Estoy tratando de replicar el modelo VGG16 en keras, el siguiente es mi código:

model = Sequential()
model.add(ZeroPadding2D((1,1),input_shape=(3,224,224)))
model.add(Convolution2D(64, 3, 3, activation='relu'))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(64, 3, 3, activation='relu'))
model.add(MaxPooling2D((2,2), strides=(2,2)))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(128, 3, 3, activation='relu'))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(128, 3, 3, activation='relu'))
model.add(MaxPooling2D((2,2), strides=(2,2))) ###This line gives error
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(256, 3, 3, activation='relu'))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(256, 3, 3, activation='relu'))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(256, 3, 3, activation='relu'))
model.add(MaxPooling2D((2,2), strides=(2,2)))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(512, 3, 3, activation='relu'))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(512, 3, 3, activation='relu'))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(512, 3, 3, activation='relu'))
model.add(MaxPooling2D((2,2), strides=(2,2)))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(512, 3, 3, activation='relu'))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(512, 3, 3, activation='relu'))
model.add(ZeroPadding2D((1,1)))
model.add(Convolution2D(512, 3, 3, activation='relu'))
model.add(MaxPooling2D((2,2), strides=(2,2)))
model.add(Flatten())
model.add(Dense(4096, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(4096, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(1000, activation='softmax'))

La capa maxpooling2d da un error en la línea que se comenta

El error dice:

ValueError: Negative dimension size caused by subtracting 2 from 1 for 'MaxPool_7' (op: 'MaxPool') with input shapes: [?,1,112,128].

¿Cuál podría ser la razón detrás de esto? ¿Cómo resolver esto?

Editar: un registro de errores más detallado:

ValueError Traceback (última llamada) en () 12 model.add (Convolution2D (128, 3, 3, activación = 'relu')) 13 ---> 14 model.add (MaxPooling2D ((2,2), zancadas = (2,2))) 15 16 model.add (ZeroPadding2D ((1,1)))

/usr/local/lib/python2.7/dist-packages/keras/models.pyc in add (self, layer) 306 output_shapes = [self.outputs [0] ._ keras_shape]) 307 más: -> 308 output_tensor = layer (self.outputs [0]) 309 if type (output_tensor) es list: 310 raise Exception ('Todas las capas en un modelo secuencial'

/usr/local/lib/python2.7/dist-packages/keras/engine/topology.pyc enllamada(self, x, mask) 512 si inbound_layers: 513 # esto llamará a layer.build () si es necesario -> 514 self.add_inbound_node (inbound_layers, node_indices, tensor_indices) 515 input_added = True 516

/usr/local/lib/python2.7/dist-packages/keras/engine/topology.pyc en add_inbound_node (self, inbound_layers, node_indices, tensor_indices) 570 # la creación del nodo actualiza automáticamente self.inbound_nodes 571 # así como outbound_nodes en capas entrantes. -> 572 Node.create_node (self, inbound_layers, node_indices, tensor_indices) 573 574 def get_output_shape_for (self, input_shape):

/usr/local/lib/python2.7/dist-packages/keras/engine/topology.pyc en create_node (cls, outbound_layer, inbound_layers, node_indices, tensor_indices) 147 148 if len (input_tensors) == 1: -> 149 output_tensors = to_list (outbound_layer.call (input_tensors [0], mask = input_masks [0])) 150 output_masks = to_list (outbound_layer.compute_mask (input_tensors [0], input_masks [0])) 151 # TODO: intente autoinferir forma si se genera una excepción por get_output_shape_for

/usr/local/lib/python2.7/dist-packages/keras/layers/pooling.pyc in call (self, x, mask) 160 strides = self.strides, 161 border_mode = self.border_mode, -> 162 dim_ordering = self.dim_ordering) 163 salida de retorno 164

/usr/local/lib/python2.7/dist-packages/keras/layers/pooling.pyc en _pooling_function (self, input, pool_size, strides, border_mode, dim_ordering) 210 border_mode, dim_ordering): 211 output = K.pool2d ( entradas, pool_size, strides, -> 212 border_mode, dim_ordering, pool_mode = 'max') 213 salida de retorno 214

/usr/local/lib/python2.7/dist-packages/keras/backend/tensorflow_backend.pyc en pool2d (x, pool_size, strides, border_mode, dim_ordering, pool_mode) 1699 1700 if pool_mode == 'max': -> 1701 x = tf.nn.max_pool (x, pool_size, strides, padding = padding) 1702 elif pool_mode == 'avg': 1703
x = tf.nn.avg_pool (x, pool_size, strides, padding = padding)

/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_ops.pyc en max_pool (valor, ksize, strides, padding, data_format, name) 1391 padding = padding, 1392
formato_datos = formato_datos, -> 1393 nombre = nombre) 1394 1395

/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_nn_ops.pyc en _max_pool (input, ksize, strides, padding, data_format, name)
1593 result = _op_def_lib.apply_op ("MaxPool", input = input, ksize = ksize, 1594 strides = strides, padding = padding, -> 1595 data_format = data_format, name = name) 1596 return result 1597

/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.pyc en apply_op (self, op_type_name, name, ** keywords) 747 op = g.create_op (op_type_name, input, output_types, nombre = ámbito, 748 input_types = input_types, attrs = attr_protos, -> 749 op_def = op_def) 750 salidas = op.outputs 751 return _Restructure (ops.convert_n_to_tensor (salidas),

/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.pyc en create_op (self, op_type, input, dtypes, input_types, name, attrs, op_def, compute_shapes, compute_depes) 2388
original_op = self._default_original_op, op_def = op_def) 2389 if compute_shapes: -> 2390 set_shapes_for_outputs (ret) 2391 self._add_op (ret) 2392
self._record_op_seen_by_control_dependencies (ret)

/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.pyc en set_shapes_for_outputs (op) 1783 raise RuntimeError ("No hay función de forma registrada para la operación estándar:% s" 1784
% op.type) -> 1785 formas = shape_func (op) 1786 si las formas son Ninguna: 1787 raise RuntimeError (

/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/common_shapes.pyc en call_cpp_shape_fn (op, input_tensors_needed, debug_python_shape_fn) 594 status) 595 excepto errores. (err.message) 597 598 # Convertir valores TensorShapeProto en output_shapes.

ValueError: tamaño de dimensión negativa causado por restar 2 de 1 para 'MaxPool_7' (op: 'MaxPool') con formas de entrada: [?, 1,112,128].