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Add more onnx ops (#615) 

* Add Celu

* Add thresholded relu

* Add softsign
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Jacky Lee 2023-02-27 10:43:41 -08:00 committed by GitHub
parent 643e8b0388
commit 1ffe8d68d5
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extra/onnx_ops.py
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@ -104,16 +104,19 @@ def Neg(input): return -input
def Reciprocal(input): return input.reciprocal()
def Sqrt(input): return input.sqrt()
def Sign(input): return input.sign()
def Softsign(input): return input / (1+input.abs())
def Abs(input): return input.abs()
def Exp(input): return input.exp()
def Log(input): return input.log()
def Mish(input): return input.mish()
def HardSigmoid(input, alpha=0.2, beta=0.5): return (alpha*input + beta).clip(0, 1)
def HardSwish(input): return input * HardSigmoid(input, 1/6, 0.5)
def Celu(X, alpha=1.0): return X.relu() - (-alpha*(X/alpha).exp()+1).relu()
def Selu(X, alpha=1.67326319217681884765625, gamma=1.05070102214813232421875): return gamma * (X.relu() - (-alpha*X.exp()+alpha).relu())
def Softplus(X): return X.softplus()
def PRelu(X, slope): return X.leakyrelu(slope)
def LeakyRelu(X, alpha=0.01): return X.leakyrelu(alpha)
def ThresholdedRelu(X, alpha=1.0): return (X-alpha).relu() + (X-alpha).relu().sign() * alpha
def Softmax(input, axis=-1): return input.softmax(axis)
def LogSoftmax(input, axis=-1): return input.log_softmax(axis)
def Clip(input, min=-3.4e38, max=3.4e38): return input.clip(min, max)