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- def Generate():
- i = 0
- while 1:
- i = i%int(Numb/batch_size)
- my_input_batch = my_input[i*batch_size : (i+1)*batch_size]
- my_output_batch = my_output[i*batch_size : (i+1)*batch_size]
- encoder_input_data = np.array(np.zeros((batch_size, max_encoder_text_length, num_dictonary),dtype='float32'))
- decoder_input_data = np.array(np.zeros((batch_size, max_decoder_text_length, num_dictonary),dtype='float32'))
- decoder_target_data = np.array(np.zeros((batch_size, max_decoder_text_length, num_dictonary),dtype='float32'))
- for i, (text_input, text_output) in enumerate(zip(my_input_batch, my_output_batch)):
- for t, word in enumerate(my_input_batch):
- encoder_input_data[i, t, word] = 1.
- for t, word in enumerate(my_output_batch):
- decoder_input_data[i, t, word] = 1.
- if t > 0:
- decoder_target_data[i, t - 1, word] = 1.
- i = i + 1
- yield ({encoder_input_data, decoder_input_data}, {decoder_target_data})
- File "test.py", line 146, in Generate
- yield ({encoder_input_data, decoder_input_data}, {decoder_target_data})
- TypeError: unhashable type: 'numpy.ndarray'
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