COMPMID-2047: Add support for dilation in CLDepthwiseConvolution.

Change-Id: I3106aa34bd168985a56791613d95072756be6e9b
Signed-off-by: Usama Arif <usama.arif@arm.com>
Reviewed-on: https://review.mlplatform.org/c/958
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

8 files changed, 70 insertions, 78 deletions

diff --git a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h
index b1c730d9a7..3b7fc7b7dc 100644
--- a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -41,31 +41,33 @@ public:
      *
      * @param[in]  input            Source tensor. DataType supported: QASYMM8/F16/F32.
      * @param[in]  weights          Weights tensor. A 3D tensor with dimensions [3, 3, IFM]. Data type supported: Same as @p input.
-     * @param[in]  biases           (Optional) Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
+     * @param[in]  biases           Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
      *                              Data type supported: Same as @p input.
      * @param[out] output           Destination tensor. Data type supported: Same as @p input.
      * @param[in]  conv_info        Padding and stride information to use for the convolution.
      * @param[in]  depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in]  act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for QASYMM8 supported.
+     * @param[in]  dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      */
     void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
-                   ActivationLayerInfo act_info) override;
+                   ActivationLayerInfo act_info, const Size2D &dilation) override;
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3NCHWKernel
      *
-     * @param[in] input            Source tensor. DataType supported: F16/F32/QASYMM8.
-     * @param[in] weights          Weights tensor. A 3D tensor with dimensions [3, 3, IFM]. Data type supported: Same as @p input.
-     * @param[in] biases           Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
+     * @param[in] input            Source tensor info. DataType supported: F16/F32/QASYMM8.
+     * @param[in] weights          Weights tensor info. A 3D tensor with dimensions [3, 3, IFM]. Data type supported: Same as @p input.
+     * @param[in] biases           Biases tensor info. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
      *                             Data type supported: Same as @p input.
      * @param[in] output           Destination tensor. Data type supported: Same as @p input.
      * @param[in] conv_info        Padding and stride information to use for the convolution.
-     * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
+     * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in] act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported.
      * @param[in] gpu_target       (Optional) GPU target to validate the kernel for. Defaults to midgard.
+     * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      *
      * @return a status
      */
     static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
-                           ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD);
+                           ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD, const Size2D &dilation = Size2D(1U, 1U));
 
     void run(const Window &window, cl::CommandQueue &queue) override;
     BorderSize border_size() const override;
diff --git a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h
index 2fc9780a2f..7d0ecec13e 100644
--- a/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h
@@ -42,30 +42,32 @@ public:
      *
      * @param[in]  input            Source tensor. DataType supported: QASYMM8.
      * @param[in]  weights          Weights tensor. A 3D tensor with dimensions [IFM, 3, 3]. Data type supported: Same as @p input.
-     * @param[in]  biases           (Optional) Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
+     * @param[in]  biases           Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
      *                              Data type supported: Same as @p input.
      * @param[out] output           Destination tensor. Data type supported: Same as @p input.
      * @param[in]  conv_info        Padding and stride information to use for the convolution.
      * @param[in]  depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in]  act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported.
+     * @param[in]  dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      */
     void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
-                   ActivationLayerInfo act_info) override;
+                   ActivationLayerInfo act_info, const Size2D &dilation) override;
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3NHWCKernel
      *
      * @param[in] input            Source tensor info. DataType supported: QASYMM8.
      * @param[in] weights          Weights tensor info. A 3D tensor with dimensions [IFM, 3, 3]. Data type supported: Same as @p input.
-     * @param[in] biases           (Optional) Biases tensor info. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
+     * @param[in] biases           Biases tensor info. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
      *                             Data type supported: Same as @p input.
      * @param[in] output           Destination tensor info. Data type supported: Same as @p input.
      * @param[in] conv_info        Padding and stride information to use for the convolution.
      * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in] act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported.
+     * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      *
      * @return a status
      */
     static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
-                           ActivationLayerInfo act_info = ActivationLayerInfo());
+                           ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLDepthwiseIm2ColKernel.h b/arm_compute/core/CL/kernels/CLDepthwiseIm2ColKernel.h
index 00d9cb64e1..15798471a8 100644
--- a/arm_compute/core/CL/kernels/CLDepthwiseIm2ColKernel.h
+++ b/arm_compute/core/CL/kernels/CLDepthwiseIm2ColKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -58,22 +58,26 @@ public:
      * @param[in]  conv_info        Contains padding and stride information described in @ref PadStrideInfo.
      * @param[in]  has_bias         Boolean that specifies if the depthwise convolution has bias.
      * @param[in]  depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
+     * @param[in]  dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      */
-    void configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias = false, unsigned int depth_multiplier = 1);
+    void configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias = false, unsigned int depth_multiplier = 1,
+                   const Size2D &dilation = Size2D(1U, 1U));
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseIm2ColKernel
      *
-     * @param[in] input            The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
+     * @param[in] input            The input tensor info to convert. 3 lower dimensions represent a single input [width, height, IFM],
      *                             while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QASYMM8/F32
-     * @param[in] output           The output tensor. First 3 lower dimensions represent a transform of each 3D input,
+     * @param[in] output           The output tensor info. First 3 lower dimensions represent a transform of each 3D input,
      *                             while every dimension above 3 represents a batch. Data types supported: Same as @p input
      * @param[in] kernel_dims      The kernel dimensions (width and height).
      * @param[in] conv_info        Contains padding and stride information described in @ref PadStrideInfo.
      * @param[in] has_bias         Boolean that specifies if the depthwise convolution has bias.
-     * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
+     * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
+     * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      *
      * @return a status
      */
-    static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier);
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier,
+                           const Size2D &dilation = Size2D(1U, 1U));
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h b/arm_compute/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h
index 3396de2e46..92eca89fd8 100644
--- a/arm_compute/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h
+++ b/arm_compute/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -52,15 +52,16 @@ public:
      *
      * @param[in]  input            Source tensor. DataType supported: QASYMM8/F16/F32.
      * @param[in]  weights          Weights tensor. A 3D tensor with dimensions [3, 3, IFM]. Data type supported: Same as @p input.
-     * @param[in]  biases           (Optional) Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
+     * @param[in]  biases           Biases tensor. A 1D tensor with dimensions [IFM]. Must be nullptr if not needed.
      *                              Data type supported: Same as @p input.
      * @param[out] output           Destination tensor. Data type supported: Same as @p input.
      * @param[in]  conv_info        Padding and stride information to use for the convolution.
      * @param[in]  depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in]  act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for QASYMM8 supported.
+     * @param[in]  dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      */
     virtual void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
-                           ActivationLayerInfo act_info = ActivationLayerInfo()) = 0;
+                           ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)) = 0;
 
 protected:
     BorderSize       _border_size;
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 26b337d5c5..b46b1b2535 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -402,10 +402,12 @@ inline TensorShape compute_transposed_shape(const ITensorInfo &input)
  * @param[in] weights          Weights tensor info
  * @param[in] conv_info        Padding and stride information to use for the convolution.
  * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth.
+ * @param[in] dilation         Dilation, in elements, across x and y. Defaults to (1, 1).
  *
  * @return the calculated shape
  */
-inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, const ITensorInfo &weights, PadStrideInfo conv_info, unsigned int depth_multiplier)
+inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, const ITensorInfo &weights, PadStrideInfo conv_info, unsigned int depth_multiplier, const Size2D &dilation = Size2D(1U,
+                                                       1U))
 {
     const TensorShape input_shape{ input.tensor_shape() };
     const TensorShape weights_shape{ weights.tensor_shape() };
@@ -415,43 +417,15 @@ inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input,
     const int        height_idx  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
     const int        channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
 
-    unsigned int output_width  = 0;
-    unsigned int output_height = 0;
-    std::tie(output_width, output_height) = scaled_dimensions(input_shape[width_idx], input_shape[height_idx],
-                                                              weights_shape[width_idx], weights_shape[height_idx],
-                                                              conv_info);
-
-    TensorShape output_shape{ input_shape };
-    output_shape.set(width_idx, output_width);
-    output_shape.set(height_idx, output_height);
-    output_shape.set(channel_idx, input_shape[channel_idx] * depth_multiplier);
-
-    return output_shape;
-}
-
-/** Calculate the depthwise convolution output shape of a tensor
- *
- * @param[in] input            Input tensor info
- * @param[in] weights_width    Weights width
- * @param[in] weights_height   Weights height
- * @param[in] conv_info        Padding and stride information to use for the convolution.
- * @param[in] depth_multiplier Multiplier to apply to the input's depth in order to retrieve the output's depth.
- *
- * @return the calculated shape
- */
-inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input, int weights_width, int weights_height, PadStrideInfo conv_info, unsigned int depth_multiplier)
-{
-    const TensorShape input_shape{ input.tensor_shape() };
-
-    const DataLayout data_layout = input.data_layout();
-    const int        width_idx   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
-    const int        height_idx  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
-    const int        channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
+    const DataLayout weights_data_layout = weights.data_layout();
+    const int        weights_width_idx   = get_data_layout_dimension_index(weights_data_layout, DataLayoutDimension::WIDTH);
+    const int        weights_height_idx  = get_data_layout_dimension_index(weights_data_layout, DataLayoutDimension::HEIGHT);
 
     unsigned int output_width  = 0;
     unsigned int output_height = 0;
     std::tie(output_width, output_height) = scaled_dimensions(input_shape[width_idx], input_shape[height_idx],
-                                                              weights_width, weights_width, conv_info);
+                                                              weights_shape[weights_width_idx], weights_shape[weights_height_idx],
+                                                              conv_info, dilation);
 
     TensorShape output_shape{ input_shape };
     output_shape.set(width_idx, output_width);
diff --git a/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h
index 23034c2b7c..b25c36a930 100644
--- a/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h
@@ -70,32 +70,34 @@ public:
      *
      * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
      * @param[in]      weights          Weights tensor. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input.
-     * @param[in]      biases           (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
+     * @param[in]      biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
      *                                  Data type supported: Same as @p input.
      * @param[out]     output           Destination tensor. Data type supported: same as @p input.
      * @param[in]      conv_info        Padding and stride information to use for the convolution.
      * @param[in]      depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in]      act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
+     * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      */
     void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
-                   ActivationLayerInfo act_info = ActivationLayerInfo());
+                   ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3
      *
-     * @param[in] input            Source tensor. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW.
-     * @param[in] weights          Weights tensor. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input.
-     * @param[in] biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
+     * @param[in] input            Source tensor info. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW.
+     * @param[in] weights          Weights tensor info. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input.
+     * @param[in] biases           Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
      *                             Data type supported: Same as @p input, S32 when input is QASYMM8.
      * @param[in] output           Destination tensor. Data type supported: same as @p input.
      * @param[in] conv_info        Padding and stride information to use for the convolution.
      * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in] act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
      * @param[in] gpu_target       (Optional) GPU target to validate the kernel for. Defaults to midgard.
+     * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      *
      * @return a status
      */
     static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
-                           ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD);
+                           ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD, const Size2D &dilation = Size2D(1U, 1U));
     // Inherited methods overriden:
     void run() override;
     void prepare() override;
@@ -142,31 +144,33 @@ public:
      *
      * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F32. (Written to only for border filling).
      * @param[in]      weights          Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.
-     * @param[in]      biases           (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
+     * @param[in]      biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
      *                                  Data type supported: Same as @p input, S32 when input is QASYMM8.
      * @param[out]     output           Destination tensor. Data type supported: same as @p input.
      * @param[in]      conv_info        Padding and stride information to use for the convolution.
      * @param[in]      depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in]      act_info         (Optional) Activation layer information in case of a fused activation.
+     * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      */
     void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
-                   unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+                   unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
 
     /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer
      *
-     * @param[in] input            Source tensor. Data type supported: QASYMM8/F32.
-     * @param[in] weights          Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.
-     * @param[in] biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
+     * @param[in] input            Source tensor info. Data type supported: QASYMM8/F32.
+     * @param[in] weights          Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.
+     * @param[in] biases           Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
      *                             Data type supported: Same as @p input, S32 when input is QASYMM8.
      * @param[in] output           Destination tensor. Data type supported: same as @p input.
      * @param[in] conv_info        Padding and stride information to use for the convolution.
      * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in] act_info         (Optional) Activation layer information in case of a fused activation.
+     * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
      *
      * @return a status
      */
     static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
-                           unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+                           unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
 
     // Inherited methods overriden:
     void run() override;
diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCDepthwiseConvolutionLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCDepthwiseConvolutionLayer.h
index 5eccc4d9e8..28db5e1310 100644
--- a/arm_compute/runtime/GLES_COMPUTE/functions/GCDepthwiseConvolutionLayer.h
+++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCDepthwiseConvolutionLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -50,15 +50,16 @@ public:
      *
      * @param[in, out] input            Source tensor. Data type supported: F16. (Written to only for border filling).
      * @param[in]      weights          Weights tensor. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input.
-     * @param[in]      biases           (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
+     * @param[in]      biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
      *                                  Data type supported: Same as @p input.
      * @param[out]     output           Destination tensor. Data type supported: same as @p input.
      * @param[in]      conv_info        Padding and stride information to use for the convolution.
      * @param[in]      depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in]      act_info         (Optional) Activation layer information in case of a fused activation.
+     * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). Currently supports (1,1) only.
      */
     void configure(IGCTensor *input, const IGCTensor *weights, const IGCTensor *biases, IGCTensor *output, const PadStrideInfo &conv_info,
-                   unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+                   unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
 
     // Inherited methods overridden:
     void run() override final;
diff --git a/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h
index 28f0560e93..c60233664d 100644
--- a/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEDepthwiseConvolutionLayer.h
@@ -67,31 +67,33 @@ public:
      *
      * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
      * @param[in]      weights          Weights tensor. These are 3D tensors with shape [3, 3, IFM]. Data type supported: Same as @p input.
-     * @param[in]      biases           (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
+     * @param[in]      biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
      *                                  Data type supported: Same as @p input.
      * @param[out]     output           Destination tensor. Data type supported: same as @p input.
      * @param[in]      conv_info        Padding and stride information to use for the convolution.
      * @param[in]      depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in]      act_info         (Optional) Activation layer information in case of a fused activation.
+     * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). Currently supports (1,1) only.
      */
     void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info,
-                   unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+                   unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
 
     /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayer3x3
      *
      * @param[in] input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
      * @param[in] weights          Weights tensor. These are 3D tensors with shape [3, 3, IFM]. Data type supported: Same as @p input.
-     * @param[in] biases           (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
+     * @param[in] biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
      *                             Data type supported: Same as @p input.
      * @param[in] output           Destination tensor. Data type supported: same as @p input.
      * @param[in] conv_info        Padding and stride information to use for the convolution.
      * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in] act_info         (Optional) Activation layer information in case of a fused activation.
+     * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). Currently supports (1,1) only.
      *
      * @return a status
      */
     static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
-                           unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+                           unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
 
     // Inherited methods overriden:
     void run() override;
@@ -102,7 +104,7 @@ private:
      *
      * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
      * @param[in]      weights          Weights tensor. These are 3D tensors with shape [3, 3, IFM]. Data type supported: Same as @p input.
-     * @param[in]      biases           (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
+     * @param[in]      biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
      *                                  Data type supported: Same as @p input.
      * @param[out]     output           Destination tensor. Data type supported: same as @p input.
      * @param[in]      conv_info        Padding and stride information to use for the convolution.
@@ -115,7 +117,7 @@ private:
      *
      * @param[in]  input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
      * @param[in]  weights          Weights tensor. These are 3D tensors with shape [3, 3, IFM]. Data type supported: Same as @p input.
-     * @param[in]  biases           (Optional) Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
+     * @param[in]  biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
      *                              Data type supported: Same as @p input.
      * @param[out] output           Destination tensor. Data type supported: same as @p input.
      * @param[in]  conv_info        Padding and stride information to use for the convolution.
@@ -184,9 +186,10 @@ public:
      * @param[in]      conv_info        Padding and stride information to use for the convolution.
      * @param[in]      depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in]      act_info         (Optional) Activation layer information in case of a fused activation.
+     * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). Currently supports (1,1) only.
      */
     void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info,
-                   unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+                   unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
 
     /** Static function to check if given info will lead to a valid configuration of @ref NEDepthwiseConvolutionLayer
      *
@@ -198,11 +201,12 @@ public:
      * @param[in] conv_info        Padding and stride information to use for the convolution.
      * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
      * @param[in] act_info         (Optional) Activation layer information in case of a fused activation.
+     * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). Currently supports (1,1) only.
      *
      * @return a status
      */
     static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
-                           unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo());
+                           unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
 
     // Inherited methods overriden:
     void run() override;