optima2005 commented on a change in pull request #4639: [Relay/Topi][Op] Conv1D
URL: https://github.com/apache/incubator-tvm/pull/4639#discussion_r365054591
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File path: tests/python/frontend/onnx/test_forward.py
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@@ -1761,18 +1773,95 @@ def verify_conv(x_shape, w_shape, y_shape, p):
def test_conv():
# Convolution with padding
- # (1, 1, 5, 5) input tensor
- # (1, 1, 3, 3) tensor for convolution weights
- # (1, 1, 5, 5) output tensor
- # [1, 1, 1, 1] list for pads
- verify_conv((1, 1, 5, 5), (1, 1, 3, 3), (1, 1, 5, 5), [1, 1, 1, 1])
+ # Conv2D
+ verify_conv(x_shape=(1, 1, 5, 5),
+ w_shape=(1, 1, 3, 3),
+ y_shape=(1, 1, 5, 5),
+ padding=[1, 1, 1, 1],
+ kernel_shape=[3, 3],
+ strides=[1, 1],
+ dilations=[1, 1])
+ # Conv1D
+ verify_conv(x_shape=(1, 1, 5),
+ w_shape=(1, 1, 3),
+ y_shape=(1, 1, 5),
+ padding=[1, 1],
+ kernel_shape=[3,],
+ strides=[1,],
+ dilations=[1,])
# Convolution without padding
- # (1, 1, 5, 5) input tensor
- # (1, 1, 3, 3) tensor for convolution weights
- # (1, 1, 3, 3) output tensor
- # [0, 0, 0, 0] list for pads
- verify_conv((1, 1, 5, 5), (1, 1, 3, 3), (1, 1, 3, 3), [0, 0, 0, 0])
+ # Conv2D
+ verify_conv(x_shape=(1, 1, 5, 5),
+ w_shape=(1, 1, 3, 3),
+ y_shape=(1, 1, 3, 3),
+ padding=[0, 0, 0, 0],
+ kernel_shape=[3, 3],
+ strides=[1, 1],
+ dilations=[1, 1])
+ # Conv1D
+ verify_conv(x_shape=(1, 1, 5),
+ w_shape=(1, 1, 3),
+ y_shape=(1, 1, 3),
+ padding=[0, 0],
+ kernel_shape=[3,],
+ strides=[1,],
+ dilations=[1,])
+
+ # Convolution with autopadding
+ verify_conv(x_shape=(1, 1, 5, 5),
+ w_shape=(1, 1, 3, 3),
+ y_shape=(1, 1, 5, 5),
+ kernel_shape=[3, 3],
+ strides=[1, 1],
+ dilations=[1, 1],
+ padding=None,
+ auto_pad="SAME_UPPER")
+ # Conv1D
+ verify_conv(x_shape=(1, 1, 5),
+ w_shape=(1, 1, 3),
+ y_shape=(1, 1, 5),
+ kernel_shape=[3,],
+ strides=[1,],
+ dilations=[1,],
+ padding=None,
+ auto_pad="SAME_UPPER")
+
+ # Convolution with non uniform stride
+ verify_conv(x_shape=(1, 1, 5, 5),
+ w_shape=(1, 1, 3, 3),
+ y_shape=(1, 1, 3, 3),
+ kernel_shape=[3, 3],
+ strides=[2, 2],
+ dilations=[1, 1],
+ padding=None,
+ auto_pad="SAME_UPPER")
+ # Conv1D
+ verify_conv(x_shape=(1, 1, 5),
+ w_shape=(1, 1, 3),
+ y_shape=(1, 1, 3),
+ kernel_shape=[3,],
+ strides=[2,],
+ dilations=[1,],
+ padding=None,
+ auto_pad="SAME_UPPER")
+
+ # Convolution with dilation
+ verify_conv(x_shape=(1, 1, 5, 5),
+ w_shape=(1, 1, 3, 3),
+ y_shape=(1, 1, 5, 5),
+ kernel_shape=[3, 3],
+ strides=[1, 1],
+ dilations=[2, 2],
+ padding=[2, 2, 2, 2])
+ # Conv1D
+ verify_conv(x_shape=(1, 1, 5),
+ w_shape=(1, 1, 3),
+ y_shape=(1, 1, 5),
+ kernel_shape=[3,],
+ strides=[1,],
+ dilations=[2,],
+ padding=[2, 2])
Review comment:
The parameter key words are not necessary for those cases.
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