당신은 주제를 찾고 있습니까 “runtimeerror attempting to capture an eagertensor without building a function. – Attempting to capture an EagerTensor without building a function“? 다음 카테고리의 웹사이트 https://ppa.charoenmotorcycles.com 에서 귀하의 모든 질문에 답변해 드립니다: https://ppa.charoenmotorcycles.com/blog. 바로 아래에서 답을 찾을 수 있습니다. 작성자 Techie Risith 이(가) 작성한 기사에는 조회수 2,634회 및 좋아요 11개 개의 좋아요가 있습니다.
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Attempting to capture an EagerTensor without building a function,
Runtime Attempting to capture an EagerTensor without building a function.
Code:
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
tf.__version__
hello=tf.constant(\”Hello\”)
hello
world=tf.constant(\”World\”)
world
type(hello)
print(hello)
#tf.compat.v1.disable_eager_execution()
with tf.Session() as sess:
print(sess.run(hello+world))
runtimeerror attempting to capture an eagertensor without building a function. 주제에 대한 자세한 내용은 여기를 참조하세요.
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주제와 관련된 이미지 runtimeerror attempting to capture an eagertensor without building a function.
주제와 관련된 더 많은 사진을 참조하십시오 Attempting to capture an EagerTensor without building a function. 댓글에서 더 많은 관련 이미지를 보거나 필요한 경우 더 많은 관련 기사를 볼 수 있습니다.
주제에 대한 기사 평가 runtimeerror attempting to capture an eagertensor without building a function.
- Author: Techie Risith
- Views: 조회수 2,634회
- Likes: 좋아요 11개
- Date Published: 2019. 11. 24.
- Video Url link: https://www.youtube.com/watch?v=NmKMQZ443b0
RuntimeError: Attempting to capture an EagerTensor without building a function
I use tf.data.datset API and use residual network. When I run code for TensorBoard for visualizing my embeddings I have this error, but when I use a two layers network I don’t have this problem.
def load_and_preprocess_from_path_label(path, label): return load_and_preprocess_image(path), label ds = tf.data.Dataset.from_tensor_slices((all_image_paths, all_image_labels)) with tf.Session() as sess: # TODO (@omoindrot): remove the hard-coded 10000 # Obtain the test labels image_label_ds = ds.map(load_and_preprocess_from_path_label) ds = image_label_ds.shuffle(image_count)
in Eagermode: RuntimeError: Attempting to captu…anycodings
I am following this tutorial:
https://cloud.google.com/architecture/clv-prediction-with-offline-training-train#introduction
and replicate it in Google Colab and anycodings_eager-execution TensorFlow 2 (see a copy of my code you can anycodings_eager-execution edit below, the DNN starts in cell 12, I anycodings_eager-execution excluded an other model and other stuff not anycodings_eager-execution needed. Just run everything):
https://colab.research.google.com/drive/1LmrgvmR6PZYu25OUzFGY49VQ19PbuFLa?usp=sharing
(All 3 datasets should be uploaded anycodings_eager-execution automatically from my anycodings_eager-execution GitHub: https://github.com/timmy-ops/DNNs_for_CLVs)
I also made the model work, but it was quite anycodings_eager-execution bad. While trying to improve it and build in anycodings_eager-execution the tf.data input pipeline of the tutorial:
def parse_csv(csv_row): “””Parse CSV data row. tf.data.Dataset.map takes a function as an input so need to call parse_fn using map(lamba x: parse_fn(x)) or do def parse_fn and return the function as we do here. Builds a pair (feature dictionary, label) tensor for each example. Args: csv_row: one example as a csv row coming from the Dataset.map() Returns: features and targets “”” columns = tf.decode_csv(csv_row, record_defaults=clvf.get_all_defaults()) features = dict(zip(clvf.get_all_names(), columns)) # Remove the headers that we don’t use for column_name in clvf.get_unused(): features.pop(column_name) target = features.pop(clvf.get_target_name()) return features, target def dataset_input_fn(data_folder, prefix=None, mode=None, params=None, count=None): “””Creates a dataset reading example from filenames. Args: data_folder: Location of the files finishing with a ‘/’ prefix: Start of the file names mode: tf.estimator.ModeKeys(TRAIN, EVAL) params: hyperparameters Returns: features and targets “”” shuffle = True if mode == tf.estimator.ModeKeys.TRAIN else False # Read CSV files into a Dataset filenames = tf.matching_files(‘{}{}*.csv’.format(data_folder, prefix)) dataset = tf.data.TextLineDataset(filenames) # Parse the record into tensors. dataset = dataset.map(parse_csv) # Shuffle the dataset if shuffle: dataset = dataset.shuffle(buffer_size=params.buffer_size) # Repeat the input indefinitely if count is None dataset = dataset.repeat(count=count) # Generate batches dataset = dataset.batch(params.batch_size) # Create a one-shot iterator iterator = dataset.make_one_shot_iterator() # Get batch X and y features, target = iterator.get_next() return features, target def read_train(data_folder, params): “””Returns a shuffled dataset for training.””” return dataset_input_fn( data_folder=data_folder, prefix=’train’, params=params, mode=tf.estimator.ModeKeys.TRAIN) def read_eval(data_folder, params): “””Returns a dataset for evaluation.””” return dataset_input_fn(data_folder=data_folder, prefix=’eval’, params=params) def read_test(data_folder, params): “””Returns a dataset for test.””” return dataset_input_fn(data_folder=data_folder, prefix=’test’, params=params, count=1)
the following Error occurs:
RuntimeError Traceback (most recent call last) /usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/ops.py in convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, dtype_hint, ctx, accepted_result_types) 1523 graph = get_default_graph() 1524 if not graph.building_function: -> 1525 raise RuntimeError(“Attempting to capture an EagerTensor without ” 1526 “building a function.”) 1527 return graph.capture(value, name=name) RuntimeError: Attempting to capture an EagerTensor without building a function.
I already tried to enable eager execution or anycodings_eager-execution switch to TF1, but it did not work. What am anycodings_eager-execution I doing wrong?
Do I have to do anything with @tf.function? anycodings_eager-execution How ould that work?
[Fixed] Attempting to capture an EagerTensor without building a function.
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LSTM don’t work with RuntimeError: Attempting to capture an EagerTensor without building a function, but GRU work · Issue #42515 · tensorflow/tensorflow
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Elmo Embedding model for TensorFlow 2
I am trying to use Elmo Embedding model Using TensorFlow 2
# Imported Elmo Layer elmo_model_path = “https://tfhub.dev/google/elmo/3” elmo_layer = hub.KerasLayer(elmo_model_path, input_shape=[], dtype=tf.string, trainable=False) model = tf.keras.Sequential([ elmo_layer, tf.keras.layers.Dense(8, activation=’sigmoid’), tf.keras.layers.Dense(1, activation=’sigmoid’) ]) # Setting hyperparameter optimizer = tf.keras.optimizers.Adam(learning_rate=0.01) model.compile(loss=’binary_crossentropy’,optimizer=optimizer,metrics=[‘accuracy’]) # Model Summary model.summary() #Data data = [‘our deeds reason earthquake may allah forgive us’, ‘forest fire near la ronge sask canada’, ‘all residents asked shelter place notified officers no evacuation shelter place orders expected’, ‘ people receive wildfires evacuation orders california’, ‘just got sent photo ruby alaska smoke wildfires pours school’, ‘rockyfire update california hwy closed directions due lake county fire cafire wildfires’, ‘flood disaster heavy rain causes flash flooding streets manitou colorado springs areas’, ‘im top hill i can see fire woods’, ‘theres emergency evacuation happening now building across street’, ‘im afraid tornado coming area’, ‘three people died heat wave far’] [‘our deeds reason earthquake may allah forgive us’, ‘forest fire near la ronge sask canada’, ‘all residents asked shelter place notified officers no evacuation shelter place orders expected’, ‘ people receive wildfires evacuation orders california’, ‘just got sent photo ruby alaska smoke wildfires pours school’] label = [‘1’, ‘1’, ‘1’, ‘1’, ‘1’] #converting the labels to int value label = list(map(np.int64, label)) #Creating Training Dataset training_data = tf.data.Dataset.from_tensor_slices((data,label)).prefetch(1) print(type(training_data)) print(training_data) # Training num_epochs = 5 history = model.fit(training_data.shuffle(10000).batch(2), epochs=num_epochs, verbose=2)
Error
python – 运行时错误 : Attempting to capture an EagerTensor without building a function – 探索字符串
我用 tf.data.datset API 并使用残差网络。当我为 TensorBoard 运行代码以可视化我的嵌入时，我遇到了这个错误，但是当我使用两层网络时，我没有这个问题。
def load_and_preprocess_from_path_label(path, label): return load_and_preprocess_image(path), label ds = tf.data.Dataset.from_tensor_slices((all_image_paths, all_image_labels)) with tf.Session() as sess: # TODO (@omoindrot): remove the hard-coded 10000 # Obtain the test labels image_label_ds = ds.map(load_and_preprocess_from_path_label) ds = image_label_ds.shuffle(image_count)
키워드에 대한 정보 runtimeerror attempting to capture an eagertensor without building a function.
다음은 Bing에서 runtimeerror attempting to capture an eagertensor without building a function. 주제에 대한 검색 결과입니다. 필요한 경우 더 읽을 수 있습니다.
이 기사는 인터넷의 다양한 출처에서 편집되었습니다. 이 기사가 유용했기를 바랍니다. 이 기사가 유용하다고 생각되면 공유하십시오. 매우 감사합니다!
사람들이 주제에 대해 자주 검색하는 키워드 Attempting to capture an EagerTensor without building a function
- Attempting to capture an EagerTensor without building a function
Attempting #to #capture #an #EagerTensor #without #building #a #function
YouTube에서 runtimeerror attempting to capture an eagertensor without building a function. 주제의 다른 동영상 보기
주제에 대한 기사를 시청해 주셔서 감사합니다 Attempting to capture an EagerTensor without building a function | runtimeerror attempting to capture an eagertensor without building a function., 이 기사가 유용하다고 생각되면 공유하십시오, 매우 감사합니다.
