tf.shape_n Stay organized with collections Save and categorize content based on your preferences.
Returns shape of a list of tensors.
tf.shape_n( input, out_type=tf.dtypes.int32, name=None )
Given a list of tensors, tf.shape_n is much faster than applying tf.shape to each tensor individually.
>>> a = tf.ones([1, 2]) >>> b = tf.ones([2, 3]) >>> c = tf.ones([3, 4]) >>> tf.shape_n([a, b, c]) [<tf.Tensor: shape=(2,), dtype=int32, numpy=array([1, 2], dtype=int32)>, <tf.Tensor: shape=(2,), dtype=int32, numpy=array([2, 3], dtype=int32)>, <tf.Tensor: shape=(2,), dtype=int32, numpy=array([3, 4], dtype=int32)>]
Args |
|---|
input | A list of at least 1 Tensor object with the same dtype. |
out_type | The specified output type of the operation (int32 or int64). Defaults to tf.int32(optional). |
name | A name for the operation (optional). |
Returns |
|---|
A list of Tensor specifying the shape of each input tensor with type of out_type. |
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Last updated 2024-04-26 UTC.
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