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Using tensor.untyped_storage() in InvertibleCheckpoint class methods. #6926

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Using tensor.untyped_storage() in InvertibleCheckpoint class methods. #6926

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Using `tensor.untyped_storage()` in `InvertibleCheckpoint` class meth…
drivanov Jan 9, 2024
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Merge branch 'master' into untyped_storage
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6 changes: 3 additions & 3 deletions python/dgl/nn/pytorch/conv/grouprevres.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,7 @@ def forward(ctx, fn, fn_inverse, num_inputs, *inputs_and_weights):
outputs = ctx.fn(*x).detach_()

# clear memory of input node features
inputs[1].storage().resize_(0)
inputs[1].untyped_storage().resize_(0)

# store for backward pass
ctx.inputs = [inputs]
Expand Down Expand Up @@ -63,10 +63,10 @@ def backward(ctx, *grad_outputs):
*((inputs[0], outputs) + inputs[2:])
)
# clear memory of outputs
outputs.storage().resize_(0)
outputs.untyped_storage().resize_(0)

x = inputs[1]
x.storage().resize_(int(np.prod(x.size())))
x.untyped_storage().resize_(int(np.prod(x.size())))
x.set_(inputs_inverted)

# compute gradients
Expand Down