What is the difference between Dataset.from_tensors and Dataset.from_tensor_slices?

Question

I have a dataset represented as a NumPy matrix of shape (num_features, num_examples) and I wish to convert it to TensorFlow type tf.Dataset.

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Answer 1

from_tensors combines the input and returns a dataset with a single element:

t = tf.constant([[1, 2], [3, 4]])
ds = tf.data.Dataset.from_tensors(t)   # [[1, 2], [3, 4]]

from_tensor_slices creates a dataset with a separate element for each row of the input tensor:

t = tf.constant([[1, 2], [3, 4]])
ds = tf.data.Dataset.from_tensor_slices(t)   # [1, 2], [3, 4]