如何在Python中的tensorflow.fit中解決此問題？

你能告訴我這段代碼有什么問題嗎？代碼的最后一行意思是

history = model.fit(partial_x_train, partial_y_train, epochs=20, batch_size=512, validation_data=(x_val, y_val))

有問題，但我不明白問題出在哪里

from tensorflow.keras.datasets import imdb
from tensorflow.keras import models
from tensorflow.keras import layers
from keras import optimizers
from keras import losses
from keras import metrics
import matplotlib.pyplot as plt
import numpy as np

(train_data, train_labels), (test_data,test_labels) = imdb.load_data(num_words=10000)

def vectorsize_sequeces(sequences, dimension=10000):
  results = np.zeros((len(sequences), dimension))
  for i, sequences in enumerate(sequences):
    results[i, sequences] = 1.
  return results

x_train = vectorsize_sequeces(train_data)
x_test = vectorsize_sequeces(test_data)

y_train = np.asarray(train_labels).astype('float32') 
y_test = np.asarray(test_labels).astype('float32')

model = models.Sequential()
model.add(layers.Dense(16,activation='relu',input_shape=(10000,)))
model.add(layers.Dense(16,activation='relu'))
model.add(layers.Dense(1,activation='sigmoid'))

model.compile(optimizer='rmsprop',loss='binary_crossentopy',metrics=['accuracy'])

x_val = x_train[:10000]
partial_x_train = x_train[10000:]
y_val = y_train[:10000]
partial_y_train = y_train[10000:]

history = model.fit(partial_x_train, partial_y_train, epochs=20, batch_size=512, validation_data=(x_val, y_val))

我們的錯誤

Epoch 1/20
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-23-be6266211430> in <module>()
----> 1 history = model.fit(partial_x_train, partial_y_train, epochs=20, batch_size=512, validation_data=(x_val, y_val))

1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py in autograph_handler(*args, **kwargs)
   1127           except Exception as e:  # pylint:disable=broad-except
   1128             if hasattr(e, "ag_error_metadata"):
-> 1129               raise e.ag_error_metadata.to_exception(e)
   1130             else:
   1131               raise

ValueError: in user code:

    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 878, in train_function  *
        return step_function(self, iterator)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 867, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 860, in run_step  **
        outputs = model.train_step(data)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 810, in train_step
        y, y_pred, sample_weight, regularization_losses=self.losses)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/compile_utils.py", line 184, in __call__
        self.build(y_pred)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/compile_utils.py", line 133, in build
        self._losses = tf.nest.map_structure(self._get_loss_object, self._losses)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/compile_utils.py", line 273, in _get_loss_object
        loss = losses_mod.get(loss)
    File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 2134, in get
        return deserialize(identifier)
    File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 2093, in deserialize
        printable_module_name='loss function')
    File "/usr/local/lib/python3.7/dist-packages/keras/utils/generic_utils.py", line 709, in deserialize_keras_object
        f'Unknown {printable_module_name}: {object_name}. Please ensure '

    ValueError: Unknown loss function: binary_crossentopy. Please ensure this object is passed to the `custom_objects` argument. See https://www.tensorflow.org/guide/keras/save_and_serialize#registering_the_custom_object for details.

uj5u.com熱心網友回復：

拼寫錯誤

二元交叉熵

你寫了：

二元交叉熵

用這個：

model.compile(optimizer='rmsprop',loss='binary_crossentropy',metrics=['accuracy'])

tf.keras.metrics.binary_crossentropy

標籤：Python 张量流 谷歌合作实验室

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