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v0.7.0

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fix CuDNN RecurrentOp Gradient init

Summary: CuDNN RecurrentNet GradientOp did not pass the DROPOUT information to the initializer, causing incorrect scratc
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h space size to be estimated. We have an assertion encorcing that scratch space is same for forward and backward ops, so this failed an assertion. We currently hard-code dropout to be 1.0, so this has had no effect on correctness in our tests. For some reason with num_layers=1 there wasn't an issue, but with num_layers>=2, the scratch space size was different.

Reviewed By: salexspb

Differential Revision: D4904715

fbshipit-source-id: 780266c5ecf1f7a32387edcb6fc498a13ac782ac

v0.6.0

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ubuntu installation instuctions for v0.6.0 (facebookarchive#244)

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