 v = math_ops.reduce_max([0, 0], constant_op.constant(0, dtype=dtype))
869 su = math_ops.reduce_max(t, [1, 2])
880 su = math_ops.reduce_max(t, [1])
891 su = math_ops.reduce_max(t, [2])
902 su = math_ops.reduce_max(t)
911 y = math_ops.reduce_max(x, [1])
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| /external/tensorflow/tensorflow/contrib/crf/python/ops/ |
| D | crf.py | 469 new_state = inputs + math_ops.reduce_max(transition_scores, [1]) # [B, O]
542 best_score = math_ops.reduce_max(squeezed_potentials, axis=1)
589 best_score = math_ops.reduce_max(last_score, axis=1) # [B]
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| /external/tensorflow/tensorflow/contrib/mpi_collectives/ |
| D | mpi_ops_test.py | 96 max_difference = tf.reduce_max(tf.abs(summed - multiplied))
140 max_difference = tf.reduce_max(tf.abs(summed - multiplied))
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| /external/tensorflow/tensorflow/python/keras/ |
| D | activations.py | 61 e = math_ops.exp(x - math_ops.reduce_max(x, axis=axis, keepdims=True))
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| /external/tensorflow/tensorflow/contrib/kernel_methods/python/ |
| D | losses.py | 133 loss = math_ops.reduce_max(margin, axis=1)
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SparseReduceMaxSparse.pbtxt | 37 `tf.reduce_max()`. In contrast to SparseReduceMax, this Op returns a
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| D | api_def_SparseReduceMax.pbtxt | 43 `tf.reduce_max()`. In particular, this Op also returns a dense `Tensor`
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| /external/tensorflow/tensorflow/contrib/metrics/python/metrics/ |
| D | classification.py | 168 return math_ops.reduce_max(f1_at_thresholds)
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| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| D | matrix_functions.py | 129 math_ops.reduce_max(math_ops.abs(mat_m - identity)) > epsilon)
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| /external/tensorflow/tensorflow/contrib/bayesflow/python/ops/ |
| D | monte_carlo_impl.py | 361 return math_ops.reduce_max(values, axis=[0])
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| /external/tensorflow/tensorflow/contrib/layers/python/ops/ |
| D | sparse_ops.py | 168 math_ops.reduce_max(row_index_indicators), shape=(1,),
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| /external/tensorflow/tensorflow/python/layers/ |
| D | convolutional_test.py | 313 b_constraint = lambda x: x / math_ops.reduce_max(x)
324 b_constraint = lambda x: x / math_ops.reduce_max(x)
335 b_constraint = lambda x: x / math_ops.reduce_max(x)
514 b_constraint = lambda x: x / math_ops.reduce_max(x)
772 b_constraint = lambda x: x / math_ops.reduce_max(x)
969 b_constraint = lambda x: x / math_ops.reduce_max(x)
1160 b_constraint = lambda x: x / math_ops.reduce_max(x)
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| /external/tensorflow/tensorflow/contrib/losses/python/metric_learning/ |
| D | metric_loss_ops.py | 135 masked_maximums = math_ops.reduce_max(
153 axis_maximums = math_ops.reduce_max(data, dim, keepdims=True)
451 row_negative_maximums = math_ops.reduce_max(
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| /external/tensorflow/tensorflow/python/ops/linalg/ |
| D | linear_operator.py | 461 cond = (math_ops.reduce_max(singular_values, axis=-1) /
473 math_ops.reduce_max([
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| /external/tensorflow/tensorflow/contrib/gan/python/losses/python/ |
| D | losses_impl.py | 831 list_max = math_ops.reduce_max([math_ops.reduce_max(math_ops.abs(x)) for x in
|