tf.keras.wrappers.scikit_learn.KerasRegressor

TensorFlow 1 version

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Transposes the last two dimensions of and conjugates tensor matrix.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.linalg.adjoint

tf.linalg.adjoint(
    matrix, name=None
)

For example:

x = tf.constant([[1 + 1j, 2 + 2j, 3 + 3j],
                 [4 + 4j, 5 + 5j, 6 + 6j]])
tf.linalg.adjoint(x)  # [[1 - 1j, 4 - 4j],
                      #  [2 - 2j, 5 - 5j],
                      #  [3 - 3j, 6 - 6j]]

Args
`matrix`	A `Tensor`. Must be `float16`, `float32`, `float64`, `complex64`, or `complex128` with shape `[..., M, M]`.
`name`	A name to give this `Op` (optional).

Returns
The adjoint (a.k.a. Hermitian transpose a.k.a. conjugate transpose) of matrix.

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tf.keras / wrappers / wrappers.scikit_learn.KerasRegressor

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For example:

Args

Returns