我正在使用数据集 API 生成训练数据,并将其分批排序到神经网络中。
以下是我的代码的最小工作示例:
代码在使用TensorFlow 1.13.1时,调用
以下是我的代码的最小工作示例:
import tensorflow as tf
import numpy as np
import random
def my_generator():
while True:
x = np.random.rand(4, 20)
y = random.randint(0, 11)
label = tf.one_hot(y, depth=12)
yield x.reshape(4, 20, 1), label
def my_input_fn():
dataset = tf.data.Dataset.from_generator(lambda: my_generator(),
output_types=(tf.float64, tf.int32))
dataset = dataset.batch(32)
iterator = dataset.make_one_shot_iterator()
batch_features, batch_labels = iterator.get_next()
return batch_features, batch_labels
if __name__ == "__main__":
tf.enable_eager_execution()
model = tf.keras.Sequential([tf.keras.layers.Flatten(input_shape=(4, 20, 1)),
tf.keras.layers.Dense(128, activation=tf.nn.relu),
tf.keras.layers.Dense(12, activation=tf.nn.softmax)])
model.compile(optimizer='adam',
loss='categorical_crossentropy',
metrics=['accuracy'])
data_generator = my_input_fn()
model.fit(data_generator)
代码在使用TensorFlow 1.13.1时,调用
model.fit()
函数失败并产生如下错误:Traceback (most recent call last):
File "scripts/min_working_example.py", line 37, in <module>
model.fit(data_generator)
File "~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py", line 880, in fit
validation_steps=validation_steps)
File "~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training_arrays.py", line 310, in model_iteration
ins_batch = slice_arrays(ins[:-1], batch_ids) + [ins[-1]]
File "~/.local/lib/python3.6/site-packages/tensorflow/python/keras/utils/generic_utils.py", line 526, in slice_arrays
return [None if x is None else x[start] for x in arrays]
File "~/.local/lib/python3.6/site-packages/tensorflow/python/keras/utils/generic_utils.py", line 526, in <listcomp>
return [None if x is None else x[start] for x in arrays]
File "~/.local/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 654, in _slice_helper
name=name)
File "~/.local/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 820, in strided_slice
shrink_axis_mask=shrink_axis_mask)
File "~/.local/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 9334, in strided_slice
_six.raise_from(_core._status_to_exception(e.code, message), None)
File "<string>", line 3, in raise_from
tensorflow.python.framework.errors_impl.InvalidArgumentError: Attr shrink_axis_mask has value 4294967295 out of range for an int32 [Op:StridedSlice] name: strided_slice/
我尝试在另一台使用TensorFlow 2.0的计算机上运行相同的代码(删除了 tf.enable_eager_execution()
这一行,因为它默认情况下会立即运行),但是出现了以下错误:
Traceback (most recent call last):
File "scripts/min_working_example.py", line 37, in <module>
model.fit(data_generator)
File "~/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 873, in fit
steps_name='steps_per_epoch')
File "~/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_arrays.py", line 352, in model_iteration
batch_outs = f(ins_batch)
File "~/.local/lib/python3.7/site-packages/tensorflow/python/keras/backend.py", line 3217, in __call__
outputs = self._graph_fn(*converted_inputs)
File "~/.local/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 558, in __call__
return self._call_flat(args)
File "~/.local/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 627, in _call_flat
outputs = self._inference_function.call(ctx, args)
File "~/.local/lib/python3.7/site-packages/tensorflow/python/eager/function.py", line 397, in call
(len(args), len(list(self.signature.input_arg))))
ValueError: Arguments and signature arguments do not match: 21 23
我尝试将model.fit()
更改为model.fit_generator()
,但是这在两个TensorFlow版本上都失败了。 在TF 1.13.1上,我会收到以下错误:
Traceback (most recent call last):
File "scripts/min_working_example.py", line 37, in <module>
model.fit_generator(data_generator)
File "~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py", line 1426, in fit_generator
initial_epoch=initial_epoch)
File "~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training_generator.py", line 115, in model_iteration
shuffle=shuffle)
File "~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training_generator.py", line 377, in convert_to_generator_like
num_samples = int(nest.flatten(data)[0].shape[0])
TypeError: __int__ returned non-int (type NoneType)
在 TF 2.0 上,我收到以下错误信息:
Traceback (most recent call last):
File "scripts/min_working_example.py", line 37, in <module>
model.fit_generator(data_generator)
File "~/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 1515, in fit_generator
steps_name='steps_per_epoch')
File "~/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_generator.py", line 140, in model_iteration
shuffle=shuffle)
File "~/.local/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_generator.py", line 477, in convert_to_generator_like
raise ValueError('You must specify `batch_size`')
ValueError: You must specify `batch_size`
然而batch_size
不是fit_generator()
的一个可识别的关键字。
我对这些错误信息感到困惑,如果有人能够解释一下或指出我的错误,我将不胜感激。
model.fit_generator(dataset, epochs=10, steps_per_epoch=30)
。 - giser_yugang