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- encoder_inputs = Input(shape=(summaries.shape[1], ), name='Encoder-Input')
- inc_emb = Embedding(nb_words, embedding_dim, weights=[word_embedding_matrix],
- mask_zero=False, name='Body-Word-Embedding')(encoder_inputs)
- x = BatchNormalization(name='Encoder-Batchnorm-1')(inc_emb)
- _, state_h = GRU(embedding_dim, return_state=True, name='Encoder-Last-GRU')(x)
- encoder_model = Model(inputs=encoder_inputs, outputs=state_h,
- name='Encoder-Model')
- seq2seq_encoder_out = encoder_model(encoder_inputs)
- decoder_inputs = Input(shape=(None,), name="Decoder-Input")
- dec_emb = Embedding(nb_words, embedding_dim, mask_zero=False,
- weights=[word_embedding_matrix],
- name="Decoder-Word-Embedding")(decoder_inputs)
- dec_bn = BatchNormalization(name='Decoder-Batchnorm-1')(dec_emb)
- decoder_gru = GRU(embedding_dim, return_state=True, return_sequences=True,
- name="Decoder-GRU")
- decoder_gru_output, _ = decoder_gru(dec_bn, initial_state=seq2seq_encoder_out)
- x = BatchNormalization(name='Decoder-Batchnorm-2')(decoder_gru_output)
- decoder_dense = Dense(nb_words, activation='softmax', name='Final-Output-Dense')
- decoder_outputs = decoder_dense(x)
- ResourceExhaustedError: OOM when allocating tensor with shape[190000,59301] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
- [[Node: Final-Output-Dense/MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/device:GPU:0"](Final-Output-Dense/Reshape, Final-Output-Dense/Reshape_1)]]
- Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
- [[Node: loss/mul/_271 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_4239_loss/mul", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
- Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
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