diff options
Diffstat (limited to 'src/backends')
6 files changed, 0 insertions, 52 deletions
diff --git a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp index 762645bfba..6b0a3b8352 100644 --- a/src/backends/cl/workloads/ClConvolution2dWorkload.cpp +++ b/src/backends/cl/workloads/ClConvolution2dWorkload.cpp @@ -28,15 +28,6 @@ arm_compute::Status ClConvolution2dWorkloadValidate(const TensorInfo& input, bool isFastMathEnabled, const ActivationDescriptor* activationDescriptor) { - // The arm_compute::CLConvolutionLayer supports both const and non const - // weights. However, in the case of non const weights we'd have to call - // prepare or configure for each inference which we're not setup to do just yet. - if (!weights.IsConstant()) - { - return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR, - "ArmNN ClConvolution2dWorkload does not support non constant weights."}; - } - const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout); diff --git a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp index 3a972d3f39..42fe400041 100644 --- a/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp +++ b/src/backends/cl/workloads/ClDepthwiseConvolutionWorkload.cpp @@ -30,15 +30,6 @@ arm_compute::Status ClDepthwiseConvolutionWorkloadValidate(const TensorInfo& inp const Optional<TensorInfo>& biases, const ActivationDescriptor* activationDescriptor) { - // The CL implemented workload does support both const and non const - // weights. However, in the case of non const weights we'd have to call - // prepare or configure for each inference which we're not setup to do just yet. - if (!weights.IsConstant()) - { - return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR, - "ArmNN ClDepthwiseConv2dWorkload does not support non constant weights."}; - } - const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); diff --git a/src/backends/cl/workloads/ClFullyConnectedWorkload.cpp b/src/backends/cl/workloads/ClFullyConnectedWorkload.cpp index c2da5f297a..0e1efe0239 100644 --- a/src/backends/cl/workloads/ClFullyConnectedWorkload.cpp +++ b/src/backends/cl/workloads/ClFullyConnectedWorkload.cpp @@ -23,14 +23,6 @@ arm_compute::Status ClFullyConnectedWorkloadValidate(const TensorInfo& input, const FullyConnectedDescriptor& descriptor, const ActivationDescriptor* activationDescriptor) { - // The CL implemented workload does support both const and non const - // weights. However, in the case of non const weights we'd have to call - // prepare or configure for each inference which we're not setup to do just yet. - if (!weights.IsConstant()) - { - return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR, - "Arm NN ClFullyConnectedWorkload does not support non constant weights."}; - } const arm_compute::TensorInfo aclInput = BuildArmComputeTensorInfo(input); const arm_compute::TensorInfo aclOutput = BuildArmComputeTensorInfo(output); arm_compute::TensorInfo aclWeights = BuildArmComputeTensorInfo(weights); diff --git a/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp b/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp index 12d8c460f9..586b9c9849 100644 --- a/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp +++ b/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp @@ -29,15 +29,6 @@ arm_compute::Status NeonConvolution2dWorkloadValidate(const TensorInfo& input, bool isFastMathEnabled, const ActivationDescriptor* activationDescriptor) { - // arm_compute::NEConvolutionLayer supports both const and non const - // weights. However, in the case of non const weights we'd have to call - // prepare or configure for each inference which we're not setup to do just yet. - if (!weights.IsConstant()) - { - return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR, - "ArmNN NeonConvolution2dWorkload does not support non constant weights."}; - } - const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout); diff --git a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp index 9eeac6e2a3..e2d0a8200f 100644 --- a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp +++ b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp @@ -33,15 +33,6 @@ arm_compute::Status NeonDepthwiseConvolutionWorkloadValidate(const TensorInfo& i const Optional<TensorInfo>& biases, const ActivationDescriptor* activationDescriptor) { - // The Neon implemented workload does support both const and non const - // weights. However, in the case of non const weights we'd have to call - // prepare or configure for each inference which we're not setup to do just yet. - if (!weights.IsConstant()) - { - return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR, - "ArmNN NeonDepthwiseConv2dWorkload does not support non constant weights."}; - } - const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); diff --git a/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp b/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp index d3716806b3..0b91eb37c2 100644 --- a/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp +++ b/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp @@ -28,14 +28,6 @@ arm_compute::Status NeonFullyConnectedWorkloadValidate(const TensorInfo& input, const FullyConnectedDescriptor& descriptor, const ActivationDescriptor* activationDescriptor) { - // The NEON implemented workload does support both const and non const - // weights. However, in the case of non const weights we'd have to call - // prepare or configure for each inference which we're not setup to do just yet. - if (!weights.IsConstant()) - { - return arm_compute::Status{arm_compute::ErrorCode::RUNTIME_ERROR, - "Arm NN NeonFullyConnectedWorkload does not support non constant weights."}; - } const arm_compute::TensorInfo aclInput = BuildArmComputeTensorInfo(input); const arm_compute::TensorInfo aclOutput = BuildArmComputeTensorInfo(output); arm_compute::TensorInfo aclWeights = BuildArmComputeTensorInfo(weights); |