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ONNX does not maintain versions for experimental ops (#1696)
* fix the versioning info for exp ops, which do not have version maintained in onnx. * remove the version 9 for dynamicslice, which is misleading partners as exp ops do not versioning maintained actually. * fix build error * update the changelog.md
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‎docs/Changelog.md‎

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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Inputs (1 - ∞)
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<dl>
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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<dl>
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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<dl>
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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<dl>
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<dd>Constrain input and output types to float tensors.</dd>
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</dl>
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### <a name="DynamicSlice-1"></a>**DynamicSlice-1**</a>
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Produces a slice of the input tensor along multiple axes. Similar to numpy:
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https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html
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Slices uses `axes`, `starts` and `ends` inputs to specify the start and end
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dimension for each axis in the list of axes, it uses this information to
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slice the input `data` tensor. If a negative value is passed for any of the
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start or end indices, it represent number of elements before the end of that
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dimension. If the value passed to start or end is larger than the `n` (the
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number of elements in this dimension), it represents `n`. For slicing to the
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end of a dimension with unknown size, it is recommended to pass in `INT_MAX`.
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If `axes` are omitted, they are set to `[0, ..., ndim-1]`.
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Example 1:
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data = [
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[1, 2, 3, 4],
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[5, 6, 7, 8],
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]
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axes = [0, 1]
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starts = [1, 0]
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ends = [2, 3]
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result = [
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[5, 6, 7],
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]
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Example 2:
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data = [
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[1, 2, 3, 4],
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[5, 6, 7, 8],
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]
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starts = [0, 1]
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ends = [-1, 1000]
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result = [
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[2, 3, 4],
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]
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#### Version
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No versioning maintained for experimental ops.
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#### Inputs (3 - 4)
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<dl>
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<dt><tt>data</tt> : T</dt>
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<dd>Tensor of data to extract slices from.</dd>
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<dt><tt>starts</tt> : Tind</dt>
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<dd>1-D tensor of starting indices of corresponding axis in `axes`</dd>
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<dt><tt>ends</tt> : Tind</dt>
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<dd>1-D tensor of ending indices (exclusive) of corresponding axis in axes</dd>
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<dt><tt>axes</tt> (optional) : Tind</dt>
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<dd>1-D tensor of axes that `starts` and `ends` apply to.</dd>
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</dl>
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#### Outputs
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<dl>
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<dt><tt>output</tt> : T</dt>
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<dd>Sliced data tensor.</dd>
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</dl>
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#### Type Constraints
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<dl>
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<dt><tt>T</tt> : tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(int8), tensor(int16), tensor(int32), tensor(int64), tensor(float16), tensor(float), tensor(double), tensor(string), tensor(bool), tensor(complex64), tensor(complex128)</dt>
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<dd>Constrain input and output types to all tensor types.</dd>
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<dt><tt>Tind</tt> : tensor(int32), tensor(int64)</dt>
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<dd>Constrain indices to integer types</dd>
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</dl>
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### <a name="Elu-1"></a>**Elu-1**</a>
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Elu takes one input data (Tensor<T>) and produces one output data
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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<dl>
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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<dl>
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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<dl>
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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<dl>
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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<dl>
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<dd>Constrain input and output types to float tensors.</dd>
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</dl>
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### <a name="DynamicSlice-9"></a>**DynamicSlice-9**</a>
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Produces a slice of the input tensor along multiple axes. Similar to numpy:
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https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html
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Slices uses `axes`, `starts` and `ends` inputs to specify the start and end
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dimension for each axis in the list of axes, it uses this information to
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slice the input `data` tensor. If a negative value is passed for any of the
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start or end indices, it represent number of elements before the end of that
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dimension. If the value passed to start or end is larger than the `n` (the
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number of elements in this dimension), it represents `n`. For slicing to the
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end of a dimension with unknown size, it is recommended to pass in `INT_MAX`.
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If `axes` are omitted, they are set to `[0, ..., ndim-1]`.
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Example 1:
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data = [
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[1, 2, 3, 4],
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[5, 6, 7, 8],
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]
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axes = [0, 1]
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starts = [1, 0]
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ends = [2, 3]
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result = [
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[5, 6, 7],
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]
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Example 2:
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data = [
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[1, 2, 3, 4],
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[5, 6, 7, 8],
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]
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starts = [0, 1]
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ends = [-1, 1000]
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result = [
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[2, 3, 4],
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]
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#### Version
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This version of the operator has been available since version 9 of the default ONNX operator set.
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#### Inputs (3 - 4)
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<dl>
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<dt><tt>data</tt> : T</dt>
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<dd>Tensor of data to extract slices from.</dd>
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<dt><tt>starts</tt> : Tind</dt>
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<dd>1-D tensor of starting indices of corresponding axis in `axes`</dd>
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<dt><tt>ends</tt> : Tind</dt>
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<dd>1-D tensor of ending indices (exclusive) of corresponding axis in axes</dd>
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<dt><tt>axes</tt> (optional) : Tind</dt>
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<dd>1-D tensor of axes that `starts` and `ends` apply to.</dd>
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</dl>
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#### Outputs
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<dl>
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<dt><tt>output</tt> : T</dt>
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<dd>Sliced data tensor.</dd>
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</dl>
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#### Type Constraints
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<dl>
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<dt><tt>T</tt> : tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(int8), tensor(int16), tensor(int32), tensor(int64), tensor(float16), tensor(float), tensor(double), tensor(string), tensor(bool), tensor(complex64), tensor(complex128)</dt>
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<dd>Constrain input and output types to all tensor types.</dd>
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<dt><tt>Tind</tt> : tensor(int32), tensor(int64)</dt>
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<dd>Constrain indices to integer types</dd>
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</dl>
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### <a name="Erf-9"></a>**Erf-9**</a>
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Computes the error function of the given input tensor element-wise.

‎docs/Operators.md‎

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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Inputs (1 - &#8734;)
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Attributes
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#### Version
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This version of the operator has been available since version 9 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Inputs (3 - 4)
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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#### Version
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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This version of the operator has been available since version 1 of the default ONNX operator set.
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This version of the operator has been available since version 1 of the default ONNX operator set.
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No versioning maintained for experimental ops.
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<dl>

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