'strided_slice_19' (op: 'StridedSlice') with input shapes - python-3.x

Question

I tried to use keras.preprocessing.image.ImageDataGenerator on TPU,but i get this error from the first epoch.the same code work with jupyter notebook but take hours for trainig.
My MODEL:
model = Sequential()
model.add(Conv2D(32, (3, 3), input_shape=input_shape))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(32, (3, 3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(64, (3, 3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Flatten())
model.add(Dense(220))
model.add(Activation('relu'))
model.add(Dropout(0.4))
model.add(Dense(120))
model.add(Activation('softmax'))
Optimizer
opt = tf.train.AdamOptimizer(learning_rate)
model.compile(
optimizer=opt,
loss='categorical_crossentropy',
metrics=['acc'])
Convert Keras to TPU
try:
device_name = os.environ['COLAB_TPU_ADDR']
TPU_ADDRESS = 'grpc://' + device_name
print('Found TPU at: {}'.format(TPU_ADDRESS))
except KeyError:
print('TPU not found')
tpu_model = tf.contrib.tpu.keras_to_tpu_model(
model,
strategy=tf.contrib.tpu.TPUDistributionStrategy(
tf.contrib.cluster_resolver.TPUClusterResolver(TPU_ADDRESS)))
ImageDataGenerator
train_datagen = ImageDataGenerator(
rescale=1. / 255,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True)
# this is the augmentation configuration we will use for testing:
# only rescaling
test_datagen = ImageDataGenerator(rescale=1. / 255)
train_generator = train_datagen.flow_from_directory(
train_data_dir,
target_size=(img_width, img_height),
batch_size=batch_size,
class_mode='categorical')#binary ,categorical
validation_generator = test_datagen.flow_from_directory(
validation_data_dir,
target_size=(img_width, img_height),
batch_size=batch_size,
class_mode='categorical')
Model Fit
model_fit=tpu_model.fit_generator(
train_generator,
epochs=50,
steps_per_epoch=60,
)
I get this error
Epoch 1/50 15/33 [============>.................] - ETA: 8s - loss:
4.7722 - acc: 0.0083INFO:tensorflow:New input shapes; (re-)compiling: mode=train (# of cores 8), [TensorSpec(shape=(0,), dtype=tf.int32,
name='core_id_60'), TensorSpec(shape=(0, 128, 128, 3),
dtype=tf.float32, name='conv2d_3_input_20'), TensorSpec(shape=(0,
120), dtype=tf.float32, name='activation_13_target_30')]
--------------------------------------------------------------------------- InvalidArgumentError Traceback (most recent call
last)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py
in _create_c_op(graph, node_def, inputs, control_inputs) 1658
try:
-> 1659 c_op = c_api.TF_FinishOperation(op_desc) 1660 except errors.InvalidArgumentError as e:
InvalidArgumentError: slice index 0 of dimension 0 out of bounds. for
'strided_slice_19' (op: 'StridedSlice') with input shapes: [0], [1],
[1], [1] and with computed input tensors: input[1] = <0>, input[2] =
<1>, input[3] = <1>.
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call
last) 17 frames
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py
in _create_c_op(graph, node_def, inputs, control_inputs) 1660
except errors.InvalidArgumentError as e: 1661 # Convert to
ValueError for backwards compatibility.
-> 1662 raise ValueError(str(e)) 1663 1664 return c_op
ValueError: slice index 0 of dimension 0 out of bounds. for
'strided_slice_19' (op: 'StridedSlice') with input shapes: [0], [1],
[1], [1] and with computed input tensors: input[1] = <0>, input[2] =
<1>, input[3] = <1>.