Error while training

I want to train data on videos and I am using lrcn architecture

width=352
height=576
depth=None

def lrcn():
    # CNN-LSTM network, also known as LRCN
    model = Sequential()

    model.add(TimeDistributed(Conv2D(128, (7, 7), strides=(2, 2), activation='relu', padding='valid'), input_shape=(depth, height, width,  3)))
    model.add(TimeDistributed(Conv2D(128, (3, 3), kernel_initializer="he_normal", activation='relu')))
    model.add(TimeDistributed(MaxPooling2D((2, 2), strides=(2, 2))))

    model.add(TimeDistributed(Conv2D(256, (3, 3), padding='VALID', activation='relu')))
    model.add(TimeDistributed(Conv2D(256, (3, 3), padding='VALID', activation='relu')))
    model.add(TimeDistributed(MaxPooling2D((2, 2), strides=(2, 2))))

    model.add(TimeDistributed(Conv2D(512, (3, 3), padding='VALID', activation='relu')))
    model.add(TimeDistributed(Conv2D(512, (3, 3), padding='VALID', activation='relu')))
    model.add(TimeDistributed(MaxPooling2D((2, 2), strides=(2, 2))))

    model.add(TimeDistributed(Conv2D(1024, (3, 3), padding='VALID', activation='relu')))
    model.add(TimeDistributed(Conv2D(1024, (3, 3), padding='VALID', activation='relu')))
    model.add(TimeDistributed(MaxPooling2D((2, 2), strides=(2, 2))))

    model.add(TimeDistributed(Conv2D(2048, (3, 3), padding='VALID', activation='relu')))
    model.add(TimeDistributed(Conv2D(2048, (3, 3), padding='VALID', activation='relu')))
    model.add(TimeDistributed(MaxPooling2D((2, 2), strides=(2, 2))))

    model.add(TimeDistributed(Flatten(name='flatten')))

    model.add(Dropout(0.5))
    model.add(LSTM(1024, return_sequences=False, dropout=0.5))
    model.add(Dense(512, activation='relu'))

    model.add(Dense(50, activation='softmax'))
    
    model.summary()
    
    return model

then I’m getting this error when I start training

Epoch 1/12
---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-20-80e473117162> in <module>()
----> 1 model.fit(train_dataset,epochs=12,steps_per_epoch=15)

1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
     53     ctx.ensure_initialized()
     54     tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
---> 55                                         inputs, attrs, num_outputs)
     56   except core._NotOkStatusException as e:
     57     if name is not None:

InvalidArgumentError: Graph execution error:

Detected at node 'sequential_1/time_distributed_19/Reshape' 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 577, in _handle_events
      self._handle_recv()
    File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 606, in _handle_recv
      self._run_callback(callback, msg)
    File "/usr/local/lib/python3.7/dist-packages/zmq/eventloop/zmqstream.py", line 556, 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 2828, 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-20-80e473117162>", line 1, in <module>
      model.fit(train_dataset,epochs=12,steps_per_epoch=15)
    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/sequential.py", line 374, in call
      return super(Sequential, self).call(inputs, training=training, mask=mask)
    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 261, in call
      inner_input_shape)
Node: 'sequential_1/time_distributed_19/Reshape'
Input to reshape is a tensor with 7827456 values, but the requested shape requires a multiple of 608256
	 [[{{node sequential_1/time_distributed_19/Reshape}}]] [Op:__inference_train_function_73834]

my data is in tfrecords form
and this is my code

Which TimeDistributed layer is failing? You can find this quickly if you add a separate, unique name to each TimeDistributed layer via the optional name= parameter.

Expecting more reply.

So I got a similar error but with Keras imagedatagenerator. I noticed the shape of my input image in my CNN was 224* 224 but when creating the train data generator, I used a target size of 300*300. Could you try using the same shape you used in your CNN, in your train data generator it might help.

Welp incase someone comes looking for this months later

@Muhammed_Magdy Did you get an answer to error?I also need help with this