api-change:backup: The latest update introduces two new attributes, VaultType and VaultState, to the DescribeBackupVault and ListBackupVaults APIs. The VaultState attribute reflects the current status of the vault, while the VaultType attribute indicates the specific category of the vault.
api-change:datazone: Amazon DataZone now adds new governance capabilities of Domain Units for organization within your Data Domains, and Authorization Policies for tighter controls.
api-change:logs: This release introduces a new optional parameter: Entity, in PutLogEvents request
api-change:redshift-data: The release include the new Redshift DataAPI feature for session use, customer execute query with --session-keep-alive-seconds parameter and can submit follow-up queries to same sessions with returnedsession-id
1.35.9
api-change:bedrock-agent-runtime: Lifting the maximum length on Bedrock KnowledgeBase RetrievalFilter array
api-change:bedrock-runtime: Add support for imported-model in invokeModel and InvokeModelWithResponseStream.
api-change:personalize: This releases ability to update automatic training scheduler for customer solutions
api-change:quicksight: Increased Character Limit for Dataset Calculation Field expressions
api-change:stepfunctions: This release adds support for static analysis to ValidateStateMachineDefinition API, which can now return optional WARNING diagnostics for semantic errors on the definition of an Amazon States Language (ASL) state machine.
api-change:wafv2: The minimum request rate for a rate-based rule is now 10. Before this, it was 100.
1.35.8
api-change:appconfig: This release adds support for deletion protection, which is a safety guardrail to prevent the unintentional deletion of a recently used AWS AppConfig Configuration Profile or Environment. This also includes a change to increase the maximum length of the Name parameter in UpdateConfigurationProfile.
api-change:datazone: Update regex to include dot character to be consistent with IAM role creation in the authorized principal field for create and update subscription target.
api-change:devicefarm: This release removed support for Calabash, UI Automation, Built-in Explorer, remote access record, remote access replay, and web performance profile framework in ScheduleRun API.
api-change:ec2: Amazon VPC IP Address Manager (IPAM) now allows customers to provision IPv4 CIDR blocks and allocate Elastic IP Addresses directly from IPAM pools with public IPv4 space
api-change:internetmonitor: Adds new querying types to show overall traffic suggestion information for monitors
api-change:pcs: Introducing AWS Parallel Computing Service (AWS PCS), a new service makes it easy to setup and manage high performance computing (HPC) clusters, and build scientific and engineering models at virtually any scale on AWS.
api-change:workspaces: Documentation-only update that clarifies the StartWorkspaces and StopWorkspaces actions, and a few other minor edits.
1.35.7
api-change:bedrock: Amazon Bedrock SDK updates for Inference Profile.
api-change:bedrock-runtime: Amazon Bedrock SDK updates for Inference Profile.
api-change:chatbot: Update documentation to be consistent with the API docs
api-change:omics: Adds data provenance to import jobs from read sets and references
api-change:polly: Amazon Polly adds 2 new voices: Jitka (cs-CZ) and Sabrina (de-CH).
1.35.6
api-change:iotsitewise: AWS IoT SiteWise now supports versioning for asset models. It enables users to retrieve active version of their asset model and perform asset model writes with optimistic lock.
api-change:workspaces: This release adds support for creating and managing directories that use AWS IAM Identity Center as user identity source. Such directories can be used to create non-Active Directory domain joined WorkSpaces Personal.Updated RegisterWorkspaceDirectory and DescribeWorkspaceDirectories APIs.
xmap has been deleted. Please use {func}shard_map as the replacement.
Changes
The minimum CuDNN version is v9.1. This was true in previous releases also,
but we now declare this version constraint formally.
The minimum Python version is now 3.10. 3.10 will remain the minimum
supported version until July 2025.
The minimum NumPy version is now 1.24. NumPy 1.24 will remain the minimum
supported version until December 2024.
The minimum SciPy version is now 1.10. SciPy 1.10 will remain the minimum
supported version until January 2025.
{func}jax.numpy.ceil, {func}jax.numpy.floor and {func}jax.numpy.trunc now return the output
of the same dtype as the input, i.e. no longer upcast integer or boolean inputs to floating point.
libdevice.10.bc is no longer bundled with CUDA wheels. It must be
installed either as a part of local CUDA installation, or via NVIDIA's CUDA
pip wheels.
{class}jax.experimental.pallas.BlockSpec now expects block_shape to
be passed beforeindex_map. The old argument order is deprecated and
will be removed in a future release.
Updated the repr of gpu devices to be more consistent
with TPUs/CPUs. For example, cuda(id=0) will now be CudaDevice(id=0).
Added the device property and to_device method to {class}jax.Array, as
part of JAX's Array API support.
Deprecations
Removed a number of previously-deprecated internal APIs related to
polymorphic shapes. From {mod}jax.core: removed canonicalize_shape,
dimension_as_value, definitely_equal, and symbolic_equal_dim.
HLO lowering rules should no longer wrap singleton ir.Values in tuples.
Instead, return singleton ir.Values unwrapped. Support for wrapped values
will be removed in a future version of JAX.
{func}jax.experimental.jax2tf.convert with native_serialization=False
or enable_xla=False is now deprecated and this support will be removed in
a future version.
Native serialization has been the default since JAX 0.4.16 (September 2023).
The previously-deprecated function jax.random.shuffle has been removed;
instead use jax.random.permutation with independent=True.
jaxlib 0.4.31 (July 29, 2024)
Bug fixes
Fixed a bug that meant that negative static_argnums to a jit were mishandled
by the jit dispatch fast path.
Fixed a bug that meant triangular solves of batches of singular matrices
produce nonsensical finite values, instead of inf or nan (#3589, #15429).
xmap has been deleted. Please use {func}shard_map as the replacement.
Changes
The minimum CuDNN version is v9.1. This was true in previous releases also,
but we now declare this version constraint formally.
The minimum Python version is now 3.10. 3.10 will remain the minimum
supported version until July 2025.
The minimum NumPy version is now 1.24. NumPy 1.24 will remain the minimum
supported version until December 2024.
The minimum SciPy version is now 1.10. SciPy 1.10 will remain the minimum
supported version until January 2025.
{func}jax.numpy.ceil, {func}jax.numpy.floor and {func}jax.numpy.trunc now return the output
of the same dtype as the input, i.e. no longer upcast integer or boolean inputs to floating point.
libdevice.10.bc is no longer bundled with CUDA wheels. It must be
installed either as a part of local CUDA installation, or via NVIDIA's CUDA
pip wheels.
{class}jax.experimental.pallas.BlockSpec now expects block_shape to
be passed beforeindex_map. The old argument order is deprecated and
will be removed in a future release.
Updated the repr of gpu devices to be more consistent
with TPUs/CPUs. For example, cuda(id=0) will now be CudaDevice(id=0).
Added the device property and to_device method to {class}jax.Array, as
part of JAX's Array API support.
Deprecations
Removed a number of previously-deprecated internal APIs related to
polymorphic shapes. From {mod}jax.core: removed canonicalize_shape,
dimension_as_value, definitely_equal, and symbolic_equal_dim.
HLO lowering rules should no longer wrap singleton ir.Values in tuples.
Instead, return singleton ir.Values unwrapped. Support for wrapped values
will be removed in a future version of JAX.
{func}jax.experimental.jax2tf.convert with native_serialization=False
or enable_xla=False is now deprecated and this support will be removed in
a future version.
Native serialization has been the default since JAX 0.4.16 (September 2023).
The previously-deprecated function jax.random.shuffle has been removed;
instead use jax.random.permutation with independent=True.
jaxlib 0.4.31 (July 29, 2024)
Bug fixes
Fixed a bug that meant that negative static_argnums to a jit were mishandled
by the jit dispatch fast path.
Fixed a bug that meant triangular solves of batches of singular matrices
produce nonsensical finite values, instead of inf or nan (#3589, #15429).
NumPy 2.1.0 provides support for the upcoming Python 3.13 release and
drops support for Python 3.9. In addition to the usual bug fixes and
updated Python support, it helps get us back into our usual release
cycle after the extended development of 2.0. The highlights for this
release are:
Support for the array-api 2023.12 standard.
Support for Python 3.13.
Preliminary support for free threaded Python 3.13.
Python versions 3.10-3.13 are supported in this release.
New functions
New function numpy.unstack
A new function np.unstack(array, axis=...) was added, which splits an
array into a tuple of arrays along an axis. It serves as the inverse of
[numpy.stack]{.title-ref}.
The fix_imports keyword argument in numpy.save is deprecated.
Since NumPy 1.17, numpy.save uses a pickle protocol that no longer
supports Python 2, and ignored fix_imports keyword. This keyword
is kept only for backward compatibility. It is now deprecated.
Passing non-integer inputs as the first argument of
[bincount]{.title-ref} is now deprecated, because such inputs are
silently cast to integers with no warning about loss of precision.
Either method can be selected when instantiating the default.tensor device by setting the method keyword argument to "tn" (tensor network) or "mps" (matrix product state).
There are several templates in PennyLane that are tensor-network focused, which are excellent candidates for the "tn" method for default.tensor. The following example shows how a circuit comprising gates in a tree tensor network architecture can be efficiently simulated using method="tn".
import pennylane as qml
n_wires = 16
dev = qml.device("default.tensor", method="tn")
@qml.qnode(dev)
def circuit(template_weights):
for i in range(n_wires):
qml.Hadamard(i)
qml.TTN(range(n_wires), n_block_wires, block, n_params_block, template_weights)
return qml.expval(qml.Z(n_wires - 1))
>>> circuit(template_weights)
0.3839174759751649
For matrix product state simulations (method="mps"), we can make the execution be approximate by setting max_bond_dim (see the device's documentation for more details). The maximum bond dimension has implications for the speed of the simulation and lets us control the degree of the approximation, as shown in the following example. First, set up the circuit:
dynamic_one_shot uses shot-vectors in the auxiliary tape to tell the device how many times to repeat the tape. Lightning-Qubit is updated accordingly. [(#724)](PennyLaneAI/pennylane-lightning#724)
dynamic_one_shot deals with post-selection during the post-processing phase, so Lightning-Qubit does not return None-valued measurements for mismatching samples anymore. [(#720)](PennyLaneAI/pennylane-lightning#720)
Lightning-Kokkos dev wheels for MacOS (x86_64, ARM64) and Linux (aarch64) are uploaded to TestPyPI upon merging a pull request. [(#765)](PennyLaneAI/pennylane-lightning#765)
Change the type of tensor network objects passed to ObservablesTNCuda and MeasurementsTNCuda classes from StateTensorT to TensorNetT. [(#759)](PennyLaneAI/pennylane-lightning#759)
Rationalize MCM tests, removing most end-to-end tests from the native MCM test file, but keeping one that validates multiple mid-circuit measurements with any allowed return. [(#754)](PennyLaneAI/pennylane#754)
Lightning-Kokkos' functors are rewritten as functions wrapping around generic gate and generator functors templated over a coefficient interaction function. This reduces boilerplate while clarifying how the various kernels differ from one another. [(#640)](PennyLaneAI/pennylane-lightning#640)
Aer 0.15 is released to support Qiskit 1.2.
As Qiskit 1.2 deprecates V1 backends and primitives, Aer also deprecates these functionalities. Also Aer 0.15 removed standalone simulator and qobj support.
Updates the requirements on botocore, awscli, boto3, amazon-braket-sdk, jax, jaxlib, numpy, optax, pennylane, pennylane-lightning, qiskit-aer, scipy, scs and sympy to permit the latest version. Updates
botocorefrom 1.35.0 to 1.35.10Changelog
Sourced from botocore's changelog.
... (truncated)
Commits
6e846e8Merge branch 'release-1.35.10'6cb9ba2Bumping version to 1.35.108c5e3e5Update endpoints model5b5356fUpdate to latest models3428c19Merge branch 'release-1.35.9' into develop606af07Merge branch 'release-1.35.9'764d893Bumping version to 1.35.99a37f04Update to latest modelsc294152Merge branch 'release-1.35.8' into developfbd8b1eMerge branch 'release-1.35.8'Updates
awsclifrom 1.34.0 to 1.34.10Commits
765bffbMerge branch 'release-1.34.10'54510ffBumping version to 1.34.1049747c5Update changelog based on model updates55d5c19Merge branch 'release-1.34.9'd8f3912Merge branch 'release-1.34.9' into develop4149108Bumping version to 1.34.97a3bb1aUpdate changelog based on model updates6f4d46cMerge branch 'release-1.34.8'a2c094cMerge branch 'release-1.34.8' into develop34b0ccaBumping version to 1.34.8Updates
boto3from 1.35.0 to 1.35.10Commits
85cba10Merge branch 'release-1.35.10'7264985Bumping version to 1.35.104e8bc10Add changelog entries from botocore6f961e2Merge branch 'release-1.35.9'25ebb36Merge branch 'release-1.35.9' into developed635b5Bumping version to 1.35.93a06379Add changelog entries from botocore0733f58Merge branch 'release-1.35.8'1cbfeecMerge branch 'release-1.35.8' into develop79f7f2cBumping version to 1.35.8Updates
amazon-braket-sdkfrom 1.86.0 to 1.86.1Release notes
Sourced from amazon-braket-sdk's releases.
Changelog
Sourced from amazon-braket-sdk's changelog.
Commits
6cad46eprepare release v1.86.18f4e88ffix: Use observable targets for targetless results (#1025)93f450bupdate development version to v1.86.1.dev0Updates
jaxfrom 0.4.29 to 0.4.31Changelog
Sourced from jax's changelog.
... (truncated)
Commits
7fd9302Start JAX and jaxlib 0.4.31 releasef070c06Merge pull request #22703 from Rifur13:plugin-fix9beb4f1Merge pull request #19760 from Blair-Johnson:fix-pytree-grads-sparse802a14cRe-pack gradients of jax.experimental.sparse.grad() to match original pytrees...85e83b5Merge pull request #22690 from jakevdp:inplace-docd1c0d99Bump the minimum CUDNN version to v9.1.6127baaIgnore the Deprecation warning produced aboutnative_serialization=False.fd23b87Bump minimum SciPy version to 1.10.cfa1e78Improve documentation for jnp.put, jnp.place, jnp.fill_diagonal0224235Skip cuda backend initialization if no nvidia GPUs are visible.Updates
jaxlibfrom 0.4.29 to 0.4.31Changelog
Sourced from jaxlib's changelog.
... (truncated)
Commits
7fd9302Start JAX and jaxlib 0.4.31 releasef070c06Merge pull request #22703 from Rifur13:plugin-fix9beb4f1Merge pull request #19760 from Blair-Johnson:fix-pytree-grads-sparse802a14cRe-pack gradients of jax.experimental.sparse.grad() to match original pytrees...85e83b5Merge pull request #22690 from jakevdp:inplace-docd1c0d99Bump the minimum CUDNN version to v9.1.6127baaIgnore the Deprecation warning produced aboutnative_serialization=False.fd23b87Bump minimum SciPy version to 1.10.cfa1e78Improve documentation for jnp.put, jnp.place, jnp.fill_diagonal0224235Skip cuda backend initialization if no nvidia GPUs are visible.Updates
numpyfrom 1.26.4 to 2.1.0Release notes
Sourced from numpy's releases.
... (truncated)
Commits
2f7fe64Merge pull request #27236 from charris/prepare-2.1.0b6f434fREL: Prepare for the NumPy 2.1.0 release [wheel build]3cf9394Merge pull request #27234 from charris/backport-259847443dccMerge pull request #27233 from charris/backport-2722385b1cabBUG: Allow fitting of degree zero polynomials with Polynomial.fit395a81dDOC: reword discussion about shared arrays to hopefully be clearer5af2e96Move NUMUSERTYPES thread safety discussion to legacy DType API docsd902c24DOC: add docs on thread safety in NumPyc080180Merge pull request #27229 from charris/backport-2722644ce7e8BUG: FixPyArray_ZeroContiguousBuffer(resize) with struct dtypesUpdates
optaxfrom 0.2.2 to 0.2.3Release notes
Sourced from optax's releases.
... (truncated)
Commits
e90eecdRelease v0.2.38c46b75Fix doctest normalize_by_update_norm5b55cccMerge pull request #1000 from fabianp:SauravMaheshkar-saurav/scale_by_grad_norm648a967Add schedule_free check for b1 != 0.f72fbfcAdd common schedule_free wrappers.2660a04Merge branch 'saurav/scale_by_grad_norm' of https://github.com/SauravMaheshka...23b7703LBFGS part 4: notebook illustrating how to use lbfgs with linesearch as a sol...10cf508Add arxiv reference to schedule_free optimizer.b849fc6docs: update transformations API docs5c01f6fdocs: update transformationsUpdates
pennylanefrom 0.35.1 to 0.37.0Release notes
Sourced from pennylane's releases.
... (truncated)
Commits
af5bd6dBump required versions of Lightning and Catalyst (#5963)9a60574Fix jax enable x64 (#5960)add20fcFF Fixes (#5931)0218745Doc fixes (#5952)ea14834QA release fixes (#5934)60f9da2[sc-59665] v0.37 changelog (#5928)b8b9f19Lazy check keras layer (#5956)9c22ac7Fix invert dunder method. (#5955)0e5dd6bFixessplit_non_commutingwith non-trainable autograd coefficients (#5945)a6f133bDocumentation fixes (#5946)Updates
pennylane-lightningfrom 0.35.1 to 0.37.0Release notes
Sourced from pennylane-lightning's releases.
... (truncated)
Commits
4ba2434Forked as v0.37.0_release to be released with tag v0.37.0.240b7edFix lint LGPU.8385da6trigger ci7b48d4eUpdate macOS-1267ac395Revert upload-pypi triggers and build all wheels with ci:build_wheels tag.8de77e9trigger ci70b9a84trigger ci8cc6b97Added pickle support for lightning.gpu device'sDevPoolattribute (#772)d1299fdMerge branch 'master' into v0.37.0_rc84b5da5Added pickle support for lightning.gpu device'sDevPoolattribute (#772)Updates
qiskit-aerfrom 0.14.2 to 0.15.0Release notes
Sourced from qiskit-aer's releases.