ValueError：图形中重复的节点名称：'write_summary'，同时使用带有 keras 和 tensorboard 的自定义回调答案

【问题标题】：ValueError: Duplicate node name in graph: 'write_summary' while using custom callback with keras and tensorboardValueError：图形中重复的节点名称：'write_summary'，同时使用带有 keras 和 tensorboard 的自定义回调
【发布时间】：2020-01-20 14:44:38
【问题描述】：

我在创建自定义回调时收到Duplicate node name in graph。这是完整的代码。

import os
import datetime
import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers


class MyCallback(tf.keras.callbacks.Callback):

    def __init__(self):
        log_dir = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
        self._logdir = os.path.join('logs', log_dir)

    def on_train_begin(self, logs=None):
        self.summary_writer = tf.summary.create_file_writer(self._logdir)

    def on_epoch_end(self, epoch, logs=None):
        t = tf.reduce_sum(self.model._targets[0])
        with self.summary_writer.as_default():
            tf.summary.scalar("test", t, step=epoch)

    def on_train_end(self, logs=None):
        self.summary_writer.close()


def get_model():
    model = tf.keras.Sequential([
    # Adds a densely-connected layer with 64 units to the model:
    layers.Dense(64, activation='relu', input_shape=(32,)),
    # Add another:
    layers.Dense(64, activation='relu'),
    # Add a softmax layer with 10 output units:
    layers.Dense(10, activation='softmax')])

    model.compile(optimizer=tf.keras.optimizers.Adam(0.01),
        loss='categorical_crossentropy',
        metrics=['accuracy'])

    return model

if __name__ == '__main__':

    model = get_model()
    data = np.random.random((1000, 32))
    labels = np.random.random((1000, 10))

    model.fit(data, labels, epochs=10, batch_size=32, callbacks=[MyCallback()])

我得到的错误是。

$ python3 test.py 
2020-01-20 20:09:00.694065: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2020-01-20 20:09:00.718085: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2592000000 Hz
2020-01-20 20:09:00.718952: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x4bead60 executing computations on platform Host. Devices:
2020-01-20 20:09:00.718974: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): Host, Default Version
Train on 1000 samples
Epoch 1/10
1000/1000 [==============================] - 1s 569us/sample - loss: 45.9223 - accuracy: 0.0980
Epoch 2/10
  32/1000 [..............................] - ETA: 0s - loss: 85.0311 - accuracy: 0.0938Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 1610, in _create_c_op
    c_op = c_api.TF_FinishOperation(op_desc)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Duplicate node name in graph: 'write_summary'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "test.py", line 48, in <module>
    model.fit(data, labels, epochs=10, batch_size=32, callbacks=[MyCallback()])
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training.py", line 728, in fit
    use_multiprocessing=use_multiprocessing)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training_v2.py", line 372, in fit
    prefix='val_')
  File "/usr/lib/python3.6/contextlib.py", line 88, in __exit__
    next(self.gen)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/engine/training_v2.py", line 685, in on_epoch
    self.callbacks.on_epoch_end(epoch, epoch_logs)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/keras/callbacks.py", line 298, in on_epoch_end
    callback.on_epoch_end(epoch, logs)
  File "test.py", line 21, in on_epoch_end
    tf.summary.scalar("test", t, step=epoch)
  File "/usr/local/lib/python3.6/dist-packages/tensorboard/plugins/scalar/summary_v2.py", line 65, in scalar
    metadata=summary_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/summary_ops_v2.py", line 646, in write
    _should_record_summaries_v2(), record, _nothing, name="summary_cond")
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/smart_cond.py", line 54, in smart_cond
    return true_fn()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/summary_ops_v2.py", line 640, in record
    name=scope)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/gen_summary_ops.py", line 868, in write_summary
    summary_metadata=summary_metadata, name=name)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/op_def_library.py", line 793, in _apply_op_helper
    op_def=op_def)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/func_graph.py", line 548, in create_op
    compute_device)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 3429, in _create_op_internal
    op_def=op_def)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 1773, in __init__
    control_input_ops)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/framework/ops.py", line 1613, in _create_c_op
    raise ValueError(str(e))
ValueError: Duplicate node name in graph: 'write_summary'

python3.6 和tensorflow-2.0.0

在TensorflowSupport的评论后编辑以下实施工作。

class MyCallback(tf.keras.callbacks.TensorBoard):

    def __init__(self):
        log_dir = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
        logdir = os.path.join('logs', log_dir)
        super(MyCallback, self).__init__(logdir)


    def on_epoch_end(self, epoch, logs=None):
        super(MyCallback, self).on_epoch_end(epoch, logs)
        with self._get_writer("train").as_default():
            t = tf.reduce_sum(self.model._targets[0])
            tf.summary.scalar("test", 90, step=epoch)

以下也可以

class MyCallback(tf.keras.callbacks.TensorBoard):

    def __init__(self):
        log_dir = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
        logdir = os.path.join('logs', log_dir)
        super(MyCallback, self).__init__(logdir)


    def on_epoch_end(self, epoch, logs=None):
        super(MyCallback, self).on_epoch_end(epoch, logs)
        with self._get_writer("train").as_default():
            tf.summary.scalar("test", 90, step=epoch)

但这不起作用并引发同样的错误。

class MyCallback(tf.keras.callbacks.TensorBoard):

    def __init__(self):
        log_dir = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
        logdir = os.path.join('logs', log_dir)
        super(MyCallback, self).__init__(logdir)


    def on_epoch_end(self, epoch, logs=None):
        super(MyCallback, self).on_epoch_end(epoch, logs)
        with self._get_writer("train").as_default():
            t = tf.reduce_sum(self.model._targets[0])
            tf.summary.scalar("test", t, step=epoch)

【问题讨论】：

：在Tensorboard Callback的这个实现中，function, _set_default_writer中已经定义了默认摘要编写器。由于您还定义了摘要编写器，因此可能有 2 个具有相同名称的节点“summary_writer”，因此可能是错误的原因。甚至错误日志也传达了相同的信息。因此，您可以尝试更改实现。谢谢！
@TensorflowSupport 我尝试了其他两种方法，并相应地修改了问题，但再次出现相同的错误。

标签： python tensorflow keras tensorflow2.0

【解决方案1】：

我的理解是，如果您将 Tensor 传递给 tf.summary.scalar，则会导致错误，但如果您传递 Scalar 对它来说，它正在执行而没有任何错误。

因此，我们可以将张量转换为标量，然后将该标量传递给 tf.summary.scalar，从而成功执行。

下面提到的代码应该可以工作：

class MyCallback(tf.keras.callbacks.TensorBoard):

    def __init__(self):
        log_dir = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
        logdir = os.path.join('logs', log_dir)
        super(MyCallback, self).__init__(logdir)


    def on_epoch_end(self, epoch, logs=None):
        super(MyCallback, self).on_epoch_end(epoch, logs)
        with self._get_writer("train").as_default():
            t = tf.reduce_sum(self.model._targets[0])
            t_scalar = t.numpy() #This line will convert Tensor to a Scalar
            tf.summary.scalar("test", t_scalar, step=epoch)

【讨论】：