tf.size

Returns the size of a tensor.

tf.size(
    input, out_type=None, name=None
)

Used in the notebooks

Used in the guide	Used in the tutorials
Matrix approximation with Core APIs Introduction to Tensors BERT Preprocessing with TF Text	Scalable model compression Client-efficient large-model federated learning via `federated_select` and sparse aggregation Sending Different Data To Particular Clients With tff.federated_select Human Pose Classification with MoveNet and TensorFlow Lite Federated Learning for Image Classification

For example:

t = tf.constant([[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]])
tf.size(t)
<tf.Tensor: shape=(), dtype=int32, numpy=12>

Args
`input`	A `Tensor` or `SparseTensor`.
`out_type`	(Optional) The specified non-quantized numeric output type of the operation. Defaults to `tf.int32`. (Note: there is an experimental flag, `tf_shape_default_int64` that changes the default to `tf.int64`. This is an unsupported, experimental setting that causes known breakages.)
`name`	A name for the operation (optional).

Returns
A `Tensor` of type `out_type`. Defaults to `tf.int32`.

numpy compatibility

Equivalent to np.size()

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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/size