abstract class DenseTensor extends TensorData
A dense subkind of tensor data. Guarantees that values in all columns except the last fill the n-dimensional rectangle in lexicographic order, e.g. for a shape [2, 3]: (0, 0, value) (0, 1, value) (0, 2, value) (1, 0, value) (1, 1, value) (1, 2, value)
Note that this implies that only integral types (INT and LONG) can be used as dimensions in dense tensors.
Can be backed by byte buffers, java.util collections, Avro, Spark, etc.
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- new DenseTensor()
Abstract Value Members
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abstract
def
asList(): List[_]
- returns
the list of values in their unraveled order. This in combination with the shape is enough to restore the entire tensor, as the dimensions can be calculated from the shape.
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abstract
def
cardinality(): Int
- returns
exact number of entries in the mapping from dimensions to values.
- Definition Classes
- TensorData
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abstract
def
estimatedCardinality(): Int
- returns
conservative estimate of number of entries in the mapping from dimensions to values. Can be cheaper to evaluate than the exact one.
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- TensorData
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abstract
def
getTypes(): Array[Representable]
- returns
the types of all dimensions and the value as a single array.
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- TensorData
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abstract
def
iterator(): TensorIterator
- returns
an iterator over entries in the mapping from dimensions to the value.
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- TensorData
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def
getArity(): Int
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the arity, which is the total number of columns. As columns are dimensions plus a value, arity is by one greater than dimensionality.
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- TensorData
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final
def
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def
getShape(): Array[Long]
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the current shape of the data or the supplied shape of the data
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- TensorData
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