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Posted to commits@tvm.apache.org by "jwfromm (via GitHub)" <gi...@apache.org> on 2023/08/17 22:43:34 UTC
[GitHub] [tvm] jwfromm opened a new pull request, #15586: [Unity][Frontend][NN] Conv2D NN module
jwfromm opened a new pull request, #15586:
URL: https://github.com/apache/tvm/pull/15586
In this PR I add support for `Conv2D` in our torch-like nn api. I'm planning on adding quite a few other such layers but wanted to get feedback on this one to make sure there arent any mistakes that would propagate :)
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[GitHub] [tvm] jwfromm merged pull request #15586: [Unity][Frontend][NN] Conv2D NN module
Posted by "jwfromm (via GitHub)" <gi...@apache.org>.
jwfromm merged PR #15586:
URL: https://github.com/apache/tvm/pull/15586
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[GitHub] [tvm] LeshengJin commented on a diff in pull request #15586: [Unity][Frontend][NN] Conv2D NN module
Posted by "LeshengJin (via GitHub)" <gi...@apache.org>.
LeshengJin commented on code in PR #15586:
URL: https://github.com/apache/tvm/pull/15586#discussion_r1297897338
##########
python/tvm/relax/frontend/nn/modules.py:
##########
@@ -107,6 +107,65 @@ def forward(self, x: Tensor) -> Tensor: # pylint: disable=invalid-name
return x
+class Conv2D(Module):
+ """
+ Module for conv2d layer.
+ """
+
+ def __init__( # pylint: disable=too-many-arguments
+ self,
+ in_channels: int,
+ out_channels: int,
+ kernel_size: int,
+ stride: int = 1,
+ padding: int = 0,
+ dilation: int = 1,
+ groups: int = 1,
+ bias: bool = True,
+ dtype: Optional[str] = None,
+ ):
+ super().__init__()
+ self.in_channels = in_channels
+ self.out_channels = out_channels
+ self.kernel_size = kernel_size
+ self.stride = stride
+ self.padding = padding
+ self.dilation = dilation
+ self.groups = groups
+
+ self.weight = Parameter(
+ (
+ self.out_channels,
+ int(self.in_channels / self.groups),
+ self.kernel_size,
+ self.kernel_size,
+ ),
+ dtype,
+ )
+ if bias:
+ self.bias = Parameter((self.out_channels,), dtype)
+ else:
+ self.bias = None
+
+ def forward(self, x: Tensor) -> Tensor: # pylint: disable=invalid-name
+ """
+ Forward method for conv2d layer.
+
+ Parameters
+ ----------
+ x : Tensor
+ The input tensor.
+
+ Returns
+ -------
+ ret : Tensor
+ The output tensor for the linear layer.
Review Comment:
A small typo.
`for the linear layer`
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[GitHub] [tvm] tvm-bot commented on pull request #15586: [Unity][Frontend][NN] Conv2D NN module
Posted by "tvm-bot (via GitHub)" <gi...@apache.org>.
tvm-bot commented on PR #15586:
URL: https://github.com/apache/tvm/pull/15586#issuecomment-1683072466
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[GitHub] [tvm] LeshengJin commented on a diff in pull request #15586: [Unity][Frontend][NN] Conv2D NN module
Posted by "LeshengJin (via GitHub)" <gi...@apache.org>.
LeshengJin commented on code in PR #15586:
URL: https://github.com/apache/tvm/pull/15586#discussion_r1297897338
##########
python/tvm/relax/frontend/nn/modules.py:
##########
@@ -107,6 +107,65 @@ def forward(self, x: Tensor) -> Tensor: # pylint: disable=invalid-name
return x
+class Conv2D(Module):
+ """
+ Module for conv2d layer.
+ """
+
+ def __init__( # pylint: disable=too-many-arguments
+ self,
+ in_channels: int,
+ out_channels: int,
+ kernel_size: int,
+ stride: int = 1,
+ padding: int = 0,
+ dilation: int = 1,
+ groups: int = 1,
+ bias: bool = True,
+ dtype: Optional[str] = None,
+ ):
+ super().__init__()
+ self.in_channels = in_channels
+ self.out_channels = out_channels
+ self.kernel_size = kernel_size
+ self.stride = stride
+ self.padding = padding
+ self.dilation = dilation
+ self.groups = groups
+
+ self.weight = Parameter(
+ (
+ self.out_channels,
+ int(self.in_channels / self.groups),
+ self.kernel_size,
+ self.kernel_size,
+ ),
+ dtype,
+ )
+ if bias:
+ self.bias = Parameter((self.out_channels,), dtype)
+ else:
+ self.bias = None
+
+ def forward(self, x: Tensor) -> Tensor: # pylint: disable=invalid-name
+ """
+ Forward method for conv2d layer.
+
+ Parameters
+ ----------
+ x : Tensor
+ The input tensor.
+
+ Returns
+ -------
+ ret : Tensor
+ The output tensor for the linear layer.
Review Comment:
A small typo
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