CODEWITHSUNDEEP
pythonconv-neural-network
Ioana
Ioana

Reputation: 67

Neural network error "Incompatible shapes"

The code I founded here: https://github.com/malhotraa/carvana-image-masking-challenge/blob/master/notebooks/model_cnn.ipynb and I try to see the result using my own pictures but it seem is not working.

    def down(filters, input_):
    down_ = Conv2D(filters, (3, 3), padding='same')(input_)
    down_ = BatchNormalization(epsilon=1e-4)(down_)
    down_ = Activation('relu')(down_)
    down_ = Conv2D(filters, (3, 3), padding='same')(down_)
    down_ = BatchNormalization(epsilon=1e-4)(down_)
    down_res = Activation('relu')(down_)
    down_pool = MaxPooling2D((2, 2), strides=(2, 2))(down_)
    return down_pool, down_res

def up(filters, input_, down_):
    up_ = UpSampling2D((2, 2))(input_)
    up_ = concatenate([down_, up_], axis=3)
    up_ = Conv2D(filters, (3, 3), padding='same')(up_)
    up_ = BatchNormalization(epsilon=1e-4)(up_)
    up_ = Activation('relu')(up_)
    up_ = Conv2D(filters, (3, 3), padding='same')(up_)
    up_ = BatchNormalization(epsilon=1e-4)(up_)
    up_ = Activation('relu')(up_)
    up_ = Conv2D(filters, (3, 3), padding='same')(up_)
    up_ = BatchNormalization(epsilon=1e-4)(up_)
    up_ = Activation('relu')(up_)
    return up_
    def cnn_model(input_shape=[64,64,3], num_classes=1):
    inputs = Input(shape=input_shape)
    with tf.device('/gpu:0'):
        #down0b, down0b_res = down(8, inputs)
        down0a, down0a_res = down(32, inputs)
        down0, down0_res = down(64, down0a)
        down1, down1_res = down(128, down0)
        down2, down2_res = down(256, down1)
        down3, down3_res = down(512, down2)
        down4, down4_res = down(1024, down3)

        center = Conv2D(1024, (3, 3), padding='same')(down4)
        center = BatchNormalization(epsilon=1e-4)(center)
        center = Activation('relu')(center)

    with tf.device('/gpu:1'):
        center = Conv2D(1024, (3, 3), padding='same')(center)
        center = BatchNormalization(epsilon=1e-4)(center)
        center = Activation('relu')(center)

        up4 = up(1024, center, down4_res)
        up3 = up(512, up4, down3_res)
        up2 = up(256, up3, down2_res)
        up1 = up(128, up2, down1_res)
        up0 = up(64, up1, down0_res)
        up0a = up(32, up0, down0a_res)
        #up0b = up(8, up0a, down0b_res)

    classify = Conv2D(num_classes, (1, 1), activation='sigmoid', name='final_layer')(up0a)

    model = Model(inputs=inputs, outputs=classify)

    return model

This is an error that I can not understand. I am using python and neural network for a short time and I have problem understanding them.

---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1326     try:
-> 1327       return fn(*args)
   1328     except errors.OpError as e:

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
   1311       return self._call_tf_sessionrun(
-> 1312           options, feed_dict, fetch_list, target_list, run_metadata)
   1313 

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
   1419             self._session, options, feed_dict, fetch_list, target_list,
-> 1420             status, run_metadata)
   1421 

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py in __exit__(self, type_arg, value_arg, traceback_arg)
    515             compat.as_text(c_api.TF_Message(self.status.status)),
--> 516             c_api.TF_GetCode(self.status.status))
    517     # Delete the underlying status object from memory otherwise it stays alive

InvalidArgumentError: Incompatible shapes: [36864] vs. [12288]
     [[Node: training/Adam/gradients/loss_1/final_layer_loss/mul_grad/BroadcastGradientArgs = BroadcastGradientArgs[T=DT_INT32, _class=["loc:@loss_1/final_layer_loss/mul"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](training/Adam/gradients/loss_1/final_layer_loss/mul_grad/Shape, training/Adam/gradients/loss_1/final_layer_loss/mul_grad/Shape_1)]]

During handling of the above exception, another exception occurred:

InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-12-f0dc1bb0c6be> in <module>()
      6         verbose = 1,
      7         validation_data = valid_generator,
----> 8         validation_steps = VALIDATION_STEPS)
      9 
     10 model_json=model.to_json()

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/legacy/interfaces.py in wrapper(*args, **kwargs)
     89                 warnings.warn('Update your `' + object_name +
     90                               '` call to the Keras 2 API: ' + signature, stacklevel=2)
---> 91             return func(*args, **kwargs)
     92         wrapper._original_function = func
     93         return wrapper

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/engine/training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
   2228                     outs = self.train_on_batch(x, y,
   2229                                                sample_weight=sample_weight,
-> 2230                                                class_weight=class_weight)
   2231 
   2232                     if not isinstance(outs, list):

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/engine/training.py in train_on_batch(self, x, y, sample_weight, class_weight)
   1881             ins = x + y + sample_weights
   1882         self._make_train_function()
-> 1883         outputs = self.train_function(ins)
   1884         if len(outputs) == 1:
   1885             return outputs[0]

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py in __call__(self, inputs)
   2480         session = get_session()
   2481         updated = session.run(fetches=fetches, feed_dict=feed_dict,
-> 2482                               **self.session_kwargs)
   2483         return updated[:len(self.outputs)]
   2484 

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    903     try:
    904       result = self._run(None, fetches, feed_dict, options_ptr,
--> 905                          run_metadata_ptr)
    906       if run_metadata:
    907         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
   1138     if final_fetches or final_targets or (handle and feed_dict_tensor):
   1139       results = self._do_run(handle, final_targets, final_fetches,
-> 1140                              feed_dict_tensor, options, run_metadata)
   1141     else:
   1142       results = []

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1319     if handle is None:
   1320       return self._do_call(_run_fn, feeds, fetches, targets, options,
-> 1321                            run_metadata)
   1322     else:
   1323       return self._do_call(_prun_fn, handle, feeds, fetches)

~/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1338         except KeyError:
   1339           pass
-> 1340       raise type(e)(node_def, op, message)
   1341 
   1342   def _extend_graph(self):

InvalidArgumentError: Incompatible shapes: [36864] vs. [12288]
     [[Node: training/Adam/gradients/loss_1/final_layer_loss/mul_grad/BroadcastGradientArgs = BroadcastGradientArgs[T=DT_INT32, _class=["loc:@loss_1/final_layer_loss/mul"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](training/Adam/gradients/loss_1/final_layer_loss/mul_grad/Shape, training/Adam/gradients/loss_1/final_layer_loss/mul_grad/Shape_1)]]

Caused by op 'training/Adam/gradients/loss_1/final_layer_loss/mul_grad/BroadcastGradientArgs', defined at:
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/runpy.py", line 184, in _run_module_as_main
    "__main__", mod_spec)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/ipykernel_launcher.py", line 16, in <module>
    app.launch_new_instance()
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/traitlets/config/application.py", line 658, in launch_instance
    app.start()
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 486, in start
    self.io_loop.start()
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tornado/platform/asyncio.py", line 127, in start
    self.asyncio_loop.run_forever()
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/asyncio/base_events.py", line 345, in run_forever
    self._run_once()
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/asyncio/base_events.py", line 1312, in _run_once
    handle._run()
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/asyncio/events.py", line 125, in _run
    self._callback(*self._args)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tornado/platform/asyncio.py", line 117, in _handle_events
    handler_func(fileobj, events)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tornado/stack_context.py", line 276, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 450, in _handle_events
    self._handle_recv()
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 480, in _handle_recv
    self._run_callback(callback, msg)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 432, in _run_callback
    callback(*args, **kwargs)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tornado/stack_context.py", line 276, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 283, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 233, in dispatch_shell
    handler(stream, idents, msg)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 399, in execute_request
    user_expressions, allow_stdin)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 208, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 537, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2662, in run_cell
    raw_cell, store_history, silent, shell_futures)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2785, in _run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2903, in run_ast_nodes
    if self.run_code(code, result):
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2963, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-12-f0dc1bb0c6be>", line 8, in <module>
    validation_steps = VALIDATION_STEPS)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
    return func(*args, **kwargs)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/engine/training.py", line 2080, in fit_generator
    self._make_train_function()
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/engine/training.py", line 992, in _make_train_function
    loss=self.total_loss)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
    return func(*args, **kwargs)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/optimizers.py", line 445, in get_updates
    grads = self.get_gradients(loss, params)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/optimizers.py", line 78, in get_gradients
    grads = K.gradients(loss, params)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 2519, in gradients
    return tf.gradients(loss, variables, colocate_gradients_with_ops=True)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/ops/gradients_impl.py", line 488, in gradients
    gate_gradients, aggregation_method, stop_gradients)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/ops/gradients_impl.py", line 625, in _GradientsHelper
    lambda: grad_fn(op, *out_grads))
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/ops/gradients_impl.py", line 379, in _MaybeCompile
    return grad_fn()  # Exit early
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/ops/gradients_impl.py", line 625, in <lambda>
    lambda: grad_fn(op, *out_grads))
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/ops/math_grad.py", line 881, in _MulGrad
    rx, ry = gen_array_ops._broadcast_gradient_args(sx, sy)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/ops/gen_array_ops.py", line 671, in _broadcast_gradient_args
    "BroadcastGradientArgs", s0=s0, s1=s1, name=name)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
    op_def=op_def)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3290, in create_op
    op_def=op_def)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1654, in __init__
    self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access

...which was originally created as op 'loss_1/final_layer_loss/mul', defined at:
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/runpy.py", line 184, in _run_module_as_main
    "__main__", mod_spec)
[elided 20 identical lines from previous traceback]
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2785, in _run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2909, in run_ast_nodes
    if self.run_code(code, result):
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2963, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-11-76ea40ddc2d1>", line 14, in <module>
    model.compile(loss=bce_dice_loss, optimizer=Adam(lr=1e-4), metrics=[dice_coef])
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/engine/training.py", line 830, in compile
    sample_weight, mask)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/keras/engine/training.py", line 429, in weighted
    score_array = fn(y_true, y_pred)
  File "<ipython-input-10-7fcc135cc389>", line 12, in bce_dice_loss
    return binary_crossentropy(y_true, y_pred) + dice_coef_loss(y_true, y_pred)
  File "<ipython-input-10-7fcc135cc389>", line 9, in dice_coef_loss
    return 1-dice_coef(y_true, y_pred)
  File "<ipython-input-10-7fcc135cc389>", line 5, in dice_coef
    intersection = K.sum(y_true_f * y_pred_f)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/ops/math_ops.py", line 971, in binary_op_wrapper
    return func(x, y, name=name)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/ops/math_ops.py", line 1198, in _mul_dispatch
    return gen_math_ops.mul(x, y, name=name)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/ops/gen_math_ops.py", line 4689, in mul
    "Mul", x=x, y=y, name=name)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
    op_def=op_def)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3290, in create_op
    op_def=op_def)
  File "/home/ioana/anaconda3/envs/carnd-term1/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1654, in __init__
    self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): Incompatible shapes: [36864] vs. [12288]
     [[Node: training/Adam/gradients/loss_1/final_layer_loss/mul_grad/BroadcastGradientArgs = BroadcastGradientArgs[T=DT_INT32, _class=["loc:@loss_1/final_layer_loss/mul"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](training/Adam/gradients/loss_1/final_layer_loss/mul_grad/Shape, training/Adam/gradients/loss_1/final_layer_loss/mul_grad/Shape_1)]]

My question is how can i resolve this error and make it work and if it has something to do with the packages I use.

Upvotes: 1

Views: 3672

Answers (1)

Ankit Paliwal
Ankit Paliwal

Reputation: 156

This type of error occurs whenever there's a discrepancy in the shape of layers which you are using for calculating loss, as highlighted in the stack-trace [36864] vs. [12288]. You should probably double check the shape of your model output and the shape of expected output(flattened).

A good practice, which I have generally found helpful while working with large networks is try to see the output shape produced by every layer, or do a model.summary(), good for debugging and following through the output of your network.

Upvotes: 1

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