Revert "Adding Reverse op (onnx#1804)" (onnx#1882)

This reverts commit 5be3e22.

Author: houseroad

docs/Changelog.md

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

docs/Operators.md

@@ -97,7 +97,6 @@
   * <a href="#Relu">Relu</a>
   * <a href="#Reshape">Reshape</a>
   * <a href="#Resize">Resize</a>
-  * <a href="#Reverse">Reverse</a>
   * <a href="#Scan">Scan</a>
   * <a href="#Scatter">Scatter</a>
   * <a href="#Selu">Selu</a>
@@ -10099,151 +10098,6 @@ expect(node, inputs=[data, scales], outputs=[output],
 </details>
 
 
-### <a name="Reverse"></a><a name="reverse">**Reverse**</a>
-
-  Reverse a tensor of arbitrary shape along the given 'axes' in its dimensions.
-  
-  Example 1:
-    input = [
-      [0.0, 1.0, 2.0],
-      [3.0, 4.0, 5.0],
-    ]
-  
-    output = [
-      [5.0, 4.0, 3.0],
-      [2.0, 1.0, 0.0],
-    ]
-  
-  Example 2:
-    input = [
-      [0.0, 1.0, 2.0],
-      [3.0, 4.0, 5.0],
-    ]
-  
-    axes = [0]
-  
-    output = [
-      [3.0, 4.0, 5.0],
-      [0.0, 1.0, 2.0],
-    ]
-    
-  Example 3:
-    input = [
-      [[0.0, 1.0, 2.0],
-       [3.0, 4.0, 5.0]],
-      [[6.0, 7.0, 8.0],
-       [9.0, 10.0, 11.0]],
-    ]
-  
-    axes = [1,-1]
-  
-    output = [
-      [[5.0, 4.0, 3.0],
-       [2.0, 1.0, 0.0]],
-      [[11.0, 10.0, 9.0],
-       [8.0, 7.0, 6.0]],
-    ]
-
-#### Version
-
-This version of the operator has been available since version 10 of the default ONNX operator set.
-
-#### Attributes
-
-<dl>
-<dt><tt>axes</tt> : list of ints</dt>
-<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>
-</dl>
-
-#### Inputs
-
-<dl>
-<dt><tt>input</tt> : T</dt>
-<dd>Tensor of rank r >= 1.</dd>
-</dl>
-
-#### Outputs
-
-<dl>
-<dt><tt>output</tt> : T</dt>
-<dd>Tensor of rank r >= 1 (same rank as input).</dd>
-</dl>
-
-#### Type Constraints
-
-<dl>
-<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>
-<dd>Input and output types can be of any tensor type.</dd>
-</dl>
-
-
-#### Examples
-
-<details>
-<summary>default</summary>
-
-```python
-input = np.arange(6.0).reshape(2, 3)
-
-node = onnx.helper.make_node(
-    'Reverse',
-    inputs=['input'],
-    outputs=['output']
-)
-
-output = np.flip(np.flip(input, 0), 1)
-
-expect(node, inputs=[input], outputs=[output],
-       name='test_reverse_default')
-```
-
-</details>
-
-
-<details>
-<summary>with_axes</summary>
-
-```python
-input = np.arange(6.0).reshape(2, 3)
-
-node = onnx.helper.make_node(
-    'Reverse',
-    inputs=['input'],
-    outputs=['output'],
-    axes=[0]
-)
-
-output = np.flip(input, 0)
-
-expect(node, inputs=[input], outputs=[output],
-       name='test_reverse_with_axes')
-```
-
-</details>
-
-
-<details>
-<summary>with_negative_axes</summary>
-
-```python
-input = np.arange(12.0).reshape(2, 2, 3)
-
-node = onnx.helper.make_node(
-    'Reverse',
-    inputs=['input'],
-    outputs=['output'],
-    axes=[1, -1]
-)
-
-output = np.flip(np.flip(input, 1), -1)
-
-expect(node, inputs=[input], outputs=[output],
-       name='test_reverse_with_negative_axes')
-```
-
-</details>
-
-
 ### <a name="Scan"></a><a name="scan">**Scan**</a>
 
   Scan can be used to iterate over one or more scan_input tensors,

docs/TestCoverage.md

@@ -5,7 +5,7 @@
 * [Overall Test Coverage](#overall-test-coverage)
 # Node Test Coverage
 ## Summary
-Node tests have covered 115/122 (94.26%, 5 generators excluded) common operators.
+Node tests have covered 114/121 (94.21%, 5 generators excluded) common operators.
 
 Node tests have covered 0/4 (0.00%, 0 generators excluded) experimental operators.
 
@@ -5391,69 +5391,6 @@ expect(node, inputs=[data, scales], outputs=[output],
 </details>
 
 
-### Reverse
-There are 3 test cases, listed as following:
-<details>
-<summary>default</summary>
-
-```python
-input = np.arange(6.0).reshape(2, 3)
-
-node = onnx.helper.make_node(
-    'Reverse',
-    inputs=['input'],
-    outputs=['output']
-)
-
-output = np.flip(np.flip(input, 0), 1)
-
-expect(node, inputs=[input], outputs=[output],
-       name='test_reverse_default')
-```
-
-</details>
-<details>
-<summary>with_axes</summary>
-
-```python
-input = np.arange(6.0).reshape(2, 3)
-
-node = onnx.helper.make_node(
-    'Reverse',
-    inputs=['input'],
-    outputs=['output'],
-    axes=[0]
-)
-
-output = np.flip(input, 0)
-
-expect(node, inputs=[input], outputs=[output],
-       name='test_reverse_with_axes')
-```
-
-</details>
-<details>
-<summary>with_negative_axes</summary>
-
-```python
-input = np.arange(12.0).reshape(2, 2, 3)
-
-node = onnx.helper.make_node(
-    'Reverse',
-    inputs=['input'],
-    outputs=['output'],
-    axes=[1, -1]
-)
-
-output = np.flip(np.flip(input, 1), -1)
-
-expect(node, inputs=[input], outputs=[output],
-       name='test_reverse_with_negative_axes')
-```
-
-</details>
-
-
 ### Scan
 There are 2 test cases, listed as following:
 <details>