tf.segment_prod()

tf.segment_prod(data, segment_ids, name=None) Computes the product along segments of a tensor. Read

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tf.rsqrt()

tf.rsqrt(x, name=None) Computes reciprocal of square root of x element-wise. I.e., \(y = 1 / \sqrt{x}\)

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tf.maximum()

tf.maximum(x, y, name=None) Returns the max of x and y (i.e. x > y ? x : y) element-wise. NOTE:

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tf.square()

tf.square(x, name=None) Computes square of x element-wise. I.e., (y = x * x = x^2).

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tf.matrix_solve()

tf.matrix_solve(matrix, rhs, adjoint=None, name=None) Solves systems of linear equations. Matrix

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tf.self_adjoint_eig()

tf.self_adjoint_eig(tensor, name=None) Computes the eigen decomposition of a batch of self-adjoint matrices.

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tf.reduce_sum()

tf.reduce_sum(input_tensor, reduction_indices=None, keep_dims=False, name=None) Computes the sum of elements across dimensions

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tf.reduce_mean()

tf.reduce_mean(input_tensor, reduction_indices=None, keep_dims=False, name=None) Computes the mean of elements across dimensions

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tf.reduce_any()

tf.reduce_any(input_tensor, reduction_indices=None, keep_dims=False, name=None) Computes the "logical or" of elements across dimensions

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tf.real()

tf.real(input, name=None) Returns the real part of a complex number. Given a tensor input

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