尝试编译 TensorFlow 模型时出现 ValueError

Question

我是 TensorFlow 的新手，我只是在进行一些实验。我正在尝试使用自定义层构建一个（非常）简单的模型，并使用最大似然对其进行拟合。 （我目前尝试使用该软件包的方式可能并不完全符合预期，但似乎 - 从理论上讲 - 它应该仍然有效。）

我正在尝试运行此代码：

import tensorflow as tf
from tensorflow import keras
import numpy as np
import pandas as pd

leng = 10000
realised = np.random.normal(1, 2, leng).astype(dtype="float32")
feat = np.ones(leng, dtype="float32")
df = pd.DataFrame({'x1' : feat, 'target' : realised})
target = df.pop('target')
dataset = tf.data.Dataset.from_tensor_slices((df.values, target.values))

class Gauss(keras.layers.Layer):
    def __init__(self, realised, units=32, input_dim=32):
        super(Gauss, self).__init__()
        w_init = tf.random_normal_initializer()
        self.w = tf.Variable(
            initial_value=w_init(shape=(input_dim, units), dtype="float32"),
            trainable=True,
        )
        s_init = tf.ones_initializer()
        self.s = tf.Variable(
            initial_value=s_init(shape=(units,), dtype="float32"), trainable=True
        )
        self.realised = tf.Variable(
            initial_value=realised, dtype="float32", trainable=False
        )

    def call(self, inputs):
        diff = tf.square(
            tf.subtract(
                tf.matmul(inputs, self.w), self.realised))
        pi2 = tf.constant((2*np.pi)**0.5, dtype="float32")
        return tf.divide(
            tf.math.exp(
                tf.divide(
                    -diff, tf.multiply(
                        2.0, tf.square(tf.math.log(1 + tf.math.exp(self.s)))))),
                            tf.math.log(1 + tf.math.exp(self.s))*pi2)

@tf.function()
def loss_fn(output, dummy_var):
    return -tf.reduce_sum(tf.math.log(output))

def get_compiled_model():
  model = tf.keras.Sequential([
    Gauss(tf.constant(target.values, shape=(leng, 1), dtype="float32"), 1, 1)
  ])

  model.compile(optimizer='adam',
                loss=loss_fn,
                metrics=['accuracy'])
  return model

model = get_compiled_model()
model.fit(dataset, epochs=3, batch_size=16)

但是，当我尝试编译模型时，我从最后一行收到了 ValueError。这是完整的错误：

Traceback (most recent call last):

  File "<ipython-input-28-c3a2ecd18f95>", line 59, in <module>
    model.fit(dataset, epochs=3, batch_size=16)

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py", line 108, in _method_wrapper
    return method(self, *args, **kwargs)

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py", line 1098, in fit
    tmp_logs = train_function(iterator)

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\def_function.py", line 780, in __call__
    result = self._call(*args, **kwds)

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\def_function.py", line 823, in _call
    self._initialize(args, kwds, add_initializers_to=initializers)

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\def_function.py", line 697, in _initialize
    *args, **kwds))

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\function.py", line 2855, in _get_concrete_function_internal_garbage_collected
    graph_function, _, _ = self._maybe_define_function(args, kwargs)

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\function.py", line 3213, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\function.py", line 3075, in _create_graph_function
    capture_by_value=self._capture_by_value),

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\func_graph.py", line 986, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\def_function.py", line 600, in wrapped_fn
    return weak_wrapped_fn().__wrapped__(*args, **kwds)

  File "C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\func_graph.py", line 973, in wrapper
    raise e.ag_error_metadata.to_exception(e)

ValueError: in user code:

    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py:806 train_function  *
        return step_function(self, iterator)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py:796 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:1211 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2585 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2945 _call_for_each_replica
        return fn(*args, **kwargs)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py:789 run_step  **
        outputs = model.train_step(data)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py:749 train_step
        y, y_pred, sample_weight, regularization_losses=self.losses)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\keras\engine\compile_utils.py:212 __call__
        batch_dim = array_ops.shape(y_t)[0]
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\util\dispatch.py:201 wrapper
        return target(*args, **kwargs)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py:1024 _slice_helper
        name=name)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\util\dispatch.py:201 wrapper
        return target(*args, **kwargs)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\array_ops.py:1196 strided_slice
        shrink_axis_mask=shrink_axis_mask)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\gen_array_ops.py:10352 strided_slice
        shrink_axis_mask=shrink_axis_mask, name=name)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py:744 _apply_op_helper
        attrs=attr_protos, op_def=op_def)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\func_graph.py:593 _create_op_internal
        compute_device)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py:3485 _create_op_internal
        op_def=op_def)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py:1975 __init__
        control_input_ops, op_def)
    C:\Users\FaberMR\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py:1815 _create_c_op
        raise ValueError(str(e))

    ValueError: slice index 0 of dimension 0 out of bounds. for '{{node strided_slice}} = StridedSlice[Index=DT_INT32, T=DT_INT32, begin_mask=0, ellipsis_mask=0, end_mask=0, new_axis_mask=0, shrink_axis_mask=1](Shape, strided_slice/stack, strided_slice/stack_1, strided_slice/stack_2)' with input shapes: [0], [1], [1], [1] and with computed input tensors: input[1] = <0>, input[2] = <1>, input[3] = <1>.

我正在 Windows 操作系统上工作，在 Spyder 4.1.5 中使用 Python 3.7.4。使用 TensorFlow 2.3.1。任何建议将不胜感激。