Merge branch 'develop' into add_parity_check_ci

test/onnx/deconv_input_pads_strides_test.onnx → test/onnx/conv_transpose_input_pads_strides_test.onnx

-deconv_input_pads_strides_test:¶

+&conv_transpose_input_pads_strides_test:

 =
 
x
 
w
y"
ConvTranspose*
 pads@
@
@
@

*
-strides@@ 
deconv_input_pads_strides_testZ
+strides@@
&conv_transpose_input_pads_strides_testZ
 
x
 

 

@@ -21,4 +21,4 @@
 

 
 
-B
+B
\ No newline at end of file

test/onnx/deconv_output_padding_3d_test.onnx → test/onnx/conv_transpose_output_padding_3d_test.onnx

-deconv_output_padding_3d_test:

+%conv_transpose_output_padding_3d_test:

 G
 
x
 
w
y"
ConvTranspose*
 output_padding@
@
@

*
-strides@@@
deconv_output_padding_3d_testZ
+strides@@@
%conv_transpose_output_padding_3d_testZ
 
x
 

 

@@ -25,4 +25,4 @@ G
 
 
 
-B
\ No newline at end of file
+B
\ No newline at end of file

test/onnx/deconv_output_padding_test.onnx → test/onnx/conv_transpose_output_padding_test.onnx

-deconv_output_padding_test:

+"conv_transpose_output_padding_test:

 C
 
x
 
w
y"
ConvTranspose*
 output_padding@
@

*
-strides@@
deconv_output_padding_testZ
+strides@@
"conv_transpose_output_padding_testZ
 
x
 

 

@@ -22,4 +22,4 @@ C
 
 
 
-B
+B
\ No newline at end of file

test/onnx/deconv_output_shape_3d_test.onnx → test/onnx/conv_transpose_output_shape_3d_test.onnx

-deconv_output_shape_3d_test:

+#conv_transpose_output_shape_3d_test:

 E
 
x
 
w
y"
ConvTranspose*
 output_shape@
 @@
*
-strides@@@
deconv_output_shape_3d_testZ
+strides@@@
#conv_transpose_output_shape_3d_testZ
 
x
 

 

@@ -26,4 +26,4 @@ E
 
 
 
-B
\ No newline at end of file
+B
\ No newline at end of file

test/onnx/deconv_output_shape_test.onnx → test/onnx/conv_transpose_output_shape_test.onnx

-deconv_output_shape_test:

+ conv_transpose_output_shape_test:

 A
 
x
 
w
y"
ConvTranspose*
 output_shape@
 @
*
-strides@@
deconv_output_shape_testZ
+strides@@
 conv_transpose_output_shape_testZ
 
x
 

 

@@ -23,4 +23,4 @@ A
 
 
 
-B
+B
\ No newline at end of file

test/onnx/deconv_input_pads_test.onnx → test/onnx/conv_transpose_stride_test.onnx

-deconv_input_pads_test:®

-=
+conv_transpose_stride_test:

+*
 
x
-
w
y"
ConvTranspose*
-pads@
@
@
@
 
*
-strides@@ 
deconv_input_pads_testZ
+
w
y"
ConvTranspose*
+strides@@
conv_transpose_stride_testZ
 
x
 

 

@@ -21,4 +20,4 @@
 

 
 
-B
+B
\ No newline at end of file

test/onnx/deconv_test.onnx → test/onnx/conv_transpose_test.onnx

-deconv_test:…

+conv_transpose_test:

 
 
x
-
w
yconv1"
ConvTransposedeconv_testZ
+
w
yconv1"
ConvTransposeconv_transpose_testZ
 
x
 

 

@@ -19,4 +19,4 @@
 

 

 
-B
+B
\ No newline at end of file

test/onnx/gen_onnx.py

@@ -1376,7 +1376,7 @@ def cosh_test():
 
 
 @onnx_test()
-def deconv_test():
+def conv_transpose_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3, 3])
     w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 1, 3, 3])
     y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 1, 5, 5])
@@ -1390,7 +1390,7 @@ def deconv_test():
 
 
 @onnx_test()
-def deconv_bias_test():
+def conv_transpose_bias_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3, 3])
     w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 1, 3, 3])
     b = helper.make_tensor_value_info('b', TensorProto.FLOAT, [1])
@@ -1405,7 +1405,7 @@ def deconv_bias_test():
 
 
 @onnx_test()
-def deconv_input_pads_strides_test():
+def conv_transpose_input_pads_strides_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3, 3])
     w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 2, 3, 3])
     y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 2, 7, 5])
@@ -1420,7 +1420,7 @@ def deconv_input_pads_strides_test():
 
 
 @onnx_test()
-def deconv_input_pads_asymm_test():
+def conv_transpose_input_pads_asymm_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3, 3])
     w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 2, 3, 3])
     y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 2, 8, 6])
@@ -1435,7 +1435,7 @@ def deconv_input_pads_asymm_test():
 
 
 @onnx_test()
-def deconv_input_pads_asymm_1d_test():
+def conv_transpose_input_pads_asymm_1d_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3])
     w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 2, 3])
     y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 2, 6])
@@ -1451,7 +1451,7 @@ def deconv_input_pads_asymm_1d_test():
 
 
 @onnx_test()
-def deconv_output_padding_test():
+def conv_transpose_output_padding_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3, 3])
     w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 2, 3, 3])
     y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 2, 10, 8])
@@ -1466,7 +1466,7 @@ def deconv_output_padding_test():
 
 
 @onnx_test()
-def deconv_output_padding_3d_test():
+def conv_transpose_output_padding_3d_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3, 3, 3])
     w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 2, 3, 3, 3])
     y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 2, 10, 8, 8])
@@ -1481,7 +1481,7 @@ def deconv_output_padding_3d_test():
 
 
 @onnx_test()
-def deconv_output_shape_test():
+def conv_transpose_output_shape_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3, 3])
     w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 2, 3, 3])
     y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 2, 10, 8])
@@ -1496,7 +1496,7 @@ def deconv_output_shape_test():
 
 
 @onnx_test()
-def deconv_output_shape_3d_test():
+def conv_transpose_output_shape_3d_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3, 3, 3])
     w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 2, 3, 3, 3])
     y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 2, 10, 8, 8])
@@ -1511,7 +1511,7 @@ def deconv_output_shape_3d_test():
 
 
 @onnx_test()
-def deconv_stride_test():
+def conv_transpose_stride_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3, 3])
     w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 2, 3, 3])
     y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 2, 7, 3])
@@ -1524,6 +1524,81 @@ def deconv_stride_test():
     return ([node], [x, w], [y])
 
 
+@onnx_test()
+def conv_transpose_auto_pad_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [1, 1, 3, 3])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 1, 3, 3])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 1, 3, 3])
+
+    node = onnx.helper.make_node('ConvTranspose',
+                                 name='conv1',
+                                 inputs=['x', 'w'],
+                                 outputs=['y'],
+                                 auto_pad='SAME_UPPER')
+
+    return ([node], [x, w], [y])
+
+
+@onnx_test()
+def conv_transpose_dyn_asym_padding_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [None, 1, 3, 3])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 2, 3, 3])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [1, 2, 8, 6])
+
+    node = onnx.helper.make_node('ConvTranspose',
+                                 inputs=['x', 'w'],
+                                 outputs=['y'],
+                                 strides=[3, 2],
+                                 pads=[0, 0, 1, 1])
+
+    return ([node], [x, w], [y])
+
+
+@onnx_test()
+def conv_transpose_dyn_output_shape_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [None, 1, 3, 3])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 2, 3, 3])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [None, 2, 10, 8])
+
+    node = onnx.helper.make_node('ConvTranspose',
+                                 inputs=['x', 'w'],
+                                 outputs=['y'],
+                                 strides=[3, 2],
+                                 output_shape=[10, 8])
+
+    return ([node], [x, w], [y])
+
+
+@onnx_test()
+def conv_transpose_dyn_batch_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [None, 1, 3, 3])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 1, 3, 3])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [None, 1, 5, 5])
+
+    node = onnx.helper.make_node('ConvTranspose',
+                                 name='conv1',
+                                 inputs=['x', 'w'],
+                                 outputs=['y'])
+
+    return ([node], [x, w], [y])
+
+
+@onnx_test()
+def conv_transpose_dyn_img_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT,
+                                      [1, 1, None, None])
+    w = helper.make_tensor_value_info('w', TensorProto.FLOAT, [1, 1, 3, 3])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT,
+                                      [1, 1, None, None])
+
+    node = onnx.helper.make_node('ConvTranspose',
+                                 name='conv1',
+                                 inputs=['x', 'w'],
+                                 outputs=['y'])
+
+    return ([node], [x, w], [y])
+
+
 @onnx_test()
 def depthtospace_test():
 
@@ -6090,6 +6165,101 @@ def shape_test():
     return ([node], [x], [y])
 
 
+@onnx_test()
+def shape_dyn_test0():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT,
+                                      [None, 4, None, None])
+    y = helper.make_tensor_value_info('y', TensorProto.INT64, [4])
+
+    node = onnx.helper.make_node(
+        'Shape',
+        inputs=['x'],
+        outputs=['y'],
+    )
+
+    return ([node], [x], [y])
+
+
+@onnx_test()
+def shape_dyn_test1():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT,
+                                      [None, 4, None, None])
+    y = helper.make_tensor_value_info('y', TensorProto.INT64, [2])
+
+    node = onnx.helper.make_node('Shape', inputs=['x'], outputs=['y'], start=2)
+
+    return ([node], [x], [y])
+
+
+@onnx_test()
+def shape_dyn_test2():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT,
+                                      [None, 4, None, None])
+    y = helper.make_tensor_value_info('y', TensorProto.INT64, [2])
+
+    node = onnx.helper.make_node('Shape',
+                                 inputs=['x'],
+                                 outputs=['y'],
+                                 start=-2)
+
+    return ([node], [x], [y])
+
+
+@onnx_test()
+def shape_dyn_test3():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT,
+                                      [None, 4, None, None])
+    y = helper.make_tensor_value_info('y', TensorProto.INT64, [2])
+
+    node = onnx.helper.make_node('Shape',
+                                 inputs=['x'],
+                                 outputs=['y'],
+                                 start=1,
+                                 end=2)
+
+    return ([node], [x], [y])
+
+
+@onnx_test()
+def shape_end_oob_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT,
+                                      [None, 4, None, None])
+    y = helper.make_tensor_value_info('y', TensorProto.INT64, [2])
+
+    node = onnx.helper.make_node('Shape', inputs=['x'], outputs=['y'], end=5)
+
+    return ([node], [x], [y])
+
+
+@onnx_test()
+def shape_start_oob_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT,
+                                      [None, 4, None, None])
+    y = helper.make_tensor_value_info('y', TensorProto.INT64, [2])
+
+    node = onnx.helper.make_node('Shape',
+                                 inputs=['x'],
+                                 outputs=['y'],
+                                 start=-6)
+
+    return ([node], [x], [y])
+
+
+@onnx_test()
+def shape_end_less_start_error():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT,
+                                      [None, 4, None, None])
+    y = helper.make_tensor_value_info('y', TensorProto.INT64, [2])
+
+    node = onnx.helper.make_node('Shape',
+                                 inputs=['x'],
+                                 outputs=['y'],
+                                 start=3,
+                                 end=1)
+
+    return ([node], [x], [y])
+
+
 @onnx_test()
 def shape_gather_test():
     values = np.array([1])