profile
viewpoint
If you are wondering where the data of this site comes from, please visit https://api.github.com/users/vinodmut/events. GitMemory does not store any data, but only uses NGINX to cache data for a period of time. The idea behind GitMemory is simply to give users a better reading experience.

milinda/Freshet-Old 47

CQL based Clojure DSL for Apache Samza

vinodmut/chef-graphite 0

A Chef cookbook to install Graphite.

vinodmut/chef-nodejs 0

A Chef cookbook to install Node.js.

vinodmut/chef-statsd 0

A Chef cookbook to install StatsD.

vinodmut/FfDL 0

Fabric for Deep Learning (FfDL) ***WORK IN PROGRESS***

vinodmut/heroku-buildpack-nodejs 0

The official Heroku buildpack for Node.js apps.

vinodmut/java-buildpack 0

Cloud Foundry buildpack for running Java applications

vinodmut/openwhisk 0

OpenWhisk is a cloud-first distributed event-based programming service.

push eventserverlesscomputing/serverlesscomputing

Aleksander Slominski

commit sha 3942c737ecb619c2c123c2dfef01777b9e94d69f

cfp

view details

push time in 4 days

push eventserverlesscomputing/serverlesscomputing

Aleksander Slominski

commit sha 454b941343bb64ebb45e95e1892ffb768d800c97

add wosc6

view details

Aleksander Slominski

commit sha 95f84440b43b0d406958ab7533d259fb5a07781b

add wosc6

view details

push time in 5 days

push eventserverlesscomputing/serverlesscomputing

Aleksander Slominski

commit sha 140b599da0f1db46ff0edef300eeded99bd9b539

edits

view details

push time in 5 days

push eventserverlesscomputing/serverlesscomputing

Aleksander Slominski

commit sha 867a7b30afa612ffda35a22c51adc2d42d24e5e6

renamed to index draft

view details

push time in 5 days

push eventserverlesscomputing/serverlesscomputing

Aleksander Slominski

commit sha 82150c9a8386557fec0399c9ba20bb65dc7a23d2

renamed to draft

view details

push time in 5 days

push eventserverlesscomputing/serverlesscomputing

Aleksander Slominski

commit sha eb59c6c9918a18d03787bd4bc17c662e732981be

draft wosc7

view details

push time in 5 days

push eventserverlesscomputing/serverlesscomputing

Aleksander Slominski

commit sha e5b80e2448f90a5c447c965d536f7c8a10929604

missing link

view details

push time in 5 days

delete branch IBM/FfDL

delete branch : dependabot/pip/community/FfDL-Seldon/tf-model/tensorflow-2.3.1

delete time in a month

PR closed IBM/FfDL

Bump tensorflow from 1.6.0 to 2.3.1 in /community/FfDL-Seldon/tf-model Dependencies python

Bumps tensorflow from 1.6.0 to 2.3.1. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/tensorflow/tensorflow/releases">tensorflow's releases</a>.</em></p> <blockquote> <h2>TensorFlow 2.3.1</h2> <h1>Release 2.3.1</h1> <h2>Bug Fixes and Other Changes</h2> <ul> <li>Fixes an undefined behavior causing a segfault in <code>tf.raw_ops.Switch</code> (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15190">CVE-2020-15190</a>)</li> <li>Fixes three vulnerabilities in conversion to DLPack format (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15191">CVE-2020-15191</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15192">CVE-2020-15192</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15193">CVE-2020-15193</a>)</li> <li>Fixes two vulnerabilities in <code>SparseFillEmptyRowsGrad</code> (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15194">CVE-2020-15194</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15195">CVE-2020-15195</a>)</li> <li>Fixes several vulnerabilities in <code>RaggedCountSparseOutput</code> and <code>SparseCountSparseOutput</code> operations (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15196">CVE-2020-15196</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15197">CVE-2020-15197</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15198">CVE-2020-15198</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15199">CVE-2020-15199</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15200">CVE-2020-15200</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15201">CVE-2020-15201</a>)</li> <li>Fixes an integer truncation vulnerability in code using the work sharder API (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15202">CVE-2020-15202</a>)</li> <li>Fixes a format string vulnerability in <code>tf.strings.as_string</code> (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15203">CVE-2020-15203</a>)</li> <li>Fixes segfault raised by calling session-only ops in eager mode (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15204">CVE-2020-15204</a>)</li> <li>Fixes data leak and potential ASLR violation from <code>tf.raw_ops.StringNGrams</code> (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15205">CVE-2020-15205</a>)</li> <li>Fixes segfaults caused by incomplete <code>SavedModel</code> validation (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15206">CVE-2020-15206</a>)</li> <li>Fixes a data corruption due to a bug in negative indexing support in TFLite (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15207">CVE-2020-15207</a>)</li> <li>Fixes a data corruption due to dimension mismatch in TFLite (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15208">CVE-2020-15208</a>)</li> <li>Fixes several vulnerabilities in TFLite saved model format (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15209">CVE-2020-15209</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15210">CVE-2020-15210</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15211">CVE-2020-15211</a>)</li> <li>Fixes several vulnerabilities in TFLite implementation of segment sum (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15212">CVE-2020-15212</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15213">CVE-2020-15213</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15214">CVE-2020-15214</a>)</li> <li>Updates <code>sqlite3</code> to <code>3.33.00</code> to handle <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15358">CVE-2020-15358</a>.</li> <li>Fixes deprecated usage of <code>collections</code> API</li> <li>Removes <code>scipy</code> dependency from <code>setup.py</code> since TensorFlow does not need it to install the pip package</li> </ul> <h2>TensorFlow 2.3.0</h2> <h1>Release 2.3.0</h1> <h2>Major Features and Improvements</h2> <ul> <li><code>tf.data</code> adds two new mechanisms to solve input pipeline bottlenecks and save resources: <ul> <li><a href="https://www.tensorflow.org/api_docs/python/tf/data/experimental/snapshot">snapshot</a></li> <li><a href="https://www.tensorflow.org/api_docs/python/tf/data/experimental/service">tf.data service</a>.</li> </ul> </li> </ul> <p>In addition checkout the detailed <a href="https://www.tensorflow.org/guide/data_performance_analysis">guide</a> for analyzing input pipeline performance with TF Profiler.</p> <ul> <li> <p><a href="https://www.tensorflow.org/api_docs/python/tf/distribute/TPUStrategy"><code>tf.distribute.TPUStrategy</code></a> is now a stable API and no longer considered experimental for TensorFlow. (earlier <code>tf.distribute.experimental.TPUStrategy</code>).</p> </li> <li> <p><a href="https://www.tensorflow.org/guide/profiler">TF Profiler</a> introduces two new tools: a memory profiler to visualize your model’s memory usage over time and a <a href="https://www.tensorflow.org/guide/profiler#events">python tracer</a> which allows you to trace python function calls in your model. Usability improvements include better diagnostic messages and <a href="https://tensorflow.org/guide/profiler#collect_performance_data">profile options</a> to customize the host and device trace verbosity level.</p> </li> <li> <p>Introduces experimental support for Keras Preprocessing Layers API (<a href="https://www.tensorflow.org/api_docs/python/tf/keras/layers/experimental/preprocessing?version=nightly"><code>tf.keras.layers.experimental.preprocessing.*</code></a>) to handle data preprocessing operations, with support for composite tensor inputs. Please see below for additional details on these layers.</p> </li> <li> <p>TFLite now properly supports dynamic shapes during conversion and inference. We’ve also added opt-in support on Android and iOS for <a href="https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/delegates/xnnpack">XNNPACK</a>, a highly optimized set of CPU kernels, as well as opt-in support for <a href="https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/performance/gpu_advanced.md#running-quantized-models-experimental">executing quantized models on the GPU</a>.</p> </li> <li> <p>Libtensorflow packages are available in GCS starting this release. We have also started to <a href="https://github.com/tensorflow/tensorflow#official-builds">release a nightly version of these packages</a>.</p> </li> <li> <p>The experimental Python API <a href="https://www.tensorflow.org/api_docs/python/tf/debugging/experimental/enable_dump_debug_info"><code>tf.debugging.experimental.enable_dump_debug_info()</code></a> now allows you to instrument a TensorFlow program and dump debugging information to a directory on the file system. The directory can be read and visualized by a new interactive dashboard in TensorBoard 2.3 called <a href="https://www.tensorflow.org/tensorboard/debugger_v2">Debugger V2</a>, which reveals the details of the TensorFlow program including graph structures, history of op executions at the Python (eager) and intra-graph levels, the runtime dtype, shape, and numerical composistion of tensors, as well as their code locations.</p> </li> </ul> <h2>Breaking Changes</h2> <ul> <li>Increases the <strong>minimum bazel version</strong> required to build TF to <strong>3.1.0</strong>.</li> <li><code>tf.data</code> <ul> <li>Makes the following (breaking) changes to the <code>tf.data</code>.</li> <li>C++ API: - <code>IteratorBase::RestoreInternal</code>, <code>IteratorBase::SaveInternal</code>, and <code>DatasetBase::CheckExternalState</code> become pure-virtual and subclasses are now expected to provide an implementation.</li> <li>The deprecated <code>DatasetBase::IsStateful</code> method is removed in favor of <code>DatasetBase::CheckExternalState</code>.</li> <li>Deprecated overrides of <code>DatasetBase::MakeIterator</code> and <code>MakeIteratorFromInputElement</code> are removed.</li> </ul> </li> </ul> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Changelog</summary> <p><em>Sourced from <a href="https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md">tensorflow's changelog</a>.</em></p> <blockquote> <h1>Release 2.3.1</h1> <h2>Bug Fixes and Other Changes</h2> <ul> <li>Fixes an undefined behavior causing a segfault in <code>tf.raw_ops.Switch</code> (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15190">CVE-2020-15190</a>)</li> <li>Fixes three vulnerabilities in conversion to DLPack format (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15191">CVE-2020-15191</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15192">CVE-2020-15192</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15193">CVE-2020-15193</a>)</li> <li>Fixes two vulnerabilities in <code>SparseFillEmptyRowsGrad</code> (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15194">CVE-2020-15194</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15195">CVE-2020-15195</a>)</li> <li>Fixes several vulnerabilities in <code>RaggedCountSparseOutput</code> and <code>SparseCountSparseOutput</code> operations (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15196">CVE-2020-15196</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15197">CVE-2020-15197</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15198">CVE-2020-15198</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15199">CVE-2020-15199</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15200">CVE-2020-15200</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15201">CVE-2020-15201</a>)</li> <li>Fixes an integer truncation vulnerability in code using the work sharder API (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15202">CVE-2020-15202</a>)</li> <li>Fixes a format string vulnerability in <code>tf.strings.as_string</code> (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15203">CVE-2020-15203</a>)</li> <li>Fixes segfault raised by calling session-only ops in eager mode (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15204">CVE-2020-15204</a>)</li> <li>Fixes data leak and potential ASLR violation from <code>tf.raw_ops.StringNGrams</code> (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15205">CVE-2020-15205</a>)</li> <li>Fixes segfaults caused by incomplete <code>SavedModel</code> validation (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15206">CVE-2020-15206</a>)</li> <li>Fixes a data corruption due to a bug in negative indexing support in TFLite (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15207">CVE-2020-15207</a>)</li> <li>Fixes a data corruption due to dimension mismatch in TFLite (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15208">CVE-2020-15208</a>)</li> <li>Fixes several vulnerabilities in TFLite saved model format (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15209">CVE-2020-15209</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15210">CVE-2020-15210</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15211">CVE-2020-15211</a>)</li> <li>Fixes several vulnerabilities in TFLite implementation of segment sum (<a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15212">CVE-2020-15212</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15213">CVE-2020-15213</a>, <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15214">CVE-2020-15214</a>)</li> <li>Updates <code>sqlite3</code> to <code>3.33.00</code> to handle <a href="https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15358">CVE-2020-15358</a>.</li> <li>Fixes deprecated usage of <code>collections</code> API</li> <li>Removes <code>scipy</code> dependency from <code>setup.py</code> since TensorFlow does not need it to install the pip package</li> </ul> <h1>Release 2.2.1</h1> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/tensorflow/tensorflow/commit/fcc4b966f1265f466e82617020af93670141b009"><code>fcc4b96</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/43446">#43446</a> from tensorflow-jenkins/version-numbers-2.3.1-16251</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/4cf223069a94c78b208e6c829d5f938a0fae7d07"><code>4cf2230</code></a> Update version numbers to 2.3.1</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/eee82247288e52e9b8a5c2badeb65f871b4da4c4"><code>eee8224</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/43441">#43441</a> from tensorflow-jenkins/relnotes-2.3.1-24672</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/0d41b1dfc97500e1177cb718a0b14b04914df661"><code>0d41b1d</code></a> Update RELEASE.md</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/d99bd631ea9b67ffc39c22b35fbf7deca77ad1f7"><code>d99bd63</code></a> Insert release notes place-fill</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/d71d3ce2520587b752e5d27b2d4a4ba8720e4bd5"><code>d71d3ce</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/43414">#43414</a> from tensorflow/mihaimaruseac-patch-1-1</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/9c91596d4d24bc07b6d36ae48581a2e7b2584edf"><code>9c91596</code></a> Fix missing import</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/f9f12f61867159120ce6eb08fdbd225d454232b5"><code>f9f12f6</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/43391">#43391</a> from tensorflow/mihaimaruseac-patch-4</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/3ed271b0b05b4f1dfd5660944c54b5fe8cc3d8dc"><code>3ed271b</code></a> Solve leftover from merge conflict</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/9cf3773b717dfd46b37be2ba8cad4f038a8ff6f7"><code>9cf3773</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/43358">#43358</a> from tensorflow/mm-patch-r2.3</li> <li>Additional commits viewable in <a href="https://github.com/tensorflow/tensorflow/compare/v1.6.0...v2.3.1">compare view</a></li> </ul> </details> <br />

Dependabot compatibility score

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


<details> <summary>Dependabot commands and options</summary> <br />

You can trigger Dependabot actions by commenting on this PR:

  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot merge will merge this PR after your CI passes on it
  • @dependabot squash and merge will squash and merge this PR after your CI passes on it
  • @dependabot cancel merge will cancel a previously requested merge and block automerging
  • @dependabot reopen will reopen this PR if it is closed
  • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
  • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
  • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
  • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
  • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

You can disable automated security fix PRs for this repo from the Security Alerts page.

</details>

+1 -1

1 comment

1 changed file

dependabot[bot]

pr closed time in a month

pull request commentIBM/FfDL

Bump tensorflow from 1.6.0 to 2.3.1 in /community/FfDL-Seldon/tf-model

Superseded by #182.

dependabot[bot]

comment created time in a month

PR opened IBM/FfDL

Bump tensorflow from 1.6.0 to 2.5.0 in /community/FfDL-Seldon/tf-model

Bumps tensorflow from 1.6.0 to 2.5.0. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/tensorflow/tensorflow/releases">tensorflow's releases</a>.</em></p> <blockquote> <h2>TensorFlow 2.5.0</h2> <h1>Release 2.5.0</h1> <h2>Major Features and Improvements</h2> <ul> <li>Support for Python3.9 has been added.</li> <li><code>tf.data</code>: <ul> <li><code>tf.data</code> service now supports strict round-robin reads, which is useful for synchronous training workloads where example sizes vary. With strict round robin reads, users can guarantee that consumers get similar-sized examples in the same step.</li> <li>tf.data service now supports optional compression. Previously data would always be compressed, but now you can disable compression by passing <code>compression=None</code> to <code>tf.data.experimental.service.distribute(...)</code>.</li> <li><code>tf.data.Dataset.batch()</code> now supports <code>num_parallel_calls</code> and <code>deterministic</code> arguments. <code>num_parallel_calls</code> is used to indicate that multiple input batches should be computed in parallel. With <code>num_parallel_calls</code> set, <code>deterministic</code> is used to indicate that outputs can be obtained in the non-deterministic order.</li> <li>Options returned by <code>tf.data.Dataset.options()</code> are no longer mutable.</li> <li>tf.data input pipelines can now be executed in debug mode, which disables any asynchrony, parallelism, or non-determinism and forces Python execution (as opposed to trace-compiled graph execution) of user-defined functions passed into transformations such as <code>map</code>. The debug mode can be enabled through <code>tf.data.experimental.enable_debug_mode()</code>.</li> </ul> </li> <li><code>tf.lite</code> <ul> <li>Enabled the new MLIR-based quantization backend by default <ul> <li>The new backend is used for 8 bits full integer post-training quantization</li> <li>The new backend removes the redundant rescales and fixes some bugs (shared weight/bias, extremely small scales, etc)</li> <li>Set <code>experimental_new_quantizer</code> in tf.lite.TFLiteConverter to False to disable this change</li> </ul> </li> </ul> </li> <li><code>tf.keras</code> <ul> <li><code>tf.keras.metrics.AUC</code> now support logit predictions.</li> <li>Enabled a new supported input type in <code>Model.fit</code>, <code>tf.keras.utils.experimental.DatasetCreator</code>, which takes a callable, <code>dataset_fn</code>. <code>DatasetCreator</code> is intended to work across all <code>tf.distribute</code> strategies, and is the only input type supported for Parameter Server strategy.</li> </ul> </li> <li><code>tf.distribute</code> <ul> <li><code>tf.distribute.experimental.ParameterServerStrategy</code> now supports training with Keras <code>Model.fit</code> when used with <code>DatasetCreator</code>.</li> <li>Creating <code>tf.random.Generator</code> under <code>tf.distribute.Strategy</code> scopes is now allowed (except for <code>tf.distribute.experimental.CentralStorageStrategy</code> and <code>tf.distribute.experimental.ParameterServerStrategy</code>). Different replicas will get different random-number streams.</li> </ul> </li> <li>TPU embedding support <ul> <li>Added <code>profile_data_directory</code> to <code>EmbeddingConfigSpec</code> in <code>_tpu_estimator_embedding.py</code>. This allows embedding lookup statistics gathered at runtime to be used in embedding layer partitioning decisions.</li> </ul> </li> <li>PluggableDevice <ul> <li>Third-party devices can now connect to TensorFlow as plug-ins through <a href="https://github.com/tensorflow/community/blob/master/rfcs/20200612-stream-executor-c-api.md">StreamExecutor C API</a>. and <a href="https://github.com/tensorflow/community/blob/master/rfcs/20200624-pluggable-device-for-tensorflow.md">PluggableDevice</a> interface. <ul> <li>Add custom ops and kernels through <a href="https://github.com/tensorflow/community/blob/master/rfcs/20190814-kernel-and-op-registration.md">kernel and op registration C API</a>.</li> <li>Register custom graph optimization passes with <a href="https://github.com/tensorflow/community/blob/master/rfcs/20201027-modular-tensorflow-graph-c-api.md">graph optimization C API</a>.</li> </ul> </li> </ul> </li> <li><a href="https://github.com/oneapi-src/oneDNN">oneAPI Deep Neural Network Library (oneDNN)</a> CPU performance optimizations from <a href="https://software.intel.com/content/www/us/en/develop/articles/intel-optimization-for-tensorflow-installation-guide.html">Intel-optimized TensorFlow</a> are now available in the official x86-64 Linux and Windows builds. <ul> <li>They are off by default. Enable them by setting the environment variable <code>TF_ENABLE_ONEDNN_OPTS=1</code>.</li> <li>We do not recommend using them in GPU systems, as they have not been sufficiently tested with GPUs yet.</li> </ul> </li> <li>TensorFlow pip packages are now built with CUDA11.2 and cuDNN 8.1.0</li> </ul> <h2>Breaking Changes</h2> <ul> <li>The <code>TF_CPP_MIN_VLOG_LEVEL</code> environment variable has been renamed to to <code>TF_CPP_MAX_VLOG_LEVEL</code> which correctly describes its effect.</li> </ul> <h2>Bug Fixes and Other Changes</h2> <ul> <li><code>tf.keras</code>: <ul> <li>Preprocessing layers API consistency changes: <ul> <li><code>StringLookup</code> added <code>output_mode</code>, <code>sparse</code>, and <code>pad_to_max_tokens</code> arguments with same semantics as <code>TextVectorization</code>.</li> <li><code>IntegerLookup</code> added <code>output_mode</code>, <code>sparse</code>, and <code>pad_to_max_tokens</code> arguments with same semantics as <code>TextVectorization</code>. Renamed <code>max_values</code>, <code>oov_value</code> and <code>mask_value</code> to <code>max_tokens</code>, <code>oov_token</code> and <code>mask_token</code> to align with <code>StringLookup</code> and <code>TextVectorization</code>.</li> <li><code>TextVectorization</code> default for <code>pad_to_max_tokens</code> switched to False.</li> <li><code>CategoryEncoding</code> no longer supports <code>adapt</code>, <code>IntegerLookup</code> now supports equivalent functionality. <code>max_tokens</code> argument renamed to <code>num_tokens</code>.</li> <li><code>Discretization</code> added <code>num_bins</code> argument for learning bins boundaries through calling <code>adapt</code> on a dataset. Renamed <code>bins</code> argument to <code>bin_boundaries</code> for specifying bins without <code>adapt</code>.</li> </ul> </li> <li>Improvements to model saving/loading: <ul> <li><code>model.load_weights</code> now accepts paths to saved models.</li> </ul> </li> </ul> </li> </ul> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Changelog</summary> <p><em>Sourced from <a href="https://github.com/tensorflow/tensorflow/blob/master/RELEASE.md">tensorflow's changelog</a>.</em></p> <blockquote> <h1>Release 2.5.0</h1> <!-- raw HTML omitted --> <h2>Breaking Changes</h2> <ul> <li> <!-- raw HTML omitted --> </li> <li>The <code>TF_CPP_MIN_VLOG_LEVEL</code> environment variable has been renamed to to <code>TF_CPP_MAX_VLOG_LEVEL</code> which correctly describes its effect.</li> </ul> <h2>Known Caveats</h2> <ul> <li><!-- raw HTML omitted --></li> <li><!-- raw HTML omitted --></li> <li><!-- raw HTML omitted --></li> </ul> <h2>Major Features and Improvements</h2> <ul> <li> <p><!-- raw HTML omitted --></p> </li> <li> <p><!-- raw HTML omitted --></p> </li> <li> <p>TPU embedding support</p> <ul> <li>Added <code>profile_data_directory</code> to <code>EmbeddingConfigSpec</code> in <code>_tpu_estimator_embedding.py</code>. This allows embedding lookup statistics gathered at runtime to be used in embedding layer partitioning decisions.</li> </ul> </li> <li> <p><code>tf.keras.metrics.AUC</code> now support logit predictions.</p> </li> <li> <p>Creating <code>tf.random.Generator</code> under <code>tf.distribute.Strategy</code> scopes is now allowed (except for <code>tf.distribute.experimental.CentralStorageStrategy</code> and <code>tf.distribute.experimental.ParameterServerStrategy</code>). Different replicas will get different random-number streams.</p> </li> <li> <p><code>tf.data</code>:</p> <ul> <li>tf.data service now supports strict round-robin reads, which is useful for synchronous training workloads where example sizes vary. With strict round robin reads, users can guarantee that consumers get similar-sized examples in the same step.</li> <li>tf.data service now supports optional compression. Previously data would always be compressed, but now you can disable compression by passing <code>compression=None</code> to <code>tf.data.experimental.service.distribute(...)</code>.</li> <li><code>tf.data.Dataset.batch()</code> now supports <code>num_parallel_calls</code> and <code>deterministic</code> arguments. <code>num_parallel_calls</code> is used to indicate that multiple input batches should be computed in parallel. With <code>num_parallel_calls</code> set, <code>deterministic</code> is used to indicate that outputs can be obtained in the non-deterministic order.</li> <li>Options returned by <code>tf.data.Dataset.options()</code> are no longer mutable.</li> <li>tf.data input pipelines can now be executed in debug mode, which disables any asynchrony, parallelism, or non-determinism and forces Python execution (as opposed to trace-compiled graph execution) of user-defined functions passed into transformations such as <code>map</code>. The debug mode can be enabled through <code>tf.data.experimental.enable_debug_mode()</code>.</li> </ul> </li> <li> <p><code>tf.lite</code></p> <ul> <li>Enabled the new MLIR-based quantization backend by default <ul> <li>The new backend is used for 8 bits full integer post-training quantization</li> <li>The new backend removes the redundant rescales and fixes some bugs (shared weight/bias, extremely small scales, etc)</li> </ul> </li> </ul> </li> </ul> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/tensorflow/tensorflow/commit/a4dfb8d1a71385bd6d122e4f27f86dcebb96712d"><code>a4dfb8d</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/49124">#49124</a> from tensorflow/mm-cherrypick-tf-data-segfault-fix-...</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/2107b1dc414edb3fc78e632bca4f4936171093b2"><code>2107b1d</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/49116">#49116</a> from tensorflow-jenkins/version-numbers-2.5.0-17609</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/16b813906fcb46306aef29a04ddd0cbdb4e77918"><code>16b8139</code></a> Update snapshot_dataset_op.cc</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/86a0d86cb5da6a28b78ea7f886ec2831d23f6d6b"><code>86a0d86</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/49126">#49126</a> from geetachavan1/cherrypicks_X9ZNY</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/9436ae693ef66a9efb7e7e7888134173d9a0821d"><code>9436ae6</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/49128">#49128</a> from geetachavan1/cherrypicks_D73J5</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/6b2bf99cd9336026689579b683a709c5efcb4ae9"><code>6b2bf99</code></a> Validate that a and b are proper sparse tensors</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/c03ad1a46d5b3f23df67dad03185a0ee16020c96"><code>c03ad1a</code></a> Ensure validation sticks in banded_triangular_solve_op</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/12a6ead7ac968c402feb85ce0a8069ccbc6bf735"><code>12a6ead</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/49120">#49120</a> from geetachavan1/cherrypicks_KJ5M9</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/b67f5b8a0a098c34c71c679aa46480035c46886e"><code>b67f5b8</code></a> Merge pull request <a href="https://github-redirect.dependabot.com/tensorflow/tensorflow/issues/49118">#49118</a> from geetachavan1/cherrypicks_BIDTR</li> <li><a href="https://github.com/tensorflow/tensorflow/commit/a13c0ade86295bd3a8356b4b8cc980cf0c5e70e0"><code>a13c0ad</code></a> [tf.data][cherrypick] Fix snapshot segfault when using repeat and prefecth</li> <li>Additional commits viewable in <a href="https://github.com/tensorflow/tensorflow/compare/v1.6.0...v2.5.0">compare view</a></li> </ul> </details> <br />

Dependabot compatibility score

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


<details> <summary>Dependabot commands and options</summary> <br />

You can trigger Dependabot actions by commenting on this PR:

  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot merge will merge this PR after your CI passes on it
  • @dependabot squash and merge will squash and merge this PR after your CI passes on it
  • @dependabot cancel merge will cancel a previously requested merge and block automerging
  • @dependabot reopen will reopen this PR if it is closed
  • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
  • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
  • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
  • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
  • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

You can disable automated security fix PRs for this repo from the Security Alerts page.

</details>

+1 -1

0 comment

1 changed file

pr created time in a month

PR opened IBM/FfDL

Bump chart.js from 2.7.2 to 2.9.4 in /dashboard

Bumps chart.js from 2.7.2 to 2.9.4. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/chartjs/Chart.js/releases">chart.js's releases</a>.</em></p> <blockquote> <h2>v2.9.4</h2> <p>This is the last release of v2 and focused on fixing bugs identified in the v2.9.3 release.</p> <h1>Bugs Fixed</h1> <ul> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7404">#7404</a> - Preserve prototypes when cloning. Thanks <a href="https://github.com/iddings"><code>@​iddings</code></a></li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7587">#7587</a> - Fix docs for external moment.js. Thanks <a href="https://github.com/mojoaxel"><code>@​mojoaxel</code></a></li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7853">#7853</a> - Fix box recursion when dimensions are NaN. Thanks <a href="https://github.com/alessandroasm"><code>@​alessandroasm</code></a></li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7883">#7883</a> - Fix call stack exception when computing label sizes. Thanks <a href="https://github.com/silentmatt"><code>@​silentmatt</code></a></li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7918">#7918</a> - Prevent global prototype pollution via the merge helper</li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7920">#7920</a> - Use Object.create(null) as <code>merge</code> target, to prevent prototype pollution</li> </ul> <h2>v2.9.3</h2> <h1>Bug Fixes</h1> <ul> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6698">#6698</a> Fix undefined variable</li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6719">#6719</a> Don't make legend empty when fill is false</li> </ul> <p>Thanks to the maintainers and collaborators for their help to improve and test Chart.js (<a href="https://github.com/kurkle"><code>@​kurkle</code></a>, <a href="https://github.com/benmccann"><code>@​benmccann</code></a>, and <a href="https://github.com/etimberg"><code>@​etimberg</code></a>).</p> <h2>v2.9.2</h2> <h1>Bug Fixes</h1> <ul> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6641">#6641</a> IE11 & Edge compatible style injection</li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6655">#6655</a> Backwards compatible default fill for radar charts</li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6660">#6660</a> Improve clipping of line charts when border widths are large</li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6661">#6661</a> When a legend item is clicked, make sure the correct item is hidden</li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6663">#6663</a> Refresh package-lock file to pick up new dependency</li> </ul> <h1>Performance</h1> <ul> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6671">#6671</a> Stop unnecessary line calculations</li> </ul> <h1>Documentation</h1> <ul> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6643">#6643</a> Combine performance documentation sections</li> </ul> <p>Thanks to the maintainers and collaborators for their help to improve and test Chart.js (<a href="https://github.com/nagix"><code>@​nagix</code></a>, <a href="https://github.com/kurkle"><code>@​kurkle</code></a>, <a href="https://github.com/benmccann"><code>@​benmccann</code></a>, <a href="https://github.com/etimberg"><code>@​etimberg</code></a> and <a href="https://github.com/simonbrunel"><code>@​simonbrunel</code></a>).</p> <h2>v2.9.1</h2> <h1>Bug Fixes</h1> <ul> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6603">#6603</a> Fix deprecation warnings for horizontal bar charts</li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6608">#6608</a> Fix zoom plugin by no longer clipping <code>scale.getDecimalForPixel</code> to the chart area</li> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6617">#6617</a> Non numeric Y axes did not work</li> </ul> <h1>Documentation</h1> <ul> <li><a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/6613">#6613</a> Add link to performance documentation</li> </ul> <!-- raw HTML omitted --> </blockquote> <p>... (truncated)</p> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/chartjs/Chart.js/commit/9bd4cf82fda9f50a5fb50b72843e06ab88124278"><code>9bd4cf8</code></a> Release v2.9.4</li> <li><a href="https://github.com/chartjs/Chart.js/commit/1d92605aa6c29add400c4c551413fc2306c15e8d"><code>1d92605</code></a> Use Object.create(null) as <code>merge</code> target (<a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7920">#7920</a>)</li> <li><a href="https://github.com/chartjs/Chart.js/commit/dff7140070c4e68731f17d577cca9fd82fe55498"><code>dff7140</code></a> When objects are merged together, the target prototype can be polluted. (<a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7918">#7918</a>)</li> <li><a href="https://github.com/chartjs/Chart.js/commit/d9191889255ceaad120c793906e1463fad382075"><code>d919188</code></a> Bump verison number to v2.9.4</li> <li><a href="https://github.com/chartjs/Chart.js/commit/42ed5895b28fcfd10d43e1ce7a54bfa7e060998b"><code>42ed589</code></a> Fix Maximum call stack size exception in computeLabelSizes (<a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7883">#7883</a>)</li> <li><a href="https://github.com/chartjs/Chart.js/commit/063b7dc075e87eeec6334808bcc90af165f7421e"><code>063b7dc</code></a> [2.9] FitBoxes recursion when dimensions are NaN (<a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7853">#7853</a>)</li> <li><a href="https://github.com/chartjs/Chart.js/commit/2493cb5a2f65ce5e5afc031eb067d3769f06a3e7"><code>2493cb5</code></a> Use node v12.18.2 on Travis CI (<a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7864">#7864</a>)</li> <li><a href="https://github.com/chartjs/Chart.js/commit/679ec4acc5b669ebf6b0f45c4b508dfce22cacea"><code>679ec4a</code></a> docs: fix rollup external moment (<a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7587">#7587</a>)</li> <li><a href="https://github.com/chartjs/Chart.js/commit/484f0d1e518963436d5013f61001558ef9788edf"><code>484f0d1</code></a> Preserve object prototypes when cloning (<a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7404">#7404</a>)</li> <li><a href="https://github.com/chartjs/Chart.js/commit/2df6986fbe466c1a4009014bf7ed3b91442f97ad"><code>2df6986</code></a> Look for any branch starting with release (<a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7087">#7087</a>) (<a href="https://github-redirect.dependabot.com/chartjs/Chart.js/issues/7089">#7089</a>)</li> <li>Additional commits viewable in <a href="https://github.com/chartjs/Chart.js/compare/v2.7.2...v2.9.4">compare view</a></li> </ul> </details> <br />

Dependabot compatibility score

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.


<details> <summary>Dependabot commands and options</summary> <br />

You can trigger Dependabot actions by commenting on this PR:

  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot merge will merge this PR after your CI passes on it
  • @dependabot squash and merge will squash and merge this PR after your CI passes on it
  • @dependabot cancel merge will cancel a previously requested merge and block automerging
  • @dependabot reopen will reopen this PR if it is closed
  • @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
  • @dependabot use these labels will set the current labels as the default for future PRs for this repo and language
  • @dependabot use these reviewers will set the current reviewers as the default for future PRs for this repo and language
  • @dependabot use these assignees will set the current assignees as the default for future PRs for this repo and language
  • @dependabot use this milestone will set the current milestone as the default for future PRs for this repo and language

You can disable automated security fix PRs for this repo from the Security Alerts page.

</details>

+119 -51

0 comment

2 changed files

pr created time in a month

create barnchIBM/FfDL

branch : dependabot/npm_and_yarn/dashboard/chart.js-2.9.4

created branch time in a month