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/external/tensorflow/tensorflow/python/ops/ragged/
Dragged_operators.py45 ragged_tensor.RaggedTensor.__getitem__ = ragged_getitem.ragged_tensor_getitem
48 ragged_tensor.RaggedTensor.__eq__ = math_ops.tensor_equals
49 ragged_tensor.RaggedTensor.__ne__ = math_ops.tensor_not_equals
50 ragged_tensor.RaggedTensor.__hash__ = ragged_hash
53 ragged_tensor.RaggedTensor.__ge__ = math_ops.greater_equal
54 ragged_tensor.RaggedTensor.__gt__ = math_ops.greater
55 ragged_tensor.RaggedTensor.__le__ = math_ops.less_equal
56 ragged_tensor.RaggedTensor.__lt__ = math_ops.less
59 ragged_tensor.RaggedTensor.__and__ = math_ops.logical_and
60 ragged_tensor.RaggedTensor.__rand__ = _right(math_ops.logical_and)
[all …]
Dragged_tensor_test.py48 from tensorflow.python.ops.ragged.ragged_tensor import RaggedTensor
70 rt = RaggedTensor.from_row_splits(
77 rt1 = RaggedTensor.from_row_splits(values, row_splits=[0, 4, 4, 7, 8, 8])
78 rt2 = RaggedTensor.from_row_lengths(values, row_lengths=[4, 0, 3, 1, 0])
79 rt3 = RaggedTensor.from_value_rowids(
81 rt4 = RaggedTensor.from_row_starts(values, row_starts=[0, 4, 4, 7, 8])
82 rt5 = RaggedTensor.from_row_limits(values, row_limits=[4, 4, 7, 8, 8])
88 inner_rt = RaggedTensor.from_row_splits(
90 outer_rt = RaggedTensor.from_row_splits(
98 rt = RaggedTensor.from_nested_row_splits(
[all …]
Dragged_from_tensor_op_test.py30 from tensorflow.python.ops.ragged.ragged_tensor import RaggedTensor
42 RaggedTensor.from_tensor(dt), [[5, 7, 0], [0, 3, 0], [6, 0, 0]])
45 RaggedTensor.from_tensor(dt, lengths=[1, 0, 3]), [[5], [], [6, 0, 0]])
48 RaggedTensor.from_tensor(dt, padding=0), [[5, 7], [0, 3], [6]])
54 RaggedTensor.from_tensor(dt_3d, lengths=([2, 0, 3], [1, 1, 2, 0, 1])),
361 rt = RaggedTensor.from_tensor(dt, lengths, padding, ragged_rank)
363 rt = RaggedTensor.from_tensor(dt, lengths, padding)
364 self.assertEqual(type(rt), RaggedTensor)
372 self.assertAllEqual(rt, RaggedTensor.from_nested_row_splits(
381 rt = RaggedTensor.from_tensor(dt, ragged_rank=ragged_rank)
[all …]
Dragged_from_sparse_op_test.py27 from tensorflow.python.ops.ragged.ragged_tensor import RaggedTensor
39 rt = RaggedTensor.from_sparse(st)
48 rt = RaggedTensor.from_sparse(st)
55 RaggedTensor.from_sparse, st1)
60 RaggedTensor.from_sparse, st2)
68 RaggedTensor.from_sparse, st3)
82 RaggedTensor.from_sparse(st1)
83 RaggedTensor.from_sparse(st2)
96 self.evaluate(RaggedTensor.from_sparse(st1))
102 self.evaluate(RaggedTensor.from_sparse(st2))
[all …]
Dragged_gather_ops.py156 result = ragged_tensor.RaggedTensor.from_nested_row_splits(
200 if not isinstance(params, ragged_tensor.RaggedTensor):
205 params = ragged_tensor.RaggedTensor.from_tensor(
207 if not isinstance(indices, ragged_tensor.RaggedTensor):
212 indices = ragged_tensor.RaggedTensor.from_tensor(
225 if not isinstance(indices, ragged_tensor.RaggedTensor):
229 if not isinstance(params, ragged_tensor.RaggedTensor):
230 params = ragged_tensor.RaggedTensor.from_tensor(
270 if not isinstance(params, ragged_tensor.RaggedTensor):
271 params = ragged_tensor.RaggedTensor.from_tensor(
[all …]
Dragged_array_ops.py112 data = ragged_tensor.RaggedTensor.from_tensor(
144 masked_values = ragged_tensor.RaggedTensor.from_nested_row_splits(
167 return ragged_tensor.RaggedTensor.from_row_splits(
173 mask = ragged_tensor.RaggedTensor.from_tensor(
192 masked_values = ragged_tensor.RaggedTensor.from_row_lengths(
202 masked_values = ragged_tensor.RaggedTensor.from_row_splits(
247 return ragged_tensor.RaggedTensor.from_nested_row_splits(
444 return ragged_tensor.RaggedTensor.from_uniform_row_length(
447 return ragged_tensor.RaggedTensor.from_uniform_row_length(
589 if isinstance(data, ragged_tensor.RaggedTensor) else None)
[all …]
Dragged_string_ops.py72 if isinstance(input, ragged_tensor.RaggedTensor):
84 return ragged_tensor.RaggedTensor.from_value_rowids(
88 return string_bytes_split(ragged_tensor.RaggedTensor.from_tensor(input))
162 ragged_tensor.RaggedTensor.from_tensor(input_tensor),
179 ragged_input_tensor = ragged_tensor.RaggedTensor.from_row_splits(
423 input = ragged_tensor.RaggedTensor.from_tensor(
427 ragged_tensor.RaggedTensor.from_tensor(
453 codepoints = ragged_tensor.RaggedTensor.from_row_splits(
458 offsets = ragged_tensor.RaggedTensor.from_row_splits(
512 if isinstance(input, ragged_tensor.RaggedTensor):
[all …]
Dragged_where_op.py175 condition_is_ragged = isinstance(condition, ragged_tensor.RaggedTensor)
176 x_is_ragged = isinstance(x, ragged_tensor.RaggedTensor)
177 y_is_ragged = isinstance(y, ragged_tensor.RaggedTensor)
215 condition_is_ragged = isinstance(condition, ragged_tensor.RaggedTensor)
216 x_is_ragged = isinstance(x, ragged_tensor.RaggedTensor)
217 y_is_ragged = isinstance(y, ragged_tensor.RaggedTensor)
227 if not isinstance(condition, ragged_tensor.RaggedTensor):
249 if isinstance(rt_input, ragged_tensor.RaggedTensor):
Dragged_tensor.py61 class RaggedTensor(composite_tensor.CompositeTensor, class
288 if isinstance(values, RaggedTensor):
338 if not isinstance(values, RaggedTensor):
806 if isinstance(values, RaggedTensor):
891 values_is_ragged = isinstance(self._values, RaggedTensor)
923 while isinstance(rt_values, RaggedTensor):
1003 while isinstance(rt_values, RaggedTensor):
1034 while isinstance(rt_values, RaggedTensor):
1098 while isinstance(rt_values, RaggedTensor):
1217 elif isinstance(self.values, RaggedTensor):
[all …]
Dragged_to_sparse_op_test.py146 bad_rt1 = ragged_tensor.RaggedTensor.from_row_splits(
152 bad_rt2 = ragged_tensor.RaggedTensor.from_row_splits(
154 bad_rt3 = ragged_tensor.RaggedTensor.from_row_splits(
156 values=ragged_tensor.RaggedTensor.from_row_splits(
165 bad_rt4 = ragged_tensor.RaggedTensor.from_row_splits(
167 values=ragged_tensor.RaggedTensor.from_row_splits(
175 bad_rt5 = ragged_tensor.RaggedTensor.from_row_splits(
Dragged_concat_ops.py167 return ragged_tensor.RaggedTensor.from_row_lengths(
186 rt_inputs[i] = ragged_tensor.RaggedTensor.from_tensor(
202 return ragged_tensor.RaggedTensor.from_row_splits(
238 return ragged_tensor.RaggedTensor.from_nested_row_splits(
282 return ragged_tensor.RaggedTensor.from_row_splits(
289 return ragged_tensor.RaggedTensor.from_row_splits(
304 rt_input = ragged_tensor.RaggedTensor.from_tensor(
Dragged_getitem_test.py32 from tensorflow.python.ops.ragged.ragged_tensor import RaggedTensor
252 rt = RaggedTensor.from_row_splits(EXAMPLE_RAGGED_TENSOR_2D_VALUES,
314 rt = RaggedTensor.from_row_splits(EXAMPLE_RAGGED_TENSOR_2D_VALUES,
394 rt = RaggedTensor.from_nested_row_splits(
420 rt = RaggedTensor.from_nested_row_splits(
433 rt = RaggedTensor.from_row_splits([], [0])
444 rt = RaggedTensor.from_row_splits([], [0])
463 rt = RaggedTensor.from_row_splits(EXAMPLE_RAGGED_TENSOR_2D_VALUES, splits)
475 rt = RaggedTensor.from_row_splits(values, [0, 1])
483 rt = RaggedTensor.from_nested_row_splits(values, [splits1, splits2])
[all …]
Dragged_tensor_supported_values_test.py40 from tensorflow.python.ops.ragged.ragged_tensor import RaggedTensor
160 rt = RaggedTensor.from_row_splits(values, row_splits)
166 rt = RaggedTensor.from_row_starts(values, row_starts)
172 rt = RaggedTensor.from_row_limits(values, row_limits)
178 rt = RaggedTensor.from_row_lengths(values, row_lengths)
183 rt = RaggedTensor.from_uniform_row_length(values, 4)
192 rt = RaggedTensor.from_nested_row_splits(values, nested_row_splits)
206 rt = RaggedTensor.from_nested_row_splits(values, nested_row_splits)
284 wrapped_x = ragged_tensor.RaggedTensor.from_nested_row_splits(
315 wrapped_x = ragged_tensor.RaggedTensor.from_nested_row_splits(
[all …]
Dragged_getitem.py143 return ragged_tensor.RaggedTensor.from_uniform_row_length(
155 sliced_rt_input = ragged_tensor.RaggedTensor.from_uniform_row_length(
219 return ragged_tensor.RaggedTensor.from_row_splits(
266 return ragged_tensor.RaggedTensor.from_uniform_row_length(
314 inner_rt = ragged_tensor.RaggedTensor.from_uniform_row_length(
448 if isinstance(values, ragged_tensor.RaggedTensor):
/external/tensorflow/tensorflow/core/api_def/base_api/
Dapi_def_RaggedTensorToVariant.pbtxt8 `RaggedTensor`.
14 A Tensor representing the values of the input `RaggedTensor`.
20 A `variant` Tensor that containing encoded `RaggedTensor`.
26 A `bool` denoting whether the input is a batched `RaggedTensor`.
30 Encodes a `RaggedTensor` into a `variant` Tensor.
34 Encodes the given `RaggedTensor` and returns a `variant` Tensor. If
35 `batched_input` is True, then input `RaggedTensor` is unbatched along the
36 zero-th dimension, each component `RaggedTensor` is encoded into a scalar
38 If `batched_input` is False, then the input `RaggedTensor` is encoded as is and
39 a scalar `variant` Tensor is returned. A `RaggedTensor` is encoded by first
[all …]
Dapi_def_RaggedTensorFromVariant.pbtxt7 A `variant` Tensor containing encoded `RaggedTensor`s.
14 `RaggedTensor`.
20 A Tensor representing the values of the output `RaggedTensor`.
26 The ragged rank of each encoded `RaggedTensor` component in the input. If set to
33 The expected ragged rank of the output `RaggedTensor`. The following must hold:
38 Decodes a `variant` Tensor into a `RaggedTensor`.
41 Decodes the given `variant` Tensor and returns a `RaggedTensor`. The input
42 could be a scalar, meaning it encodes a single `RaggedTensor` with ragged_rank
44 element is decoded into a `RaggedTensor` with ragged_rank `input_ragged_rank`
46 `RaggedTensor` with ragged_rank `output_ragged_rank`. Each `variant` element in
[all …]
Dapi_def_RaggedTensorToSparse.pbtxt6 description: "The `row_splits` for the `RaggedTensor`."
10 description: "The `flat_values` for the `RaggedTensor`."
23 `sparse_dense_shape` is a tight bounding box of the input `RaggedTensor`.
29 The ragged rank of the input RaggedTensor. `rt_nested_splits` should contain
35 Converts a `RaggedTensor` into a `SparseTensor` with the same values.
Dapi_def_RaggedGather.pbtxt8 `params` RaggedTensor input.
14 The `flat_values` for the `params` RaggedTensor. There was a terminology change
30 returned RaggedTensor.
35 description: "The `flat_values` for the returned RaggedTensor."
40 The ragged rank of the `params` RaggedTensor. `params_nested_splits` should
48 The ragged rank of the output RaggedTensor. `output_nested_splits` will contain
57 Outputs a `RaggedTensor` output composed from `output_dense_values` and
Dapi_def_RaggedRange.pbtxt18 description: "The `row_splits` for the returned `RaggedTensor`."
22 description: "The `flat_values` for the returned `RaggedTensor`."
25 Returns a `RaggedTensor` containing the specified sequences of numbers.
29 Returns a `RaggedTensor` `result` composed from `rt_dense_values` and
38 <tf.RaggedTensor [[2], [], [8, 9, 10, 11]] >
Dapi_def_RaggedCross.pbtxt6 description: "The values tensor for each RaggedTensor input."
10 description: "The row_splits tensor for each RaggedTensor input."
30 description: "The `values` for the returned `RaggedTensor`."
34 description: "The `row_splits` for the returned `RaggedTensor`."
47 RaggedTensor. See `tf.ragged.cross` for more details.
/external/tensorflow/tensorflow/python/keras/engine/
Dragged_keras_tensor_test.py180 out = ragged_tensor.RaggedTensor.from_value_rowids(
185 expected = ragged_tensor.RaggedTensor.from_value_rowids(
196 out = ragged_tensor.RaggedTensor.from_row_splits(
201 expected = ragged_tensor.RaggedTensor.from_row_splits(
212 out = ragged_tensor.RaggedTensor.from_row_lengths(
217 expected = ragged_tensor.RaggedTensor.from_row_lengths(
228 out = ragged_tensor.RaggedTensor.from_row_starts(
233 expected = ragged_tensor.RaggedTensor.from_row_starts(
246 out = ragged_tensor.RaggedTensor.from_row_limits(
251 expected = ragged_tensor.RaggedTensor.from_row_limits(
[all …]
Dinput_layer_test.py198 rt = ragged_tensor.RaggedTensor.from_row_splits(
206 rt = ragged_tensor.RaggedTensor.from_row_splits(
220 rt = ragged_tensor.RaggedTensor.from_row_splits(
229 rt = ragged_tensor.RaggedTensor.from_row_splits(
306 rt = ragged_tensor.RaggedTensor.from_row_splits(
314 rt = ragged_tensor.RaggedTensor.from_row_splits(
334 rt = ragged_tensor.RaggedTensor.from_row_splits(
343 rt = ragged_tensor.RaggedTensor.from_row_splits(
Dkeras_tensor.py476 result = ragged_tensor.RaggedTensor.from_row_splits(
480 result = ragged_tensor.RaggedTensor.from_uniform_row_length(
488 RaggedKerasTensor._overload_operator(ragged_tensor.RaggedTensor, '__add__') # pylint: disable=prot…
489 RaggedKerasTensor._overload_operator(ragged_tensor.RaggedTensor, '__radd__') # pylint: disable=pro…
490 RaggedKerasTensor._overload_operator(ragged_tensor.RaggedTensor, '__mul__') # pylint: disable=prot…
491 RaggedKerasTensor._overload_operator(ragged_tensor.RaggedTensor, '__rmul__') # pylint: disable=pro…
586 (ragged_tensor.RaggedTensor, RaggedKerasTensor),
/external/tensorflow/tensorflow/python/ops/
Dparsing_config.py716 if isinstance(rt, ragged_tensor.RaggedTensor):
732 rt = ragged_tensor.RaggedTensor.from_row_splits(
771 if isinstance(values, ragged_tensor.RaggedTensor):
773 return ragged_tensor.RaggedTensor.from_uniform_row_length(
781 return ragged_tensor.RaggedTensor.from_row_splits(
784 return ragged_tensor.RaggedTensor.from_row_lengths(
787 return ragged_tensor.RaggedTensor.from_row_starts(
790 return ragged_tensor.RaggedTensor.from_row_limits(
793 return ragged_tensor.RaggedTensor.from_value_rowids(
822 return ragged_tensor.RaggedTensor.from_row_splits(
[all …]
Dbincount_ops.py162 if isinstance(arr, ragged_tensor.RaggedTensor):
186 elif isinstance(arr, ragged_tensor.RaggedTensor):
204 elif isinstance(arr, ragged_tensor.RaggedTensor):
414 elif isinstance(values, ragged_tensor.RaggedTensor):
433 elif isinstance(values, ragged_tensor.RaggedTensor):
509 if not isinstance(weights, ragged_tensor.RaggedTensor):

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