![]() Steps_per_epoch=1, epochs=1, shuffle=False, verbose=0)įile "D:\Anaconda\envs\tf14\lib\site-packages\keras\engine\training.py", line 1239, in fitįile "D:\Anaconda\envs\tf14\lib\site-packages\keras\engine\training_arrays.py", line 152, in fit_loopįile "D:\Anaconda\envs\tf14\lib\site-packages\tensorflow\python\keras\backend. Pydev_imports.execfile(file, globals, locals) # execute the scriptįile "D:\JetBrains\Toolbox\apps\P圜harm-P\ch-0\201.6668.115\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfileĮxec(compile(contents "\n", file, 'exec'), glob, loc)įile "E:/1-Research/0-DP GCN/0/5GNNs/keras-gcn/kegra/train.py", line 88, in Arrays might store vertex data for complex shapes, recent keystrokes from the keyboard, or data read from a file. There can be arrays of numbers, characters, sentences, boolean values, and so on. The code ran fine 2 weeks back, but I am having trouble now.ĭo you think its tensorflow or keras versions?įile "D:\JetBrains\Toolbox\apps\P圜harm-P\ch-0\201.6668.115\plugins\python\helpers\pydev\pydevd.py", line 1438, in _exec Arrays can be created to hold any type of data, and each element can be individually assigned and read. I am trying to run the code as is but getting this error. ![]() ValueError: setting an array element with a sequence. > 85 return array(a, dtype, copy=False, order=order) ~/anaconda3/lib/python3.6/site-packages/numpy/core/_asarray.py in asarray(a, dtype, order) > 3277 dtype=tensor_type.as_numpy_dtype)) ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/keras/backend.py in call(self, inputs)ģ275 tensor_type = dtypes_module.as_dtype(tensor.dtype) ~/anaconda3/lib/python3.6/site-packages/keras/engine/training_arrays.py in fit_loop(model, fit_function, fit_inputs, out_labels, batch_size, epochs, verbose, callbacks, val_function, val_inputs, shuffle, initial_epoch, steps_per_epoch, validation_steps, validation_freq)ġ94 ins_batch = ins_batch.toarray() ~/anaconda3/lib/python3.6/site-packages/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs) ValueError Traceback (most recent call last) Please use tf.compat.v1.global_variables instead. WARNING:tensorflow:From /Users/manohar/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:422: The name tf.global_variables is deprecated. array (array, dtype =dtype, order =order, copy =copy ) 434 435 if ensure_2d : ValueError: setting an array element with a sequence.Dataset has 2708 nodes, 5429 edges, 1433 features. ![]() ~\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_array (array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator) 431 force_all_finite)Ĥ32 else : -> 433array = np. _validate_targets (y ) 151 ~\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_X_y (X, y, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, warn_on_dtype, estimator) 571 X = check_array(X, accept_sparse, dtype, order, copy, force_all_finite,ĥ72 ensure_2d, allow_nd, ensure_min_samples, -> 573 ensure_min_features, warn_on_dtype, estimator) 574 if multi_output : 575 y = check_array(y, 'csr', force_all_finite=True, ensure_2d=False, float64, order = 'C', accept_sparse = 'csr' ) 150 y = self. ![]() score (test_images ,test_labels ) ~\Anaconda3\lib\site-packages\sklearn\svm\base.py in fit (self, X, y, sample_weight) 147 self. Mais ca m'affiche cette erreur : ValueError Traceback (most recent call last) |clf.fit(train_images, train_labels.values) J'essaye des passer des parametre qui sont un tableau de label et un autre tableau de valeur de pixel : Alors en machine learning j'ai besoin de faire des test en utilisant des réseaux neuronal, j'ai utiliser le modele svm.SVC
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