GridsearchCV tuning KerasClassifier with callbacks error: ValueError: Found input variables with inconsistent numbers of samples - callback

Question

Using sklearn.GridSearchCV to fine tune the hyperparameters of model in Keras. Also, I add callbacks into it.
Input Format: (1500, 3, 10, 10)
Output Format: (1500,)
Grid search code:
def Grid_Search_Training(model):
# parameters grid
epochs = [300]
activations = ['relu', 'tanh']
L2_lambda = [0.01, 0.001, 0.0001]
batches = [16, 32, 64, 128]
param_grid = dict(activation=activations, epochs=epochs, batch_size=batches, L2_lambda=L2_lambda)
grid = GridSearchCV(estimator=model, param_grid=param_grid, scoring='accuracy', cv=5)
return grid
def run(grid_search = True):
model = Model()
plot_model(model, to_file='Model_plot.png', show_shapes=True, show_layer_names=True)
# save layer names into a set, to visualize all layers' output in tensorboard
embeddings_all_layer_names = set(layer.name for layer in model.layers if layer.name.startswith('tower_'))
# train and save the model weights
Model_weights_path = 'Model_weights.h5'
checkpointer = ModelCheckpoint(Model_weights_path, monitor='val_loss', verbose=1, save_best_only=True)
reduce_lr = ReduceLROnPlateau(monitor='val_loss', factor=0.2, patience=5, min_lr=0.0000001)
tensorboard_log_dir = 'ModelLogs/{}'.format(time.time())
tensorboard = TensorBoard(log_dir = tensorboard_log_dir, histogram_freq = 1,
write_graph=True, write_images=True, embeddings_freq=1,
embeddings_layer_names=embeddings_all_layer_names, embeddings_metadata=None)
callbacks_list = [checkpointer, reduce_lr, tensorboard]
fit_params = dict(callbacks=callbacks_list)
if grid_search:
t0 = time.time()
print incepModel().summary()
model = KerasClassifier(build_fn = model, verbose=1)
grid = Grid_Search_Training(model)
print 'Start Training the model......'
grid_result = grid.fit(X_train, y_train, **fit_params)
print("Best acc Score: %f using %s" % (grid_result.best_score_, grid_result.best_params_))
t1 = time.time()
t = t1-t0
print 'The GirdSearch on CNN took %.2f mins.' %(round(t/60., 2))
means = grid_result.cv_results_['mean_test_score']
stds = grid_result.cv_results_['std_test_score']
params = grid_result.cv_results_['params']
for mean, stdev, param in zip(means, stds, params):
print("%f (%f) with: %r" % (mean, stdev, param))
else:
history = model.fit(X_train, to_categorical(y_train), epochs=100, batch_size=64, validation_split=0.2, callbacks=callbacks_list)
X_train, X_test, y_train, y_test = read_split(data)
run(grid_search=True)
The error is :
grid_result = grid.fit(X_train, y_train, fit_params)
File "/Users/jd/anaconda2/lib/python2.7/site-packages/sklearn/model_selection/_search.py", line 615, in fit
X, y, groups = indexable(X, y, groups)
File "/Users/jd/anaconda2/lib/python2.7/site-packages/sklearn/utils/validation.py", line 229, in indexable
check_consistent_length(*result)
File "/Users/jd/anaconda2/lib/python2.7/site-packages/sklearn/utils/validation.py", line 204, in check_consistent_length
" samples: %r" % [int(l) for l in lengths])
ValueError: Found input variables with inconsistent numbers of samples: [1500, 1500, 1]
The code works well without callbacks, i.e. No fit_params in grid_result = grid.fit(X_train, y_train, fit_params). There is no error.
What causes such kind of error?