Получение ошибки при обучении модели CNN ⇐ Python

[Anonymous]

Я получаю ошибки при обучении моей модели CNN, которая предназначена для проверки того, что человек говорит на языке жестов. Я работаю с керасом, тензорным потоком.
Это мой код:

Код: Выделить всё

import tensorflow as tf  ;importing libraries
from tensorflow.keras import datasets,layers,models
import numpy as np
import matplotlib.pyplot as plt
from tensorflow.keras.preprocessing.image import ImageDataGenerator
; Data preprocessing
train_datagen = ImageDataGenerator(rescale = 1./255,
shear_range = 0.2,
zoom_range = 0.2,
horizontal_flip = True)
training_set = train_datagen.flow_from_directory('split__data/Train',
target_size = (64, 64),
batch_size = 32,
class_mode = 'categorical')
test_datagen = ImageDataGenerator(rescale = 1./255)
test_set = test_datagen.flow_from_directory('split__data/Test',
target_size = (64, 64),
batch_size = 32,
class_mode = 'categorical')

; Building the model
cnn = tf.keras.models.Sequential()
cnn.add(tf.keras.layers.Conv2D(filters = 16,kernel_size = 3,activation = 'relu',input_shape = [64,64,3]))
cnn.add(tf.keras.layers.MaxPool2D(pool_size=2,strides=2))

cnn.add(tf.keras.layers.Conv2D(filters = 32,kernel_size = 3,activation = 'relu',input_shape = [64,64,3]))
cnn.add(tf.keras.layers.MaxPool2D(pool_size=2,strides=2))

cnn.add(tf.keras.layers.Conv2D(filters = 64,kernel_size = 3,activation = 'relu',input_shape = [64,64,3]))
cnn.add(tf.keras.layers.MaxPool2D(pool_size=2,strides=2))
cnn.add(tf.keras.layers.Flatten())
cnn.add(tf.keras.layers.Dense(units=500,activation='relu'))
cnn.add(tf.keras.layers.Dense(units=1,activation='softmax'))

; compiling and training
cnn.compile(optimizer = 'adam' , loss= 'categorical_crossentropy',metrics = ['accuracy'])
;the next line is giving me error
cnn.fit(x = training_set,validation_data = test_set,batch_size = 32,epochs = 10)

Это ошибка. Я не могу понять, откуда генерируются эти ошибки. Я пробовал изменить размер пакета, высоту и ширину изображения, но ничего не происходит. Я получаю ту же ошибку.

Код: Выделить всё

---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
 in 
----> 1 cnn.fit(x = training_set,validation_data = test_set,batch_size = 32,epochs = 10)

C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
1181                 _r=1):
1182               callbacks.on_train_batch_begin(step)
-> 1183               tmp_logs = self.train_function(iterator)
1184               if data_handler.should_sync:
1185                 context.async_wait()

C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\eager\def_function.py in __call__(self, *args, **kwds)
887
888       with OptionalXlaContext(self._jit_compile):
--> 889         result = self._call(*args, **kwds)
890
891       new_tracing_count = self.experimental_get_tracing_count()

C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\eager\def_function.py in _call(self, *args, **kwds)
948         # Lifting succeeded, so variables are initialized and we can run the
949         # stateless function.
--> 950         return self._stateless_fn(*args, **kwds)
951     else:
952       _, _, _, filtered_flat_args = \

C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\eager\function.py in __call__(self, *args, **kwargs)
3021       (graph_function,
3022        filtered_flat_args) = self._maybe_define_function(args, kwargs)
-> 3023     return graph_function._call_flat(
3024         filtered_flat_args, captured_inputs=graph_function.captured_inputs)  # pylint: disable=protected-access
3025

C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\eager\function.py in _call_flat(self, args, captured_inputs, cancellation_manager)
1958         and executing_eagerly):
1959       # No tape is watching; skip to running the function.
-> 1960       return self._build_call_outputs(self._inference_function.call(
1961           ctx, args, cancellation_manager=cancellation_manager))
1962     forward_backward = self._select_forward_and_backward_functions(

C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\eager\function.py in call(self, ctx, args, cancellation_manager)
589       with _InterpolateFunctionError(self):
590         if cancellation_manager is None:
--> 591           outputs = execute.execute(
592               str(self.signature.name),
593               num_outputs=self._num_outputs,

C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\eager\execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
57   try:
58     ctx.ensure_initialized()
---> 59     tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
60                                         inputs, attrs, num_outputs)
61   except core._NotOkStatusException as e:

InvalidArgumentError:  In[0] mismatch In[1] shape: 35 vs. 1: [32,35] [500,1] 0 0
[[node gradient_tape/sequential/dense_1/MatMul (defined at :1) ]] [Op:__inference_train_function_847]

Function call stack:
train_function

может кто-нибудь помочь?

Подробнее здесь: https://stackoverflow.com/questions/699 ... -cnn-model