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Made some more compatibility fixes to support the latest raw ops. #74

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rxwei merged 11 commits into from
Apr 3, 2019
Merged

Made some more compatibility fixes to support the latest raw ops. #74

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a686a76
Updated the convolution ops to support explicit paddings.
eaplatanios Apr 2, 2019
8494c04
Small fix.
eaplatanios Apr 2, 2019
5dfaaee
Added documentation string for the "explicit" padding scheme.
eaplatanios Apr 2, 2019
eda9514
More fixes.
eaplatanios Apr 3, 2019
77c1385
Merge branch 'conv-fix' of github.com:eaplatanios/swift-apis into con…
eaplatanios Apr 3, 2019
4cb0198
One more fix.
eaplatanios Apr 3, 2019
ef9bbe6
Made some more fixes to the convolution and pooling ops.
eaplatanios Apr 3, 2019
2809a9b
Merged upstream changes.
eaplatanios Apr 3, 2019
a72ed91
Fixed a merge error.
eaplatanios Apr 3, 2019
94dfd36
Removed support for explicit paddings.
eaplatanios Apr 3, 2019
b9f6a47
Final fix.
eaplatanios Apr 3, 2019
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22 changes: 11 additions & 11 deletions Sources/DeepLearning/Layer.swift
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Original file line number Diff line number Diff line change
Expand Up @@ -616,7 +616,7 @@ public struct TransposedConv2D: Layer {
self.activation = activation
(self.strides.0, self.strides.1) = (Int32(strides.0), Int32(strides.1))
self.padding = padding
self.paddingIndex = padding == .same ? 0 : 1
self.paddingIndex = padding == Padding.same ? 0 : 1
}

/// Returns the output obtained from applying the layer to the given input.
Expand Down Expand Up @@ -836,7 +836,7 @@ public struct MaxPool1D<Scalar: TensorFlowFloatingPoint>: Layer {
/// The stride of the sliding window for temporal dimension.
@noDerivative let stride: Int32
/// The padding algorithm for pooling.
@noDerivative let padding: Padding
@noDerivative let padding: PaddingV1

/// Creates a max pooling layer.
///
Expand All @@ -847,7 +847,7 @@ public struct MaxPool1D<Scalar: TensorFlowFloatingPoint>: Layer {
public init(
poolSize: Int,
stride: Int,
padding: Padding
padding: PaddingV1
) {
self.poolSize = Int32(poolSize)
self.stride = Int32(stride)
Expand Down Expand Up @@ -878,13 +878,13 @@ public struct MaxPool2D<Scalar: TensorFlowFloatingPoint>: Layer {
/// Strides in non-spatial dimensions must be `1`.
@noDerivative let strides: (Int32, Int32, Int32, Int32)
/// The padding algorithm for pooling.
@noDerivative let padding: Padding
@noDerivative let padding: PaddingV1

/// Creates a max pooling layer.
public init(
poolSize: (Int, Int, Int, Int),
strides: (Int, Int, Int, Int),
padding: Padding
padding: PaddingV1
) {
(self.poolSize.0, self.poolSize.1, self.poolSize.2, self.poolSize.3)
= (Int32(poolSize.0), Int32(poolSize.1), Int32(poolSize.2), Int32(poolSize.3))
Expand All @@ -899,7 +899,7 @@ public struct MaxPool2D<Scalar: TensorFlowFloatingPoint>: Layer {
/// - poolSize: Vertical and horizontal factors by which to downscale.
/// - strides: The strides.
/// - padding: The padding.
public init(poolSize: (Int, Int), strides: (Int, Int), padding: Padding = .valid) {
public init(poolSize: (Int, Int), strides: (Int, Int), padding: PaddingV1 = .valid) {
self.poolSize = (1, Int32(poolSize.0), Int32(poolSize.1), 1)
self.strides = (1, Int32(strides.0), Int32(strides.1), 1)
self.padding = padding
Expand Down Expand Up @@ -927,7 +927,7 @@ public struct AvgPool1D<Scalar: TensorFlowFloatingPoint>: Layer {
/// The stride of the sliding window for temporal dimension.
@noDerivative let stride: Int32
/// The padding algorithm for pooling.
@noDerivative let padding: Padding
@noDerivative let padding: PaddingV1

/// Creates an average pooling layer.
///
Expand All @@ -938,7 +938,7 @@ public struct AvgPool1D<Scalar: TensorFlowFloatingPoint>: Layer {
public init(
poolSize: Int,
stride: Int,
padding: Padding
padding: PaddingV1
) {
self.poolSize = Int32(poolSize)
self.stride = Int32(stride)
Expand Down Expand Up @@ -969,13 +969,13 @@ public struct AvgPool2D<Scalar: TensorFlowFloatingPoint>: Layer {
/// Strides in non-spatial dimensions must be `1`.
@noDerivative let strides: (Int32, Int32, Int32, Int32)
/// The padding algorithm for pooling.
@noDerivative let padding: Padding
@noDerivative let padding: PaddingV1

/// Creates a average pooling layer.
public init(
poolSize: (Int, Int, Int, Int),
strides: (Int, Int, Int, Int),
padding: Padding
padding: PaddingV1
) {
(self.poolSize.0, self.poolSize.1, self.poolSize.2, self.poolSize.3)
= (Int32(poolSize.0), Int32(poolSize.1), Int32(poolSize.2), Int32(poolSize.3))
Expand All @@ -990,7 +990,7 @@ public struct AvgPool2D<Scalar: TensorFlowFloatingPoint>: Layer {
/// - poolSize: Vertical and horizontal factors by which to downscale.
/// - strides: The strides.
/// - padding: The padding.
public init(poolSize: (Int, Int), strides: (Int, Int), padding: Padding = .valid) {
public init(poolSize: (Int, Int), strides: (Int, Int), padding: PaddingV1 = .valid) {
self.poolSize = (1, Int32(poolSize.0), Int32(poolSize.1), 1)
self.strides = (1, Int32(strides.0), Int32(strides.1), 1)
self.padding = padding
Expand Down
39 changes: 34 additions & 5 deletions Sources/DeepLearning/Operators.swift
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Original file line number Diff line number Diff line change
Expand Up @@ -103,7 +103,7 @@ public extension Tensor where Scalar: BinaryFloatingPoint {

/// A padding scheme. Used by padding, convolution, and pooling ops.
// @_frozen // SR-9739
public enum Padding {
public enum Padding: Equatable {
/// The "explicit" padding scheme, which is defined by an array indicating the explicit padding
/// sizes at the start and end of each dimension.
case explicit([Int32])
Expand Down Expand Up @@ -133,6 +133,35 @@ public extension Padding {
}
}

/// An older padding scheme. Used by padding, convolution, and pooling ops.
// @_frozen // SR-9739
public enum PaddingV1 {
/// The "valid" padding scheme.
case valid
/// The "same" padding scheme.
case same
}

public extension PaddingV1 {
@inlinable
var raw: Raw.Padding {
switch self {
case .explicit: return .explicit
case .same: return .same
case .valid: return .valid
}
}

@inlinable
internal var explicitPaddings: [Int32] {
switch self {
case .explicit(let paddings): return paddings
case .same: return []
case .valid: return []
}
}
}

public extension Tensor where Scalar: TensorFlowFloatingPoint {
/// TensorFlow builtin conv2d gradient helper for the input.
@inlinable
Expand Down Expand Up @@ -232,7 +261,7 @@ public extension Tensor where Scalar: TensorFlowFloatingPoint {
internal func _vjpMaxPooled(
kernelSize: (Int32, Int32, Int32, Int32),
strides: (Int32, Int32, Int32, Int32),
padding: Padding
padding: PaddingV1
) -> (Tensor, (Tensor) -> Tensor) {
// TODO: Currently this is not higher order differentiable. Redefine in
// closed form.
Expand All @@ -254,7 +283,7 @@ public extension Tensor where Scalar: TensorFlowFloatingPoint {
internal func _vjpAveragePooled(
kernelSize: (Int32, Int32, Int32, Int32),
strides: (Int32, Int32, Int32, Int32),
padding: Padding
padding: PaddingV1
) -> (Tensor, (Tensor) -> Tensor) {
// TODO: Currently this is not higher order differentiable. Redefine in
// closed form.
Expand Down Expand Up @@ -317,7 +346,7 @@ public extension Tensor where Scalar: FloatingPoint {
func maxPooled(
kernelSize: (Int32, Int32, Int32, Int32),
strides: (Int32, Int32, Int32, Int32),
padding: Padding
padding: PaddingV1
) -> Tensor {
return Raw.maxPoolV2(
self,
Expand All @@ -344,7 +373,7 @@ public extension Tensor where Scalar: FloatingPoint {
func averagePooled(
kernelSize: (Int32, Int32, Int32, Int32),
strides: (Int32, Int32, Int32, Int32),
padding: Padding
padding: PaddingV1
) -> Tensor {
return Raw.avgPool(
value: self,
Expand Down