forked from kscience/kmath
hotfix sequence
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0365d41f31
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078686a046
@ -34,7 +34,8 @@ public open class BufferedTensor<T>(
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public fun vectorSequence(): Sequence<MutableStructure1D<T>> = sequence {
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public fun vectorSequence(): Sequence<MutableStructure1D<T>> = sequence {
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check(shape.size >= 1) {"todo"}
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check(shape.size >= 1) {"todo"}
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val vectorOffset = linearStructure.strides[0]
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val n = shape.size
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val vectorOffset = shape[n - 1]
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val vectorShape = intArrayOf(shape.last())
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val vectorShape = intArrayOf(shape.last())
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for (offset in 0 until numel step vectorOffset) {
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for (offset in 0 until numel step vectorOffset) {
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val vector = BufferedTensor<T>(vectorShape, buffer, offset).as1D()
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val vector = BufferedTensor<T>(vectorShape, buffer, offset).as1D()
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@ -44,8 +45,9 @@ public open class BufferedTensor<T>(
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public fun matrixSequence(): Sequence<MutableStructure2D<T>> = sequence {
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public fun matrixSequence(): Sequence<MutableStructure2D<T>> = sequence {
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check(shape.size >= 2) {"todo"}
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check(shape.size >= 2) {"todo"}
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val matrixOffset = linearStructure.strides[1]
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val n = shape.size
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val matrixShape = intArrayOf(shape[shape.size - 2], shape.last()) //todo better way?
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val matrixOffset = shape[n - 1] * shape[n - 2]
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val matrixShape = intArrayOf(shape[n - 2], shape[n - 1]) //todo better way?
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for (offset in 0 until numel step matrixOffset) {
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for (offset in 0 until numel step matrixOffset) {
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val matrix = BufferedTensor<T>(matrixShape, buffer, offset).as2D()
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val matrix = BufferedTensor<T>(matrixShape, buffer, offset).as2D()
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yield(matrix)
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yield(matrix)
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