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Adding Reverse op (onnx#1804)
* Adding Reverse Op * fixing merge conflicts
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‎docs/Changelog.md

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@@ -9649,6 +9649,83 @@ This version of the operator has been available since version 10 of the default
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<dd>Constrain input 'X' and output 'Y' to all tensor types.</dd>
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</dl>
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### <a name="Reverse-10"></a>**Reverse-10**</a>
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Reverse a tensor of arbitrary shape along the given 'axes' in its dimensions.
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Example 1:
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input = [
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[0.0, 1.0, 2.0],
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[3.0, 4.0, 5.0],
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]
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output = [
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[5.0, 4.0, 3.0],
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[2.0, 1.0, 0.0],
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]
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Example 2:
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input = [
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[0.0, 1.0, 2.0],
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[3.0, 4.0, 5.0],
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]
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axes = [0]
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output = [
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[3.0, 4.0, 5.0],
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[0.0, 1.0, 2.0],
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]
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Example 3:
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input = [
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[[0.0, 1.0, 2.0],
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[3.0, 4.0, 5.0]],
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[[6.0, 7.0, 8.0],
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[9.0, 10.0, 11.0]],
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]
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axes = [1,-1]
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output = [
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[[5.0, 4.0, 3.0],
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[2.0, 1.0, 0.0]],
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[[11.0, 10.0, 9.0],
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[8.0, 7.0, 6.0]],
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]
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#### Version
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This version of the operator has been available since version 10 of the default ONNX operator set.
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#### Attributes
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<dl>
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<dt><tt>axes</tt> : list of ints</dt>
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<dd>A list of integers indicating the axes to reverse. Negative values mean counting dimensions from the back.By default, reverse over all axes of input dimensions</dd>
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</dl>
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#### Inputs
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<dl>
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<dt><tt>input</tt> : T</dt>
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<dd>Tensor of rank r >= 1.</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>Tensor of rank r >= 1 (same rank as input).</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>Input and output types can be of any tensor type.</dd>
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</dl>
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### <a name="Slice-10"></a>**Slice-10**</a>
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Produces a slice of the input tensor along multiple axes. Similar to numpy:

‎docs/Operators.md

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@@ -97,6 +97,7 @@
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* <a href="#Relu">Relu</a>
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* <a href="#Reshape">Reshape</a>
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* <a href="#Resize">Resize</a>
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* <a href="#Reverse">Reverse</a>
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* <a href="#Scan">Scan</a>
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* <a href="#Scatter">Scatter</a>
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* <a href="#Selu">Selu</a>
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</details>
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### <a name="Reverse"></a><a name="reverse">**Reverse**</a>
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Reverse a tensor of arbitrary shape along the given 'axes' in its dimensions.
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Example 1:
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input = [
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[0.0, 1.0, 2.0],
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[3.0, 4.0, 5.0],
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]
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output = [
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[5.0, 4.0, 3.0],
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[2.0, 1.0, 0.0],
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]
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Example 2:
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input = [
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[0.0, 1.0, 2.0],
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[3.0, 4.0, 5.0],
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]
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axes = [0]
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output = [
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[3.0, 4.0, 5.0],
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[0.0, 1.0, 2.0],
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]
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Example 3:
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input = [
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[[0.0, 1.0, 2.0],
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[3.0, 4.0, 5.0]],
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[[6.0, 7.0, 8.0],
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[9.0, 10.0, 11.0]],
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]
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axes = [1,-1]
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output = [
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[[5.0, 4.0, 3.0],
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[2.0, 1.0, 0.0]],
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[[11.0, 10.0, 9.0],
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[8.0, 7.0, 6.0]],
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]
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#### Version
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This version of the operator has been available since version 10 of the default ONNX operator set.
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#### Attributes
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<dl>
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<dt><tt>axes</tt> : list of ints</dt>
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<dd>A list of integers indicating the axes to reverse. Negative values mean counting dimensions from the back.By default, reverse over all axes of input dimensions</dd>
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</dl>
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#### Inputs
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<dl>
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<dt><tt>input</tt> : T</dt>
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<dd>Tensor of rank r >= 1.</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>Tensor of rank r >= 1 (same rank as input).</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>Input and output types can be of any tensor type.</dd>
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</dl>
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#### Examples
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<details>
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<summary>default</summary>
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```python
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input = np.arange(6.0).reshape(2, 3)
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node = onnx.helper.make_node(
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'Reverse',
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inputs=['input'],
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outputs=['output']
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)
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output = np.flip(np.flip(input, 0), 1)
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expect(node, inputs=[input], outputs=[output],
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name='test_reverse_default')
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```
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</details>
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<details>
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<summary>with_axes</summary>
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```python
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input = np.arange(6.0).reshape(2, 3)
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node = onnx.helper.make_node(
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'Reverse',
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inputs=['input'],
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outputs=['output'],
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axes=[0]
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)
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output = np.flip(input, 0)
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expect(node, inputs=[input], outputs=[output],
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name='test_reverse_with_axes')
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```
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</details>
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<details>
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<summary>with_negative_axes</summary>
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```python
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input = np.arange(12.0).reshape(2, 2, 3)
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node = onnx.helper.make_node(
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'Reverse',
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inputs=['input'],
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outputs=['output'],
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axes=[1, -1]
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)
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output = np.flip(np.flip(input, 1), -1)
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expect(node, inputs=[input], outputs=[output],
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name='test_reverse_with_negative_axes')
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```
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</details>
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### <a name="Scan"></a><a name="scan">**Scan**</a>
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Scan can be used to iterate over one or more scan_input tensors,

‎docs/TestCoverage.md

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* [Overall Test Coverage](#overall-test-coverage)
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# Node Test Coverage
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## Summary
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Node tests have covered 114/121 (94.21%, 5 generators excluded) common operators.
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Node tests have covered 115/122 (94.26%, 5 generators excluded) common operators.
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Node tests have covered 0/4 (0.00%, 0 generators excluded) experimental operators.
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@@ -5391,6 +5391,69 @@ expect(node, inputs=[data, scales], outputs=[output],
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</details>
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### Reverse
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There are 3 test cases, listed as following:
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<details>
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<summary>default</summary>
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```python
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input = np.arange(6.0).reshape(2, 3)
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node = onnx.helper.make_node(
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'Reverse',
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inputs=['input'],
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outputs=['output']
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)
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output = np.flip(np.flip(input, 0), 1)
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expect(node, inputs=[input], outputs=[output],
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name='test_reverse_default')
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```
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</details>
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<details>
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<summary>with_axes</summary>
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```python
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input = np.arange(6.0).reshape(2, 3)
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node = onnx.helper.make_node(
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'Reverse',
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inputs=['input'],
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outputs=['output'],
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axes=[0]
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)
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output = np.flip(input, 0)
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expect(node, inputs=[input], outputs=[output],
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name='test_reverse_with_axes')
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```
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</details>
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<details>
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<summary>with_negative_axes</summary>
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```python
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input = np.arange(12.0).reshape(2, 2, 3)
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5441+
node = onnx.helper.make_node(
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'Reverse',
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inputs=['input'],
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outputs=['output'],
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axes=[1, -1]
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)
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output = np.flip(np.flip(input, 1), -1)
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expect(node, inputs=[input], outputs=[output],
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name='test_reverse_with_negative_axes')
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```
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</details>
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### Scan
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There are 2 test cases, listed as following:
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<details>

‎onnx/backend/test/case/node/reverse.py

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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import numpy as np # type: ignore
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import onnx
9+
from ..base import Base
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from . import expect
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12+
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class Reverse(Base):
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@staticmethod
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def export_default(): # type: () -> None
17+
input = np.arange(6.0).reshape(2, 3)
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node = onnx.helper.make_node(
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'Reverse',
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inputs=['input'],
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outputs=['output']
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)
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output = np.flip(np.flip(input, 0), 1)
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expect(node, inputs=[input], outputs=[output],
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name='test_reverse_default')
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@staticmethod
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def export_with_axes(): # type: () -> None
32+
input = np.arange(6.0).reshape(2, 3)
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node = onnx.helper.make_node(
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'Reverse',
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inputs=['input'],
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outputs=['output'],
38+
axes=[0]
39+
)
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output = np.flip(input, 0)
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expect(node, inputs=[input], outputs=[output],
44+
name='test_reverse_with_axes')
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@staticmethod
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def export_with_negative_axes(): # type: () -> None
48+
input = np.arange(12.0).reshape(2, 2, 3)
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node = onnx.helper.make_node(
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'Reverse',
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inputs=['input'],
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outputs=['output'],
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axes=[1, -1]
55+
)
56+
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output = np.flip(np.flip(input, 1), -1)
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expect(node, inputs=[input], outputs=[output],
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name='test_reverse_with_negative_axes')

‎onnx/backend/test/data/node/test_reverse_default/model.onnx

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 backend-test:c
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inputoutput"Reversetest_reverse_defaultZ
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input
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b
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output
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B

‎onnx/backend/test/data/node/test_reverse_default/test_data_set_0/input_0.pb

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‎onnx/backend/test/data/node/test_reverse_default/test_data_set_0/output_0.pb

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‎onnx/backend/test/data/node/test_reverse_with_axes/model.onnx

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‎onnx/backend/test/data/node/test_reverse_with_axes/test_data_set_0/input_0.pb

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‎onnx/backend/test/data/node/test_reverse_with_axes/test_data_set_0/output_0.pb

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