COMPMID-1096 - Add fast_math flag to CLConvolutionLayer
COMPMID-1103 - CLWinogradConvolutionLayer mismatches
Change-Id: Iceaa9482a1790ec39d2720c220261aaea8043978
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/129398
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/arm_compute/core/NEON/kernels/NEReshapeLayerKernel.h b/arm_compute/core/NEON/kernels/NEReshapeLayerKernel.h
index cd70198..0a3fc44 100644
--- a/arm_compute/core/NEON/kernels/NEReshapeLayerKernel.h
+++ b/arm_compute/core/NEON/kernels/NEReshapeLayerKernel.h
@@ -40,7 +40,7 @@
}
/** Set the input and output of the kernel
*
- * @param[in] input Source tensor. Data type supported: U8/S8/QS8/U16/S16/QS16/U32/S32/F16/F32
+ * @param[in] input Source tensor. Data type supported: U8/S8/QS8/U16/S16/QS16/QASYMM8/U32/S32/F16/F32
* @param[out] output Destination tensor. Data type supported: Same as @p input
*/
void configure(const ITensor *input, ITensor *output);
diff --git a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
index a1cd155..5c05334 100644
--- a/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLConvolutionLayer.h
@@ -37,6 +37,7 @@
/** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions:
*
* -# @ref CLGEMMConvolutionLayer
+ * -# @ref CLWinogradConvolutionLayer
* -# @ref CLDirectConvolutionLayer
*/
class CLConvolutionLayer : public IFunction
@@ -46,57 +47,63 @@
CLConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Set the input and output tensors.
*
- * @param[in] input Source tensor. 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: QS8/QASYMM8/QS16/F16/F32.
- * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input.
- * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
- * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type.
- * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
- * Data types supported: Same as @p input.
- * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
- * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. Data type supported: Same as @p input.
- * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ * @param[in] input Source tensor. 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: QS8/QASYMM8/QS16/F16/F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input.
+ * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
+ * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type.
+ * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
+ * Data types supported: Same as @p input.
+ * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
+ * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. Data type supported: Same as @p input.
+ * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
+ * available which may introduce a drop of accuracy as well. Default is false
*/
void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo(),
- const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo());
+ const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
/** Static function to check if given info will lead to a valid configuration of @ref CLConvolutionLayer
*
- * @param[in] input Source tensor. 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: QS8/QASYMM8/QS16/F16/F32.
- * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
- * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported:Same as @p input.
- * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
- * Data types supported: Same as @p input.
- * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
- * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. Data type supported: Same as @p input.
- * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ * @param[in] input Source tensor. 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: QS8/QASYMM8/QS16/F16/F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
+ * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported:Same as @p input.
+ * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
+ * Data types supported: Same as @p input.
+ * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
+ * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. Data type supported: Same as @p input.
+ * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
+ * available which may introduce a drop of accuracy as well. Default is false
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
- const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo());
+ const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
/** Static function to check if given info will return the convolution called by @ref CLConvolutionLayer
*
- * @param[in] input Source tensor. 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: QS8/QASYMM8/QS16/F16/F32.
- * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
- * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
- * Data types supported: Same as @p input.
- * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
- * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. Data type supported: Same as @p input.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
- * @param[in] gpu_target Specifies the @p GPUTarget.
- * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+ * @param[in] input Source tensor. 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: QS8/QASYMM8/QS16/F16/F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
+ * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
+ * Data types supported: Same as @p input.
+ * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
+ * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. Data type supported: Same as @p input.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ * @param[in] gpu_target Specifies the @p GPUTarget.
+ * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
+ * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
+ * available which may introduce a drop of accuracy as well. Default is false
*
* @return a status
*/
static ConvolutionMethod get_convolution_method(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *output, const PadStrideInfo &conv_info,
- const WeightsInfo &weights_info, const ActivationLayerInfo &act_info, const GPUTarget gpu_target, const Size2D &dilation = Size2D(1U, 1U));
+ const WeightsInfo &weights_info, const ActivationLayerInfo &act_info, const GPUTarget gpu_target, const Size2D &dilation = Size2D(1U, 1U), bool enable_fast_math = false);
// Inherited methods overridden:
void run() override;
diff --git a/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
index 2cf1f77..a279769 100644
--- a/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
@@ -51,38 +51,44 @@
CLWinogradConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Set the input and output tensors.
*
- * @note: This function only works with 3x3 kernels and unit strides
+ * @note: This function only works with 3x3 and 5x5 kernels along with unit strides
+ * @note Some Winograd configurations (i.e. F(4x4, 3x3) and F(4x4, 5x5)) are supported only with enable_fast_math = true
*
- * @param[in] input Source tensor. 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: F32.
- * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
- * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input
- * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
- * Data types supported: Same as @p input.
- * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ * @param[in] input Source tensor. 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: F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
+ * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input
+ * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
+ * Data types supported: Same as @p input.
+ * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
+ * available which may introduce a drop of accuracy as well. Default is false
*/
void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
- const ActivationLayerInfo &act_info = ActivationLayerInfo());
+ const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
/** Static function to check if given info will lead to a valid configuration of @ref CLWinogradConvolutionLayer
*
- * @note: This function only works with 3x3 kernels and unit strides
+ * @note: This function only works with 3x3 and 5x5 kernels along with unit strides
+ * @note Some Winograd configurations (i.e. F(4x4, 3x3) and F(4x4, 5x5)) are supported only with enable_fast_math = true
*
- * @param[in] input Source tensor. 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: F32.
- * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
- * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input
- * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
- * Data types supported: Same as @p input.
- * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
- * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ * @param[in] input Source tensor. 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: F32.
+ * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input.
+ * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input
+ * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
+ * Data types supported: Same as @p input.
+ * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation.
+ * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation
+ * available which may introduce a drop of accuracy as well. Default is false
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
- const ActivationLayerInfo &act_info = ActivationLayerInfo());
+ const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
// Inherited methods overridden:
void run() override;
diff --git a/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h
index ce9a3ed..b82ba89 100644
--- a/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h
@@ -52,7 +52,7 @@
*
* @param[in] input Source tensor. 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: QS8/QASYMM8/QS16/F32.
+ * Data types supported: QS8/QASYMM8/QS16/F16/F32.
* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
* Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type.
diff --git a/arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h b/arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h
index 7d5e397..ba96ae6 100644
--- a/arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h
+++ b/arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h
@@ -37,11 +37,11 @@
public:
/** Initialise the kernel's inputs, output and convertion policy.
*
- * @param[in, out] input1 An input tensor. Data types supported: U8/QS8/S16/F32.
+ * @param[in, out] input1 An input tensor. Data types supported: U8/QS8/S16/F16/F32.
* The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
* @param[in, out] input2 An input tensor. Data types supported: same as @p input1.
* The input tensor is [in, out] because its TensorInfo might be modified inside the kernel in case of broadcasting of dimension 0.
- * @param[out] output Output tensor. Data types supported: U8/QS8/S16/F32.
+ * @param[out] output Output tensor. Data types supported: U8/QS8/S16/F16/F32.
* @param[in] scale Scale to apply after multiplication.
* Scale must be positive and its value must be either 1/255 or 1/2^n where n is between 0 and 15. For QS8 and QS16 scale must be 1.
* @param[in] overflow_policy Overflow policy.
@@ -50,9 +50,9 @@
void configure(ITensor *input1, ITensor *input2, ITensor *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy);
/** Static function to check if given info will lead to a valid configuration of @ref NEPixelWiseMultiplication
*
- * @param[in] input1 First tensor info input. Data types supported: U8/QS8/S16/F32.
- * @param[in] input2 Second tensor info input. Data types supported: U8/QS8/S16/F32.
- * @param[in] output Output tensor info. Data types supported: U8/QS8/S16/F32.
+ * @param[in] input1 First tensor info input. Data types supported: U8/QS8/S16/F16/F32.
+ * @param[in] input2 Second tensor info input. Data types supported: U8/QS8/S16/F16/F32.
+ * @param[in] output Output tensor info. Data types supported: U8/QS8/S16/F16/F32.
* @param[in] scale Scale to apply after multiplication. Must be positive.
* @param[in] overflow_policy Overflow policy.
* @param[in] rounding_policy Rounding policy.
diff --git a/arm_compute/runtime/NEON/functions/NEReshapeLayer.h b/arm_compute/runtime/NEON/functions/NEReshapeLayer.h
index 369f50e..0bab534 100644
--- a/arm_compute/runtime/NEON/functions/NEReshapeLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEReshapeLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -37,7 +37,7 @@
public:
/** Initialise the kernel's inputs and outputs
*
- * @param[in] input First tensor input. Data type supported: U8/S8/QS8/U16/S16/QS16/U32/S32/F16/F32
+ * @param[in] input First tensor input. Data type supported: U8/S8/QS8/QASYMM8//U16/S16/QS16/U32/S32/F16/F32
* @param[out] output Output tensor. Data type supported: Same as @p input
*/
void configure(const ITensor *input, ITensor *output);