Input to reshape is a tensor with 268435456 values, but the requested shape requires a multiple of 5033164

Question

I'm trying to implement Sensor3D architecture(https://arxiv.org/pdf/1807.02437.pdf) in order to perform semantic segmentation of left ventricle from CT images.I performed Data Augmentation with ImageDataGenerator and train-test split. At the end I build the model(inspired by U-NET) able to segment the images. I want to send to the model 3 images simultaneously.

I implemented this code(input_shape= (time_steps,IMG_HEIGHT,IMG_WIDTH,IMG_CHANNELS)=(3,512,512,1)).

x =  tf.keras.layers.TimeDistributed(tf.keras.layers.Conv2D( 64, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (input_l)
conv2 = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv2D( 64, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (x)
x=tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPooling2D(pool_size=(2,2)))(conv2)
x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv2D( 128, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (x)
conv5 = tf.keras.layers.TimeDistributed( tf.keras.layers.Conv2D( 128, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (x)
x=layers.TimeDistributed(layers.MaxPooling2D(pool_size=(2,2)))(conv5)
x = layers.TimeDistributed( layers.Conv2D( 256, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (x)
conv8 = layers.TimeDistributed( layers.Conv2D( 256, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (x)
x=layers.TimeDistributed(layers.MaxPooling2D(pool_size=(2,2)))(conv8)
x=layers.Bidirectional(layers.ConvLSTM2D(256,kernel_size=(3,3),padding='same',strides=(1,1),return_sequences=True))(x)
up1 = layers.TimeDistributed( layers.Conv2DTranspose( 512,kernel_size=(3,3),padding='same',strides=(2,2)))(x)
concat1 = layers.concatenate([up1, conv8])
x = layers.TimeDistributed( layers.Conv2D( 256, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (concat1)
x = layers.TimeDistributed( layers.Conv2D( 256, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (x)
up2 = layers.TimeDistributed( layers.Conv2DTranspose( 256,kernel_size=(3,3),padding='same',strides=(2,2)))(x)
concat2 = layers.concatenate([up2, conv5])
x = layers.TimeDistributed( layers.Conv2D( 128, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (concat2)
x = layers.TimeDistributed( layers.Conv2D( 128, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (x)
up3 = layers.TimeDistributed( layers.Conv2DTranspose( 128,kernel_size=(3,3),padding='same',strides=(2,2)))(x)
concat3 = layers.concatenate([up3, conv2])
x = layers.TimeDistributed( layers.Conv2D( 64, kernel_size=(3, 3),padding='same',strides=(1,1) ) ) (concat3)
x=layers.Bidirectional(layers.ConvLSTM2D(32,kernel_size=(3,3),padding='same',strides=(1,1),return_sequences=True))(x)
out = tf.keras.layers.Conv2D(1, (1, 1), activation='sigmoid')(x)

model = tf.keras.Model(inputs=[input_l], outputs=[out])
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
model.summary()
history=model.fit(train_img_gen,
          steps_per_epoch=steps_per_epoch,
          epochs=10,
          verbose=1,
          validation_data=val_img_gen,
          validation_steps=val_steps_per_epoch)````

But this error occurs : 

   

` Detected at node 'model_7/time_distributed_107/Reshape_1' defined at (most recent call last):
    File "/usr/lib/python3.7/runpy.py", line 193, in _run_module_as_main
      "__main__", mod_spec)
    File "/usr/lib/python3.7/runpy.py", line 85, in _run_code
      exec(code, run_globals)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py", line 16, in <module>
      app.launch_new_instance()
    File "/usr/local/lib/python3.7/dist-packages/traitlets/config/application.py", line 846, in launch_instance
      app.start()
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelapp.py", line 499, in start
      self.io_loop.start()
    File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 132, in start
      self.asyncio_loop.run_forever()
    File "/usr/lib/python3.7/asyncio/base_events.py", line 541, in run_forever
      self._run_once()
    File "/usr/lib/python3.7/asyncio/base_events.py", line 1786, in _run_once
      handle._run()
    File "/usr/lib/python3.7/asyncio/events.py", line 88, in _run
      self._context.run(self._callback, *self._args)
    File "/usr/local/lib/python3.7/dist-packages/tornado/platform/asyncio.py", line 122, in _handle_events
      handler_func(fileobj, events)
    File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
      return fn(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 452, in _handle_events
      self._handle_recv()
    File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 481, in _handle_recv
      self._run_callback(callback, msg)
    File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 431, in _run_callback
      callback(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/tornado/stack_context.py", line 300, in null_wrapper
      return fn(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 283, in dispatcher
      return self.dispatch_shell(stream, msg)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 233, in dispatch_shell
      handler(stream, idents, msg)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
      user_expressions, allow_stdin)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/ipkernel.py", line 208, in do_execute
      res = shell.run_cell(code, store_history=store_history, silent=silent)
    File "/usr/local/lib/python3.7/dist-packages/ipykernel/zmqshell.py", line 537, in run_cell
      return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
      interactivity=interactivity, compiler=compiler, result=result)
    File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
      if self.run_code(code, result):
    File "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
      exec(code_obj, self.user_global_ns, self.user_ns)
    File "<ipython-input-34-b527975d6b78>", line 6, in <module>
      validation_steps=val_steps_per_epoch)
    File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
      return fn(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1384, in fit
      tmp_logs = self.train_function(iterator)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1021, in train_function
      return step_function(self, iterator)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1010, in step_function
      outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1000, in run_step
      outputs = model.train_step(data)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 859, in train_step
      y_pred = self(x, training=True)
    File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
      return fn(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1096, in __call__
      outputs = call_fn(inputs, *args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler
      return fn(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 452, in call
      inputs, training=training, mask=mask)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/functional.py", line 589, in _run_internal_graph
      outputs = node.layer(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 64, in error_handler
      return fn(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/base_layer.py", line 1096, in __call__
      outputs = call_fn(inputs, *args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py", line 92, in error_handler
      return fn(*args, **kwargs)
    File "/usr/local/lib/python3.7/dist-packages/keras/layers/wrappers.py", line 275, in call
      y = tf.__internal__.nest.map_structure_up_to(y, tf.reshape, y, output_shape)
Node: 'model_7/time_distributed_107/Reshape_1'
Input to reshape is a tensor with 268435456 values, but the requested shape requires a multiple of 50331648
     [[{{node model_7/time_distribenter code hereuted_107/Reshape_1}}]] [Op:__inference_train_function_82500]`
 How can I solve this issue?