mlx - merge master into mlx

.github/workflows/actions.yml

@@ -126,3 +126,12 @@ jobs:
           fi
       - name: Lint
         run: bash shell/lint.sh
+      - name: Check for API changes
+        run: |
+          bash shell/api_gen.sh
+          git status
+          clean=$(git status | grep "nothing to commit")
+          if [ -z "$clean" ]; then
+            echo "Please run shell/api_gen.sh to generate API."
+            exit 1
+          fi

.github/workflows/nightly.yml

@@ -92,6 +92,16 @@ jobs:
           fi
       - name: Lint
         run: bash shell/lint.sh
+      - name: Check for API changes
+        run: |
+          bash shell/api_gen.sh
+          git status
+          clean=$(git status | grep "nothing to commit")
+          if [ -z "$clean" ]; then
+            echo "Please run shell/api_gen.sh to generate API."
+            exit 1
+          fi
+
 
   nightly:
     name: Build Wheel file and upload

.github/workflows/scorecard.yml

@@ -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@5d5d22a31266ced268874388b861e4b58bb5c2f3 # v4.3.1
+        uses: actions/upload-artifact@65462800fd760344b1a7b4382951275a0abb4808 # v4.3.3
         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@1b1aada464948af03b950897e5eb522f92603cc2 # v3.24.9
+        uses: github/codeql-action/upload-sarif@d39d31e687223d841ef683f52467bd88e9b21c14 # v3.25.3
         with:
           sarif_file: results.sarif

.github/workflows/stale-issue-pr.yaml

@@ -10,6 +10,7 @@ jobs:
     permissions:
       issues: write
       pull-requests: write
+      actions: write
     steps:
       - name: Awaiting response issues
         uses: actions/stale@v9

SECURITY.md

@@ -59,7 +59,7 @@ Besides the virtual environment, the hardware (GPUs or TPUs) can also be attacke
 
 ## Reporting a Vulnerability
 
-Beware that none of the topics under [Using Keras Securely](#using-Keras-securely) are considered vulnerabilities of Keras.
+Beware that none of the topics under [Using Keras Securely](#using-keras-securely) are considered vulnerabilities of Keras.
 
 If you have discovered a security vulnerability in this project, please report it
 privately. **Do not disclose it as a public issue.** This gives us time to work with you

api_gen.py

@@ -7,6 +7,7 @@
 """
 
 import os
+import re
 import shutil
 
 import namex
@@ -78,8 +79,7 @@ def create_legacy_directory(package_dir):
         for path in os.listdir(os.path.join(src_dir, "legacy"))
         if os.path.isdir(os.path.join(src_dir, "legacy", path))
     ]
-
-    for root, _, fnames in os.walk(os.path.join(package_dir, "_legacy")):
+    for root, _, fnames in os.walk(os.path.join(api_dir, "_legacy")):
         for fname in fnames:
             if fname.endswith(".py"):
                 legacy_fpath = os.path.join(root, fname)
@@ -110,6 +110,20 @@ def create_legacy_directory(package_dir):
                             f"keras.api.{legacy_submodule}",
                             f"keras.api._tf_keras.keras.{legacy_submodule}",
                         )
+                    # Remove duplicate generated comments string.
+                    legacy_contents = re.sub(r"\n", r"\\n", legacy_contents)
+                    legacy_contents = re.sub('""".*"""', "", legacy_contents)
+                    legacy_contents = re.sub(r"\\n", r"\n", legacy_contents)
+                    # If the same module is in legacy and core_api, use legacy
+                    legacy_imports = re.findall(
+                        r"import (\w+)", legacy_contents
+                    )
+                    for import_name in legacy_imports:
+                        core_api_contents = re.sub(
+                            f"\n.* import {import_name}\n",
+                            r"\n",
+                            core_api_contents,
+                        )
                     legacy_contents = core_api_contents + "\n" + legacy_contents
                 with open(tf_keras_fpath, "w") as f:
                     f.write(legacy_contents)

keras/api/_tf_keras/keras/__init__.py

@@ -6,7 +6,6 @@
 
 from keras.api import activations
 from keras.api import applications
-from keras.api import backend
 from keras.api import callbacks
 from keras.api import config
 from keras.api import constraints
@@ -15,21 +14,21 @@
 from keras.api import dtype_policies
 from keras.api import export
 from keras.api import initializers
-from keras.api import layers
 from keras.api import legacy
-from keras.api import losses
-from keras.api import metrics
 from keras.api import mixed_precision
 from keras.api import models
 from keras.api import ops
 from keras.api import optimizers
-from keras.api import preprocessing
 from keras.api import quantizers
 from keras.api import random
 from keras.api import regularizers
-from keras.api import saving
 from keras.api import tree
 from keras.api import utils
+from keras.api._tf_keras.keras import backend
+from keras.api._tf_keras.keras import layers
+from keras.api._tf_keras.keras import losses
+from keras.api._tf_keras.keras import metrics
+from keras.api._tf_keras.keras import preprocessing
 from keras.src.backend.common.keras_tensor import KerasTensor
 from keras.src.backend.common.stateless_scope import StatelessScope
 from keras.src.backend.exports import Variable

keras/api/_tf_keras/keras/backend/__init__.py

@@ -17,4 +17,127 @@
 from keras.src.backend.config import set_epsilon
 from keras.src.backend.config import set_floatx
 from keras.src.backend.config import set_image_data_format
+from keras.src.legacy.backend import abs
+from keras.src.legacy.backend import all
+from keras.src.legacy.backend import any
+from keras.src.legacy.backend import arange
+from keras.src.legacy.backend import argmax
+from keras.src.legacy.backend import argmin
+from keras.src.legacy.backend import batch_dot
+from keras.src.legacy.backend import batch_flatten
+from keras.src.legacy.backend import batch_get_value
+from keras.src.legacy.backend import batch_normalization
+from keras.src.legacy.backend import batch_set_value
+from keras.src.legacy.backend import bias_add
+from keras.src.legacy.backend import binary_crossentropy
+from keras.src.legacy.backend import binary_focal_crossentropy
+from keras.src.legacy.backend import cast
+from keras.src.legacy.backend import cast_to_floatx
+from keras.src.legacy.backend import categorical_crossentropy
+from keras.src.legacy.backend import categorical_focal_crossentropy
+from keras.src.legacy.backend import clip
+from keras.src.legacy.backend import concatenate
+from keras.src.legacy.backend import constant
+from keras.src.legacy.backend import conv1d
+from keras.src.legacy.backend import conv2d
+from keras.src.legacy.backend import conv2d_transpose
+from keras.src.legacy.backend import conv3d
+from keras.src.legacy.backend import cos
+from keras.src.legacy.backend import count_params
+from keras.src.legacy.backend import ctc_batch_cost
+from keras.src.legacy.backend import ctc_decode
+from keras.src.legacy.backend import ctc_label_dense_to_sparse
+from keras.src.legacy.backend import cumprod
+from keras.src.legacy.backend import cumsum
+from keras.src.legacy.backend import depthwise_conv2d
+from keras.src.legacy.backend import dot
+from keras.src.legacy.backend import dropout
+from keras.src.legacy.backend import dtype
+from keras.src.legacy.backend import elu
+from keras.src.legacy.backend import equal
+from keras.src.legacy.backend import eval
+from keras.src.legacy.backend import exp
+from keras.src.legacy.backend import expand_dims
+from keras.src.legacy.backend import eye
+from keras.src.legacy.backend import flatten
+from keras.src.legacy.backend import foldl
+from keras.src.legacy.backend import foldr
+from keras.src.legacy.backend import gather
+from keras.src.legacy.backend import get_value
+from keras.src.legacy.backend import gradients
+from keras.src.legacy.backend import greater
+from keras.src.legacy.backend import greater_equal
+from keras.src.legacy.backend import hard_sigmoid
+from keras.src.legacy.backend import in_top_k
+from keras.src.legacy.backend import int_shape
+from keras.src.legacy.backend import is_sparse
+from keras.src.legacy.backend import l2_normalize
+from keras.src.legacy.backend import less
+from keras.src.legacy.backend import less_equal
+from keras.src.legacy.backend import log
+from keras.src.legacy.backend import map_fn
+from keras.src.legacy.backend import max
+from keras.src.legacy.backend import maximum
+from keras.src.legacy.backend import mean
+from keras.src.legacy.backend import min
+from keras.src.legacy.backend import minimum
+from keras.src.legacy.backend import moving_average_update
+from keras.src.legacy.backend import name_scope
+from keras.src.legacy.backend import ndim
+from keras.src.legacy.backend import not_equal
+from keras.src.legacy.backend import one_hot
+from keras.src.legacy.backend import ones
+from keras.src.legacy.backend import ones_like
+from keras.src.legacy.backend import permute_dimensions
+from keras.src.legacy.backend import pool2d
+from keras.src.legacy.backend import pool3d
+from keras.src.legacy.backend import pow
+from keras.src.legacy.backend import prod
+from keras.src.legacy.backend import random_bernoulli
+from keras.src.legacy.backend import random_normal
+from keras.src.legacy.backend import random_normal_variable
+from keras.src.legacy.backend import random_uniform
+from keras.src.legacy.backend import random_uniform_variable
+from keras.src.legacy.backend import relu
+from keras.src.legacy.backend import repeat
+from keras.src.legacy.backend import repeat_elements
+from keras.src.legacy.backend import reshape
+from keras.src.legacy.backend import resize_images
+from keras.src.legacy.backend import resize_volumes
+from keras.src.legacy.backend import reverse
+from keras.src.legacy.backend import rnn
+from keras.src.legacy.backend import round
+from keras.src.legacy.backend import separable_conv2d
+from keras.src.legacy.backend import set_value
+from keras.src.legacy.backend import shape
+from keras.src.legacy.backend import sigmoid
+from keras.src.legacy.backend import sign
+from keras.src.legacy.backend import sin
+from keras.src.legacy.backend import softmax
+from keras.src.legacy.backend import softplus
+from keras.src.legacy.backend import softsign
+from keras.src.legacy.backend import sparse_categorical_crossentropy
+from keras.src.legacy.backend import spatial_2d_padding
+from keras.src.legacy.backend import spatial_3d_padding
+from keras.src.legacy.backend import sqrt
+from keras.src.legacy.backend import square
+from keras.src.legacy.backend import squeeze
+from keras.src.legacy.backend import stack
+from keras.src.legacy.backend import std
+from keras.src.legacy.backend import stop_gradient
+from keras.src.legacy.backend import sum
+from keras.src.legacy.backend import switch
+from keras.src.legacy.backend import tanh
+from keras.src.legacy.backend import temporal_padding
+from keras.src.legacy.backend import tile
+from keras.src.legacy.backend import to_dense
+from keras.src.legacy.backend import transpose
+from keras.src.legacy.backend import truncated_normal
+from keras.src.legacy.backend import update
+from keras.src.legacy.backend import update_add
+from keras.src.legacy.backend import update_sub
+from keras.src.legacy.backend import var
+from keras.src.legacy.backend import variable
+from keras.src.legacy.backend import zeros
+from keras.src.legacy.backend import zeros_like
 from keras.src.utils.naming import get_uid

keras/api/_tf_keras/keras/dtype_policies/__init__.py

@@ -4,6 +4,9 @@
 since your modifications would be overwritten.
 """
 
+from keras.src.dtype_policies import deserialize
+from keras.src.dtype_policies import get
+from keras.src.dtype_policies import serialize
 from keras.src.dtype_policies.dtype_policy import DTypePolicy
 from keras.src.dtype_policies.dtype_policy import FloatDTypePolicy
 from keras.src.dtype_policies.dtype_policy import QuantizedDTypePolicy

keras/api/_tf_keras/keras/layers/__init__.py

@@ -157,7 +157,6 @@
 from keras.src.layers.regularization.activity_regularization import (
     ActivityRegularization,
 )
-from keras.src.layers.regularization.alpha_dropout import AlphaDropout
 from keras.src.layers.regularization.dropout import Dropout
 from keras.src.layers.regularization.gaussian_dropout import GaussianDropout
 from keras.src.layers.regularization.gaussian_noise import GaussianNoise
@@ -190,6 +189,10 @@
 from keras.src.layers.rnn.simple_rnn import SimpleRNNCell
 from keras.src.layers.rnn.stacked_rnn_cells import StackedRNNCells
 from keras.src.layers.rnn.time_distributed import TimeDistributed
+from keras.src.legacy.layers import AlphaDropout
+from keras.src.legacy.layers import RandomHeight
+from keras.src.legacy.layers import RandomWidth
+from keras.src.legacy.layers import ThresholdedReLU
 from keras.src.utils.jax_layer import FlaxLayer
 from keras.src.utils.jax_layer import JaxLayer
 from keras.src.utils.torch_utils import TorchModuleWrapper

keras/api/_tf_keras/keras/losses/__init__.py

@@ -4,6 +4,7 @@
 since your modifications would be overwritten.
 """
 
+from keras.src.legacy.losses import Reduction
 from keras.src.losses import deserialize
 from keras.src.losses import get
 from keras.src.losses import serialize
@@ -38,12 +39,18 @@
 from keras.src.losses.losses import dice
 from keras.src.losses.losses import hinge
 from keras.src.losses.losses import huber
-from keras.src.losses.losses import kl_divergence
-from keras.src.losses.losses import log_cosh
-from keras.src.losses.losses import mean_absolute_error
-from keras.src.losses.losses import mean_absolute_percentage_error
-from keras.src.losses.losses import mean_squared_error
-from keras.src.losses.losses import mean_squared_logarithmic_error
+from keras.src.losses.losses import kl_divergence as KLD
+from keras.src.losses.losses import kl_divergence as kld
+from keras.src.losses.losses import kl_divergence as kullback_leibler_divergence
+from keras.src.losses.losses import log_cosh as logcosh
+from keras.src.losses.losses import mean_absolute_error as MAE
+from keras.src.losses.losses import mean_absolute_error as mae
+from keras.src.losses.losses import mean_absolute_percentage_error as MAPE
+from keras.src.losses.losses import mean_absolute_percentage_error as mape
+from keras.src.losses.losses import mean_squared_error as MSE
+from keras.src.losses.losses import mean_squared_error as mse
+from keras.src.losses.losses import mean_squared_logarithmic_error as MSLE
+from keras.src.losses.losses import mean_squared_logarithmic_error as msle
 from keras.src.losses.losses import poisson
 from keras.src.losses.losses import sparse_categorical_crossentropy
 from keras.src.losses.losses import squared_hinge

keras/api/_tf_keras/keras/metrics/__init__.py

@@ -11,12 +11,18 @@
 from keras.src.losses.losses import categorical_hinge
 from keras.src.losses.losses import hinge
 from keras.src.losses.losses import huber
-from keras.src.losses.losses import kl_divergence
-from keras.src.losses.losses import log_cosh
-from keras.src.losses.losses import mean_absolute_error
-from keras.src.losses.losses import mean_absolute_percentage_error
-from keras.src.losses.losses import mean_squared_error
-from keras.src.losses.losses import mean_squared_logarithmic_error
+from keras.src.losses.losses import kl_divergence as KLD
+from keras.src.losses.losses import kl_divergence as kld
+from keras.src.losses.losses import kl_divergence as kullback_leibler_divergence
+from keras.src.losses.losses import log_cosh as logcosh
+from keras.src.losses.losses import mean_absolute_error as MAE
+from keras.src.losses.losses import mean_absolute_error as mae
+from keras.src.losses.losses import mean_absolute_percentage_error as MAPE
+from keras.src.losses.losses import mean_absolute_percentage_error as mape
+from keras.src.losses.losses import mean_squared_error as MSE
+from keras.src.losses.losses import mean_squared_error as mse
+from keras.src.losses.losses import mean_squared_logarithmic_error as MSLE
+from keras.src.losses.losses import mean_squared_logarithmic_error as msle
 from keras.src.losses.losses import poisson
 from keras.src.losses.losses import sparse_categorical_crossentropy
 from keras.src.losses.losses import squared_hinge

keras/api/_tf_keras/keras/ops/__init__.py

@@ -56,6 +56,7 @@
 from keras.src.ops.nn import categorical_crossentropy
 from keras.src.ops.nn import conv
 from keras.src.ops.nn import conv_transpose
+from keras.src.ops.nn import ctc_decode
 from keras.src.ops.nn import ctc_loss
 from keras.src.ops.nn import depthwise_conv
 from keras.src.ops.nn import elu
@@ -71,6 +72,7 @@
 from keras.src.ops.nn import multi_hot
 from keras.src.ops.nn import normalize
 from keras.src.ops.nn import one_hot
+from keras.src.ops.nn import psnr
 from keras.src.ops.nn import relu
 from keras.src.ops.nn import relu6
 from keras.src.ops.nn import selu
@@ -100,6 +102,7 @@
 from keras.src.ops.numpy import arctanh
 from keras.src.ops.numpy import argmax
 from keras.src.ops.numpy import argmin
+from keras.src.ops.numpy import argpartition
 from keras.src.ops.numpy import argsort
 from keras.src.ops.numpy import array
 from keras.src.ops.numpy import average
@@ -190,10 +193,12 @@
 from keras.src.ops.numpy import reshape
 from keras.src.ops.numpy import roll
 from keras.src.ops.numpy import round
+from keras.src.ops.numpy import select
 from keras.src.ops.numpy import sign
 from keras.src.ops.numpy import sin
 from keras.src.ops.numpy import sinh
 from keras.src.ops.numpy import size
+from keras.src.ops.numpy import slogdet
 from keras.src.ops.numpy import sort
 from keras.src.ops.numpy import split
 from keras.src.ops.numpy import sqrt
@@ -218,6 +223,7 @@
 from keras.src.ops.numpy import true_divide
 from keras.src.ops.numpy import var
 from keras.src.ops.numpy import vdot
+from keras.src.ops.numpy import vectorize
 from keras.src.ops.numpy import vstack
 from keras.src.ops.numpy import where
 from keras.src.ops.numpy import zeros