Adding test for output that is a tensor of integers. Updating passthrough layer. #1526
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This pull request was exported from Phabricator. Differential Revision: D70919347 |
…h#1521) Summary: Pull Request resolved: pytorch#1521 This is to make sure that we control for when the output is not a 2D tensor We also include an output accessor that parses a dictionary model output to get final output. Differential Revision: D69876980
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…ough layer. (pytorch#1526) Summary: We are adding tests for different types of unsupported and non-differentiable layer output. Here, we add a test for layer output that is a tensor of integers. We split by the cases for unsupported layers from the case when the layer output is used by some tasks and not others. When layer output is not supported (layer output is a List of Tensors or a Tensor of integers), we don't get attributions and return None for those layers. In the case when a layer output is not used by a task, we should output a tensor of zeros for that task. Differential Revision: D70919347
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…ough layer. (pytorch#1526) Summary: Pull Request resolved: pytorch#1526 We are adding tests for different types of unsupported and non-differentiable layer output. Here, we add a test for layer output that is a tensor of integers. We split by the cases for unsupported layers from the case when the layer output is used by some tasks and not others. When layer output is not supported (layer output is a List of Tensors or a Tensor of integers), we don't get attributions and return None for those layers. In the case when a layer output is not used by a task, we should output a tensor of zeros for that task. Differential Revision: D70919347
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This pull request has been merged in b899732. |
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Summary: We are adding tests for different types of unsupported and non-differentiable layer output. Here, we add a test for layer output that is a tensor of integers.
Differential Revision: D70919347