tf.compat.v1.sparse_to

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 specifying axis.

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 a `RaggedTensor`.
`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.

TensorFlow

tf.compat / v1 / v1.sparse_to_dense

Used in the notebooks

For example:

Args

Returns

Raises

TensorFlow

tf

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tf.compat / v1 / v1.sparse_to_dense

Used in the notebooks

For example:

Args

Returns

Raises