def testTensorParamsAndTensorIndices(self):
params = ['a', 'b', 'c', 'd', 'e']
indices = [2, 0, 2, 1]
self.assertRaggedEqual(ragged_array_ops.gather(params, indices),
[b'c', b'a', b'c', b'b'])
self.assertIsInstance(ragged_array_ops.gather(params, indices),
ops.Tensor)
def testDocStringExamples(self):
params = constant_op.constant(['a', 'b', 'c', 'd', 'e'])
indices = constant_op.constant([3, 1, 2, 1, 0])
ragged_params = ragged_factory_ops.constant([['a', 'b', 'c'], ['d'],
[], ['e']])
ragged_indices = ragged_factory_ops.constant([[3, 1, 2], [1], [], [0]])
self.assertRaggedEqual(ragged_array_ops.gather(params, ragged_indices),
[[b'd', b'b', b'c'], [b'b'], [], [b'a']])
self.assertRaggedEqual(
ragged_array_ops.gather(ragged_params, indices),
[[b'e'], [b'd'], [], [b'd'], [b'a', b'b', b'c']])
self.assertRaggedEqual(
ragged_array_ops.gather(ragged_params, ragged_indices),
[[[b'e'], [b'd'], []], [[b'd']], [], [[b'a', b'b', b'c']]])
def testRaggedParamsAndTensorIndices(self):
params = ragged_factory_ops.constant([['a', 'b'], ['c', 'd', 'e'],
['f'], [], ['g']])
indices = [2, 0, 2, 1]
self.assertRaggedEqual(
ragged_array_ops.gather(params, indices),
[[b'f'], [b'a', b'b'], [b'f'], [b'c', b'd', b'e']])
def testOutOfBoundsError(self):
tensor_params = ['a', 'b', 'c']
tensor_indices = [0, 1, 2]
ragged_params = ragged_factory_ops.constant([['a', 'b'], ['c']])
ragged_indices = ragged_factory_ops.constant([[0, 3]])
with self.assertRaisesRegexp(errors.InvalidArgumentError,
r'indices\[1\] = 3 is not in \[0, 3\)'):
self.evaluate(
ragged_array_ops.gather(tensor_params, ragged_indices))
with self.assertRaisesRegexp(errors.InvalidArgumentError,
r'indices\[2\] = 2 is not in \[0, 2\)'):
self.evaluate(
ragged_array_ops.gather(ragged_params, tensor_indices))
with self.assertRaisesRegexp(errors.InvalidArgumentError,
r'indices\[1\] = 3 is not in \[0, 2\)'):
self.evaluate(
ragged_array_ops.gather(ragged_params, ragged_indices))
def _ragged_gather_v1(params, indices, validate_indices=None, name=None,
axis=0):
return ragged_array_ops.gather(
params=params,
indices=indices,
validate_indices=validate_indices,
axis=axis,
name=name)
def testTensorParamsAnd4DRaggedIndices(self):
indices = ragged_factory_ops.constant(
[[[[3, 4], [0, 6]], []], [[[2, 1], [1, 0]], [[2, 5]], [[2, 3]]],
[[[1, 0]]]], # pyformat: disable
ragged_rank=2,
inner_shape=(2, ))
params = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
self.assertRaggedEqual(
ragged_array_ops.gather(params, indices),
[[[[b'd', b'e'], [b'a', b'g']], []],
[[[b'c', b'b'], [b'b', b'a']], [[b'c', b'f']], [[b'c', b'd']]],
[[[b'b', b'a']]]]) # pyformat: disable
def testRaggedParamsAndRaggedIndices(self):
params = ragged_factory_ops.constant([['a', 'b'], ['c', 'd', 'e'],
['f'], [], ['g']])
indices = ragged_factory_ops.constant([[2, 1], [1, 2, 0], [3]])
self.assertRaggedEqual(
ragged_array_ops.gather(params, indices),
[
[[b'f'], [b'c', b'd', b'e']], # [[p[2], p[1] ],
[[b'c', b'd', b'e'], [b'f'], [b'a', b'b']
], # [p[1], p[2], p[0]],
[[]]
] # [p[3] ]]
) # pyformat: disable
def test3DRaggedParamsAnd2DTensorIndices(self):
params = ragged_factory_ops.constant([[['a', 'b'], []],
[['c', 'd'], ['e'], ['f']],
[['g']]])
indices = [[1, 2], [0, 1], [2, 2]]
self.assertRaggedEqual(
ragged_array_ops.gather(params, indices),
[
[[[b'c', b'd'], [b'e'], [b'f']], [[b'g']]], # [[p1, p2],
[[[b'a', b'b'], []], [[b'c', b'd'], [b'e'], [b'f']]
], # [p0, p1],
[[[b'g']], [[b'g']]]
] # [p2, p2]]
) # pyformat: disable
def _build_ragged_tensor_from_value_ranges(starts, limits, step, values):
"""Returns a `RaggedTensor` containing the specified sequences of values.
Returns a RaggedTensor `output` where:
```python
output.shape[0] = starts.shape[0]
output[i] = values[starts[i]:limits[i]:step]
```
Requires that `starts.shape == limits.shape` and
`0 <= starts[i] <= limits[i] <= values.shape[0]`.
Args:
starts: 1D integer Tensor specifying the start indices for the sequences of
values to include.
limits: 1D integer Tensor specifying the limit indices for the sequences of
values to include.
step: Integer value specifying the step size for strided slices.
values: The set of values to select from.
Returns:
A `RaggedTensor`.
Raises:
ValueError: Until the prerequisite ops are checked in.
"""
# Use `ragged_range` to get the index of each value we should include.
if step is None:
step = 1
step = ops.convert_to_tensor(step, name="step")
if step.dtype.is_integer:
step = math_ops.cast(step, dtypes.int64)
else:
raise TypeError("slice strides must be integers or None")
value_indices = ragged_math_ops.range(starts, limits, step)
# Use `ragged_gather` or `array_ops.gather` to collect the values.
if isinstance(values, ragged_tensor.RaggedTensor):
gathered_values = ragged_array_ops.gather(params=values,
indices=value_indices.values)
else:
gathered_values = array_ops.gather(params=values,
indices=value_indices.values)
# Assemble the RaggedTensor from splits & values.
return value_indices.with_values(gathered_values)
def _build_ragged_tensor_from_value_ranges(starts, limits, step, values):
"""Returns a `RaggedTensor` containing the specified sequences of values.
Returns a RaggedTensor `output` where:
```python
output.shape[0] = starts.shape[0]
output[i] = values[starts[i]:limits[i]:step]
```
Requires that `starts.shape == limits.shape` and
`0 <= starts[i] <= limits[i] <= values.shape[0]`.
Args:
starts: 1D integer Tensor specifying the start indices for the sequences of
values to include.
limits: 1D integer Tensor specifying the limit indices for the sequences of
values to include.
step: Integer value specifying the step size for strided slices.
values: The set of values to select from.
Returns:
A `RaggedTensor`.
Raises:
ValueError: Until the prerequisite ops are checked in.
"""
# Use `ragged_range` to get the index of each value we should include.
if step is None:
step = 1
step = ops.convert_to_tensor(step, name="step")
if step.dtype.is_integer:
step = math_ops.cast(step, dtypes.int64)
else:
raise TypeError("slice strides must be integers or None")
value_indices = ragged_math_ops.range(starts, limits, step)
# Use `ragged_gather` or `array_ops.gather` to collect the values.
if isinstance(values, ragged_tensor.RaggedTensor):
gathered_values = ragged_array_ops.gather(
params=values, indices=value_indices.values)
else:
gathered_values = array_ops.gather(
params=values, indices=value_indices.values)
# Assemble the RaggedTensor from splits & values.
return value_indices.with_values(gathered_values)
def testTensorParamsAndRaggedIndices(self):
params = ['a', 'b', 'c', 'd', 'e']
indices = ragged_factory_ops.constant([[2, 1], [1, 2, 0], [3]])
self.assertRaggedEqual(ragged_array_ops.gather(params, indices),
[[b'c', b'b'], [b'b', b'c', b'a'], [b'd']])
