Colab VERIFICATION_SCRIPT ModuleNotFoundError: No module named 'tensorflow.python.keras.applications'

[BWWS]

I am trying to run the code direct from uploading into COLAB from GitHub I am unable to get past the VERIFICATION_SCRIPT

It reports the following error:

Traceback (most recent call last): File "Tensorflow/models/research/object_detection/builders/model_builder_tf2_test.py", line 25, in from object_detection.builders import model_builder File "/usr/local/lib/python3.7/dist-packages/object_detection/builders/model_builder.py", line 37, in from object_detection.meta_architectures import deepmac_meta_arch File "/usr/local/lib/python3.7/dist-packages/object_detection/meta_architectures/deepmac_meta_arch.py", line 19, in from object_detection.models.keras_models import resnet_v1 File "/usr/local/lib/python3.7/dist-packages/object_detection/models/keras_models/resnet_v1.py", line 22, in from tensorflow.python.keras.applications import resnet ModuleNotFoundError: No module named 'tensorflow.python.keras.applications'

Using the latest Colab versions:
tensorflow 2.8.0 tensorflow-io 0.23.1 keras 2.8.0 Keras-Preprocessing 1.1.2

I have tried using older versions ranging from 2.3.0 but these just lead to different errors

Please advise if you have a solution to this.

[SauBuen]

install 'tf-models-official==2.7.1',

you can also change the script: Tensorflow/models/research/object_detection/packages/tf2/setup.py

'tf-models-official==2.7.1',

[BWWS]

Hi SauBuen, Thanks but did not work fully. Passes the verification script but now fails at the training script:

python Tensorflow/models/research/object_detection/model_main_tf2.py --model_dir=Tensorflow/workspace/models/Seep_ssd_mobnet --pipeline_config_path=Tensorflow/workspace/models/Seep_ssd_mobnet/pipeline.config --num_train_steps=2000

2022-02-08 10:31:17.000189: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-02-08 10:31:17.009763: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-02-08 10:31:17.010590: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-02-08 10:31:17.011815: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2022-02-08 10:31:17.012111: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-02-08 10:31:17.012903: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-02-08 10:31:17.013704: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-02-08 10:31:17.570257: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-02-08 10:31:17.571145: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-02-08 10:31:17.571903: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero 2022-02-08 10:31:17.572642: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0. 2022-02-08 10:31:17.572721: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1510] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 10663 MB memory: -> device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7 INFO:tensorflow:Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:0',) I0208 10:31:17.578470 139906285909888 mirrored_strategy.py:369] Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:GPU:0',) INFO:tensorflow:Maybe overwriting train_steps: 2000 I0208 10:31:17.583169 139906285909888 config_util.py:552] Maybe overwriting train_steps: 2000 INFO:tensorflow:Maybe overwriting use_bfloat16: False I0208 10:31:17.583358 139906285909888 config_util.py:552] Maybe overwriting use_bfloat16: False WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py:564: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version. Instructions for updating: rename to distribute_datasets_from_function W0208 10:31:17.613617 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py:564: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version. Instructions for updating: rename to distribute_datasets_from_function INFO:tensorflow:Reading unweighted datasets: ['Tensorflow/workspace/annotations/train.record'] I0208 10:31:17.618627 139906285909888 dataset_builder.py:163] Reading unweighted datasets: ['Tensorflow/workspace/annotations/train.record'] INFO:tensorflow:Reading record datasets for input file: ['Tensorflow/workspace/annotations/train.record'] I0208 10:31:17.618862 139906285909888 dataset_builder.py:80] Reading record datasets for input file: ['Tensorflow/workspace/annotations/train.record'] INFO:tensorflow:Number of filenames to read: 1 I0208 10:31:17.619039 139906285909888 dataset_builder.py:81] Number of filenames to read: 1 WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards. W0208 10:31:17.619182 139906285909888 dataset_builder.py:88] num_readers has been reduced to 1 to match input file shards. WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE) instead. If sloppy execution is desired, use tf.data.Options.experimental_deterministic. W0208 10:31:17.622419 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:105: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE) instead. If sloppy execution is desired, use tf.data.Options.experimental_deterministic. WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.data.Dataset.map() W0208 10:31:17.646344 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/object_detection/builders/dataset_builder.py:237: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version. Instructions for updating: Usetf.data.Dataset.map() WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version. Instructions for updating: Create a tf.sparse.SparseTensor and use tf.sparse.to_dense instead. W0208 10:31:26.506816 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version. Instructions for updating: Create a tf.sparse.SparseTensor and use tf.sparse.to_dense instead. WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version. Instructions for updating: seed2 arg is deprecated.Use sample_distorted_bounding_box_v2 instead. W0208 10:31:30.294101 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/util/dispatch.py:206: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version. Instructions for updating: seed2 arg is deprecated.Use sample_distorted_bounding_box_v2 instead. WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py:464: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.cast instead. W0208 10:31:32.181428 139906285909888 deprecation.py:345] From /usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py:464: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use tf.cast instead. 2022-02-08 10:31:34.971475: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2) /usr/local/lib/python3.7/dist-packages/keras/backend.py:401: UserWarning: tf.keras.backend.set_learning_phase is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the training argument of the __call__ method of your layer or model. warnings.warn('tf.keras.backend.set_learning_phase is deprecated and ' 2022-02-08 10:31:58.458210: E tensorflow/stream_executor/cuda/cuda_dnn.cc:362] Loaded runtime CuDNN library: 8.0.5 but source was compiled with: 8.1.0. CuDNN library needs to have matching major version and equal or higher minor version. If using a binary install, upgrade your CuDNN library. If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration. 2022-02-08 10:31:58.461067: E tensorflow/stream_executor/cuda/cuda_dnn.cc:362] Loaded runtime CuDNN library: 8.0.5 but source was compiled with: 8.1.0. CuDNN library needs to have matching major version and equal or higher minor version. If using a binary install, upgrade your CuDNN library. If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration. Traceback (most recent call last): File "Tensorflow/models/research/object_detection/model_main_tf2.py", line 115, in tf.compat.v1.app.run() File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/platform/app.py", line 40, in run _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef) File "/usr/local/lib/python3.7/dist-packages/absl/app.py", line 312, in run _run_main(main, args) File "/usr/local/lib/python3.7/dist-packages/absl/app.py", line 258, in _run_main sys.exit(main(argv)) File "Tensorflow/models/research/object_detection/model_main_tf2.py", line 112, in main record_summaries=FLAGS.record_summaries) File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 609, in train_loop train_input, unpad_groundtruth_tensors) File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 400, in load_fine_tune_checkpoint _ensure_model_is_built(model, input_dataset, unpad_groundtruth_tensors) File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 178, in _ensure_model_is_built labels, File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py", line 1286, in run return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/distribute_lib.py", line 2849, in call_for_each_replica return self._call_for_each_replica(fn, args, kwargs) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/mirrored_strategy.py", line 671, in _call_for_each_replica self._container_strategy(), fn, args, kwargs) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/distribute/mirrored_run.py", line 86, in call_for_each_replica return wrapped(args, kwargs) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/def_function.py", line 885, in call result = self._call(*args, *kwds) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/def_function.py", line 950, in _call return self._stateless_fn(args, **kwds) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/function.py", line 3040, in call filtered_flat_args, captured_inputs=graph_function.captured_inputs) # pylint: disable=protected-access File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/function.py", line 1964, in _call_flat ctx, args, cancellation_manager=cancellation_manager)) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/function.py", line 596, in call ctx=ctx) File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/execute.py", line 60, in quick_execute inputs, attrs, num_outputs) tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above. [[node ssd_mobile_net_v2fpn_keras_feature_extractor/model/Conv1/Conv2D (defined at /usr/local/lib/python3.7/dist-packages/object_detection/models/ssd_mobilenet_v2_fpn_keras_feature_extractor.py:219) ]] [Op:inferencedummy_computation_fn_15081]

Errors may have originated from an input operation. Input Source operations connected to node ssd_mobile_net_v2fpn_keras_feature_extractor/model/Conv1/Conv2D: args_1 (defined at /usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py:178)

Function call stack: _dummy_computation_fn

[SauBuen]

Now I am having the same issue, before it was working

[SauBuen]

I asked this same question in the TensorFlow models guithub issue#10505 I think there it is more probable to get help there