Description
i am getting the error after this code
def simple_model(input_shape, output_sequence_length, english_vocab_size, french_vocab_size):
"""
Build and train a basic RNN on x and y
:param input_shape: Tuple of input shape
:param output_sequence_length: Length of output sequence
:param english_vocab_size: Number of unique English words in the dataset
:param french_vocab_size: Number of unique French words in the dataset
:return: Keras model built, but not trained
"""
# TODO: Build the layers
learning_rate = 1e-3
input_seq = Input(input_shape[1:])
rnn = GRU(64, return_sequences = True)(input_seq)
logits = TimeDistributed(Dense(french_vocab_size))(rnn)
model = Model(input_seq, Activation('softmax')(logits))
model.compile(loss = sparse_categorical_crossentropy,
optimizer = Adam(learning_rate),
metrics = ['accuracy'])
return model
tests.test_simple_model(simple_model)
Reshaping the input to work with a basic RNN
tmp_x = pad(preproc_english_sentences, max_french_sequence_length)
tmp_x = tmp_x.reshape((-1, preproc_french_sentences.shape[-2], 1))
Train the neural network
simple_rnn_model = simple_model(
tmp_x.shape,
max_french_sequence_length,
english_vocab_size,
french_vocab_size)
simple_rnn_model.fit(tmp_x, preproc_french_sentences, batch_size=1024, epochs=10, validation_split=0.2)
Print prediction(s)
print(logits_to_text(simple_rnn_model.predict(tmp_x[:1])[0], french_tokenizer))
i am getting assertion error of not using the sparse cross entropy function ....using tensorflow 2.1.0 and python 3.6