{
	"name": "InvalidArgumentError",
	"message": "Graph execution error:

Detected at node 'mean_squared_error/SquaredDifference' defined at (most recent call last):
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\runpy.py\", line 197, in _run_module_as_main
      return _run_code(code, main_globals, None,
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\runpy.py\", line 87, in _run_code
      exec(code, run_globals)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel_launcher.py\", line 18, in <module>
      app.launch_new_instance()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\traitlets\\config\\application.py\", line 1075, in launch_instance
      app.start()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\kernelapp.py\", line 739, in start
      self.io_loop.start()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\tornado\\platform\\asyncio.py\", line 205, in start
      self.asyncio_loop.run_forever()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\asyncio\\base_events.py\", line 601, in run_forever
      self._run_once()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\asyncio\\base_events.py\", line 1905, in _run_once
      handle._run()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\asyncio\\events.py\", line 80, in _run
      self._context.run(self._callback, *self._args)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 545, in dispatch_queue
      await self.process_one()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 534, in process_one
      await dispatch(*args)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 437, in dispatch_shell
      await result
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 359, in execute_request
      await super().execute_request(stream, ident, parent)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 778, in execute_request
      reply_content = await reply_content
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 446, in do_execute
      res = shell.run_cell(
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\zmqshell.py\", line 549, in run_cell
      return super().run_cell(*args, **kwargs)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3048, in run_cell
      result = self._run_cell(
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3103, in _run_cell
      result = runner(coro)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 129, in _pseudo_sync_runner
      coro.send(None)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3308, in run_cell_async
      has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3490, in run_ast_nodes
      if await self.run_code(code, result, async_=asy):
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3550, in run_code
      exec(code_obj, self.user_global_ns, self.user_ns)
    File \"C:\\Users\\arisa\\AppData\\Local\\Temp\\ipykernel_18504\\2926787601.py\", line 7, in <module>
      model.fit(
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\utils\\traceback_utils.py\", line 65, in error_handler
      return fn(*args, **kwargs)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 1564, in fit
      tmp_logs = self.train_function(iterator)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 1160, in train_function
      return step_function(self, iterator)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 1146, in step_function
      outputs = model.distribute_strategy.run(run_step, args=(data,))
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 1135, in run_step
      outputs = model.train_step(data)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 994, in train_step
      loss = self.compute_loss(x, y, y_pred, sample_weight)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 1052, in compute_loss
      return self.compiled_loss(
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\compile_utils.py\", line 265, in __call__
      loss_value = loss_obj(y_t, y_p, sample_weight=sw)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\losses.py\", line 152, in __call__
      losses = call_fn(y_true, y_pred)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\losses.py\", line 272, in call
      return ag_fn(y_true, y_pred, **self._fn_kwargs)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\losses.py\", line 1486, in mean_squared_error
      return backend.mean(tf.math.squared_difference(y_pred, y_true), axis=-1)
Node: 'mean_squared_error/SquaredDifference'
required broadcastable shapes
\t [[{{node mean_squared_error/SquaredDifference}}]] [Op:__inference_train_function_4333]",
	"stack": "---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
Cell In[7], line 7
      3 train_generator = data_generator_lstm(30)
      5 # Update total_samples, train_samples, and val_samples according to your dataset after transformations
----> 7 model.fit(
      8     train_generator,
      9     steps_per_epoch=50,
     10     epochs=75,
     11     # Add validation_data if you have a validation generator
     12 )

File c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\utils\\traceback_utils.py:70, in filter_traceback.<locals>.error_handler(*args, **kwargs)
     67     filtered_tb = _process_traceback_frames(e.__traceback__)
     68     # To get the full stack trace, call:
     69     # `tf.debugging.disable_traceback_filtering()`
---> 70     raise e.with_traceback(filtered_tb) from None
     71 finally:
     72     del filtered_tb

File c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\tensorflow\\python\\eager\\execute.py:54, in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name)
     52 try:
     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 'mean_squared_error/SquaredDifference' defined at (most recent call last):
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\runpy.py\", line 197, in _run_module_as_main
      return _run_code(code, main_globals, None,
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\runpy.py\", line 87, in _run_code
      exec(code, run_globals)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel_launcher.py\", line 18, in <module>
      app.launch_new_instance()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\traitlets\\config\\application.py\", line 1075, in launch_instance
      app.start()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\kernelapp.py\", line 739, in start
      self.io_loop.start()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\tornado\\platform\\asyncio.py\", line 205, in start
      self.asyncio_loop.run_forever()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\asyncio\\base_events.py\", line 601, in run_forever
      self._run_once()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\asyncio\\base_events.py\", line 1905, in _run_once
      handle._run()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\asyncio\\events.py\", line 80, in _run
      self._context.run(self._callback, *self._args)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 545, in dispatch_queue
      await self.process_one()
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 534, in process_one
      await dispatch(*args)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 437, in dispatch_shell
      await result
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 359, in execute_request
      await super().execute_request(stream, ident, parent)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\kernelbase.py\", line 778, in execute_request
      reply_content = await reply_content
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\ipkernel.py\", line 446, in do_execute
      res = shell.run_cell(
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\ipykernel\\zmqshell.py\", line 549, in run_cell
      return super().run_cell(*args, **kwargs)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3048, in run_cell
      result = self._run_cell(
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3103, in _run_cell
      result = runner(coro)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 129, in _pseudo_sync_runner
      coro.send(None)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3308, in run_cell_async
      has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3490, in run_ast_nodes
      if await self.run_code(code, result, async_=asy):
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3550, in run_code
      exec(code_obj, self.user_global_ns, self.user_ns)
    File \"C:\\Users\\arisa\\AppData\\Local\\Temp\\ipykernel_18504\\2926787601.py\", line 7, in <module>
      model.fit(
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\utils\\traceback_utils.py\", line 65, in error_handler
      return fn(*args, **kwargs)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 1564, in fit
      tmp_logs = self.train_function(iterator)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 1160, in train_function
      return step_function(self, iterator)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 1146, in step_function
      outputs = model.distribute_strategy.run(run_step, args=(data,))
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 1135, in run_step
      outputs = model.train_step(data)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 994, in train_step
      loss = self.compute_loss(x, y, y_pred, sample_weight)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\training.py\", line 1052, in compute_loss
      return self.compiled_loss(
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\engine\\compile_utils.py\", line 265, in __call__
      loss_value = loss_obj(y_t, y_p, sample_weight=sw)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\losses.py\", line 152, in __call__
      losses = call_fn(y_true, y_pred)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\losses.py\", line 272, in call
      return ag_fn(y_true, y_pred, **self._fn_kwargs)
    File \"c:\\Users\\arisa\\.conda\\envs\\tf\\lib\\site-packages\\keras\\losses.py\", line 1486, in mean_squared_error
      return backend.mean(tf.math.squared_difference(y_pred, y_true), axis=-1)
Node: 'mean_squared_error/SquaredDifference'
required broadcastable shapes
\t [[{{node mean_squared_error/SquaredDifference}}]] [Op:__inference_train_function_4333]"
}