Revert "IVGCVSW-7703 Ensure PyArmNN has been updated with new"
This reverts commit 9a5e5b7032788249055f40edd763420f6bdba8fe.
Reason for revert: Build failing while building pyarmnn
Change-Id: I465c494ee1a19a830bf85a8ab078ead08cefccd4
diff --git a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_descriptors.i b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_descriptors.i
index 755d3c5..9374945 100644
--- a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_descriptors.i
+++ b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_descriptors.i
@@ -91,104 +91,6 @@
%feature("docstring",
"
- A descriptor for the BatchMatMul layer. See `INetwork.AddBatchMatMulLayer()`.
-
- Contains:
- m_TransposeX (bool): Transpose the slices of input tensor X. Transpose and Adjoint can not both be set to true for the same tensor at the same time.
- m_TransposeY (bool): Transpose the slices of input tensor Y. Transpose and Adjoint can not both be set to true for the same tensor at the same time.
- m_AdjointX (bool): Adjoint the slices of input tensor X. Transpose and Adjoint can not both be set to true for the same tensor at the same time.
- m_AdjointY (bool): Adjoint the slices of input tensor Y. Transpose and Adjoint can not both be set to true for the same tensor at the same time.
- m_DataLayoutX (DataLayout): Data layout of input tensor X, such as NHWC/NDHWC (leave as default for arbitrary layout).
- m_DatalayoutY (DataLayout): Data layout of input tensor X, such as NHWC/NDHWC (leave as default for arbitrary layout)
- ") BatchMatMulDescriptor;
-struct BatchMatMulDescriptor
-{
- BatchMatMulDescriptor(bool transposeX = false,
- bool transposeY = false,
- bool adjointX = false,
- bool adjointY = false,
- DataLayout dataLayoutX = DataLayout::NCHW,
- DataLayout dataLayoutY = DataLayout::NCHW)
- : m_TransposeX(transposeX)
- , m_TransposeY(transposeY)
- , m_AdjointX(adjointX)
- , m_AdjointY(adjointY)
- , m_DataLayoutX(dataLayoutX)
- , m_DataLayoutY(dataLayoutY)
- {}
-
- bool operator ==(const BatchMatMulDescriptor &rhs) const
- {
- return m_TransposeX == rhs.m_TransposeX &&
- m_TransposeY == rhs.m_TransposeY &&
- m_AdjointX == rhs.m_AdjointX &&
- m_AdjointY == rhs.m_AdjointY &&
- m_DataLayoutX == rhs.m_DataLayoutX &&
- m_DataLayoutY == rhs.m_DataLayoutY;
- }
-
- bool m_TransposeX;
- bool m_TransposeY;
- bool m_AdjointX;
- bool m_AdjointY;
- DataLayout m_DataLayoutX;
- DataLayout m_DataLayoutY;
-
- static std::pair<std::pair<unsigned int, unsigned int>, std::pair<unsigned int, unsigned int>> GetAxesToMul(
- const BatchMatMulDescriptor& desc,
- const armnn::TensorShape& tensorXShape,
- const armnn::TensorShape& tensorYShape);
-
- static std::pair<std::vector<unsigned int>, std::vector<unsigned int>> GetAxesNotMul(
- const BatchMatMulDescriptor& desc,
- const armnn::TensorShape& inputXShape,
- const armnn::TensorShape& inputYShape);
-
- %feature("docstring",
- "
- Static helper to get the two axes (for each input) for multiplication
- Args:
- dataLayout (DataLayout)
- tensorShape (TensorShape)
-
- Returns:
- std::pair<unsigned int, unsigned int>
- ") GetAxesToMul;
- static std::pair<unsigned int, unsigned int> GetAxesToMul(
- DataLayout dataLayout,
- const TensorShape& tensorShape);
-
- %feature("docstring",
- "
- Static helper to get the two axes (for each input) that will not be multiplied together
- Args:
- dataLayout (DataLayout)
- tensorShape (TensorShape)
-
- Returns:
- std::vector<unsigned int>
- ") GetAxesToNotMul;
- static std::vector<unsigned int> GetAxesNotMul(
- DataLayout dataLayout,
- const TensorShape& tensorShape);
-
- %feature("docstring",
- "
- Static helper to get the axes which will be transposed
- Args:
- dataLayout (DataLayout)
- tensorShape (TensorShape)
-
- Returns:
- PermutationVector
- ") GetPermuteVec;
- static PermutationVector GetPermuteVec(
- armnn::DataLayout dataLayout,
- const armnn::TensorShape& tensorShape);
-};
-
-%feature("docstring",
- "
A descriptor for the BatchNormalization layer. See `INetwork.AddBatchNormalizationLayer()`.
Contains:
@@ -777,26 +679,6 @@
%feature("docstring",
"
- A descriptor for the ElementwiseBinary layer. See `INetwork.AddElementwiseBinaryLayer()`.
- Contains:
- m_Operation (int): Indicates which Binary operation to use. (`BinaryOperation_Add`, `BinaryOperation_Div`,
- `BinaryOperation_Maximum`, `BinaryOperation_Minimum`, `BinaryOperation_Mul`, `BinaryOperation_Sub`,
- `BinaryOperation_SqDiff`, `BinaryOperation_Power`)
- Default: `BinaryOperation_Add`.
-
- ") ElementwiseBinaryDescriptor;
-struct ElementwiseBinaryDescriptor
-{
- ElementwiseBinaryDescriptor();
- ElementwiseBinaryDescriptor(BinaryOperation operation);
-
- BinaryOperation m_Operation;
-
- bool operator ==(const ElementwiseBinaryDescriptor &rhs) const;
-};
-
-%feature("docstring",
- "
A descriptor for the ElementwiseUnary layer. See `INetwork.AddElementwiseUnaryLayer()`.
Contains:
@@ -1329,24 +1211,6 @@
%feature("docstring",
"
- A descriptor for the Tile layer. See `INetwork.AddTileLayer()`.
-
- Contains:
- m_Multiples (std::vector<uint32_t>): The vector to multiply the input shape by
-
- ") TileDescriptor;
-struct TileDescriptor
-{
- TileDescriptor();
- TileDescriptor(const std::vector<uint32_t>& multiples);
-
- std::vector<uint32_t> m_Multiples;
-
- bool operator ==(const TileDescriptor &rhs) const;
-};
-
-%feature("docstring",
- "
A descriptor for the Transpose layer. See `INetwork.AddTransposeLayer()`.
Contains:
diff --git a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i
index 0b7f55d..c9eef86 100644
--- a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i
+++ b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_network.i
@@ -396,21 +396,6 @@
%feature("docstring",
"
- Adds a Batch Matrix Multiplication layer to the network.
-
- Args:
- desc (BatchMatMulDescriptor): Parameters for the BatchMatMul layer.
- name (str): Optional name for the layer.
-
- Returns:
- IConnectableLayer: Interface for configuring the layer.
- ") AddBatchMatMulLayer;
- armnn::IConnectableLayer* AddBatchMatMulLayer(const armnn::BatchMatMulDescriptor& desc,
- const char* name = nullptr);
-
-
- %feature("docstring",
- "
Adds a Batch Normalization layer to the network.
Args:
@@ -610,20 +595,6 @@
%feature("docstring",
"
- Adds an Elementwise Binary layer to the network. Type of binary operation to use is decided by elementwiseBinaryDescriptor. Binary operations supported are (Add, Div, Maximum, Minimum, Mul, Sub, SqDiff, Power)
-
- Args:
- elementwiseBinaryDescriptor (ElementwiseBinaryDescriptor): ElementwiseBinaryDescriptor to configure the choice of binary operation added to the network.
- name (str): Optional name for the layer.
-
- Returns:
- IConnectableLayer: Interface for configuring the layer.
- ") AddElementwiseBinaryLayer;
- armnn::IConnectableLayer* AddElementwiseBinaryLayer(const ElementwiseBinaryDescriptor& elementwiseBinaryDescriptor,
- const char* name = nullptr);
-
- %feature("docstring",
- "
Adds an Elementwise Unary layer to the network. Type of unary operation to use is decided by elementwiseUnaryDescriptor. Unary operations supported are (Abs, Exp, Neg, Rsqrt, Sqrt)
Args:
@@ -972,18 +943,6 @@
%feature("docstring",
"
- Adds a ReverseV2 layer to the network.
-
- Args:
- name (str): Optional name for the layer.
-
- Returns:
- IConnectableLayer: Interface for configuring the layer.
- ") AddReverseV2Layer;
- armnn::IConnectableLayer* AddReverseV2Layer(const char* name = nullptr);
-
- %feature("docstring",
- "
Adds a Shape layer to the network.
Args:
@@ -1163,20 +1122,6 @@
%feature("docstring",
"
- Adds a Tile layer to the network.
-
- Args:
- tileDescriptor (TileDescriptor): Description of the tile layer.
- name (str): Optional name for the layer.
-
- Returns:
- IConnectableLayer: Interface for configuring the layer.
- ") AddTileLayer;
- armnn::IConnectableLayer* AddTileLayer(const armnn::TileDescriptor& tileDescriptor,
- const char* name = nullptr);
-
- %feature("docstring",
- "
Adds a Transpose layer to the network.
Args:
diff --git a/python/pyarmnn/test/test_network.py b/python/pyarmnn/test/test_network.py
index 2fe8938..88be5a8 100644
--- a/python/pyarmnn/test/test_network.py
+++ b/python/pyarmnn/test/test_network.py
@@ -190,7 +190,6 @@
'AddActivationLayer',
'AddAdditionLayer',
'AddArgMinMaxLayer',
- 'AddBatchMatMulLayer',
'AddBatchNormalizationLayer',
'AddBatchToSpaceNdLayer',
'AddCastLayer',
@@ -205,7 +204,6 @@
'AddDequantizeLayer',
'AddDetectionPostProcessLayer',
'AddDivisionLayer',
- 'AddElementWiseBinaryLayer',
'AddElementwiseUnaryLayer',
'AddFloorLayer',
'AddFillLayer',
@@ -236,7 +234,6 @@
'AddReduceLayer',
'AddReshapeLayer',
'AddResizeLayer',
- 'AddReverseV2Layer',
'AddShapeLayer',
'AddSliceLayer',
'AddSoftmaxLayer',
@@ -248,7 +245,6 @@
'AddStridedSliceLayer',
'AddSubtractionLayer',
'AddSwitchLayer',
- 'AddTileLayer',
'AddTransposeConvolution2dLayer',
'AddTransposeLayer'
])