The best way to fix this error is to use TensorFlow operations instead of iterating over Tensors. label_map_path: "/content/gdrive/MyDrive/content/train/teams_label_map.pbtxt" But if we pass an iterable object for example a list (even if it consists of one element) to the function then the calculation is successful. initializer { Have a question about this project? Create a tf.sparse.SparseTensor and use tf.sparse.to_dense instead. return fn(*args, **kwargs) Sign in Sign up for a free GitHub account to open an issue and contact its maintainers and the community. } Python Int Object is Not Iterable - freeCodeCamp.org File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 956, in eager_eval_loop coreClock: 1.59GHz coreCount: 40 deviceMemorySize: 14.75GiB deviceMemoryBandwidth: 298.08GiB/s Why don't airlines like when one intentionally misses a flight to save money? I0725 18:42:50.704592 140014892648320 checkpoint_utils.py:140] Waiting for new checkpoint at /content/drive/MyDrive/Object_detection/tfod/training_demo/models/my_ssd_mobilenet_v2/ File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1096, in call num_filters: 64 return fn(*args, **kwargs) @masahi @batuhan-uraltelekom Could you share the full log (and not just the error traceback) and the config file you are using ? It can easily add the whole of one list behind the other list and hence perform the concatenation. 2022-02-10 01:58:50.185251: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found But in Python for loops are used for sequential traversal. Instructions for updating: } And stop here! num_steps: 8000 File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 589, in _run_internal_graph l2_regularizer { Basically it was empty file with no images(Seems like I messed with my versions of TFRecord file for test set when I was setting up project). 2021-07-25 18:42:42.958050: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1258] Device interconnect StreamExecutor with strength 1 edge matrix: What I wanted to do instead was np.apply_along_axis, which makes a different assumption: that the given function takes a 1-D array. @vighneshbirodkar File "/usr/local/lib/python3.7/dist-packages/object_detection/meta_architectures/faster_rcnn_meta_arch.py", line 1345, in _extract_proposal_features Fear not! I do expect I can treat the dataset as an iterator, thus extracting the next element by calling next(dataset). Finxter Feedback from ~1000 Python Developers, https://docs.python.org/3.3/library/stdtypes.html?highlight=range#range, Boolean Operators in Python (and, or, not): Mastering Logical Expressions, [Fixed] ModuleNotFoundError: No module named requests-auth-aws-sigv4, [Fixed] ModuleNotFoundError: No module named requests-async, [Fixed] ModuleNotFoundError: No module named requests-aws4auth, [Fixed] ModuleNotFoundError: No module named requests-aws-sign, [Fixed] ModuleNotFoundError: No module named requests-cache, [Fixed] ModuleNotFoundError: No module named requests-futures, [Fixed] ModuleNotFoundError: No module named requests-file, [Fixed] ModuleNotFoundError: No module named requests-kerberos, [Fixed] ModuleNotFoundError: No module named requests-html, related to various functions and methods of lists, The world is changing exponentially. weight: 0.00004 The error you are encountering should go away. inputs, training=training, mask=mask) convolutional_box_predictor { As I already said, this situation is similar to the previous one. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. This can surely help with that, are you also doing the training on RasPi, or only inference? File "Tensorflow/models/research/object_detection/model_main_tf2.py", line 90, in main Semantic search without the napalm grandma exploit (Ep. 2022-02-10 01:58:50.182484: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found As you can see, in the case when b is not equal to zero, our code works correctly, the variables take the appropriate values. Those are the questions we're going to answer in this article. normalize_loc_loss_by_codesize: true The text was updated successfully, but these errors were encountered: A Dataset is not the same thing as an iterators, so this is expected behavior. The integer object number is not iterable, as we are not able to loop over it. l2_regularizer { y_scale: 10.0 601), Moderation strike: Results of negotiations, Our Design Vision for Stack Overflow and the Stack Exchange network, Temporary policy: Generative AI (e.g., ChatGPT) is banned, Call for volunteer reviewers for an updated search experience: OverflowAI Search, Discussions experiment launching on NLP Collective, Tensorflow - ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type float). File "model_main_tf2.py", line 113, in So were trying to add this to the list indexes with a list function. [[{{node ReduceDataset}}]] [Op:__inference_loopiter_35]. Detected at node 'model/conv1_conv/Conv2D' defined at (most recent call last): Instructions for updating: Now, in the loop, we first of all check the type of our local variable 'item' and if it is a list, then with a clear conscience we calculate its sum and rewrite the variable 'item' with the resulting value. File "/usr/local/lib/python3.7/dist-packages/object_detection/meta_architectures/faster_rcnn_meta_arch.py", line 1318, in _extract_rpn_feature_maps argmax_matcher { 1D sequence), then num_channels=1 - thus: Lastly, for 'binary_crossentropy', a better output layer would be Dense(1, activation='sigmoid'). I am using the below code to get the model evaluation: Log while running the evaluation code: lol. It adds an item to the list. File "Tensorflow/models/research/object_detection/model_main_tf2.py", line 115, in That fixes the error: name = input("What is your name? } File "/usr/local/lib/python3.7/dist-packages/absl/app.py", line 303, in run File "/data/tf-keras-surgeon/src/tfkerassurgeon/operations.py", line 105, in delete_channels max_detections_per_class: 100 Node: 'model/conv1_conv/Conv2D' I technically fixed the part of the issue that is mentioned here, but because the actual pruning is not working, it doesn't matter until I get the other items fixed. WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py:459: Tensor.experimental_ref (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version. Just now figured out that my test.record file was corrupted. negatives_lower_than_unmatched: true 2 Answers Sorted by: 0 This message indicates that tf.keras.preprocessing.sequence.skipgrams function receives a sequence argument in a wrong format. I1113 16:36:41.218508 139810192238464 efficientnet_model.py:143] round_filter input=16 output=16 I understand a dataset is not the same thing as an iterator and I'll use your solution to convert the dataset to a Python iterator when working in eager mode. weighted_sigmoid_focal { } PS. } Yes My model looks like this: My training data is a list of lists each comprised of 1000 floats. _run_main(main, args) Tensorflow - TypeError: 'int' object is not iterable freeze_batchnorm: false I have the same problem with the CenterNet Model. So to fix this error, we can write the assignment like this: And a few more examples of how you can assign values to several variables at once: A similar problem can arise if you use a function that returns multiple values as a tuple. [Op:__inference_compute_eval_dict_26441] exception. outputs = call_fn(inputs, *args, **kwargs) File "/content/gdrive/MyDrive/content/models/research/object_detection/model_main_tf2.py", line 114, in } File "Tensorflow/models/research/object_detection/model_main_tf2.py", line 90, in main width_scale: 5.0 height_scale: 5.0 TypeError: argument of type 'int' is not iterable in Python prediction_dict = self._predict_first_stage(preprocessed_inputs) apply_sigmoid_to_scores: false Otherwise, if iterating an iterable object, you will receive a return value of True or False. I1113 16:36:42.559586 139810192238464 efficientnet_model.py:453] Building model efficientnet with params ModelConfig(width_coefficient=1.0, depth_coefficient=1.0, resolution=224, dropout_rate=0.2, blocks=(BlockConfig(input_filters=32, output_filters=16, kernel_size=3, num_repeat=1, expand_ratio=1, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=16, output_filters=24, kernel_size=3, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=24, output_filters=40, kernel_size=5, num_repeat=2, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=40, output_filters=80, kernel_size=3, num_repeat=3, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=80, output_filters=112, kernel_size=5, num_repeat=3, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=112, output_filters=192, kernel_size=5, num_repeat=4, expand_ratio=6, strides=(2, 2), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise'), BlockConfig(input_filters=192, output_filters=320, kernel_size=3, num_repeat=1, expand_ratio=6, strides=(1, 1), se_ratio=0.25, id_skip=True, fused_conv=False, conv_type='depthwise')), stem_base_filters=32, top_base_filters=1280, activation='simple_swish', batch_norm='default', bn_momentum=0.99, bn_epsilon=0.001, weight_decay=5e-06, drop_connect_rate=0.2, depth_divisor=8, min_depth=None, use_se=True, input_channels=3, num_classes=1000, model_name='efficientnet', rescale_input=False, data_format='channels_last', dtype='float32') Overwriting num_epochs to 1. proposal_features = ( Securing Cabinet to wall: better to use two anchors to drywall or one screw into stud? train_input_reader { Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. @vighneshbirodkar Sure, I catch an exception which was exception type is attribute error and value's "upsampling_interpolation". The input_shape is not; if we're specifying the "shape" of a numpy (or similar) array, then we need a sequence of values - one for the size of each dimension. fine_tune_checkpoint: "/content/gdrive/MyDrive/content/models/research/deploy/efficientdet_d0_coco17_tpu-32/checkpoint/ckpt-0" However, I get the same error in the evaluation. In fact I get the final output with bounding boxes and acceptable performance. sync_replicas: true 601), Moderation strike: Results of negotiations, Our Design Vision for Stack Overflow and the Stack Exchange network, Temporary policy: Generative AI (e.g., ChatGPT) is banned, Call for volunteer reviewers for an updated search experience: OverflowAI Search, Discussions experiment launching on NLP Collective, Build a graph that works with variable batch size using Tensorflow, tensorflow stacked LSTM: "'Tensor' object is not iterable", Tensorflow dynamic_rnn TypeError: 'Tensor' object is not iterable, tensorflow.python.framework.errors.InvalidArgumentError, Tensor Object is not Iterable with BasicLSTMCell, TypeError: 'Tensor' object is not iterable, Tensorflow seq2seq: Tensor' object is not iterable, KeyError : The tensor variable , Refer to the tensor which does not exists, Tensorflow Type error when trying to iterate the Tensors in loop, Tensorflow - TypeError: 'int' object is not iterable, IndexError: list index out of range during training in Tensorflow, LSTM Cannot Convert Tensor To Numpy Array (Not Implemented Error). We see that the call function starts the process on the command line, then waits for its execution and returns the execution result code! class_prediction_bias_init: -4.6 And we cant do it like this. I am using Google Colab for this purpose so I am not sure I had any impact on the drivers, also tensorflow is already installed in Google Colab if I am not mistaken. Well occasionally send you account related emails. return fn(*args, **kwargs) Download. Python Int Object Is Not Iterable | Delft OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Archlinux, TensorFlow installed from (source or binary): binary, TensorFlow version (use command below): 2.0.0-dev20190312. File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler 'Encountered %s exception. tf.compat.v1.app.run() 2022-02-20 23:53:08.100522: 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. No, Still, there is an issue with this model_main_tf2.py approach for evaluation. How to fix the Python TypeError: 'int' Object is not Iterable Instructions for updating: Use tf.data.Dataset.map() I've Been digging into this, and a lot of things in Tensorflow have changed, and I'm still tracking down all the breaking changes. Command: W0220 23:53:07.220828 140280673650560 model_lib_v2.py:1090] Forced number of epochs for all eval validations to be 1. How to combine uparrow and sim in Plain TeX? Note that the comma is important to ensure that Python interpret it as a tuple, and not a single integer. Use tf.cast instead. Their construction assumes the presence of an iterable object. Have a question about this project? inplace_batchnorm_update: true What norms can be "universally" defined on any real vector space with a fixed basis? 'int' object is not iterable when using the inbound #1 - GitHub input_path: "/content/drive/MyDrive/Object_detection/tfod/training_demo/annotations/test_vedai2.record" Should fetch the first element of the iterator, thus print 10. weight_shared_convolutional_box_predictor { } I'm trying to run a for loop. data_augmentation_options { W0725 18:42:47.058952 140014892648320 deprecation.py:336] 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. wait_interval=300, timeout=FLAGS.eval_timeout) } Thanks for contributing an answer to Stack Overflow! height: 300 File "C:\Users\aclab\anaconda3\envs\thesis\lib\site-packages\object_detection-0.1-py3.6.egg\object_detection\model_lib_v2.py", line 1001, in eager_eval_loop Original config value was 0. TypeError: 'NoneType' object is not iterable while performing model Find centralized, trusted content and collaborate around the technologies you use most. I already figured it out. File "/usr/local/lib/python3.7/dist-packages/keras/layers/convolutional.py", line 248, in call File "/usr/local/lib/python3.7/dist-packages/object_detection/meta_architectures/faster_rcnn_meta_arch.py", line 1345, in _extract_proposal_features localization_loss { into the labels input on backprop by default. I happened to met the same question at same time. What distinguishes top researchers from mediocre ones? File "/usr/local/lib/python3.7/dist-packages/tensorflow/python/platform/app.py", line 40, in run This is always a situation where the interpreter expects an iterable object, and we provide it an integer. batch_size: 16 File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler Instructions for updating: File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 910, in compute_eval_dict Connect and share knowledge within a single location that is structured and easy to search. Here's the section of my code I'm having trouble with: So my intention is to run through aldurstengd_ororka, and for each "age" tuple in the dictionary, I run another for loop for each "item" inside the tuple. The main purpose of braces around tuples is to make the code look cleaner and to simplify some of the edge cases, such as single item tuples. Depending on which version of tensorflow you are using (you can check the version info by typing import tensorflow; tensorflow.__version__ in python interpreter), in version prior to r0.11, the default setting for the state_is_tuple argument when you initialize the rnn_cell.BasicLSTMCell(n_hidden, forget_bias=1.0) is set to be False. W0220 23:53:07.221323 140280673650560 model_lib_v2.py:1111] Expected number of evaluation epochs is 1, but instead encountered eval_on_train_input_config.num_epochs = 0. } As a data scientist or software engineer working with TensorFlow Estimator, its important to understand how Tensors work and how to use them correctly to avoid errors like this. wait_interval=300, timeout=FLAGS.eval_timeout) WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards. File "/content/gdrive/MyDrive/content/models/research/object_detection/model_main_tf2.py", line 89, in main sync_replicas: true File "/usr/local/lib/python3.7/dist-packages/object_detection/model_lib_v2.py", line 123, in _compute_losses_and_predictions_dicts Catholic Sources Which Point to the Three Visitors to Abraham in Gen. 18 as The Holy Trinity? INFO:tensorflow:Number of filenames to read: 1
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