{"payload":{"feedbackUrl":"https://github.com/orgs/community/discussions/53140","repo":{"id":154739597,"defaultBranch":"main","name":"jax","ownerLogin":"google","currentUserCanPush":false,"isFork":false,"isEmpty":false,"createdAt":"2018-10-25T21:25:02.000Z","ownerAvatar":"https://avatars.githubusercontent.com/u/1342004?v=4","public":true,"private":false,"isOrgOwned":true},"refInfo":{"name":"","listCacheKey":"v0:1714780515.0","currentOid":""},"activityList":{"items":[{"before":"a1c82219e2d23ec994e42761ebcaf4c53d9e4ea7","after":"047ea210e8f803f8624c39cfddaf6027e255b34a","ref":"refs/heads/main","pushedAt":"2024-05-05T02:09:58.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Update XLA dependency to use revision\nhttp://github.com/openxla/xla/commit/8833ecd8705f94c25502cb3580071ede8a2fe705.\n\nPiperOrigin-RevId: 630731298","shortMessageHtmlLink":"Update XLA dependency to use revision"}},{"before":"2fe4bf3f778ff07d1ae25e5c50321c0a1fc48c64","after":"78d5001672528f85191c08bf27c2a6db5e25f1b8","ref":"refs/heads/test_616865795","pushedAt":"2024-05-04T21:14:45.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":"b238ec84fa77fafd38dadb9105186461bacbeda9","after":"2fe4bf3f778ff07d1ae25e5c50321c0a1fc48c64","ref":"refs/heads/test_616865795","pushedAt":"2024-05-04T21:06:17.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":"41d6d6eb457154d9380b9aa02880b5a4859d3df5","after":"b238ec84fa77fafd38dadb9105186461bacbeda9","ref":"refs/heads/test_616865795","pushedAt":"2024-05-04T21:00:03.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":"1b804a772026becc81901fed1e97ef23e65cd5a4","after":"a1c82219e2d23ec994e42761ebcaf4c53d9e4ea7","ref":"refs/heads/main","pushedAt":"2024-05-04T02:19:44.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Update XLA dependency to use revision\nhttp://github.com/openxla/xla/commit/25d66ce58c51869f1220bc3b4df96a6939d8fbf6.\n\nPiperOrigin-RevId: 630557277","shortMessageHtmlLink":"Update XLA dependency to use revision"}},{"before":"e95173a4d39b86c44291a79a46e9f51dc3dd6a8f","after":"1b804a772026becc81901fed1e97ef23e65cd5a4","ref":"refs/heads/main","pushedAt":"2024-05-04T02:06:50.000Z","pushType":"push","commitsCount":2,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Merge pull request #21056 from mattjj:vmap-grad-remat-shmap-bug\n\nPiperOrigin-RevId: 630555588","shortMessageHtmlLink":"Merge pull request #21056 from mattjj:vmap-grad-remat-shmap-bug"}},{"before":"a506976cd8f894ba04911340f31c98d24f15a1c7","after":"41d6d6eb457154d9380b9aa02880b5a4859d3df5","ref":"refs/heads/test_616865795","pushedAt":"2024-05-04T01:02:57.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":"4947b76bf7c43400157c90d30d0bbc01a0cd72b8","after":"4bd7efcf6f78bacd2fac15f18e6629d999a846d7","ref":"refs/heads/test_627085500","pushedAt":"2024-05-04T00:58:10.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Generic reduce window jvp\n\nThe problem is that we want to generically jvp and tranpose over any reduction_fn. Jax already handles some of the hard parts for us, namely, ensuring that the user provided fn is jax capturable. All that is left then, is to write a jvp and tranpose fn that utilize the jax utils correctly.\n\nHowever, this is not so straightforward because in order to get the transpose of a reduction window, we need to be able to use both the tangents and primals. The current reduce_fn operates on (x, y) - but we actually need is, under jvp, to operate on `(x_primal, y_primal, x_tangent, y_tangent)`. In turn, this means we need to push down notions of a jvp-specific reduction_fn (captured via the usual machinery of as_fun `as_fun(jvp_fn(closed(user_reduction_jaxp)))`).\n\nFor the jvp fn, we stack the primal operand and the tangent operand together, and we stack their respective initial values together - this means a good deal of changes to safety checks and assurances downstream (as well as unpacking) as the shape of the operand has changed from [K,...Kt] to [K, ...Kt, 2] where the last dim is the stacked primal and tangent values.\n\nIn following CLs, we will add (1) re-entrant/recursive is_jvp and (2) transposition\n\nPiperOrigin-RevId: 627085500","shortMessageHtmlLink":"Generic reduce window jvp"}},{"before":"a0458b95f43dd2c2851682a656505352a6ec5141","after":"a506976cd8f894ba04911340f31c98d24f15a1c7","ref":"refs/heads/test_616865795","pushedAt":"2024-05-04T00:40:45.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":"9b68fe20fb2a8731b76792a1b308adf3108920a9","after":"a0458b95f43dd2c2851682a656505352a6ec5141","ref":"refs/heads/test_616865795","pushedAt":"2024-05-04T00:22:35.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":"25498e84948069545466da938200de02a3eb53b8","after":"4947b76bf7c43400157c90d30d0bbc01a0cd72b8","ref":"refs/heads/test_627085500","pushedAt":"2024-05-04T00:16:26.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Generic reduce window jvp\n\nThe problem is that we want to generically jvp and tranpose over any reduction_fn. Jax already handles some of the hard parts for us, namely, ensuring that the user provided fn is jax capturable. All that is left then, is to write a jvp and tranpose fn that utilize the jax utils correctly.\n\nHowever, this is not so straightforward because in order to get the transpose of a reduction window, we need to be able to use both the tangents and primals. The current reduce_fn operates on (x, y) - but we actually need is, under jvp, to operate on `(x_primal, y_primal, x_tangent, y_tangent)`. In turn, this means we need to push down notions of a jvp-specific reduction_fn (captured via the usual machinery of as_fun `as_fun(jvp_fn(closed(user_reduction_jaxp)))`).\n\nFor the jvp fn, we stack the primal operand and the tangent operand together, and we stack their respective initial values together - this means a good deal of changes to safety checks and assurances downstream (as well as unpacking) as the shape of the operand has changed from [K,...Kt] to [K, ...Kt, 2] where the last dim is the stacked primal and tangent values.\n\nIn following CLs, we will add (1) re-entrant/recursive is_jvp and (2) transposition\n\nPiperOrigin-RevId: 627085500","shortMessageHtmlLink":"Generic reduce window jvp"}},{"before":"9f622775fa8dbf25eef10a5edb8e64cdcbfa089e","after":"9b68fe20fb2a8731b76792a1b308adf3108920a9","ref":"refs/heads/test_616865795","pushedAt":"2024-05-04T00:12:31.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":"e95173a4d39b86c44291a79a46e9f51dc3dd6a8f","after":null,"ref":"refs/heads/test_630362617","pushedAt":"2024-05-03T23:55:15.000Z","pushType":"branch_deletion","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"}},{"before":"53208ffe270c5da0690849d55a98028c74984bad","after":"e95173a4d39b86c44291a79a46e9f51dc3dd6a8f","ref":"refs/heads/main","pushedAt":"2024-05-03T23:55:14.000Z","pushType":"push","commitsCount":1,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Require arraylike input for several jax.numpy functions\n\nPiperOrigin-RevId: 630532821","shortMessageHtmlLink":"Require arraylike input for several jax.numpy functions"}},{"before":"e079333222925d7afee611abb4827e6625f9c6f4","after":"e95173a4d39b86c44291a79a46e9f51dc3dd6a8f","ref":"refs/heads/test_630362617","pushedAt":"2024-05-03T23:55:13.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Require arraylike input for several jax.numpy functions\n\nPiperOrigin-RevId: 630532821","shortMessageHtmlLink":"Require arraylike input for several jax.numpy functions"}},{"before":"4918e9455bf408571791681c99b48ff4e3bf34d4","after":"e079333222925d7afee611abb4827e6625f9c6f4","ref":"refs/heads/test_630362617","pushedAt":"2024-05-03T23:34:09.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Require arraylike input for several jax.numpy functions\n\nPiperOrigin-RevId: 630362617","shortMessageHtmlLink":"Require arraylike input for several jax.numpy functions"}},{"before":"fc6a5d3a8da29e8683fa97ec73001051930b1d38","after":"53208ffe270c5da0690849d55a98028c74984bad","ref":"refs/heads/main","pushedAt":"2024-05-03T22:14:17.000Z","pushType":"push","commitsCount":2,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Merge pull request #21058 from jakevdp:jnp-delete-doc\n\nPiperOrigin-RevId: 630510340","shortMessageHtmlLink":"Merge pull request #21058 from jakevdp:jnp-delete-doc"}},{"before":null,"after":"d552c13e21440277f11dc395dd40fdf738f7120c","ref":"refs/heads/test_630504428","pushedAt":"2024-05-03T21:51:58.000Z","pushType":"branch_creation","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"[XLA] Add pattern matchers for AsyncStart and AsyncDone.\n\nPiperOrigin-RevId: 630504428","shortMessageHtmlLink":"[XLA] Add pattern matchers for AsyncStart and AsyncDone."}},{"before":"20722248f8e03612421d262106f94d474db6442c","after":"fc6a5d3a8da29e8683fa97ec73001051930b1d38","ref":"refs/heads/main","pushedAt":"2024-05-03T21:35:07.000Z","pushType":"push","commitsCount":2,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Merge pull request #21059 from jakevdp:numpy-doc-tests\n\nPiperOrigin-RevId: 630500410","shortMessageHtmlLink":"Merge pull request #21059 from jakevdp:numpy-doc-tests"}},{"before":"d6ef0a52de706317aab00be02171feef4a18ce59","after":"9f622775fa8dbf25eef10a5edb8e64cdcbfa089e","ref":"refs/heads/test_616865795","pushedAt":"2024-05-03T21:21:38.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":"bc865e0e1f8f5fa431ac73434b7c64120cf17900","after":"d6ef0a52de706317aab00be02171feef4a18ce59","ref":"refs/heads/test_616865795","pushedAt":"2024-05-03T20:42:59.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":"7e20e5303287e9c0624495af14cd0f0dbb70220d","after":"20722248f8e03612421d262106f94d474db6442c","ref":"refs/heads/main","pushedAt":"2024-05-03T20:39:06.000Z","pushType":"push","commitsCount":2,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Merge pull request #21064 from jakevdp:doc-new-tutorials\n\nPiperOrigin-RevId: 630484720","shortMessageHtmlLink":"Merge pull request #21064 from jakevdp:doc-new-tutorials"}},{"before":"0f0bb109c60744355348283f9f28c9b41b681340","after":"bc865e0e1f8f5fa431ac73434b7c64120cf17900","ref":"refs/heads/test_616865795","pushedAt":"2024-05-03T20:26:33.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":null,"after":"4402116104bf918be367070813493a80cf051439","ref":"refs/heads/test_629530367","pushedAt":"2024-05-03T19:15:35.000Z","pushType":"branch_creation","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"[Pallas][Mosaic] Support dynamic roll (part 1) - change roll amount to dynamic\n\nPiperOrigin-RevId: 629530367","shortMessageHtmlLink":"[Pallas][Mosaic] Support dynamic roll (part 1) - change roll amount t…"}},{"before":null,"after":"4918e9455bf408571791681c99b48ff4e3bf34d4","ref":"refs/heads/test_630362617","pushedAt":"2024-05-03T19:04:46.000Z","pushType":"branch_creation","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Require arraylike input for several jax.numpy functions\n\nPiperOrigin-RevId: 630362617","shortMessageHtmlLink":"Require arraylike input for several jax.numpy functions"}},{"before":"84d7ea0edbf15e658261f7aa8de18e6296c6fac5","after":"b1c590dd68f68606c11b84ed7bc15a9e047b35fa","ref":"refs/heads/test_629223390","pushedAt":"2024-05-03T18:52:46.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"[Pallas][Mosaic] Exposes LLO PRNG Ops in Mosaic/Pallas.\n\nPiperOrigin-RevId: 629223390","shortMessageHtmlLink":"[Pallas][Mosaic] Exposes LLO PRNG Ops in Mosaic/Pallas."}},{"before":null,"after":"84d7ea0edbf15e658261f7aa8de18e6296c6fac5","ref":"refs/heads/test_629223390","pushedAt":"2024-05-03T18:51:42.000Z","pushType":"branch_creation","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"[Pallas][Mosaic] Exposes LLO PRNG Ops in Mosaic/Pallas.\n\nPiperOrigin-RevId: 629223390","shortMessageHtmlLink":"[Pallas][Mosaic] Exposes LLO PRNG Ops in Mosaic/Pallas."}},{"before":"a1b864e0739a2f56bdfe51f3932c76243262eff4","after":"27a08f523021d8243a19c23ab60be6511fc8e5b0","ref":"refs/heads/test_630366504","pushedAt":"2024-05-03T18:19:53.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Remove deprecated `kind` argument from `jnp.sort` and `jnp.argsort`.\n\nPiperOrigin-RevId: 630366504","shortMessageHtmlLink":"Remove deprecated kind argument from jnp.sort and jnp.argsort."}},{"before":"2d1eb3c9cff70ea21aca0b81174e9442991b33a0","after":"0f0bb109c60744355348283f9f28c9b41b681340","ref":"refs/heads/test_616865795","pushedAt":"2024-05-03T17:59:43.000Z","pushType":"force_push","commitsCount":0,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Introduce hermetic CUDA in Google ML projects.\n\nInstead of having pre-installed NVIDIA CUDA and CUDNN libraries and setting environment variables pointing to the installation locations, Bazel should automatically download CUDA and CUDNN distributives in the cache and use them during build and test phases.\n\nThe Bazel version used in JAX is bumped from 6.1.2 to 6.5.0.\n\nPiperOrigin-RevId: 616865795","shortMessageHtmlLink":"Introduce hermetic CUDA in Google ML projects."}},{"before":"e70191bd9e67030fdce07ce5118f0380558dc53a","after":"7e20e5303287e9c0624495af14cd0f0dbb70220d","ref":"refs/heads/main","pushedAt":"2024-05-03T17:50:01.000Z","pushType":"push","commitsCount":2,"pusher":{"login":"copybara-service[bot]","name":null,"path":"/apps/copybara-service","primaryAvatarUrl":"https://avatars.githubusercontent.com/in/44061?s=80&v=4"},"commit":{"message":"Merge pull request #21057 from jakevdp:scipy-imports\n\nPiperOrigin-RevId: 630435054","shortMessageHtmlLink":"Merge pull request #21057 from jakevdp:scipy-imports"}}],"hasNextPage":true,"hasPreviousPage":false,"activityType":"all","actor":null,"timePeriod":"all","sort":"DESC","perPage":30,"cursor":"djE6ks8AAAAEQaiTzgA","startCursor":null,"endCursor":null}},"title":"Activity · google/jax"}