tf.broadcast_dynamic_shape
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Computes the shape of a broadcast given symbolic shapes.
tf.broadcast_dynamic_shape(
shape_x, shape_y
)
When shape_x and shape_y are Tensors representing shapes (i.e. the result
of calling tf.shape on another Tensor) this computes a Tensor which is the
shape of the result of a broadcasting op applied in tensors of shapes
shape_x and shape_y.
This is useful when validating the result of a broadcasting operation when the
tensors do not have statically known shapes.
Example:
shape_x = (1, 2, 3)
shape_y = (5, 1, 3)
tf.broadcast_dynamic_shape(shape_x, shape_y)
<tf.Tensor: shape=(3,), dtype=int32, numpy=array([5, 2, 3], ...>
Args |
|---|
shape_x
|
A rank 1 integer Tensor, representing the shape of x.
|
shape_y
|
A rank 1 integer Tensor, representing the shape of y.
|
Returns |
|---|
A rank 1 integer Tensor representing the broadcasted shape.
|
Raises |
|---|
InvalidArgumentError
|
If the two shapes are incompatible for
broadcasting.
|
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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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26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.broadcast_dynamic_shape\n\n\u003cbr /\u003e\n\n|-----------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/array_ops.py#L526-L557) |\n\nComputes the shape of a broadcast given symbolic shapes.\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.broadcast_dynamic_shape`](https://www.tensorflow.org/api_docs/python/tf/broadcast_dynamic_shape)\n\n\u003cbr /\u003e\n\n tf.broadcast_dynamic_shape(\n shape_x, shape_y\n )\n\nWhen `shape_x` and `shape_y` are Tensors representing shapes (i.e. the result\nof calling tf.shape on another Tensor) this computes a Tensor which is the\nshape of the result of a broadcasting op applied in tensors of shapes\n`shape_x` and `shape_y`.\n\nThis is useful when validating the result of a broadcasting operation when the\ntensors do not have statically known shapes.\n\n#### Example:\n\n shape_x = (1, 2, 3)\n shape_y = (5, 1, 3)\n tf.broadcast_dynamic_shape(shape_x, shape_y)\n \u003ctf.Tensor: shape=(3,), dtype=int32, numpy=array([5, 2, 3], ...\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------|---------------------------------------------------------|\n| `shape_x` | A rank 1 integer `Tensor`, representing the shape of x. |\n| `shape_y` | A rank 1 integer `Tensor`, representing the shape of y. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A rank 1 integer `Tensor` representing the broadcasted shape. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|------------------------|------------------------------------------------------|\n| `InvalidArgumentError` | If the two shapes are incompatible for broadcasting. |\n\n\u003cbr /\u003e"]]
View source on GitHub