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shoumikhinshoumikhin
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Helpers to create random normal tensor.
Differential Revision: D74020939 Pull Request resolved: pytorch#10648
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‎extension/apple/ExecuTorch/Exported/ExecuTorchTensor.h‎

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@@ -980,4 +980,87 @@ __attribute__((deprecated("This API is experimental.")))
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@end
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#pragma mark - RandomNormal Category
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@interface ExecuTorchTensor (RandomNormal)
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/**
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* Creates a tensor with random values drawn from a normal distribution,
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* with full specification of shape, strides, data type, and shape dynamism.
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*
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* @param shape An NSArray of NSNumber objects representing the desired shape.
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* @param strides An NSArray of NSNumber objects representing the desired strides.
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* @param dataType An ExecuTorchDataType value specifying the element type.
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* @param shapeDynamism An ExecuTorchShapeDynamism value specifying whether the shape is static or dynamic.
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* @return A new ExecuTorchTensor instance filled with values from a normal distribution.
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*/
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+ (instancetype)randomNormalTensorWithShape:(NSArray<NSNumber *> *)shape
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strides:(NSArray<NSNumber *> *)strides
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dataType:(ExecuTorchDataType)dataType
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shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism
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NS_SWIFT_NAME(randn(shape:strides:dataType:shapeDynamism:));
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/**
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* Creates a tensor with random values drawn from a normal distribution,
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* with the specified shape and data type.
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*
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* @param shape An NSArray of NSNumber objects representing the desired shape.
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* @param dataType An ExecuTorchDataType value specifying the element type.
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* @param shapeDynamism An ExecuTorchShapeDynamism value specifying whether the shape is static or dynamic.
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* @return A new ExecuTorchTensor instance filled with values from a normal distribution.
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*/
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+ (instancetype)randomNormalTensorWithShape:(NSArray<NSNumber *> *)shape
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dataType:(ExecuTorchDataType)dataType
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shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism
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NS_SWIFT_NAME(randn(shape:dataType:shapeDynamism:));
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/**
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* Creates a tensor with random values drawn from a normal distribution,
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* with the specified shape (using dynamic bound shape) and data type.
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*
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* @param shape An NSArray of NSNumber objects representing the desired shape.
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* @param dataType An ExecuTorchDataType value specifying the element type.
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* @return A new ExecuTorchTensor instance filled with values from a normal distribution.
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*/
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+ (instancetype)randomNormalTensorWithShape:(NSArray<NSNumber *> *)shape
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dataType:(ExecuTorchDataType)dataType
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NS_SWIFT_NAME(randn(shape:dataType:));
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/**
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* Creates a tensor with random normal values similar to an existing tensor,
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* with the specified data type and shape dynamism.
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*
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* @param tensor An existing ExecuTorchTensor instance whose shape and strides are used.
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* @param dataType An ExecuTorchDataType value specifying the desired element type.
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* @param shapeDynamism An ExecuTorchShapeDynamism value specifying whether the shape is static or dynamic.
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* @return A new ExecuTorchTensor instance filled with values from a normal distribution.
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*/
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+ (instancetype)randomNormalTensorLikeTensor:(ExecuTorchTensor *)tensor
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dataType:(ExecuTorchDataType)dataType
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shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism
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NS_SWIFT_NAME(randn(like:dataType:shapeDynamism:));
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/**
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* Creates a tensor with random normal values similar to an existing tensor,
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* with the specified data type.
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*
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* @param tensor An existing ExecuTorchTensor instance whose shape and strides are used.
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* @param dataType An ExecuTorchDataType value specifying the desired element type.
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* @return A new ExecuTorchTensor instance filled with values from a normal distribution.
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*/
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+ (instancetype)randomNormalTensorLikeTensor:(ExecuTorchTensor *)tensor
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dataType:(ExecuTorchDataType)dataType
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NS_SWIFT_NAME(randn(like:dataType:));
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/**
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* Creates a tensor with random normal values similar to an existing tensor.
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*
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* @param tensor An existing ExecuTorchTensor instance.
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* @return A new ExecuTorchTensor instance filled with values from a normal distribution.
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*/
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+ (instancetype)randomNormalTensorLikeTensor:(ExecuTorchTensor *)tensor
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NS_SWIFT_NAME(randn(like:));
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@end
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NS_ASSUME_NONNULL_END

‎extension/apple/ExecuTorch/Exported/ExecuTorchTensor.mm‎

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}
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@end
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@implementation ExecuTorchTensor (RandomNormal)
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+ (instancetype)randomNormalTensorWithShape:(NSArray<NSNumber *> *)shape
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strides:(NSArray<NSNumber *> *)strides
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dataType:(ExecuTorchDataType)dataType
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shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism {
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auto tensor = randn_strided(
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utils::toVector<SizesType>(shape),
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utils::toVector<StridesType>(strides),
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static_cast<ScalarType>(dataType),
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static_cast<TensorShapeDynamism>(shapeDynamism)
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);
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return [[self alloc] initWithNativeInstance:&tensor];
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}
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+ (instancetype)randomNormalTensorWithShape:(NSArray<NSNumber *> *)shape
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dataType:(ExecuTorchDataType)dataType
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shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism {
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return [self randomNormalTensorWithShape:shape
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strides:@[]
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dataType:dataType
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shapeDynamism:shapeDynamism];
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}
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+ (instancetype)randomNormalTensorWithShape:(NSArray<NSNumber *> *)shape
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dataType:(ExecuTorchDataType)dataType {
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return [self randomNormalTensorWithShape:shape
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strides:@[]
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dataType:dataType
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shapeDynamism:ExecuTorchShapeDynamismDynamicBound];
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}
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+ (instancetype)randomNormalTensorLikeTensor:(ExecuTorchTensor *)tensor
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dataType:(ExecuTorchDataType)dataType
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shapeDynamism:(ExecuTorchShapeDynamism)shapeDynamism {
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return [self randomNormalTensorWithShape:tensor.shape
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strides:tensor.strides
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dataType:dataType
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shapeDynamism:shapeDynamism];
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}
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+ (instancetype)randomNormalTensorLikeTensor:(ExecuTorchTensor *)tensor
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dataType:(ExecuTorchDataType)dataType {
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return [self randomNormalTensorWithShape:tensor.shape
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strides:tensor.strides
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dataType:dataType
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shapeDynamism:tensor.shapeDynamism];
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}
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+ (instancetype)randomNormalTensorLikeTensor:(ExecuTorchTensor *)tensor {
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return [self randomNormalTensorWithShape:tensor.shape
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strides:tensor.strides
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dataType:tensor.dataType
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shapeDynamism:tensor.shapeDynamism];
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}
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@end

‎extension/apple/ExecuTorch/__tests__/TensorTest.swift‎

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XCTAssertEqual(tensor.shape, other.shape)
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XCTAssertEqual(tensor.count, other.count)
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}
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func testRandomNormal() {
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let tensor = Tensor.randn(shape: [4], dataType: .double)
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XCTAssertEqual(tensor.shape, [4])
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XCTAssertEqual(tensor.count, 4)
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tensor.bytes { pointer, count, dataType in
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XCTAssertEqual(dataType, .double)
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let buffer = UnsafeBufferPointer(start: pointer.assumingMemoryBound(to: Double.self), count: count)
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XCTAssertEqual(buffer.count, 4)
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}
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}
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func testRandomNormalLike() {
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let other = Tensor.zeros(shape: [4], dataType: .float)
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let tensor = Tensor.randn(like: other)
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XCTAssertEqual(tensor.shape, other.shape)
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XCTAssertEqual(tensor.count, other.count)
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}
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}

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