def string_format(template, inputs, placeholder="{}", summarize=3, name=None):
r"""Formats a string template using a list of tensors.
Formats a string template using a list of tensors, abbreviating tensors by
only printing the first and last `summarize` elements of each dimension
(recursively). If formatting only one tensor into a template, the tensor does
not have to be wrapped in a list.
Example:
Formatting a single-tensor template:
>>> tensor = tf.range(5)
>>> tf.strings.format("tensor: {}, suffix", tensor)
<tf.Tensor: shape=(), dtype=string, numpy=b'tensor: [0 1 2 3 4], suffix'>
Formatting a multi-tensor template:
>>> tensor_a = tf.range(2)
>>> tensor_b = tf.range(1, 4, 2)
>>> tf.strings.format("a: {}, b: {}, suffix", (tensor_a, tensor_b))
<tf.Tensor: shape=(), dtype=string, numpy=b'a: [0 1], b: [1 3], suffix'>
Args:
template: A string template to format tensor values into.
inputs: A list of `Tensor` objects, or a single Tensor.
The list of tensors to format into the template string. If a solitary
tensor is passed in, the input tensor will automatically be wrapped as a
list.
placeholder: An optional `string`. Defaults to `{}`.
At each placeholder occurring in the template, a subsequent tensor
will be inserted.
summarize: An optional `int`. Defaults to `3`.
When formatting the tensors, show the first and last `summarize`
entries of each tensor dimension (recursively). If set to -1, all
elements of the tensor will be shown.
name: A name for the operation (optional).
Returns:
A scalar `Tensor` of type `string`.
Raises:
ValueError: if the number of placeholders does not match the number of
inputs.
"""
# If there is only one tensor to format, we will automatically wrap it in a
# list to simplify the user experience
if tensor_util.is_tensor(inputs):
inputs = [inputs]
if template.count(placeholder) != len(inputs):
raise ValueError(
"%s placeholder(s) in template does not match %s tensor(s)"
" provided as input" % (template.count(placeholder), len(inputs)))
return gen_string_ops.string_format(inputs,
template=template,
placeholder=placeholder,
summarize=summarize,
name=name)
def string_format(template, inputs, placeholder="{}", summarize=3, name=None):
r"""Formats a string template using a list of tensors.
Formats a string template using a list of tensors, abbreviating tensors by
only printing the first and last `summarize` elements of each dimension
(recursively). If formatting only one tensor into a template, the tensor does
not have to be wrapped in a list.
Example:
Formatting a single-tensor template:
```python
sess = tf.Session()
with sess.as_default():
tensor = tf.range(10)
formatted = tf.strings.format("tensor: {}, suffix", tensor)
out = sess.run(formatted)
expected = "tensor: [0 1 2 ... 7 8 9], suffix"
assert(out.decode() == expected)
```
Formatting a multi-tensor template:
```python
sess = tf.Session()
with sess.as_default():
tensor_one = tf.reshape(tf.range(100), [10, 10])
tensor_two = tf.range(10)
formatted = tf.strings.format("first: {}, second: {}, suffix",
(tensor_one, tensor_two))
out = sess.run(formatted)
expected = ("first: [[0 1 2 ... 7 8 9]\n"
" [10 11 12 ... 17 18 19]\n"
" [20 21 22 ... 27 28 29]\n"
" ...\n"
" [70 71 72 ... 77 78 79]\n"
" [80 81 82 ... 87 88 89]\n"
" [90 91 92 ... 97 98 99]], second: [0 1 2 ... 7 8 9], suffix")
assert(out.decode() == expected)
```
Args:
template: A string template to format tensor values into.
inputs: A list of `Tensor` objects, or a single Tensor.
The list of tensors to format into the template string. If a solitary
tensor is passed in, the input tensor will automatically be wrapped as a
list.
placeholder: An optional `string`. Defaults to `{}`.
At each placeholder occurring in the template, a subsequent tensor
will be inserted.
summarize: An optional `int`. Defaults to `3`.
When formatting the tensors, show the first and last `summarize`
entries of each tensor dimension (recursively). If set to -1, all
elements of the tensor will be shown.
name: A name for the operation (optional).
Returns:
A scalar `Tensor` of type `string`.
Raises:
ValueError: if the number of placeholders does not match the number of
inputs.
"""
# If there is only one tensor to format, we will automatically wrap it in a
# list to simplify the user experience
if tensor_util.is_tensor(inputs):
inputs = [inputs]
if template.count(placeholder) != len(inputs):
raise ValueError("%s placeholder(s) in template does not match %s tensor(s)"
" provided as input" % (template.count(placeholder),
len(inputs)))
return gen_string_ops.string_format(inputs,
template=template,
placeholder=placeholder,
summarize=summarize,
name=name)
