python/pyarmnn/src/pyarmnn/swig/modules/armnn_tensor.i - ml/armnn - Gitiles

 //
 // Copyright © 2020 Arm Ltd. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
 %{
 #include "armnn/Tensor.hpp"
 %}

 %include <typemaps/tensor_memory.i>
 %include <typemaps/tensor_shape.i>

 namespace armnn
 {

 %feature("docstring",
 "
 Class for holding the shape information of an Arm NN tensor.

 This class is iterable. You can iterate over it to get each value of the Tensor shape.

 Examples:
     Obtain tensor shape information as a list.
     >>> import pyarmnn as ann
     >>> import numpy as np
     >>>
     >>> tensor_info = ann.TensorInfo(ann.TensorShape((4, 2, 1, 3)), ann.DataType_Float32)
     >>> tensor = ann.ConstTensor(tensor_info, np.ones([4, 2, 1, 3], dtype=np.float32))
     >>> print(list(tensor.GetShape()))
     [4, 2, 1, 3]

 ") TensorShape;
 class TensorShape
 {
     // Make TensorShape iterable so we can return shape dims easily.
     %pythoncode %{
     def __iter__(self):
         for dim in range(self.GetNumDimensions()):
             yield self[dim]
     %}


 public:
     %tensor_shape_typemap(unsigned int numDimensions, const unsigned int* dimensionSizes);
     TensorShape(unsigned int numDimensions, const unsigned int* dimensionSizes);
     %clear_tensor_shape_typemap(unsigned int numDimensions, const unsigned int* dimensionSizes);

     %feature("docstring",
     "
     Returns the number of dimensions in this TensorShape.

     Returns:
         int: The number of dimensions in this TensorShape.

     ") GetNumDimensions;
     unsigned int GetNumDimensions() const;

     %feature("docstring",
     "
     Returns the total number of elements for a tensor with this TensorShape.

     Returns:
         int: The total number of elements for a tensor with this TensorShape.

     ") GetNumElements;
     unsigned int GetNumElements() const;

 };

 %extend TensorShape {

     unsigned int __getitem__(unsigned int i) const {
         return $self->operator[](i);
     }
     void __setitem__(unsigned int i, unsigned int val) {
          $self->operator[](i) = val;
     }

     std::string __str__() {
         std::string dim = "NumDimensions: " + std::to_string($self->GetNumDimensions());
         std::string elm = "NumElements: " + std::to_string($self->GetNumElements());

         std::string shapeStr = "TensorShape{Shape(";

         auto numDimensions = $self->GetNumDimensions();
         auto sizeDims = $self->GetNumDimensions();
          for (unsigned int i = 0; i < numDimensions; i++) {
             shapeStr += std::to_string($self->operator[](i));

             if (sizeDims - 1 > 0) {
                 shapeStr += ", ";
             }
             sizeDims--;
             }
         shapeStr = shapeStr + "), " + dim + ", " + elm + "}";
         return shapeStr;
     }

 }


 %feature("docstring",
 "
 Class for holding the tensor information of an Arm NN tensor such as quantization, datatype, shape etc.

 ") TensorInfo;
 class TensorInfo
 {
 public:
     TensorInfo();

     TensorInfo(const TensorInfo& other);

     TensorInfo(const TensorShape& shape, DataType dataType,
         float quantizationScale = 0.0f, int32_t quantizationOffset = 0,
         bool isConstant = False);

     %feature("docstring",
     "
     Get the tensor shape.

     Return:
         TensorShape: Current shape of the tensor.

     ") GetShape;
     TensorShape& GetShape();

     %feature("docstring",
     "
     Set the tensor shape. Must have the same number of elements as current tensor.

     Args:
         newShape (TensorShape): New tensor shape to reshape to.

     ") SetShape;
     void SetShape(const TensorShape& newShape);

     %feature("docstring",
     "
     Returns the number of dimensions in this Tensor.

     Returns:
         int: The number of dimensions in this Tensor.

     ") GetNumDimensions;
     unsigned int GetNumDimensions() const;

     %feature("docstring",
     "
     Returns the total number of elements for this Tensor.

     Returns:
         int: The total number of elements for this Tensor.

     ") GetNumElements;
     unsigned int GetNumElements() const;

     %feature("docstring",
     "
     Get the tensor datatype.

     Returns:
         DataType: Current tensor DataType.

     ") GetDataType;
     DataType GetDataType() const;

     %feature("docstring",
     "
     Set the tensor datatype.

     Args:
         type (DataType): DataType to set the tensor to.

     ") SetDataType;
     void SetDataType(DataType type);

     %feature("docstring",
     "
     Get the value of the tensors quantization scale.

     Returns:
         float: Tensor quantization scale value.

     ") GetQuantizationScale;
     float GetQuantizationScale() const;

     %feature("docstring",
     "
     Get the value of the tensors quantization offset.

     Returns:
         int: Tensor quantization offset value.

     ") GetQuantizationOffset;
     int32_t GetQuantizationOffset() const;

     %feature("docstring",
     "
     Set the value of the tensors quantization scale.

     Args:
         scale (float): Scale value to set.

     ") SetQuantizationScale;
     void SetQuantizationScale(float scale);

     %feature("docstring",
     "
     Set the value of the tensors quantization offset.

     Args:
         offset (int): Offset value to set.

     ") SetQuantizationOffset;
     void SetQuantizationOffset(int32_t offset);

     %feature("docstring",
     "
     Returns true if the tensor is a quantized data type.

     Returns:
         bool: True if the tensor is a quantized data type.

     ") IsQuantized;
     bool IsQuantized() const;

     %feature("docstring",
     "
     Returns true if the tensor info is constant.

     Returns:
         bool: True if the tensor info is constant.

     ") IsConstant;
     bool IsConstant() const;

     %feature("docstring",
     "
     Sets the tensor info to be constant.

     Args:
         IsConstant (bool): Sets tensor info to constant.

     ") SetConstant;
     void SetConstant(const bool IsConstant = True);


     %feature("docstring",
     "
     Check that the types are the same and, if quantize, that the quantization parameters are the same.

     Returns:
         bool: True if matched, else False.

     ") IsTypeSpaceMatch;
     bool IsTypeSpaceMatch(const TensorInfo& other) const;

     %feature("docstring",
     "
     Get the number of bytes needed for this tensor.

     Returns:
         int: Number of bytes consumed by this tensor.

     ") GetNumBytes;
     unsigned int GetNumBytes() const;

 };

 %extend TensorInfo {

     std::string __str__() {
         const std::string tmp = "TensorInfo{DataType: " + std::to_string(static_cast<int>($self->GetDataType()))
                         + ", IsQuantized: " + std::to_string($self->IsQuantized())
                         + ", QuantizationScale: " + std::to_string( $self->GetQuantizationScale())
                         + ", QuantizationOffset: " + std::to_string($self->GetQuantizationOffset())
                         + ", IsConstant: " + std::to_string($self->IsConstant())
                         + ", NumDimensions: " + std::to_string($self->GetNumDimensions())
                         + ", NumElements: " + std::to_string($self->GetNumElements()) + "}";
         return tmp;
     }

 }

 class Tensor
 {
 public:
     ~Tensor();
     Tensor();
     Tensor(const Tensor& other);

     %mutable_memory(void* memory);
     Tensor(const TensorInfo& info, void* memory);
     %clear_mutable_memory(void* memory);

     const TensorInfo& GetInfo() const;
     const TensorShape& GetShape() const;

     DataType GetDataType() const;
     unsigned int GetNumDimensions() const;
     unsigned int GetNumBytes() const;
     unsigned int GetNumElements() const;

     /* we want to disable getting the memory area from here - forcing use of get_memory_area() in public api.
      void* GetMemoryArea() const;*/
 };

 %extend Tensor {

      std::string __str__() {
         const std::string tmp = "Tensor{DataType: " + std::to_string(static_cast<int>($self->GetDataType()))
                         + ", NumBytes: " + std::to_string($self->GetNumBytes())
                         + ", NumDimensions: " + std::to_string( $self->GetNumDimensions())
                         + ", NumElements: " + std::to_string($self->GetNumElements()) + "}";
         return tmp;
     }
 }

 class ConstTensor
 {
 public:
     ~ConstTensor();
     ConstTensor();
     ConstTensor(const Tensor& other);
     ConstTensor(const ConstTensor& other);

     %const_memory(const void* memory);
     ConstTensor(const TensorInfo& info, const void* memory);
     %clear_const_memory(const void* memory);

     const TensorInfo& GetInfo() const;
     const TensorShape& GetShape() const;

     DataType GetDataType() const;
     unsigned int GetNumDimensions() const;
     unsigned int GetNumBytes() const;
     unsigned int GetNumElements() const;

     /* we want to disable getting the memory area from here - forcing use of get_memory_area() in public api.
      void* GetMemoryArea() const;*/
 };

 %extend ConstTensor {

     std::string __str__() {
         const std::string tmp = "ConstTensor{DataType: " + std::to_string(static_cast<int>($self->GetDataType()))
                         + ", NumBytes: " + std::to_string($self->GetNumBytes())
                         + ", NumDimensions: " + std::to_string( $self->GetNumDimensions())
                         + ", NumElements: " + std::to_string($self->GetNumElements()) + "}";
         return tmp;
     }
 }

 }
	//
	// Copyright © 2020 Arm Ltd. All rights reserved.
	// SPDX-License-Identifier: MIT
	//
	%{
	#include "armnn/Tensor.hpp"
	%}

	%include <typemaps/tensor_memory.i>
	%include <typemaps/tensor_shape.i>

	namespace armnn
	{

	%feature("docstring",
	"
	Class for holding the shape information of an Arm NN tensor.

	This class is iterable. You can iterate over it to get each value of the Tensor shape.

	Examples:
	Obtain tensor shape information as a list.
	>>> import pyarmnn as ann
	>>> import numpy as np
	>>>
	>>> tensor_info = ann.TensorInfo(ann.TensorShape((4, 2, 1, 3)), ann.DataType_Float32)
	>>> tensor = ann.ConstTensor(tensor_info, np.ones([4, 2, 1, 3], dtype=np.float32))
	>>> print(list(tensor.GetShape()))
	[4, 2, 1, 3]

	") TensorShape;
	class TensorShape
	{
	// Make TensorShape iterable so we can return shape dims easily.
	%pythoncode %{
	def __iter__(self):
	for dim in range(self.GetNumDimensions()):
	yield self[dim]
	%}


	public:
	%tensor_shape_typemap(unsigned int numDimensions, const unsigned int* dimensionSizes);
	TensorShape(unsigned int numDimensions, const unsigned int* dimensionSizes);
	%clear_tensor_shape_typemap(unsigned int numDimensions, const unsigned int* dimensionSizes);

	%feature("docstring",
	"
	Returns the number of dimensions in this TensorShape.

	Returns:
	int: The number of dimensions in this TensorShape.

	") GetNumDimensions;
	unsigned int GetNumDimensions() const;

	%feature("docstring",
	"
	Returns the total number of elements for a tensor with this TensorShape.

	Returns:
	int: The total number of elements for a tensor with this TensorShape.

	") GetNumElements;
	unsigned int GetNumElements() const;

	};

	%extend TensorShape {

	unsigned int __getitem__(unsigned int i) const {
	return $self->operator[](i);
	}
	void __setitem__(unsigned int i, unsigned int val) {
	$self->operator[](i) = val;
	}

	std::string __str__() {
	std::string dim = "NumDimensions: " + std::to_string($self->GetNumDimensions());
	std::string elm = "NumElements: " + std::to_string($self->GetNumElements());

	std::string shapeStr = "TensorShape{Shape(";

	auto numDimensions = $self->GetNumDimensions();
	auto sizeDims = $self->GetNumDimensions();
	for (unsigned int i = 0; i < numDimensions; i++) {
	shapeStr += std::to_string($self->operator[](i));

	if (sizeDims - 1 > 0) {
	shapeStr += ", ";
	}
	sizeDims--;
	}
	shapeStr = shapeStr + "), " + dim + ", " + elm + "}";
	return shapeStr;
	}

	}


	%feature("docstring",
	"
	Class for holding the tensor information of an Arm NN tensor such as quantization, datatype, shape etc.

	") TensorInfo;
	class TensorInfo
	{
	public:
	TensorInfo();

	TensorInfo(const TensorInfo& other);

	TensorInfo(const TensorShape& shape, DataType dataType,
	float quantizationScale = 0.0f, int32_t quantizationOffset = 0,
	bool isConstant = False);

	%feature("docstring",
	"
	Get the tensor shape.

	Return:
	TensorShape: Current shape of the tensor.

	") GetShape;
	TensorShape& GetShape();

	%feature("docstring",
	"
	Set the tensor shape. Must have the same number of elements as current tensor.

	Args:
	newShape (TensorShape): New tensor shape to reshape to.

	") SetShape;
	void SetShape(const TensorShape& newShape);

	%feature("docstring",
	"
	Returns the number of dimensions in this Tensor.

	Returns:
	int: The number of dimensions in this Tensor.

	") GetNumDimensions;
	unsigned int GetNumDimensions() const;

	%feature("docstring",
	"
	Returns the total number of elements for this Tensor.

	Returns:
	int: The total number of elements for this Tensor.

	") GetNumElements;
	unsigned int GetNumElements() const;

	%feature("docstring",
	"
	Get the tensor datatype.

	Returns:
	DataType: Current tensor DataType.

	") GetDataType;
	DataType GetDataType() const;

	%feature("docstring",
	"
	Set the tensor datatype.

	Args:
	type (DataType): DataType to set the tensor to.

	") SetDataType;
	void SetDataType(DataType type);

	%feature("docstring",
	"
	Get the value of the tensors quantization scale.

	Returns:
	float: Tensor quantization scale value.

	") GetQuantizationScale;
	float GetQuantizationScale() const;

	%feature("docstring",
	"
	Get the value of the tensors quantization offset.

	Returns:
	int: Tensor quantization offset value.

	") GetQuantizationOffset;
	int32_t GetQuantizationOffset() const;

	%feature("docstring",
	"
	Set the value of the tensors quantization scale.

	Args:
	scale (float): Scale value to set.

	") SetQuantizationScale;
	void SetQuantizationScale(float scale);

	%feature("docstring",
	"
	Set the value of the tensors quantization offset.

	Args:
	offset (int): Offset value to set.

	") SetQuantizationOffset;
	void SetQuantizationOffset(int32_t offset);

	%feature("docstring",
	"
	Returns true if the tensor is a quantized data type.

	Returns:
	bool: True if the tensor is a quantized data type.

	") IsQuantized;
	bool IsQuantized() const;

	%feature("docstring",
	"
	Returns true if the tensor info is constant.

	Returns:
	bool: True if the tensor info is constant.

	") IsConstant;
	bool IsConstant() const;

	%feature("docstring",
	"
	Sets the tensor info to be constant.

	Args:
	IsConstant (bool): Sets tensor info to constant.

	") SetConstant;
	void SetConstant(const bool IsConstant = True);



	%feature("docstring",
	"
	Check that the types are the same and, if quantize, that the quantization parameters are the same.

	Returns:
	bool: True if matched, else False.

	") IsTypeSpaceMatch;
	bool IsTypeSpaceMatch(const TensorInfo& other) const;

	%feature("docstring",
	"
	Get the number of bytes needed for this tensor.

	Returns:
	int: Number of bytes consumed by this tensor.

	") GetNumBytes;
	unsigned int GetNumBytes() const;

	};

	%extend TensorInfo {

	std::string __str__() {
	const std::string tmp = "TensorInfo{DataType: " + std::to_string(static_cast<int>($self->GetDataType()))
	+ ", IsQuantized: " + std::to_string($self->IsQuantized())
	+ ", QuantizationScale: " + std::to_string( $self->GetQuantizationScale())
	+ ", QuantizationOffset: " + std::to_string($self->GetQuantizationOffset())
	+ ", IsConstant: " + std::to_string($self->IsConstant())
	+ ", NumDimensions: " + std::to_string($self->GetNumDimensions())
	+ ", NumElements: " + std::to_string($self->GetNumElements()) + "}";
	return tmp;
	}

	}

	class Tensor
	{
	public:
	~Tensor();
	Tensor();
	Tensor(const Tensor& other);

	%mutable_memory(void* memory);
	Tensor(const TensorInfo& info, void* memory);
	%clear_mutable_memory(void* memory);

	const TensorInfo& GetInfo() const;
	const TensorShape& GetShape() const;

	DataType GetDataType() const;
	unsigned int GetNumDimensions() const;
	unsigned int GetNumBytes() const;
	unsigned int GetNumElements() const;

	/* we want to disable getting the memory area from here - forcing use of get_memory_area() in public api.
	void* GetMemoryArea() const;*/
	};

	%extend Tensor {

	std::string __str__() {
	const std::string tmp = "Tensor{DataType: " + std::to_string(static_cast<int>($self->GetDataType()))
	+ ", NumBytes: " + std::to_string($self->GetNumBytes())
	+ ", NumDimensions: " + std::to_string( $self->GetNumDimensions())
	+ ", NumElements: " + std::to_string($self->GetNumElements()) + "}";
	return tmp;
	}
	}

	class ConstTensor
	{
	public:
	~ConstTensor();
	ConstTensor();
	ConstTensor(const Tensor& other);
	ConstTensor(const ConstTensor& other);

	%const_memory(const void* memory);
	ConstTensor(const TensorInfo& info, const void* memory);
	%clear_const_memory(const void* memory);

	const TensorInfo& GetInfo() const;
	const TensorShape& GetShape() const;

	DataType GetDataType() const;
	unsigned int GetNumDimensions() const;
	unsigned int GetNumBytes() const;
	unsigned int GetNumElements() const;

	/* we want to disable getting the memory area from here - forcing use of get_memory_area() in public api.
	void* GetMemoryArea() const;*/
	};

	%extend ConstTensor {

	std::string __str__() {
	const std::string tmp = "ConstTensor{DataType: " + std::to_string(static_cast<int>($self->GetDataType()))
	+ ", NumBytes: " + std::to_string($self->GetNumBytes())
	+ ", NumDimensions: " + std::to_string( $self->GetNumDimensions())
	+ ", NumElements: " + std::to_string($self->GetNumElements()) + "}";
	return tmp;
	}
	}

	}