nvidia-cuda-nvcc-cu12>=12.5.82,<13.0
nvidia-cuda-nvrtc-cu12>=12.5.82,<13.0
nvidia-cuda-runtime-cu12>=12.5.82,<13.0
# The upper bound is set for the CUDNN API compatibility.
# See
# https://docs.nvidia.com/deeplearning/cudnn/backend/latest/developer/forward-compatibility.html#cudnn-api-compatibility
nvidia-cudnn-cu12>=9.3.0.75,<10.0
nvidia-cufft-cu12>=11.2.3.61,<12.0
nvidia-curand-cu12>=10.3.6.82,<11.0
nvidia-cusolver-cu12>=11.6.3.83,<12.0

            if (stage.specificBuilds.contains(SpecificBuild.SanityCheck)) {
                buildReportTab(
                    "API Compatibility Report",
                    "$HIDDEN_ARTIFACT_DESTINATION/report-architecture-test-binary-compatibility-report.html",
                )
                buildReportTab("Incubating APIs Report", "incubation-reports/all-incubating.html")
            }

    validations:
      required: false

  - type: textarea
    id: go-backwards-compatiblity
    attributes:
      label: Is this change backward compatible?
      description: Breaking the Go 1 compatibility guarantee is a large cost and requires a large benefit.
      placeholder: |
       Yes or No

       If yes, 

      - run: ./gradlew sanityCheck -DdisableLocalCache=true ${{ needs.build.outputs.sys-prop-args }}
      - name: Upload Compatibility Report
        if: always()
        uses: actions/upload-artifact@v4
        with:
          name: binary-compatibility-report
          path: testing/architecture-test/build/reports/binary-compatibility/report.html

  unit-test:
    name: "${{ matrix.bucket.name }} (Unit Test)"
    permissions:

---
title: "Go, Backwards Compatibility, and GODEBUG"
layout: article
---

<!--
This document is kept in the Go repo, not x/website,
because it documents the full list of known GODEBUG settings,
which are tied to a specific release.
-->

## Introduction {#intro}

Go's emphasis on backwards compatibility is one of its key strengths.
There are, however, times when we cannot maintain complete compatibility.

   
   **1. Installing **TensorFlow-GPU** (TF) prebuilt binaries**
   
   
   Make sure you are using compatible TF and CUDA versions.
   Please refer following TF version and CUDA version compatibility table.
   
   | TF  | CUDA |
   
   | :-------------: | :-------------: |
   
   | 2.5.0  | 11.2 |
   
   | 2.4.0  | 11.0 |
   
   | 2.1.0 - 2.3.0  | 10.1 |
   
   | 1.13.1 - 2.0  | 10.0  |

go1.txt (and similarly named files) are frozen once a version has been
shipped. Each file adds new lines but does not remove any.

except.txt lists features that may disappear without breaking true
compatibility.

Starting with go1.19.txt, each API feature line must end in "#nnnnn"
giving the GitHub issue number of the proposal issue that accepted
the new API. This helps with our end-of-cycle audit of new APIs.

  "$python" -c 'import sys; import tensorflow as tf; sys.exit(0 if "keras" in tf.keras.__name__ else 1)'
fi
# Import tf nightly wheel built with numpy2 from PyPI in numpy1 env for testing.
# This aims to maintain TF compatibility with NumPy 1.x until 2025 b/361369076.
if [[ "$TFCI_WHL_NUMPY_VERSION" == 1 ]]; then
  # Uninstall tf nightly wheel built with numpy1.
  "$python" -m pip uninstall -y tf_nightly_numpy1

        subprojects/internal-build-reports/build/reports/incubation/all-incubating.html => incubation-reports
        testing/architecture-test/build/reports/binary-compatibility/report.html => binary-compatibility-reports
        build/reports/dependency-verification/** => dependency-verification-reports
        build/reports/problems/problems-report.html
        """.trimIndent()

				// here.
			} else if portRemoved(feature) {
				// okay.
			} else if featureSet[featureWithoutContext(feature)] {
				// okay.
			} else {
				fmt.Fprintf(w, "-%s\n", feature)
				ok = false // broke compatibility
			}
		case len(required) == 0 || (len(features) > 0 && required[0] > features[0]):
			newFeature := take(&features)
			fmt.Fprintf(w, "+%s\n", newFeature)
			ok = false // feature not in api/next/*
		default: