Kerasでニューラルネットワークを実装中にValueErrorエラーが発生してしまいました

Question

前提・実現したいこと

Kerasでニューラルネットワークを実装中に以下のエラーが発生してしまいました。

発生している問題・エラーメッセージ

Traceback (most recent call last):
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\Projects\Repair Audio\main.py", line 45, in <module>
    model.fit(x=x_train, y=y_train, epochs=20)
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\training.py", line 1184, in fit
    tmp_logs = self.train_function(iterator)
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\eager\def_function.py", line 885, in __call__
    result = self._call(*args, **kwds)
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\eager\def_function.py", line 933, in _call
    self._initialize(args, kwds, add_initializers_to=initializers)
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\eager\def_function.py", line 759, in _initialize
    self._stateful_fn._get_concrete_function_internal_garbage_collected(  # pylint: disable=protected-access
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\eager\function.py", line 3066, in _get_concrete_function_internal_garbage_collected
    graph_function, _ = self._maybe_define_function(args, kwargs)
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\eager\function.py", line 3463, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\eager\function.py", line 3298, in _create_graph_function
    func_graph_module.func_graph_from_py_func(
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\framework\func_graph.py", line 1007, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\eager\def_function.py", line 668, in wrapped_fn
    out = weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\framework\func_graph.py", line 994, in wrapper
    raise e.ag_error_metadata.to_exception(e)
ValueError: in user code:

    C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\training.py:853 train_function  *
        return step_function(self, iterator)
    C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\training.py:842 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:1286 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:2849 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\tensorflow\python\distribute\distribute_lib.py:3632 _call_for_each_replica
        return fn(*args, **kwargs)
    C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\training.py:835 run_step  **
        outputs = model.train_step(data)
    C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\training.py:787 train_step
        y_pred = self(x, training=True)
    C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\base_layer.py:1020 __call__
        input_spec.assert_input_compatibility(self.input_spec, inputs, self.name)
    C:\Users\sukep\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\engine\input_spec.py:250 assert_input_compatibility
        raise ValueError(

    ValueError: Input 0 of layer sequential is incompatible with the layer: expected axis -1 of input shape to have value 256 but received input with shape (32, 1)

該当のソースコード

from keras.models import Sequential
from keras.layers import Dense, Activation
from pydub import AudioSegment
import numpy as np
import matplotlib.pyplot as plt
import random


BUFFER_SIZE = 256


class Audio:
    def __init__(self, filename):
        self.sound = AudioSegment.from_file(filename)
        self.samples = np.array(self.sound.get_array_of_samples())

        if self.sound.channels == 1:
            self.left = self.samples
            self.right = self.samples
        else:
            self.left = self.samples[::2]
            self.right = self.samples[1::2]
            

if __name__ == "__main__":
    wav = Audio("Alan Walker - Faded.wav")
    mp3 = Audio("Alan Walker - Faded.mp3")

    offset = random.randrange(wav.left.size - BUFFER_SIZE)
    
    if random.randint(0, 1) == 0:
        x_train = np.fft.fft(mp3.left[offset:offset + BUFFER_SIZE] / 32768)
        y_train = np.fft.fft(wav.left[offset:offset + BUFFER_SIZE] / 32768)
    else:
        x_train = np.fft.fft(mp3.right[offset:offset + BUFFER_SIZE] / 32768)
        y_train = np.fft.fft(wav.right[offset:offset + BUFFER_SIZE] / 32768)
    
    model = Sequential()
    model.add(Dense(BUFFER_SIZE, input_dim=BUFFER_SIZE))
    model.add(Activation("linear"))
    model.add(Dense(BUFFER_SIZE))
    model.add(Activation("linear"))

    model.compile(optimizer="adam", loss="mse", metrics=["accuracy"])
    model.fit(x=x_train, y=y_train, epochs=20)

補足情報（FW/ツールのバージョンなど）

IDLE Shell 3.9.7

Answer 1

下記のようにすれば、エラーは出なくなると思います
ただし、質問者さんがやりたい目的と合致してるのかは、分かりません

    model.fit(x=x_train, y=y_train, epochs=20)

↓ reshapeを追加

    x_train = x_train.reshape((1, -1))
    y_train = y_train.reshape((1, -1))
    model.fit(x=x_train, y=y_train, epochs=20)