tf.strings.to_number
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Converts each string in the input Tensor to the specified numeric type.
tf.strings.to_number(
input,
out_type=tf.dtypes.float32,
name=None
)
Used in the notebooks
| Used in the guide |
Used in the tutorials |
|
|
|
(Note that int32 overflow results in an error while float overflow
results in a rounded value.)
Examples:
tf.strings.to_number("1.55")
<tf.Tensor: shape=(), dtype=float32, numpy=1.55>
tf.strings.to_number("3", tf.int32)
<tf.Tensor: shape=(), dtype=int32, numpy=3>
Args |
|---|
input
|
A Tensor of type string.
|
out_type
|
An optional tf.DType from: tf.float32, tf.float64, tf.int32,
tf.int64. Defaults to tf.float32.
The numeric type to interpret each string in string_tensor as.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor of type out_type.
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.strings.to_number\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/string_ops.py#L462-L488) |\n\nConverts each string in the input Tensor to the specified numeric type. \n\n tf.strings.to_number(\n input,\n out_type=../../tf/dtypes#float32,\n name=None\n )\n\n### Used in the notebooks\n\n| Used in the guide | Used in the tutorials |\n|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| - [Introduction to Tensors](https://www.tensorflow.org/guide/tensor) - [Migrating Keras 2 code to multi-backend Keras 3](https://www.tensorflow.org/guide/keras/migrating_to_keras_3) - [Signatures in TensorFlow Lite](https://www.tensorflow.org/lite/guide/signatures) | - [Robust machine learning on streaming data using Kafka and Tensorflow-IO](https://www.tensorflow.org/io/tutorials/kafka) - [TensorFlow 2 TPUEmbeddingLayer: Quick Start](https://www.tensorflow.org/recommenders/examples/tpu_embedding_layer) - [Sending Different Data To Particular Clients With tff.federated_select](https://www.tensorflow.org/federated/tutorials/federated_select) |\n\n(Note that int32 overflow results in an error while float overflow\nresults in a rounded value.)\n\n#### Examples:\n\n tf.strings.to_number(\"1.55\")\n \u003ctf.Tensor: shape=(), dtype=float32, numpy=1.55\u003e\n tf.strings.to_number(\"3\", tf.int32)\n \u003ctf.Tensor: shape=(), dtype=int32, numpy=3\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `input` | A `Tensor` of type `string`. |\n| `out_type` | An optional [`tf.DType`](../../tf/dtypes/DType) from: `tf.float32, tf.float64, tf.int32, tf.int64`. Defaults to `tf.float32`. The numeric type to interpret each string in `string_tensor` as. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor` of type `out_type`. ||\n\n\u003cbr /\u003e"]]
View source on GitHub