Upgrade Colab base image (#1533)

From `20251024-060052_RC00` to `20260126-060048_RC00`.

Added justification to the diff about other changes included.

Next: Move the CPU image to use the Colab dedicated CPU base image.

http://b/331651883

Author: rosbo

Dockerfile.tmpl

@@ -23,15 +23,9 @@ RUN uv pip uninstall --system --no-cache google-cloud-bigquery-storage
 # to avoid affecting the larger build, we'll post-install it.
 RUN uv pip install --no-build-isolation --no-cache --system "git+https://github.com/Kaggle/learntools"
 
-# newer daal4py requires tbb>=2022, but libpysal is downgrading it for some reason
-RUN uv pip install --system --no-cache "tbb>=2022" "libpysal==4.9.2"
-
-# b/404590350: Ray and torchtune have conflicting tune cli, we will prioritize torchtune.
-# b/315753846: Unpin translate package, currently conflicts with adk 1.17.0
-# b/468379293: Unpin Pandas once cuml/cudf are compatible, version 3.0 causes issues
-# b/468383498: numpy will auto-upgrade to 2.4.x, which causes issues with numerous packages
+# b/404590350: Ray and torchtune have conflicting cli named `tune`. `ray` is not part of Colab's base image. Re-install `tune` to ensure the torchtune CLI is available by default.
 # b/468367647: Unpin protobuf, version greater than v5.29.5 causes issues with numerous packages
-RUN uv pip install --system --force-reinstall --no-cache --no-deps torchtune "google-cloud-translate==3.12.1" "numpy==2.0.2" "pandas==2.2.2"
+RUN uv pip install --system --force-reinstall --no-cache --no-deps torchtune
 RUN uv pip install --system --force-reinstall --no-cache "protobuf==5.29.5"
 
 # Adding non-package dependencies:

config.txt

@@ -1,4 +1,4 @@
 BASE_IMAGE=us-docker.pkg.dev/colab-images/public/runtime
-BASE_IMAGE_TAG=release-colab-external_20251024-060052_RC00
+BASE_IMAGE_TAG=release-colab-external_20260126-060048_RC00
 CUDA_MAJOR_VERSION=12
 CUDA_MINOR_VERSION=5

kaggle_requirements.txt

@@ -65,8 +65,7 @@ keras-nlp
 keras-tuner
 kornia
 langid
-# b/328788268: libpysal 4.10 seems to fail with "module 'shapely' has no attribute 'Geometry'. Did you mean: 'geometry'"
-libpysal<=4.9.2
+libpysal
 lime
 line_profiler
 mamba
@@ -116,8 +115,9 @@ scikit-plot
 scikit-surprise
 git+https://github.com/facebookresearch/segment-anything.git
 squarify
-tensorflow-cloud
 tensorflow-io
+# Must be compatible with torch version: https://github.com/meta-pytorch/torchcodec?tab=readme-ov-file#installing-torchcodec
+torchcodec==0.9
 torchinfo
 torchmetrics
 torchtune

tests/test_tensorflow_cloud.py

@@ -6,7 +6,7 @@
 from kaggle_gcp import KaggleKernelCredentials, KaggleKernelWithProjetCredentials, init_translation_v2, init_translation_v3
 from test.support.os_helper import EnvironmentVarGuard
 from google.api_core import client_options
-from google.cloud import translate, translate_v2
+from google.cloud import translate_v3 as translate, translate_v2
 
 def _make_credentials():
     import google.auth.credentials
@@ -48,7 +48,7 @@ def test_user_provided_credentials_v2(self):
             self.assertIsNotNone(client.credentials)
             self.assertNotIsInstance(client.credentials, KaggleKernelCredentials)
 
-    @patch("google.cloud.translate.TranslationServiceClient", new=FakeClient)
+    @patch("google.cloud.translate_v3.TranslationServiceClient", new=FakeClient)
     def test_default_credentials_v3(self):
         env = EnvironmentVarGuard()
         env.set('KAGGLE_USER_SECRETS_TOKEN', 'foobar')
@@ -60,7 +60,7 @@ def test_default_credentials_v3(self):
             self.assertIsInstance(client.credentials, KaggleKernelCredentials)
 
 
-    @patch("google.cloud.translate.TranslationServiceClient", new=FakeClient)
+    @patch("google.cloud.translate_v3.TranslationServiceClient", new=FakeClient)
     def test_user_provided_credentials_v3(self):
         credentials = _make_credentials()
         env = EnvironmentVarGuard()
@@ -107,13 +107,12 @@ def test_monkeypatching_idempotent(self):
             self.assertEqual(client2_1, client2_2)
             self.assertEqual(client3_1, client3_2)
 
-    @patch("google.cloud.translate.TranslationServiceClient", new=FakeClient)
+    @patch("google.cloud.translate_v3.TranslationServiceClient", new=FakeClient)
     def test_client_credential_uniqueness_v3(self):
         """
         Client instance must use unique KaggleKernelWithProjetCredentials with quota_project_id
         when client_options.quota_project_id provided. (even if quota_project_id is same)
         """
-        credentials = _make_credentials()
         env = EnvironmentVarGuard()
         env.set('KAGGLE_USER_SECRETS_TOKEN', 'foobar')
         env.set('KAGGLE_KERNEL_INTEGRATIONS', 'CLOUDAI')

tests/test_translation.py

@@ -200,22 +200,6 @@ def call_get_cloudai_access_token():
             client = UserSecretsClient()
             secret_response = client._get_cloudai_access_token()
             self.assertEqual(secret_response, (secret, now + timedelta(seconds=3600)))
-        def call_get_translation_access_token():
-            client = UserSecretsClient()
-            secret_response = client._get_translation_access_token()
-            self.assertEqual(secret_response, (secret, now + timedelta(seconds=3600)))
-        def call_get_natural_lang_access_token():
-            client = UserSecretsClient()
-            secret_response = client._get_natural_language_access_token()
-            self.assertEqual(secret_response, (secret, now + timedelta(seconds=3600)))
-        def call_get_video_intell_access_token():
-            client = UserSecretsClient()
-            secret_response = client._get_video_intelligence_access_token()
-            self.assertEqual(secret_response, (secret, now + timedelta(seconds=3600)))
-        def call_get_vision_access_token():
-            client = UserSecretsClient()
-            secret_response = client._get_vision_access_token()
-            self.assertEqual(secret_response, (secret, now + timedelta(seconds=3600)))
 
         self._test_client(call_get_bigquery_access_token,
                           '/requests/GetUserSecretRequest', {'Target': GcpTarget.BIGQUERY.target},