tf.type_spec_from_value
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Returns a tf.TypeSpec that represents the given value.
tf.type_spec_from_value(
value
) -> tf.TypeSpec
Used in the notebooks
Examples |
|---|
>>> tf.type_spec_from_value(tf.constant([1, 2, 3]))
TensorSpec(shape=(3,), dtype=tf.int32, name=None)
>>> tf.type_spec_from_value(np.array([4.0, 5.0], np.float64))
TensorSpec(shape=(2,), dtype=tf.float64, name=None)
>>> tf.type_spec_from_value(tf.ragged.constant([[1, 2], [3, 4, 5]]))
RaggedTensorSpec(TensorShape([2, None]), tf.int32, 1, tf.int64)
example_input = tf.ragged.constant([[1, 2], [3]])
@tf.function(input_signature=[tf.type_spec_from_value(example_input)])
def f(x):
return tf.reduce_sum(x, axis=1)
|
Returns |
|---|
A TypeSpec that is compatible with value.
|
Raises |
|---|
TypeError
|
If a TypeSpec cannot be built for value, because its type
is not supported.
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.type_spec_from_value\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/framework/type_spec.py#L958-L1004) |\n\nReturns a [`tf.TypeSpec`](../tf/TypeSpec) that represents the given `value`.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.type_spec_from_value`](https://www.tensorflow.org/api_docs/python/tf/type_spec_from_value)\n\n\u003cbr /\u003e\n\n tf.type_spec_from_value(\n value\n ) -\u003e ../tf/TypeSpec\n\n### Used in the notebooks\n\n| Used in the guide |\n|----------------------------------------------------------------------|\n| - [Extension types](https://www.tensorflow.org/guide/extension_type) |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Examples -------- ||\n|---|---|\n| \u003cbr /\u003e \u003e\u003e\u003e tf.type_spec_from_value(tf.constant([1, 2, 3])) TensorSpec(shape=(3,), dtype=tf.int32, name=None) \u003e\u003e\u003e tf.type_spec_from_value(np.array([4.0, 5.0], np.float64)) TensorSpec(shape=(2,), dtype=tf.float64, name=None) \u003e\u003e\u003e tf.type_spec_from_value(tf.ragged.constant([[1, 2], [3, 4, 5]])) RaggedTensorSpec(TensorShape([2, None]), tf.int32, 1, tf.int64) example_input = tf.ragged.constant([[1, 2], [3]]) @tf.function(input_signature=[tf.type_spec_from_value(example_input)]) def f(x): return tf.reduce_sum(x, axis=1) \u003cbr /\u003e ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `value` | A value that can be accepted or returned by TensorFlow APIs. Accepted types for `value` include [`tf.Tensor`](../tf/Tensor), any value that can be converted to [`tf.Tensor`](../tf/Tensor) using [`tf.convert_to_tensor`](../tf/convert_to_tensor), and any subclass of `CompositeTensor` (such as [`tf.RaggedTensor`](../tf/RaggedTensor)). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `TypeSpec` that is compatible with `value`. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|-------------|-------------------------------------------------------------------------------|\n| `TypeError` | If a TypeSpec cannot be built for `value`, because its type is not supported. |\n\n\u003cbr /\u003e"]]
View source on GitHub