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This issue has been automatically marked as stale because it has not had recent activity. ImageCleaner now works with the solution above. Will experimental_distribute_dataset or experimental_distribute_datasets_from_function distribute same data in more than one batch ? Reload to refresh your session. 'Tensor' object has no attribute '_keras_shape'. AttributeError: 'KerasTensor' object has no attribute 'numpy' I use the eager execution. 2 You can access the layers via weights of the Hub model. nn.add(layers.Dense(10, activation='softmax')), nn.compile(optimizer='rmsprop', Is your model a keras one or tf.keras one? Closing as stale. 196 self._batch_payloads = tuple(b.payload for b in batch) privacy statement. Get values of KerasTensor - General Discussion - TensorFlow Forum For instance, if a, b and c are Keras tensors, it becomes possible to do: model = Model (input= [a, b], output=c) So technically it doesn't have any value. When I get to the Cleaning Up section in the lesson the cell fails to run and gives me a AttributeError: Tensor object has no attribute ndim. 34 I was using Sequential model. Next, I am trying to save both the model in SavedModel format using the model.save() API. After saving the models, I want to apply post-training float16 quantization. AttributeError: 'Tensor' object has no attribute 'node' We read every piece of feedback, and take your input very seriously. I had a similar issue when I changed my computer with a different tensorflow version. ax[idx].imshow(image, cmap=plt.cm.Greys) AttributeError: 'KerasTensor' object has no attribute 'numpy'. I am facing the same issue. 175 I am building models based on tensorflow probability layers, and in the newest version, they suddenly stopped providing layers shape. The error is AttributeError: 'UserRegisteredTypeKerasTensor' object has no attribute 'input_shape'. Usually, for any keras layer, you can ask their input and output shape, but at least for MultivariateNormalTriL and KLDivergenceAddLoss, it fails. I provided a minimum example in this colab. I am trying to append a dictionary to a DataFrame object, but I get the following error: AttributeError: 'DataFrame' object has no attribute 'append'. The topic is not straightforwardly mentioned in the TF-docs unfortunately. KerasTensor object has no attribute 'graph'. can anyone help with this? Currently we don't support tensorflow 2.4.0, is it possible you downgrade to tf 2.3.0? To see all available qualifiers, see our documentation. I am sorry, actually using tf.shape(distr_layer), it works, I replied too soon without noticing I had to remove the .shape part. Layers in KerasLayer object When I get to the 'Cleaning Up' section in the lesson the cell fails to run and gives me a AttributeError: 'Tensor' object has no attribute 'ndim'. KerasAttributeError: 'Tensor' object has no attribute - Qiita 369 try: return int(o), AttributeError: Tensor object has no attribute ndim, I had the same problem, using Azure VMs. This is because the ".numpy ()" method is only available for tensors that are stored on the CPU and not on the GPU. On mac M1 only TF 2.4. is available from Apple. Error "'DataFrame' object has no attribute 'append'" I am currently looking into it. from keras import layers, nn = models.Sequential() 365 Try to convert o to int, default to o if not possible. I need this to access and check the outputs of some layers of my sequential model. AttributeError: 'KerasTensor' object has no attribute 'numpy' and if i feed the scalar directly to the Discretization function without using .numpy (), i get the following error :. Does anyone know how to resolve the issue? @cserpell and @ahoereth, did you find a solution? 194 if self.before_next_batch and hasattr(self, _batch_payloads): self.before_next_batch(self._batch_payloads) Unfortunately, it uninstalled the fastai library, so I had to reinstall that in the end with conda install fastai -c fastai. Keras "AttributeError: 'Tensor' object has no attribute '_keras_history' " KerasLayer Layerattribute keras.layers (DenseActivation)Layer Well occasionally send you account related emails. 'Tensor' object has no attribute '_keras_shape' #97 - GitHub Using tf.GradientTape as a part of Keras functional model construction is unsupported, and we have no plans on the roadmap to add support for it at this point in time. We read every piece of feedback, and take your input very seriously. Previously the probability layers acted the same as core tensorflow layers. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. The Azure VMs use the fastai environment for the course, so thats the one to upgrade. AttributeError: 'KerasTensor' object has no attribute 'node' You can add the following line: torch.Tensor.ndim = property(lambda x: len(x.size())), Powered by Discourse, best viewed with JavaScript enabled, SOLVED - ImageCleaner causes AttributeError: Tensor object has no attribute ndim. ----> 8 onnx_model = onnxmltools.convert_keras(nn) print(test_labels.shape), fig, ax = plt.subplots(1, n, figsize=(10, 2)) Is there a work around for this . You signed in with another tab or window. Setup import tensorflow as tf import keras from keras import layers import numpy as np Introduction Keras provides default training and evaluation loops, fit () and evaluate () . 7 mode.save() API raises AttributeError: 'Tensor' object has no attribute ax[idx].set_xticks([]) privacy statement. AttributeError: 'KerasTensor' object has no attribute '_keras_shape' 31 By clicking Sign up for GitHub, you agree to our terms of service and It gives an error: ax[idx].set_title(train_labels[idx], fontsize=18), train_images = train_images.reshape((60000, 28 * 28)), train_images = train_images.astype('float32') / 255, test_images = test_images.reshape((10000, 28 * 28)) Their usage is covered in the guide Training & evaluation with the built-in methods. > 195 batch = tuple(islice(self._all_images, self.batch_size)) Please find the gist of it here. By clicking Sign up for GitHub, you agree to our terms of service and UPDATE: I got pytorch 1.3.1 to work by doing this Contributor Ive tried making sure that I am in a notebook and not a lab. Keras: AttributeError: 'int' object has no attribute 'lower' First, I removed and reinstalled the fastai library using conda to make sure I had all the latest packages. to your account. It seems that moving to tensorflow 2.4.0 broke some things in tensorflow probability. 197 self.render(batch). AttributeError Traceback (most recent call last) Another temporary solution Thanks! Writing a training loop from scratch | TensorFlow Core https://github.com/tensorflow/tensorflow/blob/30b95925a42d0dcf6a387c51b1128012d8ae092c/tensorflow/python/keras/engine/keras_tensor.py#L475. 368 if isinstance(o, collections.Sized) or getattr(o,array_interface,False): return o I was using a custom layer that includes both standard TF layers (dense) as well as math operations on tensors (+, -, tf.exp, ). 306 output_dict.update(extract_outputs_from_inbound_nodes(model)), AttributeError: 'KerasTensor' object has no attribute 'graph', (train_images, train_labels), (test_images, test_labels) = mnist.load_data() Please reopen if you'd like to work on this further. Reload to refresh your session. 214 def make_payload(self, idx:int): return {file_path: self._dataset.x.items[idx]}, /opt/conda/envs/fastai/lib/python3.6/site-packages/fastai/widgets/image_cleaner.py in next_batch(self, _) @thondeboers solution worked like a charm. 3 # runtime state including all local variables will be lost. TensorFlow 2.0 , but sadly keras contrib has conflicts with tensor flow 2.0 due to this "y_pred does not have _keras_history". Try: 121 else: return self.new(self.items[idxs], inner_df=index_row(self.inner_df, idxs)), /opt/conda/envs/fastai/lib/python3.6/site-packages/fastai/torch_core.py in try_int(o) to your account. 305 output_names.extend([n.name for n in model.outputs]) metrics=['accuracy']), nn.fit(train_images, train_labels, epochs=5, batch_size=128), test_loss, test_accuracy = nn.evaluate(test_images, test_labels), onnx_model = onnxmltools.convert_keras(nn), onnxmltools.utils.save_model(onnx_model, 'keras_example.onnx'). The problem lied in the fact that using every tf operation should be encapsulated by either: Designated keras functions with the same behavior. Thanks a lot. To see all available qualifiers, see our documentation. Good temporary solution. You switched accounts on another tab or window. 302 return extract_outputs_from_subclassing_model(model, output_dict, input_names, output_names) 303 else: Also a newbie to the forum so I hope I am putting up appropriate information. Oh yes, you can see which version of pytorch you have by importing it (generally, indirectly with from fastai.vision import *), and evaluating torch.version. You switched accounts on another tab or window. You switched accounts on another tab or window. What solved it for me was using .shape instead of ._keras_shape. #1500. There are various reasons why you are encountering this error: This error message occurs if you are trying to convert a tensor object to a NumPy array using the ".numpy ()" method. Thanks! First, I want to say thank you to everyone who responded on this thread and helped out! Apparently, Python/Jupyter maintain many environments, which bind you to a set of package versions. I have Python code I tried to convert it to ONNX with this: from tensorflow.keras.models import load_model import onnx import keras2onnx import tensorflow as tf onnx_model_name = 'name.onnx' model = load_model ('name.keras') onnx_model = keras2onnx.convert_keras (model, model.name) onnx.save_model (onnx_model, onnx_model_name) but it gave the error 193 Fetches a next batch of images for rendering. KerasTensor object has no attribute 'graph' Issue #662 - GitHub The TF 2.2.0, while iterating over layers, runs the following piece of code: This was the source of this error. 213 You switched accounts on another tab or window. When you are using tf operation - you are getting tf tensor object which doesn't have history field. Already on GitHub? Have a question about this project? To see all available qualifiers, see our documentation. again, i am stuck to .numpy() problem - Google Groups Does this mean I need to compile pytorch from source myself to support GPU? I'm getting the below error: Describe the expected behavior mode.save() API raises AttributeError: 'Tensor' object has no attribute '_keras_mask', Reshape layer drops mask from previous layers, AttributeError: 'Tensor' object has no attribute '_keras_mask' TF 2.7. Refer to this , revise the code . > 212 self.next_batch() The symbol version is preceded and followed by two underscore characters. Pre-trained models and datasets built by Google and the community In Tensorflow 1. x we have to manually set this parameter but in Tensorflow 2.0 it is by default True. Python 3.7.7 There probably is a better way to do everything without having to uninstall fastai, reinstall it, then reinstall it again at the end, but I was just trying to find a solution and move on. 118 returns a single item based if idxs is an integer or a new ItemList object if idxs is a range. When I run: uff_model = uff.from_tensorflow(Ava_SSL_GAN_NCHW, ["Discriminator/Softmax"]) I get the . Environment (please complete the following information): My model is simply the official torchvision mobilenetv2, what's the problem here? raises AttributeError: 'UserRegisteredTypeKerasTensor' object has no attribute 'input_shape', same as when trying output_shape. The model trains successfully using the teacher-forcing technique. conda -n fastai update pytorch # or maybe just torch tensorflow 2.4.0 loss='categorical_crossentropy', > 367 if isinstance(o, (np.ndarray,Tensor)): return o if o.ndim else int(o) Sign in Sign up for a free GitHub account to open an issue and contact its maintainers and the community. I am on Gradient on the GPU free tier. I think this issue is related. privacy statement. print(test_images.shape) Sign in Returns whether x is a Keras tensor. 2 Answers Sorted by: 1 I had provided an argument to the flatten layer when I shouldn't have. compute gradient error: 'KerasTensor' object has no attribute '_id I pasted it below. No. I'm using LSTM in both the encoder and decoder architecture. The text was updated successfully, but these errors were encountered: Thanks for reporting! As far as I know, DataFrame does have the method "append". 10 onnxmltools.utils.save_model(onnx_model, 'keras_example.onnx'), \python\python37\lib\site-packages\onnxmltools\convert\main.py in convert_keras(model, name, initial_types, doc_string, target_opset, targeted_onnx, channel_first_inputs, custom_conversion_functions, custom_shape_calculators, default_batch_size)