Merge remote-tracking branch 'upstream/master' into rkazants/poc_open…

…vino_backend

.devcontainer/devcontainer.json

@@ -1,6 +1,6 @@
 {
     "image": "mcr.microsoft.com/vscode/devcontainers/python:3.10",
-    "postCreateCommand": "sh ./.devcontainer/setup.sh",
+    "postCreateCommand": "sh ./.devcontainer/setup.sh && pip install -r requirements.txt",
     "customizations": {
         "vscode": {
             "settings": {
@@ -27,4 +27,4 @@
     "features": {
         "ghcr.io/devcontainers/features/github-cli:1": {}
     }
-}
+}

.github/workflows/scorecard.yml

@@ -30,7 +30,7 @@ jobs:
           persist-credentials: false
 
       - name: "Run analysis"
-        uses: ossf/scorecard-action@0864cf19026789058feabb7e87baa5f140aac736 # v2.3.1
+        uses: ossf/scorecard-action@62b2cac7ed8198b15735ed49ab1e5cf35480ba46 # v2.4.0
         with:
           results_file: results.sarif
           results_format: sarif
@@ -48,14 +48,14 @@ jobs:
       # Upload the results as artifacts (optional). Commenting out will disable uploads of run results in SARIF
       # format to the repository Actions tab.
       - name: "Upload artifact"
-        uses: actions/upload-artifact@65462800fd760344b1a7b4382951275a0abb4808 # v4.3.3
+        uses: actions/upload-artifact@50769540e7f4bd5e21e526ee35c689e35e0d6874 # v4.4.0
         with:
           name: SARIF file
           path: results.sarif
           retention-days: 5
 
       # Upload the results to GitHub's code scanning dashboard.
       - name: "Upload to code-scanning"
-        uses: github/codeql-action/upload-sarif@d39d31e687223d841ef683f52467bd88e9b21c14 # v3.25.3
+        uses: github/codeql-action/upload-sarif@4dd16135b69a43b6c8efb853346f8437d92d3c93 # v3.26.6
         with:
           sarif_file: results.sarif

.github/workflows/scripts/auto-assignment.js

@@ -29,7 +29,7 @@ module.exports = async ({ github, context }) => {
   // Is this an issue? If so, assign the issue number. Otherwise, assign the PR number.
   if (context.payload.issue) {
     //assignee List for issues. 
-    assigneesList = ["SuryanarayanaY", "sachinprasadhs"];
+    assigneesList = ["mehtamansi29", "sachinprasadhs"];
     issueNumber = context.payload.issue.number;
   } else {
     //assignee List for PRs. 

.github/workflows/scripts/labeler.js

@@ -23,16 +23,16 @@ You may obtain a copy of the License at
 
 module.exports = async ({ github, context }) => {
     const issue_title = context.payload.issue ?  context.payload.issue.title : context.payload.pull_request.title
-    const issue_discription = context.payload.issue ? context.payload.issue.body : context.payload.pull_request.body
+    const issue_description = context.payload.issue ? context.payload.issue.body : context.payload.pull_request.body
     const issue_number = context.payload.issue ? context.payload.issue.number : context.payload.pull_request.number
     const keyword_label =  {
          gemma:'Gemma'
     }
     const labelsToAdd = []
-    console.log(issue_title,issue_discription,issue_number)
+    console.log(issue_title,issue_description,issue_number)
 
     for(const [keyword, label] of Object.entries(keyword_label)){
-     if(issue_title.toLowerCase().indexOf(keyword) !=-1 || issue_discription.toLowerCase().indexOf(keyword) !=-1 ){
+     if(issue_title.toLowerCase().indexOf(keyword) !=-1 || issue_description.toLowerCase().indexOf(keyword) !=-1 ){
         console.log(`'${keyword}'keyword is present inside the title or description. Pushing label '${label}' to row.`)
         labelsToAdd.push(label)
     }

.kokoro/github/ubuntu/gpu/build.sh

@@ -57,6 +57,8 @@ then
                --ignore keras/src/backend/jax/distribution_lib_test.py \
                --ignore keras/src/distribution/distribution_lib_test.py \
                --cov=keras
+
+   pytest keras/src/distribution/distribution_lib_test.py --cov=keras
 fi
 
 if [ "$KERAS_BACKEND" == "torch" ]

api_gen.py

@@ -6,13 +6,15 @@
 It generates API and formats user and generated APIs.
 """
 
+import importlib
 import os
 import re
 import shutil
 
 import namex
 
-package = "keras"
+PACKAGE = "keras"
+BUILD_DIR_NAME = "tmp_build_dir"
 
 
 def ignore_files(_, filenames):
@@ -21,12 +23,12 @@ def ignore_files(_, filenames):
 
 def copy_source_to_build_directory(root_path):
     # Copy sources (`keras/` directory and setup files) to build dir
-    build_dir = os.path.join(root_path, "tmp_build_dir")
+    build_dir = os.path.join(root_path, BUILD_DIR_NAME)
     if os.path.exists(build_dir):
         shutil.rmtree(build_dir)
     os.mkdir(build_dir)
     shutil.copytree(
-        package, os.path.join(build_dir, package), ignore=ignore_files
+        PACKAGE, os.path.join(build_dir, PACKAGE), ignore=ignore_files
     )
     return build_dir
 
@@ -140,49 +142,33 @@ def export_version_string(api_init_fname):
         f.write(contents)
 
 
-def update_package_init(init_fname):
-    contents = """
-# Import everything from /api/ into keras.
-from keras.api import *  # noqa: F403
-from keras.api import __version__  # Import * ignores names start with "_".
-
-import os
-
-# Add everything in /api/ to the module search path.
-__path__.append(os.path.join(os.path.dirname(__file__), "api"))  # noqa: F405
-
-# Don't pollute namespace.
-del os
-
-# Never autocomplete `.src` or `.api` on an imported keras object.
-def __dir__():
-    keys = dict.fromkeys((globals().keys()))
-    keys.pop("src")
-    keys.pop("api")
-    return list(keys)
-
-
-# Don't import `.src` or `.api` during `from keras import *`.
-__all__ = [
-    name
-    for name in globals().keys()
-    if not (name.startswith("_") or name in ("src", "api"))
-]"""
-    with open(init_fname) as f:
-        init_contents = f.read()
-    with open(init_fname, "w") as f:
-        f.write(init_contents.replace("\nfrom keras import api", contents))
+def update_package_init(template_fname, dest_fname, api_module):
+    with open(template_fname) as template_file:
+        with open(dest_fname, "w") as dest_file:
+            for line in template_file:
+                if "# DO NOT EDIT." in line:
+                    dest_file.write(line)
+                    # Import all public symbols from `api/` and `__version__`.
+                    for symbol in api_module.__dict__.keys():
+                        if symbol.startswith("_") and symbol != "__version__":
+                            continue
+                        dest_file.write(f"from keras.api import {symbol}\n")
+                    # Skip the previous autogenerated block.
+                    for line in template_file:
+                        if "# END DO NOT EDIT." in line:
+                            break
+                dest_file.write(line)
 
 
 def build():
     # Backup the `keras/__init__.py` and restore it on error in api gen.
     root_path = os.path.dirname(os.path.abspath(__file__))
-    code_api_dir = os.path.join(root_path, package, "api")
-    code_init_fname = os.path.join(root_path, package, "__init__.py")
+    code_api_dir = os.path.join(root_path, PACKAGE, "api")
+    code_init_fname = os.path.join(root_path, PACKAGE, "__init__.py")
     # Create temp build dir
     build_dir = copy_source_to_build_directory(root_path)
-    build_api_dir = os.path.join(build_dir, package, "api")
-    build_init_fname = os.path.join(build_dir, package, "__init__.py")
+    build_api_dir = os.path.join(build_dir, PACKAGE, "api")
+    build_init_fname = os.path.join(build_dir, PACKAGE, "__init__.py")
     build_api_init_fname = os.path.join(build_api_dir, "__init__.py")
     try:
         os.chdir(build_dir)
@@ -195,12 +181,13 @@ def build():
         namex.generate_api_files(
             "keras", code_directory="src", target_directory="api"
         )
-        # Creates `keras/__init__.py` importing from `keras/api`
-        update_package_init(build_init_fname)
-        # Add __version__ to keras package
+        # Add __version__ to `api/`.
         export_version_string(build_api_init_fname)
         # Creates `_tf_keras` with full keras API
-        create_legacy_directory(package_dir=os.path.join(build_dir, package))
+        create_legacy_directory(package_dir=os.path.join(build_dir, PACKAGE))
+        # Update toplevel init with all `api/` imports.
+        api_module = importlib.import_module(f"{BUILD_DIR_NAME}.keras.api")
+        update_package_init(code_init_fname, build_init_fname, api_module)
         # Copy back the keras/api and keras/__init__.py from build directory
         if os.path.exists(code_api_dir):
             shutil.rmtree(code_api_dir)

guides/training_with_built_in_methods.py

@@ -338,7 +338,7 @@ def result(self):
 
     def reset_state(self):
         # The state of the metric will be reset at the start of each epoch.
-        self.true_positives.assign(0.0)
+        self.true_positives.assign(0)
 
 
 model = get_uncompiled_model()
@@ -592,6 +592,7 @@ def call(self, targets, logits, sample_weights=None):
 
 The method `__getitem__` should return a complete batch.
 If you want to modify your dataset between epochs, you may implement `on_epoch_end`.
+You may also implement `on_epoch_begin` to be called at the start of each epoch.
 
 Here's a quick example:
 """
@@ -649,7 +650,7 @@ def __getitem__(self, idx):
     `True` if your dataset can be safely pickled.
 - `max_queue_size`: Maximum number of batches to keep in the queue
     when iterating over the dataset in a multithreaded or
-    multipricessed setting.
+    multiprocessed setting.
     You can reduce this value to reduce the CPU memory consumption of
     your dataset. It defaults to 10.
 

integration_tests/dataset_tests/cifar100_test.py

@@ -26,9 +26,9 @@ def test_shapes_coarse_label_mode(self):
     def test_dtypes(self):
         (x_train, y_train), (x_test, y_test) = cifar100.load_data()
         self.assertEqual(x_train.dtype, np.uint8)
-        self.assertEqual(y_train.dtype, np.uint8)
+        self.assertEqual(y_train.dtype, np.int64)
         self.assertEqual(x_test.dtype, np.uint8)
-        self.assertEqual(y_test.dtype, np.uint8)
+        self.assertEqual(y_test.dtype, np.int64)
 
     def test_invalid_label_mode(self):
         with self.assertRaises(ValueError):

integration_tests/dataset_tests/imdb_test.py

@@ -7,9 +7,9 @@
 class ImdbLoadDataTest(testing.TestCase):
     def test_load_data_default(self):
         (x_train, y_train), (x_test, y_test) = imdb.load_data()
-        self.assertIsInstance(x_train, list)
+        self.assertIsInstance(x_train, np.ndarray)
         self.assertIsInstance(y_train, np.ndarray)
-        self.assertIsInstance(x_test, list)
+        self.assertIsInstance(x_test, np.ndarray)
         self.assertIsInstance(y_test, np.ndarray)
 
         # Check lengths