masahi commented on a change in pull request #8443:
URL: https://github.com/apache/tvm/pull/8443#discussion_r670324562
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File path: python/tvm/relay/frontend/pytorch.py
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@@ -2329,6 +2331,30 @@ def flip(self, inputs, input_types):
axis = inputs[1]
return _op.transform.reverse(data, axis=axis[0])
+ def grid_sampler(self, inputs, input_types):
+ data = inputs[0]
+ grid = inputs[1]
+
+ # Torch grid shape is like [batch, out_height, out_width, 2], but
+ # TVM grid is [batch, 2, out_height, out_width], so here grid need to
be converted
+ grid = _op.transform.transpose(grid, axes=[0, 3, 1, 2])
+ return _op.image.grid_sample(data, grid, method="bilinear",
layout="NCHW")
+
+ def im2col(self, inputs, input_types):
+ r"""
+ Torch F.unfold set kerenl_size, dilation, padding, stride as pairs
before calling im2col
+ but it brokern TVM "if condition expression", so please USE
torch._C._nn.im2col instead
+ of F.unfold and make sure giving paired parameters. Please reference
test_forward_im2col
+ in file tests/python/frontend/pytorch/test_forward.py.
Review comment:
First of all, please fix the typo and grammar error, otherwise the
comments do not make sense. I don't understand what is "if condition
expression". Please revisit this problem assuming you don't need to support
script mode. `torch._C._nn.im2col` is not supposed to be used by users, we
should support the usage of `torch.unfold`.
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