Elu - 1 vs 22¶
Next section compares an older to a newer version of the same operator after both definition are converted into markdown text. Green means an addition to the newer version, red means a deletion. Anything else is unchanged.
- Elu1 → Elu22 +28 -7
Elu1 → Elu22
RENAMED
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@@ -1 +1 @@
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1
1
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Elu takes one input data (Tensor<T>) and produces one output data
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2
2
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(Tensor<T>) where the function f(x) = alpha * (exp(x) - 1.) for x <
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3
3
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0, f(x) = x for x >= 0., is applied to the tensor elementwise.
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4
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+
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5
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+
#### Function Body
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6
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+
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7
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+
The function definition for this operator.
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8
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+
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9
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+
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10
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+
<
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11
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+
domain: "",
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12
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+
opset_import: ["" : 18]
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13
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+
>
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14
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+
Elu <alpha>(X) => (Y)
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15
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+
{
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16
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+
Alpha = Constant <value_float: float = @alpha> ()
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17
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+
AlphaCast = CastLike (Alpha, X)
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18
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+
Zero = Constant <value: tensor = float {0}> ()
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19
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+
ZeroCast = CastLike (Zero, X)
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20
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+
One = Constant <value: tensor = float {1}> ()
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21
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+
OneCast = CastLike (One, X)
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22
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+
XLessThanZero = Less (X, ZeroCast)
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23
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+
ExpX = Exp (X)
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24
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+
ExpXSubOne = Sub (ExpX, OneCast)
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25
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+
AlphaMulExpXSubOne = Mul (AlphaCast, ExpXSubOne)
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26
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Y = Where (XLessThanZero, AlphaMulExpXSubOne, X)
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27
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+
}
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28
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+
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4
29
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### Attributes
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5
30
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* **alpha - FLOAT** (default is '1.0'):
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31
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+
Coefficient of ELU.
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6
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-
Coefficient of ELU default to 1.0.
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7
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-
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8
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-
* **consumed_inputs - INTS** :
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9
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-
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10
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-
legacy optimization attribute.
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11
32
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### Inputs
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12
33
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- **X** (heterogeneous) - **T**:
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13
34
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1D input tensor
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14
35
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### Outputs
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15
36
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- **Y** (heterogeneous) - **T**:
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16
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-
1D
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37
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+
1D output tensor
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17
38
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### Type Constraints
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18
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-
* **T** in ( tensor(double), tensor(float), tensor(float16) ):
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39
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+
* **T** in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16) ):
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19
40
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Constrain input and output types to float tensors.
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