tf.broadcast_static_shape
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Computes the shape of a broadcast given known shapes.
tf.broadcast_static_shape(
shape_x, shape_y
)
When shape_x and shape_y are fully known TensorShapes this computes a
TensorShape which is the shape of the result of a broadcasting op applied in
tensors of shapes shape_x and shape_y.
For example, if shape_x is TensorShape([1, 2, 3]) and shape_y is
TensorShape([5, 1, 3]), the result is a TensorShape whose value is
TensorShape([5, 2, 3]).
This is useful when validating the result of a broadcasting operation when the
tensors have statically known shapes.
Example:
shape_x = tf.TensorShape([1, 2, 3])
shape_y = tf.TensorShape([5, 1 ,3])
tf.broadcast_static_shape(shape_x, shape_y)
TensorShape([5, 2, 3])
Args |
|---|
shape_x
|
A TensorShape
|
shape_y
|
A TensorShape
|
Returns |
|---|
A TensorShape representing the broadcasted shape.
|
Raises |
|---|
ValueError
|
If the two shapes can not be broadcasted.
|
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Last updated 2024-04-26 UTC.
[null,null,["Last updated 2024-04-26 UTC."],[],[],null,["# tf.broadcast_static_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#L560-L593) |\n\nComputes the shape of a broadcast given known 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_static_shape`](https://www.tensorflow.org/api_docs/python/tf/broadcast_static_shape)\n\n\u003cbr /\u003e\n\n tf.broadcast_static_shape(\n shape_x, shape_y\n )\n\nWhen `shape_x` and `shape_y` are fully known `TensorShape`s this computes a\n`TensorShape` which is the shape of the result of a broadcasting op applied in\ntensors of shapes `shape_x` and `shape_y`.\n\nFor example, if shape_x is `TensorShape([1, 2, 3])` and shape_y is\n`TensorShape([5, 1, 3])`, the result is a TensorShape whose value is\n`TensorShape([5, 2, 3])`.\n\nThis is useful when validating the result of a broadcasting operation when the\ntensors have statically known shapes.\n\n#### Example:\n\n shape_x = tf.TensorShape([1, 2, 3])\n shape_y = tf.TensorShape([5, 1 ,3])\n tf.broadcast_static_shape(shape_x, shape_y)\n TensorShape([5, 2, 3])\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------|-----------------|\n| `shape_x` | A `TensorShape` |\n| `shape_y` | A `TensorShape` |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `TensorShape` 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| `ValueError` | If the two shapes can not be broadcasted. |\n\n\u003cbr /\u003e"]]
View source on GitHub