def raise_zero_rank_error():
msg = gen_string_ops.string_join([
'len requires non-zero rank, got ',
gen_string_ops.as_string(rank)
])
with ops.control_dependencies([control_flow_ops.Assert(False, [msg])]):
return constant_op.constant(0, dtype=dtypes.int32)
def string_join(inputs, separator="", name=None):
"""Perform element-wise concatenation of a list of string tensors.
Given a list of string tensors of same shape, performs element-wise
concatenation of the strings of the same index in all tensors.
>>> tf.strings.join(['abc','def']).numpy()
b'abcdef'
>>> tf.strings.join([['abc','123'],
... ['def','456'],
... ['ghi','789']]).numpy()
array([b'abcdefghi', b'123456789'], dtype=object)
>>> tf.strings.join([['abc','123'],
... ['def','456']],
... separator=" ").numpy()
array([b'abc def', b'123 456'], dtype=object)
Args:
inputs: A list of `tf.Tensor` objects of same size and `tf.string` dtype.
separator: A string added between each string being joined.
name: A name for the operation (optional).
Returns:
A `tf.string` tensor.
"""
return gen_string_ops.string_join(inputs, separator=separator, name=name)
def _tf_dataset_len(s):
l = cardinality.cardinality(s)
msg = gen_string_ops.string_join([
'len requires dataset with definitive cardinality, got ',
gen_string_ops.as_string(l)
])
# TODO (yongtang): UNKNOWN is treated as an error.
# In case there are more UNKNOWN cases for dataset, we could
# use dataset.reduce() to find out the length (in an expensive way).
with ops.control_dependencies([
control_flow_ops.Assert(
math_ops.logical_and(
math_ops.not_equal(l, cardinality.INFINITE),
math_ops.not_equal(l, cardinality.UNKNOWN)), [msg])
]):
l = array_ops.identity(l)
return l
def raise_zero_rank_error():
msg = gen_string_ops.string_join(
['len requires non-zero rank, got ',
gen_string_ops.as_string(rank)])
with ops.control_dependencies([control_flow_ops.Assert(False, [msg])]):
return constant_op.constant(0, dtype=dtypes.int32)
