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[TF] Change APIs to use Int instead of Int32. #24012

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Merged
merged 8 commits into from
Apr 16, 2019
Merged

[TF] Change APIs to use Int instead of Int32. #24012

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34ede4a
[TF] Change APIs to use `Int` instead of `Int32`.
dan-zheng Apr 13, 2019
739e6c2
Temporarily use friend `swift-apis` branch.
dan-zheng Apr 13, 2019
1ebd796
Merge branch 'tensorflow-real' into use-int-in-tf-apis
dan-zheng Apr 15, 2019
2281fbd
Address feedback from @rxwei.
dan-zheng Apr 15, 2019
dca20f7
Merge branch 'tensorflow-real' into use-int-in-tf-apis
dan-zheng Apr 16, 2019
6960e35
Merge branch 'tensorflow-real' into use-int-in-tf-apis
dan-zheng Apr 16, 2019
eefcd07
Disable newly failing GPE tests.
dan-zheng Apr 16, 2019
ae1f0db
Update checkout.
dan-zheng Apr 16, 2019
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9 changes: 2 additions & 7 deletions stdlib/public/TensorFlow/CompilerRuntime.swift
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Original file line number Diff line number Diff line change
Expand Up @@ -1910,7 +1910,7 @@ func _TFCOpSetAttrTensorShapeArray(_ op: CTFEOp,
_ value: Array<TensorShape>,
_ status: CTFStatus) {
let flattenedDims = value.flatMap { $0.dimensions.map(Int64.init) }
let ranks = value.map { $0.rank }
let ranks = value.map { Int32($0.rank) }
setAttrShapeList(op: op, attrName: attrName, flattenedDims: flattenedDims,
ranks: ranks, status: status)
}
Expand All @@ -1927,12 +1927,7 @@ func _TFCOpSetAttrOptionalTensorShapeArray(_ op: CTFEOp,
}
return []
}
let ranks = value.map { tensorShapeOpt -> Int32 in
if let tensorShape = tensorShapeOpt {
return tensorShape.rank
}
return -1
}
let ranks = value.map { shape in (shape?.rank).map(Int32.init) ?? -1 }
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Why are the parentheses necessary?

setAttrShapeList(op: op, attrName: attrName, flattenedDims: flattenedDims,
ranks: ranks, status: status)
}
Expand Down
2 changes: 1 addition & 1 deletion stdlib/public/TensorFlow/CompositeMath.swift
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Expand Up @@ -44,7 +44,7 @@ public func softmax<T : FloatingPoint>(_ x: Tensor<T>) -> Tensor<T> {
/// Specifically, computes `exp(x) / exp(x).sum(alongAxes: axis)`.
@inlinable @inline(__always)
public func softmax<T : TensorFlowFloatingPoint>(
_ x: Tensor<T>, alongAxis axis: Int32
_ x: Tensor<T>, alongAxis axis: Int
) -> Tensor<T> {
let expx = exp(x)
return expx / expx.sum(alongAxes: axis)
Expand Down
17 changes: 13 additions & 4 deletions stdlib/public/TensorFlow/Gradients.swift
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Expand Up @@ -509,15 +509,15 @@ extension Tensor where Scalar : TensorFlowFloatingPoint {

@inlinable
func _vjpTransposed(
withPermutations permutations: [Int32]
withPermutations permutations: [Int]
) -> (Tensor, (Tensor) -> Tensor) {
let value = transposed(withPermutations: permutations)
return (value, { $0.transposed(withPermutations: permutations) })
}

@inlinable
func _vjpTransposed(
withPermutations permutations: Int32...
withPermutations permutations: Int...
) -> (Tensor, (Tensor) -> Tensor) {
let value = transposed(withPermutations: permutations)
return (value, { $0.transposed(withPermutations: permutations) })
Expand Down Expand Up @@ -545,7 +545,7 @@ extension Tensor where Scalar : TensorFlowFloatingPoint {
}

@inlinable
func _vjpSqueezingShape(at axes: [Int32]) -> (Tensor, (Tensor) -> Tensor) {
func _vjpSqueezingShape(at axes: [Int]) -> (Tensor, (Tensor) -> Tensor) {
let value = squeezingShape(at: axes)
return (value, { [shape = shapeTensor] v in
v.reshaped(toShape: shape)
Expand All @@ -554,7 +554,7 @@ extension Tensor where Scalar : TensorFlowFloatingPoint {

@inlinable
func _vjpExpandingShape(
at shapeIndex: Int32
at shapeIndex: Int
) -> (Tensor, (Tensor) -> Tensor) {
let value = expandingShape(at: shapeIndex)
return (value, { v in
Expand Down Expand Up @@ -591,6 +591,15 @@ extension Tensor where Scalar : TensorFlowFloatingPoint {
})
}

@inlinable
func _vjpMean(squeezingAxes axes: [Int]) -> (Tensor, (Tensor) -> Tensor) {
let value = mean(squeezingAxes: axes)
return (value, { [shape = shapeTensor,
count = axes.map { shape[$0] }.reduce(1, *)] in
$0.broadcast(toShape: shape) / Tensor(Scalar(count))
})
}

@inlinable
func _vjpMean(
squeezingAxes axes: Tensor<Int32>
Expand Down
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