From d93603325ac3f2911ee24f8a98a5a79caf29c0ca Mon Sep 17 00:00:00 2001 From: Teresa Charlin Date: Tue, 30 Aug 2022 14:27:10 +0100 Subject: IVGCVSW-7006 Remove deprecated code due to be removed in 22.08 * AddConv and AddDWConv with weights and bias * ResizeBilinearDescriptor * b,blacklist option in accuracy tool !android-nn-driver:8172 Signed-off-by: Teresa Charlin Change-Id: Ibbc04fd18be7f938b11590bf67cd7af103cb4d99 --- .../src/pyarmnn/swig/modules/armnn_network.i | 26 ++-------------------- python/pyarmnn/test/test_network.py | 14 +----------- 2 files changed, 3 insertions(+), 37 deletions(-) (limited to 'python') diff --git a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i index 55b6795c90..f91bccc449 100644 --- a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i +++ b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i @@ -1179,25 +1179,15 @@ public: Args: convolution2dDescriptor (Convolution2dDescriptor): Description of the 2D convolution layer. - weights (ConstTensor): Tensor for the weights data. - biases (ConstTensor): Optional tensor for the bias data. If specified, must match the output tensor shape. name (str): Optional name for the layer. Returns: IConnectableLayer: Interface for configuring the layer. ") AddConvolution2dLayer; armnn::IConnectableLayer* AddConvolution2dLayer(const armnn::Convolution2dDescriptor& convolution2dDescriptor, - const armnn::ConstTensor& weights, - armnn::ConstTensor* biases = nullptr, const char* name = nullptr) { - if (biases) { - return $self->AddConvolution2dLayer(convolution2dDescriptor, weights, - armnn::Optional(*biases), name); - } else { - return $self->AddConvolution2dLayer(convolution2dDescriptor, weights, - armnn::Optional(), name); - } + return $self->AddConvolution2dLayer(convolution2dDescriptor, name); } %feature("docstring", @@ -1206,8 +1196,6 @@ public: Args: convolution2dDescriptor (DepthwiseConvolution2dDescriptor): Description of the 2D depthwise convolution layer. - weights (ConstTensor): Tensor for the weights. Expected format: [channelMultiplier, inputChannels, height, width]. - biases (ConstTensor): Optional tensor for the bias data. If specified, must match the output tensor shape. name (str): Optional name for the layer. Returns: @@ -1216,19 +1204,9 @@ public: armnn::IConnectableLayer* AddDepthwiseConvolution2dLayer( const armnn::DepthwiseConvolution2dDescriptor& convolution2dDescriptor, - const armnn::ConstTensor& weights, - const armnn::ConstTensor* biases = nullptr, const char* name = nullptr) { - ARMNN_NO_DEPRECATE_WARN_BEGIN - if (biases) { - return $self->AddDepthwiseConvolution2dLayer(convolution2dDescriptor, weights, - armnn::Optional(*biases), name); - } else { - return $self->AddDepthwiseConvolution2dLayer(convolution2dDescriptor, weights, - armnn::Optional(), name); - } - ARMNN_NO_DEPRECATE_WARN_END + return $self->AddDepthwiseConvolution2dLayer(convolution2dDescriptor, name); } } diff --git a/python/pyarmnn/test/test_network.py b/python/pyarmnn/test/test_network.py index ce1dffb86b..88be5a8e7f 100644 --- a/python/pyarmnn/test/test_network.py +++ b/python/pyarmnn/test/test_network.py @@ -253,17 +253,7 @@ def test_network_method_exists(method): def test_Convolution2d_layer_optional_none(): net = ann.INetwork() - layer = net.AddConvolution2dLayer(convolution2dDescriptor=ann.Convolution2dDescriptor(), - weights=ann.ConstTensor()) - - assert layer - - -def test_Convolution2d_layer_optional_provided(): - net = ann.INetwork() - layer = net.AddConvolution2dLayer(convolution2dDescriptor=ann.Convolution2dDescriptor(), - weights=ann.ConstTensor(), - biases=ann.ConstTensor()) + layer = net.AddConvolution2dLayer(convolution2dDescriptor=ann.Convolution2dDescriptor()) assert layer @@ -271,8 +261,6 @@ def test_Convolution2d_layer_optional_provided(): def test_Convolution2d_layer_all_args(): net = ann.INetwork() layer = net.AddConvolution2dLayer(convolution2dDescriptor=ann.Convolution2dDescriptor(), - weights=ann.ConstTensor(), - biases=ann.ConstTensor(), name='NAME1') assert layer -- cgit v1.2.1