Привет, Keras ошибка?

Question

[The-TS]

Код:

import numpy
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten, BatchNormalization, Activation
from keras.layers.convolutional import Conv2D, MaxPooling2D
from keras.constraints import maxnorm
from keras.utils import np_utils
from keras.datasets import cifar10

# Set random seed for purposes of reproducibility
seed = 21

# loading in the data
(X_train, y_train), (X_test, y_test) = cifar10.load_data()

# normalize the inputs from 0-255 to between 0 and 1 by dividing by 255
X_train = X_train.astype('float32')
X_test = X_test.astype('float32')
X_train = X_train / 255.0
X_test = X_test / 255.0

# one hot encode outputs
y_train = np_utils.to_categorical(y_train)
y_test = np_utils.to_categorical(y_test)
class_num = y_test.shape[1]

model = Sequential()
model.add(Conv2D(32, (3, 3), input_shape=(3, 32, 32), activation='relu', padding='same'))
model.add(Dropout(0.2))
model.add(BatchNormalization())

model.add(Conv2D(64, (3, 3), padding='same'))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.2))
model.add(BatchNormalization())

model.add(Conv2D(128, (3, 3), padding='same'))
model.add(Activation('relu'))
model.add(Dropout(0.2))
model.add(BatchNormalization())

model.add(Flatten())
model.add(Dropout(0.2))

model.add(Dense(256, kernel_constraint=maxnorm(3)))
model.add(Activation('relu'))
model.add(Dropout(0.2))
model.add(BatchNormalization())
model.add(Dense(128, kernel_constraint=maxnorm(3)))
model.add(Activation('relu'))
model.add(Dropout(0.2))
model.add(BatchNormalization())

model.add(Dense(class_num))
model.add(Activation('softmax'))

epochs = 25
optimizer = 'adam'
model.compile(loss='categorical_crossentropy', optimizer=optimizer, metrics=['accuracy'])

numpy.random.seed(seed)
model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=epochs, batch_size=64)

print(model.summary())

Ошибка:

2020-11-22 08:10:53.567298: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory
2020-11-22 08:10:53.567365: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2020-11-22 08:11:13.784870: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcuda.so.1
2020-11-22 08:11:14.631460: E tensorflow/stream_executor/cuda/cuda_driver.cc:314] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected
2020-11-22 08:11:14.631523: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (MyNameIsTS): /proc/driver/nvidia/version does not exist
2020-11-22 08:11:14.632226: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2020-11-22 08:11:14.644377: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 1996420000 Hz
2020-11-22 08:11:14.644827: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x562252ec6a40 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-11-22 08:11:14.644898: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2020-11-22 08:11:15.825281: W tensorflow/core/framework/cpu_allocator_impl.cc:81] Allocation of 614400000 exceeds 10% of free system memory.
Epoch 1/25
Traceback (most recent call last):
  File "API_TS.py", line 62, in <module>
    model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=epochs, batch_size=32)
  File "/home/ts/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 108, in _method_wrapper
    return method(self, *args, **kwargs)
  File "/home/ts/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1098, in fit
    tmp_logs = train_function(iterator)
  File "/home/ts/.local/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 780, in __call__
    result = self._call(*args, **kwds)
  File "/home/ts/.local/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 823, in _call
    self._initialize(args, kwds, add_initializers_to=initializers)
  File "/home/ts/.local/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 696, in _initialize
    self._stateful_fn._get_concrete_function_internal_garbage_collected(  # pylint: disable=protected-access
  File "/home/ts/.local/lib/python3.8/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 "/home/ts/.local/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3213, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "/home/ts/.local/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3065, in _create_graph_function
    func_graph_module.func_graph_from_py_func(
  File "/home/ts/.local/lib/python3.8/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 "/home/ts/.local/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 600, in wrapped_fn
    return weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "/home/ts/.local/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 973, in wrapper
    raise e.ag_error_metadata.to_exception(e)
ValueError: in user code:

    /home/ts/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:806 train_function  *
        return step_function(self, iterator)
    /home/ts/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:796 step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    /home/ts/.local/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:1211 run
        return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
    /home/ts/.local/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:2585 call_for_each_replica
        return self._call_for_each_replica(fn, args, kwargs)
    /home/ts/.local/lib/python3.8/site-packages/tensorflow/python/distribute/distribute_lib.py:2945 _call_for_each_replica
        return fn(*args, **kwargs)
    /home/ts/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:789 run_step  **
        outputs = model.train_step(data)
    /home/ts/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py:747 train_step
        y_pred = self(x, training=True)
    /home/ts/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py:975 __call__
        input_spec.assert_input_compatibility(self.input_spec, inputs,
    /home/ts/.local/lib/python3.8/site-packages/tensorflow/python/keras/engine/input_spec.py:212 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 32 but received input with shape [None, 32, 32, 3]

Привет, Как исправить?
Спасибо!

Comments

[Andrey Dugin]

Читайте сообщение об ошибке, там всё написано.

[The-TS]

Andrey Dugin, Можно подробнее?

[Andrey Dugin]

secret secretom, можно:
1. Найдите сообщение об ошибке.
2. Начните читать его построчно.
3. Когда дойдёте до строки, объясняющей, что именно произошло, постарайтесь понять и устранить причину.
4. В случае необходимости воспользуйтесь Google Translate.

[The-TS]

Andrey Dugin,

ValueError: Input 0 of layer sequential is incompatible with the layer: expected axis -1 of input shape to have value 32 but received input with shape [None, 32, 32, 3]

?