Module dfdx::tensor_ops
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Implementations of all operations for tensors, including activations, binary operations, and other methods.
Traits
Functions
Applies a DifferentiableFunction to the tensor.
Clamps all values in t to between min and max
Numerically stable computation of log(softmax(t)). Does t - logsumexp(t) under the hood.
Computes the LogSumExp function.
Equivalent to Log(sum(exp(data))) or data.exp().sum(-1).log().
Matrix multiplication.
Replaces any nans in t with value.
Negates all values in t.
Computes the softmax function.
Equivalent to t.log_softmax().exp() or exp(log_softmax(t)) or exp(t) / sum(exp(t))
Sets t to value anywhere mask equals value
vector * matrix multiplication.