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Running cell 6 in notebooks/demo.ipynb gives the following error-
Using TensorFlow backend. --------------------------------------------------------------------------- InvalidArgumentError Traceback (most recent call last) ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs) 1625 try: -> 1626 c_op = c_api.TF_FinishOperation(op_desc) 1627 except errors.InvalidArgumentError as e: InvalidArgumentError: Shape must be rank 1 but is rank 0 for 'input_batchnorm/cond/Reshape_4' (op: 'Reshape') with input shapes: [1,256,1,1], []. During handling of the above exception, another exception occurred: ValueError Traceback (most recent call last) <ipython-input-6-9b6eecc00968> in <module> 1 if not me_player: ----> 2 me_player = get_player(default_config) 3 action = me_player.action(env, False) 4 print(f"bestmove {action}") <ipython-input-3-a13dfe07b64a> in get_player(config) 3 from chess_zero.lib.model_helper import load_best_model_weight 4 model = ChessModel(config) ----> 5 if not load_best_model_weight(model): 6 raise RuntimeError("Best model not found!") 7 return ChessPlayer(config, model.get_pipes(config.play.search_threads)) ~/dev/chess-alpha-zero/src/chess_zero/lib/model_helper.py in load_best_model_weight(model) 13 :return: 14 """ ---> 15 return model.load(model.config.resource.model_best_config_path, model.config.resource.model_best_weight_path) 16 17 ~/dev/chess-alpha-zero/src/chess_zero/agent/model_chess.py in load(self, config_path, weight_path) 143 logger.debug(f"loading model from {config_path}") 144 with open(config_path, "rt") as f: --> 145 self.model = Model.from_config(json.load(f)) 146 self.model.load_weights(weight_path) 147 self.model._make_predict_function() ~/anaconda3/lib/python3.6/site-packages/keras/engine/network.py in from_config(cls, config, custom_objects) 1030 if layer in unprocessed_nodes: 1031 for node_data in unprocessed_nodes.pop(layer): -> 1032 process_node(layer, node_data) 1033 1034 name = config.get('name') ~/anaconda3/lib/python3.6/site-packages/keras/engine/network.py in process_node(layer, node_data) 989 # and building the layer if needed. 990 if input_tensors: --> 991 layer(unpack_singleton(input_tensors), **kwargs) 992 993 def process_layer(layer_data): ~/anaconda3/lib/python3.6/site-packages/keras/engine/base_layer.py in __call__(self, inputs, **kwargs) 455 # Actually call the layer, 456 # collecting output(s), mask(s), and shape(s). --> 457 output = self.call(inputs, **kwargs) 458 output_mask = self.compute_mask(inputs, previous_mask) 459 ~/anaconda3/lib/python3.6/site-packages/keras/layers/normalization.py in call(self, inputs, training) 204 return K.in_train_phase(normed_training, 205 normalize_inference, --> 206 training=training) 207 208 def get_config(self): ~/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py in in_train_phase(x, alt, training) 3121 3122 # else: assume learning phase is a placeholder tensor. -> 3123 x = switch(training, x, alt) 3124 if uses_learning_phase: 3125 x._uses_learning_phase = True ~/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py in switch(condition, then_expression, else_expression) 3056 x = tf.cond(condition, 3057 then_expression_fn, -> 3058 else_expression_fn) 3059 else: 3060 # tf.where needs its condition tensor ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs) 486 'in a future version' if date is None else ('after %s' % date), 487 instructions) --> 488 return func(*args, **kwargs) 489 return tf_decorator.make_decorator(func, new_func, 'deprecated', 490 _add_deprecated_arg_notice_to_docstring( ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py in cond(pred, true_fn, false_fn, strict, name, fn1, fn2) 2085 try: 2086 context_f.Enter() -> 2087 orig_res_f, res_f = context_f.BuildCondBranch(false_fn) 2088 if orig_res_f is None: 2089 raise ValueError("false_fn must have a return value.") ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py in BuildCondBranch(self, fn) 1918 """Add the subgraph defined by fn() to the graph.""" 1919 pre_summaries = ops.get_collection(ops.GraphKeys._SUMMARY_COLLECTION) # pylint: disable=protected-access -> 1920 original_result = fn() 1921 post_summaries = ops.get_collection(ops.GraphKeys._SUMMARY_COLLECTION) # pylint: disable=protected-access 1922 if len(post_summaries) > len(pre_summaries): ~/anaconda3/lib/python3.6/site-packages/keras/layers/normalization.py in normalize_inference() 165 broadcast_gamma, 166 axis=self.axis, --> 167 epsilon=self.epsilon) 168 else: 169 return K.batch_normalization( ~/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py in batch_normalization(x, mean, var, beta, gamma, axis, epsilon) 1906 # so it may have extra axes with 1, it is not needed and should be removed 1907 if ndim(mean) > 1: -> 1908 mean = tf.reshape(mean, (-1)) 1909 if ndim(var) > 1: 1910 var = tf.reshape(var, (-1)) ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py in reshape(tensor, shape, name) 6294 if _ctx is None or not _ctx._eager_context.is_eager: 6295 _, _, _op = _op_def_lib._apply_op_helper( -> 6296 "Reshape", tensor=tensor, shape=shape, name=name) 6297 _result = _op.outputs[:] 6298 _inputs_flat = _op.inputs ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py in _apply_op_helper(self, op_type_name, name, **keywords) 785 op = g.create_op(op_type_name, inputs, output_types, name=scope, 786 input_types=input_types, attrs=attr_protos, --> 787 op_def=op_def) 788 return output_structure, op_def.is_stateful, op 789 ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs) 486 'in a future version' if date is None else ('after %s' % date), 487 instructions) --> 488 return func(*args, **kwargs) 489 return tf_decorator.make_decorator(func, new_func, 'deprecated', 490 _add_deprecated_arg_notice_to_docstring( ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in create_op(***failed resolving arguments***) 3270 input_types=input_types, 3271 original_op=self._default_original_op, -> 3272 op_def=op_def) 3273 self._create_op_helper(ret, compute_device=compute_device) 3274 return ret ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in __init__(self, node_def, g, inputs, output_types, control_inputs, input_types, original_op, op_def) 1788 op_def, inputs, node_def.attr) 1789 self._c_op = _create_c_op(self._graph, node_def, grouped_inputs, -> 1790 control_input_ops) 1791 1792 # Initialize self._outputs. ~/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs) 1627 except errors.InvalidArgumentError as e: 1628 # Convert to ValueError for backwards compatibility. -> 1629 raise ValueError(str(e)) 1630 1631 return c_op ValueError: Shape must be rank 1 but is rank 0 for 'input_batchnorm/cond/Reshape_4' (op: 'Reshape') with input shapes: [1,256,1,1], [].
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Running cell 6 in notebooks/demo.ipynb gives the following error-
The text was updated successfully, but these errors were encountered: