@@ -32,9 +32,9 @@ public struct Conv1D<Scalar: TensorFlowFloatingPoint>: Layer {
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@noDerivative public let padding : Padding
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/// The dilation factor for the temporal dimension.
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@noDerivative public let dilation : Int
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-
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- /// Creates a `Conv1D` layer with the specified filter, bias, activation function, stride, and
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- /// padding.
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+
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+ /// Creates a `Conv1D` layer with the specified filter, bias, activation function, stride,
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+ /// dilation and padding.
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///
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/// - Parameters:
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/// - filter: The 3-D convolution kernel `[width, inputChannels, outputChannels]`.
@@ -76,7 +76,7 @@ public struct Conv1D<Scalar: TensorFlowFloatingPoint>: Layer {
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}
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public extension Conv1D where Scalar. RawSignificand: FixedWidthInteger {
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- /// Creates a `Conv1D` layer with the specified filter shape, stride, padding, and
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+ /// Creates a `Conv1D` layer with the specified filter shape, stride, padding, dilation and
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/// element-wise activation function. The filter tensor is initialized using Glorot uniform
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/// initialization with the specified generator. The bias vector is initialized with zeros.
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///
@@ -112,7 +112,7 @@ public extension Conv1D where Scalar.RawSignificand: FixedWidthInteger {
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}
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public extension Conv1D {
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- /// Creates a `Conv1D` layer with the specified filter shape, strides, padding, and
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+ /// Creates a `Conv1D` layer with the specified filter shape, strides, padding, dilation and
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/// element-wise activation function. The filter tensor is initialized using Glorot uniform
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/// initialization with the specified seed. The bias vector is initialized with zeros.
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///
@@ -163,19 +163,19 @@ public struct Conv2D<Scalar: TensorFlowFloatingPoint>: Layer {
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@noDerivative public let strides : ( Int , Int )
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/// The padding algorithm for convolution.
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@noDerivative public let padding : Padding
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- /// The dilation factor for spatials dimensions.
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+ /// The dilation factor for spatial dimensions.
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@noDerivative public let dilations : ( Int , Int )
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-
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- /// Creates a `Conv2D` layer with the specified filter, bias, activation function, strides, and
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- /// padding.
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+
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+ /// Creates a `Conv2D` layer with the specified filter, bias, activation function, strides,
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+ /// dilations and padding.
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///
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/// - Parameters:
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/// - filter: The 4-D convolution kernel.
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/// - bias: The bias vector.
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/// - activation: The element-wise activation function.
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/// - strides: The strides of the sliding window for spatial dimensions.
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/// - padding: The padding algorithm for convolution.
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- /// - dilations: The dilation factor for spatials dimensions.
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+ /// - dilations: The dilation factor for spatial dimensions.
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public init (
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filter: Tensor < Scalar > ,
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bias: Tensor < Scalar > ,
@@ -208,7 +208,7 @@ public struct Conv2D<Scalar: TensorFlowFloatingPoint>: Layer {
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}
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public extension Conv2D {
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- /// Creates a `Conv2D` layer with the specified filter shape, strides, padding, and
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+ /// Creates a `Conv2D` layer with the specified filter shape, strides, padding, dilations and
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/// element-wise activation function. The filter tensor is initialized using Glorot uniform
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/// initialization with the specified generator. The bias vector is initialized with zeros.
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///
@@ -243,7 +243,7 @@ public extension Conv2D {
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}
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public extension Conv2D {
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- /// Creates a `Conv2D` layer with the specified filter shape, strides, padding, and
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+ /// Creates a `Conv2D` layer with the specified filter shape, strides, padding, dilations and
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/// element-wise activation function. The filter tensor is initialized using Glorot uniform
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/// initialization with the specified seed. The bias vector is initialized with zeros.
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///
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