# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

name: Upload SIG Build docker containers regularly

on:
  workflow_dispatch:
  schedule:
      # Run once a week on Sunday at midnight. See http://crontab.guru
      - cron: '0 0 * * 0'
  push:
    paths:

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

name: Upload SIG Build docker containers modified for release branches

on:
  workflow_dispatch:
  push:
    paths:
      - '.github/workflows/sigbuild-docker-branch.yml'
      - 'tensorflow/tools/tf_sig_build_dockerfiles/**'

          publish_results: true

      # Upload the results as artifacts (optional).
      - name: "Upload artifact"
        uses: actions/upload-artifact@83fd05a356d7e2593de66fc9913b3002723633cb # v3.1.1
        with:
          name: SARIF file
          path: results.sarif
          retention-days: 5

      # Upload the results to GitHub's code scanning dashboard.
      - name: "Upload to code-scanning"

      - name: Upload pip wheel to PyPI
        if: github.event_name == 'schedule' || (github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v2')) # only if it is a scheduled nightly or tagged
        shell: bash

# ==============================================================================

name: OSV-Scanner Scheduled Scan

on:
  schedule:
    - cron: 0 4 * * 1

permissions:
  # Require writing security events to upload SARIF file to security tab
  security-events: write
  # Only need to read contents
  contents: read

jobs:
  scan-scheduled:
    if: github.repository == 'tensorflow/tensorflow'

   
   
   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.

index 185402f..bbdeae0 100644
--- a/sysdeps/aarch64/dl-machine.h
+++ b/sysdeps/aarch64/dl-machine.h
@@ -49,23 +49,11 @@ elf_machine_load_address (void)
   /* To figure out the load address we use the definition that for any symbol:
      dynamic_addr(symbol) = static_addr(symbol) + load_addr
 
-     The choice of symbol is arbitrary. The static address we obtain
-     by constructing a non GOT reference to the symbol, the dynamic