tf.compat.v1.squeeze | TensorFlow v2.16.1 (original) (raw)
tf.compat.v1.squeeze
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Removes dimensions of size 1 from the shape of a tensor. (deprecated arguments)
tf.compat.v1.squeeze(
input, axis=None, name=None, squeeze_dims=None
)
Used in the notebooks
| Used in the tutorials |
|---|
| Wiki40B Language Models |
Given a tensor input, this operation returns a tensor of the same type with all dimensions of size 1 removed. If you don't want to remove all size 1 dimensions, you can remove specific size 1 dimensions by specifyingaxis.
For example:
# 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
t = tf.ones([1, 2, 1, 3, 1, 1])
print(tf.shape(tf.squeeze(t)).numpy())
[2 3]
Or, to remove specific size 1 dimensions:
# 't' is a tensor of shape [1, 2, 1, 3, 1, 1]
t = tf.ones([1, 2, 1, 3, 1, 1])
print(tf.shape(tf.squeeze(t, [2, 4])).numpy())
[1 2 3 1]
| Args | |
|---|---|
| input | A Tensor. The input to squeeze. |
| axis | An optional list of ints. Defaults to []. If specified, only squeezes the dimensions listed. The dimension index starts at 0. It is an error to squeeze a dimension that is not 1. Must be in the range[-rank(input), rank(input)). Must be specified if input is aRaggedTensor. |
| name | A name for the operation (optional). |
| squeeze_dims | Deprecated keyword argument that is now axis. |
| Returns |
|---|
| A Tensor. Has the same type as input. Contains the same data as input, but has one or more dimensions of size 1 removed. |
| Raises | |
|---|---|
| ValueError | When both squeeze_dims and axis are specified. |