sparsify_tensor#
- ivy.sparsify_tensor(x, card, /, *, out=None)[source]#
Zeros out all elements in the tensor except card elements with maximum absolute values.
- Parameters:
- Return type:
- Returns:
ivy.array of shape tensor.shape
Examples
>>> x = ivy.arange(100) >>> x = ivy.reshape(x, (10, 10)) >>> sparsify_tensor(x, 10) ivy.array([[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [90, 91, 92, 93, 94, 95, 96, 97, 98, 99]])
- Array.sparsify_tensor(self, card, /, *, out=None)[source]#
ivy.Array class method variant of ivy.sparsify_tensor. This method simply wraps the function, and so the docstring for ivy.sparsify_tensor also applies to this method with minimal changes.
- Parameters:
self (array) – The tensor to sparsify.
card (int) – The number of values to keep.
out (array, optional) – Optional output array, for writing the result to.
- Return type:
Array
- Returns:
ret (array) – The sparsified tensor.
Examples
>>> x = ivy.arange(100) >>> x = ivy.reshape(x, (10, 10)) >>> x.sparsify_tensor(10) ivy.array([[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [90, 91, 92, 93, 94, 95, 96, 97, 98, 99]])
- Container.sparsify_tensor(self, card, /, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, out=None)[source]#
ivy.Container instance method variant of ivy.sparsify_tensor.
This method simply wraps the function, and so the docstring for ivy.sparsify_tensor also applies to this method with minimal changes.
- Return type:
Container