error.txt

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\eager\context.py in __enter__(self)
   1508     try:
-> 1509       new_device_name, new_device_spec = _device_parsing_cache[cache_key]
   1510     except TypeError:

KeyError: ('', '/job:localhost/replica:0/task:0/device:GPU:0')

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\framework\op_def_library.py in _apply_op_helper(self, op_type_name, name, **keywords)
    526                 as_ref=input_arg.is_ref,
--> 527                 preferred_dtype=default_dtype)
    528           except TypeError as err:

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\framework\ops.py in internal_convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, ctx, accept_composite_tensors)
   1295     if ret is None:
-> 1296       ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
   1297 

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\ops\resource_variable_ops.py in _dense_var_to_tensor(var, dtype, name, as_ref)
   1788 def _dense_var_to_tensor(var, dtype=None, name=None, as_ref=False):
-> 1789   return var._dense_var_to_tensor(dtype=dtype, name=name, as_ref=as_ref)  # pylint: disable=protected-access
   1790 

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\ops\resource_variable_ops.py in _dense_var_to_tensor(***failed resolving arguments***)
   1213     else:
-> 1214       return self.value()
   1215 

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\ops\resource_variable_ops.py in value(self)
    522     with ops.colocate_with(None, ignore_existing=True):
--> 523       with ops.device(self._handle.device):
    524         return self._read_variable_op()

~\.conda\envs\gpu2\lib\contextlib.py in __enter__(self)
    111         try:
--> 112             return next(self.gen)
    113         except StopIteration:

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\framework\ops.py in combined(device_name_or_function)
   5137         if not callable(device_name_or_function):
-> 5138           with context.device(device_name_or_function):
   5139             yield

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\eager\context.py in __enter__(self)
   1525           new_device_spec = pydev.DeviceSpec.from_string(
-> 1526               ctx._context_devices[0])  # pylint: disable=protected-access
   1527         new_device_spec = new_device_spec.make_merged_spec(device_spec)

TypeError: 'NoneType' object is not subscriptable

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
<ipython-input-11-1a87c6240309> in <module>
      1 if __name__ == '__main__':
----> 2     load_data()
      3 

<ipython-input-10-8f0b4bf7265c> in load_data()
      1 def load_data():
----> 2     data_loader = Dataloader(r'Fight-Detection/images',['Violence','NonViolence'],40,(224,224),3,r'Fight-Detection\images\saving_things')
      3     x_val,y_val = data_loader.get_all_sequence_in_memory()

<ipython-input-2-56a78c44df72> in __init__(self, datapath, classes, max_frames, img_shape, channels, saving_dir)
      7         self.width = img_shape[1]
      8         self.channels = channels
----> 9         self.model = ResNet152(include_top = False,input_shape=(224,224,3),weights = 'imagenet')
     10 
     11         for layer in self.model.layers:

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\keras\applications\__init__.py in wrapper(*args, **kwargs)
     47     kwargs['models'] = models
     48     kwargs['utils'] = utils
---> 49     return base_fun(*args, **kwargs)
     50   return wrapper
     51 

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\keras\applications\resnet.py in ResNet152(*args, **kwargs)
     45 @keras_modules_injection
     46 def ResNet152(*args, **kwargs):
---> 47   return resnet.ResNet152(*args, **kwargs)
     48 
     49 

~\.conda\envs\gpu2\lib\site-packages\keras_applications\resnet_common.py in ResNet152(include_top, weights, input_tensor, input_shape, pooling, classes, **kwargs)
    473                   input_tensor, input_shape,
    474                   pooling, classes,
--> 475                   **kwargs)
    476 
    477 

~\.conda\envs\gpu2\lib\site-packages\keras_applications\resnet_common.py in ResNet(stack_fn, preact, use_bias, model_name, include_top, weights, input_tensor, input_shape, pooling, classes, **kwargs)
    361 
    362     x = layers.ZeroPadding2D(padding=((3, 3), (3, 3)), name='conv1_pad')(img_input)
--> 363     x = layers.Conv2D(64, 7, strides=2, use_bias=use_bias, name='conv1_conv')(x)
    364 
    365     if preact is False:

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\keras\engine\base_layer.py in __call__(self, inputs, *args, **kwargs)
    840                     not base_layer_utils.is_in_eager_or_tf_function()):
    841                   with auto_control_deps.AutomaticControlDependencies() as acd:
--> 842                     outputs = call_fn(cast_inputs, *args, **kwargs)
    843                     # Wrap Tensors in `outputs` in `tf.identity` to avoid
    844                     # circular dependencies.

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\keras\layers\convolutional.py in call(self, inputs)
    195 
    196   def call(self, inputs):
--> 197     outputs = self._convolution_op(inputs, self.kernel)
    198 
    199     if self.use_bias:

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\ops\nn_ops.py in __call__(self, inp, filter)
   1132           call_from_convolution=False)
   1133     else:
-> 1134       return self.conv_op(inp, filter)
   1135     # copybara:strip_end
   1136     # copybara:insert return self.conv_op(inp, filter)

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\ops\nn_ops.py in __call__(self, inp, filter)
    637 
    638   def __call__(self, inp, filter):  # pylint: disable=redefined-builtin
--> 639     return self.call(inp, filter)
    640 
    641 

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\ops\nn_ops.py in __call__(self, inp, filter)
    236         padding=self.padding,
    237         data_format=self.data_format,
--> 238         name=self.name)
    239 
    240 

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\ops\nn_ops.py in conv2d(input, filter, strides, padding, use_cudnn_on_gpu, data_format, dilations, name, filters)
   2008                            data_format=data_format,
   2009                            dilations=dilations,
-> 2010                            name=name)
   2011 
   2012 

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\ops\gen_nn_ops.py in conv2d(input, filter, strides, padding, use_cudnn_on_gpu, explicit_paddings, data_format, dilations, name)
   1069                   padding=padding, use_cudnn_on_gpu=use_cudnn_on_gpu,
   1070                   explicit_paddings=explicit_paddings,
-> 1071                   data_format=data_format, dilations=dilations, name=name)
   1072   _result = _op.outputs[:]
   1073   _inputs_flat = _op.inputs

~\.conda\envs\gpu2\lib\site-packages\tensorflow_core\python\framework\op_def_library.py in _apply_op_helper(self, op_type_name, name, **keywords)
    534                   "type '%s' instead. Error: %s" %
    535                   (dtypes.as_dtype(dtype).name, input_arg.name, op_type_name,
--> 536                    repr(values), type(values).__name__, err))
    537           except ValueError:
    538             # What type does convert_to_tensor think it has?

TypeError: Expected float32 passed to parameter 'filter' of op 'Conv2D', got <tf.Variable 'conv1_conv_2/kernel:0' shape=(7, 7, 3, 64) dtype=float32> of type 'ResourceVariable' instead. Error: 'NoneType' object is not subscriptable