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added more precondition #614

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Jan 14, 2020
Merged

added more precondition #614

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ba3c911
added more precondition
SumanSudhir Jan 11, 2020
c472656
corrected plural stat
SumanSudhir Jan 11, 2020
787c920
added another precondition helper
SumanSudhir Jan 13, 2020
e1b6b40
NFC: update doc comment.
dan-zheng Jan 13, 2020
40680f5
NFC: edit doc comment.
dan-zheng Jan 14, 2020
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9 changes: 8 additions & 1 deletion Sources/TensorFlow/Operators/Basic.swift
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Original file line number Diff line number Diff line change
Expand Up @@ -1219,6 +1219,13 @@ extension Tensor {
return axis >= -rank && axis < rank
}

/// Returns `true` if the given scalar tensor is in the range `[-rank, rank)`.
@usableFromInline
internal func isAxisInRange(_ axis: Tensor<Int32>) -> Bool {
precondition(axis.rank == 0, "Axis must have rank 0.")
return areAxesInRange(axis.scalars)
}

/// Returns `true` if all given axes are in the range `[-rank, rank)`.
@usableFromInline
internal func areAxesInRange<T: BinaryInteger>(_ axes: [T]) -> Bool {
Expand All @@ -1228,7 +1235,7 @@ extension Tensor {
/// Returns `true` if all scalars of the given 1-D tensor are in the range `[-rank, rank)`.
@usableFromInline
internal func areAxesInRange(_ axes: Tensor<Int32>) -> Bool {
precondition(axes.rank == 1, "Axes must have rank 1")
precondition(axes.rank == 1, "Axes must have rank 1.")
return areAxesInRange(axes.scalars)
}
}
50 changes: 36 additions & 14 deletions Sources/TensorFlow/Operators/Math.swift
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Expand Up @@ -1543,7 +1543,8 @@ public extension Tensor {
@inlinable
@differentiable(wrt: (self, other) where Scalar: TensorFlowFloatingPoint)
func replacing(with other: Tensor, where mask: Tensor<Bool>) -> Tensor {
_Raw.select(condition: mask, t: other, e: self)
precondition(self.shape == other.shape, "`self` and `other` must have the same shape.")
return _Raw.select(condition: mask, t: other, e: self)
}
}

Expand Down Expand Up @@ -1590,6 +1591,7 @@ public extension Tensor where Scalar == Bool {
/// - Precondition: Each value in `axes` must be in the range `-rank..<rank`.
@inlinable
func all(squeezingAxes axes: Int...) -> Tensor {
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
let axes = axes.map(Int32.init)
return _Raw.all(self, reductionIndices: Tensor<Int32>(axes), keepDims: false)
}
Expand All @@ -1600,6 +1602,7 @@ public extension Tensor where Scalar == Bool {
/// - Precondition: Each value in `axes` must be in the range `-rank..<rank`.
@inlinable
func any(squeezingAxes axes: Int...) -> Tensor {
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
let axes = axes.map(Int32.init)
return _Raw.any(self, reductionIndices: Tensor<Int32>(axes), keepDims: false)
}
Expand All @@ -1610,6 +1613,7 @@ public extension Tensor where Scalar == Bool {
/// - Precondition: Each value in `axes` must be in the range `-rank..<rank`.
@inlinable
func all(alongAxes axes: Int...) -> Tensor {
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
let axes = axes.map(Int32.init)
return _Raw.all(self, reductionIndices: Tensor<Int32>(axes), keepDims: true)
}
Expand All @@ -1620,6 +1624,7 @@ public extension Tensor where Scalar == Bool {
/// - Precondition: Each value in `axes` must be in the range `-rank..<rank`.
@inlinable
func any(alongAxes axes: Int...) -> Tensor {
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
let axes = axes.map(Int32.init)
return _Raw.any(self, reductionIndices: Tensor<Int32>(axes), keepDims: true)
}
Expand Down Expand Up @@ -1650,6 +1655,7 @@ public extension Tensor where Scalar: Numeric & Comparable {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func max(squeezingAxes axes: Tensor<Int32>) -> Tensor {
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
return _Raw.max(self, reductionIndices: axes, keepDims: false)
}

Expand Down Expand Up @@ -1679,7 +1685,8 @@ public extension Tensor where Scalar: Numeric & Comparable {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func min(squeezingAxes axes: Tensor<Int32>) -> Tensor {
_Raw.min(self, reductionIndices: axes, keepDims: false)
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
return _Raw.min(self, reductionIndices: axes, keepDims: false)
}

/// Returns the minimum values along the specified axes. The reduced dimensions are removed.
Expand Down Expand Up @@ -1708,7 +1715,8 @@ public extension Tensor where Scalar: Numeric & Comparable {
/// - Precondition: Each value in `axes` must be in the range `-rank..<rank`.
@inlinable
func argmax(squeezingAxis axis: Int) -> Tensor<Int32> {
_Raw.argMax(self, dimension: Tensor<Int32>(Int32(axis)))
precondition(isAxisInRange(axis), "Axis must be in the range `[-rank, rank)`.")
return _Raw.argMax(self, dimension: Tensor<Int32>(Int32(axis)))
}

/// Returns the indices of the minimum values along the specified axes. The reduced dimensions
Expand All @@ -1717,7 +1725,8 @@ public extension Tensor where Scalar: Numeric & Comparable {
/// - Precondition: Each value in `axes` must be in the range `-rank..<rank`.
@inlinable
func argmin(squeezingAxis axis: Int) -> Tensor<Int32> {
_Raw.argMin(self, dimension: Tensor<Int32>(Int32(axis)))
precondition(isAxisInRange(axis), "Axis must be in the range `[-rank, rank)`.")
return _Raw.argMin(self, dimension: Tensor<Int32>(Int32(axis)))
}

/// Returns the minimum along the specified axes. The reduced dimensions are retained with
Expand All @@ -1727,7 +1736,8 @@ public extension Tensor where Scalar: Numeric & Comparable {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func min(alongAxes axes: Tensor<Int32>) -> Tensor {
_Raw.min(self, reductionIndices: axes, keepDims: true)
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
return _Raw.min(self, reductionIndices: axes, keepDims: true)
}

/// Returns the minimum along the specified axes. The reduced dimensions are retained with
Expand Down Expand Up @@ -1759,7 +1769,8 @@ public extension Tensor where Scalar: Numeric & Comparable {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func max(alongAxes axes: Tensor<Int32>) -> Tensor {
_Raw.max(self, reductionIndices: axes, keepDims: true)
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
return _Raw.max(self, reductionIndices: axes, keepDims: true)
}

/// Returns the minimum along the specified axes. The reduced dimensions are retained with
Expand Down Expand Up @@ -1886,7 +1897,8 @@ public extension Tensor where Scalar: Numeric {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func sum(squeezingAxes axes: Tensor<Int32>) -> Tensor {
_Raw.sum(self, reductionIndices: axes, keepDims: false)
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
return _Raw.sum(self, reductionIndices: axes, keepDims: false)
}

/// Returns the sum along the specified axes. The reduced dimensions are removed.
Expand Down Expand Up @@ -1921,7 +1933,8 @@ public extension Tensor where Scalar: Numeric {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func sum(alongAxes axes: Tensor<Int32>) -> Tensor {
_Raw.sum(self, reductionIndices: axes, keepDims: true)
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
return _Raw.sum(self, reductionIndices: axes, keepDims: true)
}

/// Returns the sum along the specified axes. The reduced dimensions are retained with value 1.
Expand Down Expand Up @@ -1953,7 +1966,8 @@ public extension Tensor where Scalar: Numeric {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func product(squeezingAxes axes: Tensor<Int32>) -> Tensor {
_Raw.prod(self, reductionIndices: axes, keepDims: false)
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
return _Raw.prod(self, reductionIndices: axes, keepDims: false)
}

/// Returns the product along the specified axes. The reduced dimensions are removed.
Expand Down Expand Up @@ -1990,7 +2004,8 @@ public extension Tensor where Scalar: Numeric {
/// - Precondition: Each value in `axes` must be in the range `-rank..<rank`.
@inlinable
func product(alongAxes axes: Tensor<Int32>) -> Tensor {
_Raw.prod(self, reductionIndices: axes, keepDims: true)
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
return _Raw.prod(self, reductionIndices: axes, keepDims: true)
}

/// Returns the product along the specified axes. The reduced dimensions are retained with
Expand Down Expand Up @@ -2021,7 +2036,8 @@ public extension Tensor where Scalar: Numeric {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func mean(squeezingAxes axes: Tensor<Int32>) -> Tensor {
_Raw.mean(self, reductionIndices: axes, keepDims: false)
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
return _Raw.mean(self, reductionIndices: axes, keepDims: false)
}

/// Returns the arithmetic mean along the specified axes. The reduced dimensions are removed.
Expand Down Expand Up @@ -2057,7 +2073,8 @@ public extension Tensor where Scalar: Numeric {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func mean(alongAxes axes: Tensor<Int32>) -> Tensor {
_Raw.mean(self, reductionIndices: axes, keepDims: true)
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
return _Raw.mean(self, reductionIndices: axes, keepDims: true)
}

/// Returns the arithmetic mean along the specified axes. The reduced dimensions are retained
Expand Down Expand Up @@ -2091,6 +2108,7 @@ public extension Tensor where Scalar: Numeric {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func variance(squeezingAxes axes: Tensor<Int32>) -> Tensor {
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
let squaredDiff = squaredDifference(self, mean(alongAxes: axes))
return squaredDiff.mean(squeezingAxes: axes)
}
Expand Down Expand Up @@ -2132,6 +2150,7 @@ public extension Tensor where Scalar: Numeric {
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
func variance(alongAxes axes: Tensor<Int32>) -> Tensor {
precondition(areAxesInRange(axes), "All axes must be in the range `[-rank, rank)`.")
let squaredDiff = squaredDifference(self, mean(alongAxes: axes))
return squaredDiff.mean(alongAxes: axes)
}
Expand Down Expand Up @@ -2229,7 +2248,8 @@ public extension Tensor where Scalar: Numeric {
exclusive: Bool = false,
reverse: Bool = false
) -> Tensor {
_Raw.cumsum(self, axis: axis, exclusive: exclusive, reverse: reverse)
precondition(isAxisInRange(axis), "Axis must be in the range `[-rank, rank)`.")
return _Raw.cumsum(self, axis: axis, exclusive: exclusive, reverse: reverse)
}

/// Returns the cumulative product of this tensor along the specified axis. By default, this
Expand Down Expand Up @@ -2294,6 +2314,7 @@ public extension Tensor where Scalar: Numeric {
/// - exclusive: Indicates whether to perform an exclusive cumulative product.
/// - reverse: Indicates whether to perform the cumulative product in reversed order.
/// - Returns: Result of the cumulative product operation.
/// - Precondition: `axis` must have rank `0`.
/// - Precondition: `axis` must be in the range `-rank..<rank`.
@inlinable
@differentiable(wrt: self where Scalar: TensorFlowFloatingPoint)
Expand All @@ -2302,7 +2323,8 @@ public extension Tensor where Scalar: Numeric {
exclusive: Bool = false,
reverse: Bool = false
) -> Tensor {
_Raw.cumprod(self, axis: axis, exclusive: exclusive, reverse: reverse)
precondition(isAxisInRange(axis), "Axis must be in the range `[-rank, rank)`.")
return _Raw.cumprod(self, axis: axis, exclusive: exclusive, reverse: reverse)
}
}

Expand Down