add chol
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@ -30,6 +30,7 @@ graph(::typeof(mean), x, dim=nothing) = TensorFlow.reduce_mean(x;axis=dim)
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graph(::typeof(svd), x) = svd(x)
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graph(::typeof(svd), x) = svd(x)
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graph(::typeof(size), x, dim) = TensorFlow.size(x,convert(Tensor{Int32}, dim))
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graph(::typeof(size), x, dim) = TensorFlow.size(x,convert(Tensor{Int32}, dim))
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graph(::typeof(size), x) = TensorFlow.size(x)
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graph(::typeof(size), x) = TensorFlow.size(x)
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graph(::typeof(chol), args...) = TensorFlow.transpose(TensorFlow.cholesky(args...))
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for op in (*, .*, .+, .^, log, exp, ceil, floor, sqrt, abs, cos,
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for op in (*, .*, .+, .^, log, exp, ceil, floor, sqrt, abs, cos,
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sin, tan, atan, asin, acos, tanh, lgamma, erf, erfc, real, imag, conj,
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sin, tan, atan, asin, acos, tanh, lgamma, erf, erfc, real, imag, conj,
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@ -44,6 +44,9 @@ end
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A = randn(4,5)
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A = randn(4,5)
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@test tf(@net x -> size(x))(A) == [4,5]
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@test tf(@net x -> size(x))(A) == [4,5]
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@test tf(@net (x,y) -> size(x,y))(A,1) == 4
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@test tf(@net (x,y) -> size(x,y))(A,1) == 4
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A = randn(6,5)
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A = A'*A
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@test tf(@net x -> chol(x))(A) ≈ chol(A)
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end
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end
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end
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end
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