ValueError: Node 'gradients/InceptionResnetV1/Bottleneck/BatchNorm/cond/FusedBatchNorm_1_grad/FusedBatchNormGrad' has an _output_shapes attribute inconsistent with the GraphDef for output #3: Dimension 0 in both shapes must be equal, but are 0 and 512. Shapes are [0] and [512].

[NguyenDucTruong2504]

C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\venv\Scripts\python.exe C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\detection.py
2023-12-28 18:11:21.029652: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable TF_ENABLE_ONEDNN_OPTS=0.
WARNING:tensorflow:From C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\venv\Lib\site-packages\keras\src\losses.py:2976: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.

WARNING:tensorflow:From C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\detection.py:13: The name tf.disable_eager_execution is deprecated. Please use tf.compat.v1.disable_eager_execution instead.

2023-12-28 18:11:30.795362: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: SSE SSE2 SSE3 SSE4.1 SSE4.2 AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
WARNING:tensorflow:From C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\venv\Lib\site-packages\tensorflow\python\util\dispatch.py:1260: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Deprecated in favor of operator or tf.math.divide.
2023-12-28 18:11:30.961375: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:388] MLIR V1 optimization pass is not enabled
WARNING:tensorflow:From C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\align\detect_face.py:172: The name tf.nn.xw_plus_b is deprecated. Please use tf.compat.v1.nn.xw_plus_b instead.

Model directory: models
Metagraph file: model-20180402-114759.meta
Checkpoint file: model-20180402-114759.ckpt-275
WARNING:tensorflow:From C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\facenett\facenet.py:382: The name tf.train.import_meta_graph is deprecated. Please use tf.compat.v1.train.import_meta_graph instead.

Traceback (most recent call last):
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\venv\Lib\site-packages\tensorflow\python\framework\importer.py", line 511, in _import_graph_def_internal
results = c_api.TF_GraphImportGraphDefWithResults(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
tensorflow.python.framework.errors_impl.InvalidArgumentError: Node 'gradients/InceptionResnetV1/Bottleneck/BatchNorm/cond/FusedBatchNorm_1_grad/FusedBatchNormGrad' has an _output_shapes attribute inconsistent with the GraphDef for output #3: Dimension 0 in both shapes must be equal, but are 0 and 512. Shapes are [0] and [512].

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\detection.py", line 132, in
run('models', 'models/facemodel.pkl')
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\detection.py", line 97, in run
face_recognition = Recognition(model_checkpoint, classifier)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\facenett\face_contrib.py", line 31, in init
self.encoder = Encoder(facenet_model_checkpoint)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\facenett\face_contrib.py", line 71, in init
load_model(facenet_model_checkpoint)
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\facenett\facenet.py", line 382, in load_model
saver = tf.compat.v1.train.import_meta_graph(os.path.join(model_exp, meta_file), input_map=input_map)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\venv\Lib\site-packages\tensorflow\python\training\saver.py", line 1583, in import_meta_graph
return _import_meta_graph_with_return_elements(meta_graph_or_file,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\venv\Lib\site-packages\tensorflow\python\training\saver.py", line 1604, in _import_meta_graph_with_return_elements
meta_graph.import_scoped_meta_graph_with_return_elements(
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\venv\Lib\site-packages\tensorflow\python\framework\meta_graph.py", line 785, in import_scoped_meta_graph_with_return_elements
imported_return_elements = importer.import_graph_def(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\venv\Lib\site-packages\tensorflow\python\util\deprecation.py", line 588, in new_func
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\venv\Lib\site-packages\tensorflow\python\framework\importer.py", line 407, in import_graph_def
return _import_graph_def_internal(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Choso\PycharmProjects\AttendanceSystemDemo\venv\Lib\site-packages\tensorflow\python\framework\importer.py", line 516, in _import_graph_def_internal
raise ValueError(str(e))
ValueError: Node 'gradients/InceptionResnetV1/Bottleneck/BatchNorm/cond/FusedBatchNorm_1_grad/FusedBatchNormGrad' has an _output_shapes attribute inconsistent with the GraphDef for output #3: Dimension 0 in both shapes must be equal, but are 0 and 512. Shapes are [0] and [512].

Process finished with exit code 1

[NguyenDucTruong2504]

def load_model(model, input_map=None):
# Check if the model is a model directory (containing a metagraph and a checkpoint file)
# or if it is a protobuf file with a frozen graph
model_exp = os.path.expanduser(model)
if (os.path.isfile(model_exp)):
print('Model filename: %s' % model_exp)
with gfile.FastGFile(model_exp, 'rb') as f:
graph_def = tf.compat.v1.GraphDef()
graph_def.ParseFromString(f.read())
tf.import_graph_def(graph_def, input_map=input_map, name='')
else:
print('Model directory: %s' % model_exp)
meta_file, ckpt_file = get_model_filenames(model_exp)

    print('Metagraph file: %s' % meta_file)
    print('Checkpoint file: %s' % ckpt_file)

    saver = tf.compat.v1.train.import_meta_graph(os.path.join(model_exp, meta_file), input_map=input_map)
    saver.restore(tf.compat.v1.get_default_session(), os.path.join(model_exp, ckpt_file))