Unary & Activations

abs

def abs(x: 'Tensor') -> 'Tensor':

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neg

def neg(x: 'Tensor') -> 'Tensor':

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exp

def exp(x: 'Tensor') -> 'Tensor':

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log

def log(x: 'Tensor') -> 'Tensor':

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log1p

def log1p(x: 'Tensor') -> 'Tensor':

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sqrt

def sqrt(x: 'Tensor') -> 'Tensor':

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rsqrt

def rsqrt(x: 'Tensor') -> 'Tensor':

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sin

def sin(x: 'Tensor') -> 'Tensor':

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cos

def cos(x: 'Tensor') -> 'Tensor':

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acos

def acos(x: 'Tensor') -> 'Tensor':

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atanh

def atanh(x: 'Tensor') -> 'Tensor':

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erf

def erf(x: 'Tensor') -> 'Tensor':

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floor

def floor(x: 'Tensor') -> 'Tensor':

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round

def round(x: 'Tensor') -> 'Tensor':

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trunc

def trunc(x: 'Tensor') -> 'Tensor':

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cast

def cast(x: 'Tensor', dtype: 'DType | None' = None) -> 'Tensor':

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is_inf

def is_inf(x: 'Tensor') -> 'Tensor':

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is_nan

def is_nan(x: 'Tensor') -> 'Tensor':

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relu

def relu(x: 'Tensor') -> 'Tensor':

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sigmoid

def sigmoid(x: 'Tensor') -> 'Tensor':

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tanh

def tanh(x: 'Tensor') -> 'Tensor':

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gelu

def gelu(x: 'Tensor') -> 'Tensor':

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silu

def silu(x: 'Tensor') -> 'Tensor':

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softmax

def softmax(x: 'Tensor', axis: 'int' = -1) -> 'Tensor':

A composition of existing nabla ops

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logsoftmax

def logsoftmax(x: 'Tensor', axis: 'int' = -1) -> 'Tensor':

LogSoftmax implementation with sharding support.

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