Tucker tensor
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class ivy.data_classes.factorized_tensor.tucker_tensor.TuckerTensor(tucker_tensor)[source]
Bases: FactorizedTensor
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__init__(tucker_tensor)[source]
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_abc_impl = <_abc._abc_data object>
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mode_dot(matrix_or_vector, mode, keep_dim, copy)[source]
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property n_param
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to_tensor()[source]
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to_unfolded(mode)[source]
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to_vec()[source]
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tucker_copy()[source]
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static tucker_mode_dot(tucker_tensor, matrix_or_vector, mode, keep_dim=False, copy=False)[source]
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static tucker_n_param(shape, rank)[source]
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static tucker_normalize(tucker_tensor)[source]
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static tucker_to_tensor(tucker_tensor, skip_factor=None, transpose_factors=False)[source]
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static tucker_to_unfolded(tucker_tensor, mode=0, skip_factor=None, transpose_factors=False)[source]
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static tucker_to_vec(tucker_tensor, skip_factor=None, transpose_factors=False)[source]
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static validate_tucker_rank(tensor_shape, rank='same', rounding='round', fixed_modes=None)[source]
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static validate_tucker_tensor(tucker_tensor)[source]
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ivy.data_classes.factorized_tensor.tucker_tensor._bisection_root_finder(fun, a, b, tol=1e-06, max_iter=100)[source]
This should have hopefully given you an overview of the tucker_tensor submodule, if you have any questions, please feel free to reach out on our discord!