francesco-mannella / echo-state-networks Goto Github PK

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AttributeError                            Traceback (most recent call last)
~\Anaconda3\lib\site-packages\numpy\core\fromnumeric.py in _wrapfunc(obj, method, *args, **kwds)
     50     try:
---> 51         return getattr(obj, method)(*args, **kwds)
     52 

~\Anaconda3\lib\site-packages\pandas\core\generic.py in __getattr__(self, name)
   4375                 return self[name]
-> 4376             return object.__getattribute__(self, name)
   4377 

AttributeError: 'Series' object has no attribute 'reshape'

During handling of the above exception, another exception occurred:

Exception                                 Traceback (most recent call last)
<ipython-input-83-c189dc55e5ae> in <module>
----> 1 esn.fit(x_train, y_train)

~\Desktop\Machine Learning\pyESN.py in fit(self, inputs, outputs, inspect)
    163             inputs = np.reshape(inputs, (len(inputs), -1))
    164         if outputs.ndim < 2:
--> 165             outputs = np.reshape(outputs, (len(outputs), -1))
    166         # transform input and teacher signal:
    167         inputs_scaled = self._scale_inputs(inputs)

~\Anaconda3\lib\site-packages\numpy\core\fromnumeric.py in reshape(a, newshape, order)
    277            [5, 6]])
    278     """
--> 279     return _wrapfunc(a, 'reshape', newshape, order=order)
    280 
    281 

~\Anaconda3\lib\site-packages\numpy\core\fromnumeric.py in _wrapfunc(obj, method, *args, **kwds)
     59     # a downstream library like 'pandas'.
     60     except (AttributeError, TypeError):
---> 61         return _wrapit(obj, method, *args, **kwds)
     62 
     63 

~\Anaconda3\lib\site-packages\numpy\core\fromnumeric.py in _wrapit(obj, method, *args, **kwds)
     43         if not isinstance(result, mu.ndarray):
     44             result = asarray(result)
---> 45         result = wrap(result)
     46     return result
     47 

~\Anaconda3\lib\site-packages\pandas\core\series.py in __array_wrap__(self, result, context)
    646         """
    647         return self._constructor(result, index=self.index,
--> 648                                  copy=False).__finalize__(self)
    649 
    650     def __array_prepare__(self, result, context=None):

~\Anaconda3\lib\site-packages\pandas\core\series.py in __init__(self, data, index, dtype, name, copy, fastpath)
    273             else:
    274                 data = _sanitize_array(data, index, dtype, copy,
--> 275                                        raise_cast_failure=True)
    276 
    277                 data = SingleBlockManager(data, index, fastpath=True)

~\Anaconda3\lib\site-packages\pandas\core\series.py in _sanitize_array(data, index, dtype, copy, raise_cast_failure)
   4163     elif subarr.ndim > 1:
   4164         if isinstance(data, np.ndarray):
-> 4165             raise Exception('Data must be 1-dimensional')
   4166         else:
   4167             subarr = com._asarray_tuplesafe(data, dtype=dtype)

Exception: Data must be 1-dimensional

---------------------------------------------------------------------------
OperatorNotAllowedInGraphError            Traceback (most recent call last)
<ipython-input-51-ec63cda2780d> in <module>
     19 # put all together in a keras sequential model
     20 model = keras.models.Sequential()
---> 21 model.add(recurrent_layer)
     22 model.add(output)

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
    515     self._self_setattr_tracking = False  # pylint: disable=protected-access
    516     try:
--> 517       result = method(self, *args, **kwargs)
    518     finally:
    519       self._self_setattr_tracking = previous_value  # pylint: disable=protected-access

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/keras/engine/sequential.py in add(self, layer)
    206           # and create the node connecting the current layer
    207           # to the input layer we just created.
--> 208           layer(x)
    209           set_inputs = True
    210 

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent.py in __call__(self, inputs, initial_state, constants, **kwargs)
    658 
    659     if initial_state is None and constants is None:
--> 660       return super(RNN, self).__call__(inputs, **kwargs)
    661 
    662     # If any of `initial_state` or `constants` are specified and are Keras

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, *args, **kwargs)
    949     # >> model = tf.keras.Model(inputs, outputs)
    950     if _in_functional_construction_mode(self, inputs, args, kwargs, input_list):
--> 951       return self._functional_construction_call(inputs, args, kwargs,
    952                                                 input_list)
    953 

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py in _functional_construction_call(self, inputs, args, kwargs, input_list)
   1088           layer=self, inputs=inputs, build_graph=True, training=training_value):
   1089         # Check input assumptions set after layer building, e.g. input shape.
-> 1090         outputs = self._keras_tensor_symbolic_call(
   1091             inputs, input_masks, args, kwargs)
   1092 

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py in _keras_tensor_symbolic_call(self, inputs, input_masks, args, kwargs)
    820       return nest.map_structure(keras_tensor.KerasTensor, output_signature)
    821     else:
--> 822       return self._infer_output_signature(inputs, args, kwargs, input_masks)
    823 
    824   def _infer_output_signature(self, inputs, args, kwargs, input_masks):

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py in _infer_output_signature(self, inputs, args, kwargs, input_masks)
    861           # TODO(kaftan): do we maybe_build here, or have we already done it?
    862           self._maybe_build(inputs)
--> 863           outputs = call_fn(inputs, *args, **kwargs)
    864 
    865         self._handle_activity_regularization(inputs, outputs)

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent.py in call(self, inputs, mask, training, initial_state, constants)
    792           new_states = [new_states]
    793         return output, new_states
--> 794     last_output, outputs, states = K.rnn(
    795         step,
    796         inputs,

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py in wrapper(*args, **kwargs)
    199     """Call target, and fall back on dispatchers if there is a TypeError."""
    200     try:
--> 201       return target(*args, **kwargs)
    202     except (TypeError, ValueError):
    203       # Note: convert_to_eager_tensor currently raises a ValueError, not a

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/keras/backend.py in rnn(step_function, inputs, initial_states, go_backwards, mask, constants, unroll, input_length, time_major, zero_output_for_mask)
   4346     # output_time_zero is used to determine the cell output shape and its dtype.
   4347     # the value is discarded.
-> 4348     output_time_zero, _ = step_function(
   4349         input_time_zero, tuple(initial_states) + tuple(constants))
   4350     output_ta = tuple(

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/keras/layers/recurrent.py in step(inputs, states)
    788       def step(inputs, states):
    789         states = states[0] if len(states) == 1 and is_tf_rnn_cell else states
--> 790         output, new_states = cell_call_fn(inputs, states, **kwargs)
    791         if not nest.is_nested(new_states):
    792           new_states = [new_states]

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, *args, **kwargs)
   1010         with autocast_variable.enable_auto_cast_variables(
   1011             self._compute_dtype_object):
-> 1012           outputs = call_fn(inputs, *args, **kwargs)
   1013 
   1014         if self._activity_regularizer:

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py in wrapper(*args, **kwargs)
    665       try:
    666         with conversion_ctx:
--> 667           return converted_call(f, args, kwargs, options=options)
    668       except Exception as e:  # pylint:disable=broad-except
    669         if hasattr(e, 'ag_error_metadata'):

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py in converted_call(f, args, kwargs, caller_fn_scope, options)
    348   if conversion.is_in_allowlist_cache(f, options):
    349     logging.log(2, 'Allowlisted %s: from cache', f)
--> 350     return _call_unconverted(f, args, kwargs, options, False)
    351 
    352   if ag_ctx.control_status_ctx().status == ag_ctx.Status.DISABLED:

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py in _call_unconverted(f, args, kwargs, options, update_cache)
    476 
    477   if kwargs is not None:
--> 478     return f(*args, **kwargs)
    479   return f(*args)
    480 

/mnt/d/projects/recirculation/esn/ESN.py in call(self, inputs, states)
    195 
    196         rkernel = self.setAlpha(self.recurrent_kernel_init)
--> 197         if self.alpha != self.alpha_store:
    198             self.clip_variables()
    199             self.echo_ratio.assign(self.echoStateRatio(rkernel))

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/framework/ops.py in __bool__(self)
    883       `TypeError`.
    884     """
--> 885     self._disallow_bool_casting()
    886 
    887   def __nonzero__(self):

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/framework/ops.py in _disallow_bool_casting(self)
    490     else:
    491       # Default: V1-style Graph execution.
--> 492       self._disallow_in_graph_mode("using a `tf.Tensor` as a Python `bool`")
    493 
    494   def _disallow_iteration(self):

~/software/miniconda3/envs/recirc/lib/python3.8/site-packages/tensorflow/python/framework/ops.py in _disallow_in_graph_mode(self, task)
    477 
    478   def _disallow_in_graph_mode(self, task):
--> 479     raise errors.OperatorNotAllowedInGraphError(
    480         "{} is not allowed in Graph execution. Use Eager execution or decorate"
    481         " this function with @tf.function.".format(task))

OperatorNotAllowedInGraphError: using a `tf.Tensor` as a Python `bool` is not allowed in Graph execution. Use Eager execution or decorate this function with @tf.function.