Python 因'的1减去3而导致的负尺寸；最大池2d_8/MaxPool'；
我在尝试实现AlexNet以解决GTSRB问题时收到此错误消息：“max_poolig2d_8/MaxPool”的1减去3导致维度大小为负 错误位于标有#3的块中 代码：Python 因'的1减去3而导致的负尺寸；最大池2d_8/MaxPool'；,python,tensorflow,keras,Python,Tensorflow,Keras,我在尝试实现AlexNet以解决GTSRB问题时收到此错误消息：“max_poolig2d_8/MaxPool”的1减去3导致维度大小为负 错误位于标有#3的块中 代码： modelAlex=buildAlex（28,28,1,43） 回溯： --------------------------------------------------------------------------- InvalidArgumentError Traceback
modelAlex=buildAlex（28,28,1,43）---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
1550 try:
-> 1551 c_op = c_api.TF_FinishOperation(op_desc)
1552 except errors.InvalidArgumentError as e:
InvalidArgumentError: Negative dimension size caused by subtracting 3 from 1 for 'max_pooling2d_8/MaxPool' (op: 'MaxPool') with input shapes: [?,1,1,256].
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-36-7205823f509c> in <module>
----> 1 modelAlex = buildAlex(28, 28, 1, 43)
<ipython-input-35-e4a6adb73a0a> in buildAlex(width, height, depth, classes, reg)
36 model.add(Activation("relu"))
37 model.add(BatchNormalization(axis=chanDim))
---> 38 model.add(MaxPooling2D(pool_size=(3, 3), strides=(2, 2))) #3
39 model.add(Dropout(0.25))
40
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
456 self._self_setattr_tracking = False # pylint: disable=protected-access
457 try:
--> 458 result = method(self, *args, **kwargs)
459 finally:
460 self._self_setattr_tracking = previous_value # pylint: disable=protected-access
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py in add(self, layer)
191 # If the model is being built continuously on top of an input layer:
192 # refresh its output.
--> 193 output_tensor = layer(self.outputs[0])
194 if len(nest.flatten(output_tensor)) != 1:
195 raise TypeError('All layers in a Sequential model '
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, inputs, *args, **kwargs)
660 not base_layer_utils.is_in_eager_or_tf_function()):
661 with auto_control_deps.AutomaticControlDependencies() as acd:
--> 662 outputs = call_fn(inputs, *args, **kwargs)
663 # Wrap Tensors in `outputs` in `tf.identity` to avoid
664 # circular dependencies.
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/keras/layers/pooling.py in call(self, inputs)
246 strides=strides,
247 padding=self.padding.upper(),
--> 248 data_format=conv_utils.convert_data_format(self.data_format, 4))
249 return outputs
250
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/ops/nn_ops.py in max_pool(value, ksize, strides, padding, data_format, name, input)
3750 padding=padding,
3751 data_format=data_format,
-> 3752 name=name)
3753
3754
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/ops/gen_nn_ops.py in max_pool(input, ksize, strides, padding, data_format, name)
5670 _, _, _op = _op_def_lib._apply_op_helper(
5671 "MaxPool", input=input, ksize=ksize, strides=strides, padding=padding,
-> 5672 data_format=data_format, name=name)
5673 _result = _op.outputs[:]
5674 _inputs_flat = _op.inputs
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py in _apply_op_helper(self, op_type_name, name, **keywords)
786 op = g.create_op(op_type_name, inputs, dtypes=None, name=scope,
787 input_types=input_types, attrs=attr_protos,
--> 788 op_def=op_def)
789 return output_structure, op_def.is_stateful, op
790
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py in create_op(***failed resolving arguments***)
463 return super(FuncGraph, self).create_op(
464 op_type, inputs, dtypes, input_types, name, attrs, op_def,
--> 465 compute_device=compute_device)
466
467 def capture(self, tensor, name=None):
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs)
505 'in a future version' if date is None else ('after %s' % date),
506 instructions)
--> 507 return func(*args, **kwargs)
508
509 doc = _add_deprecated_arg_notice_to_docstring(
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in create_op(***failed resolving arguments***)
3294 input_types=input_types,
3295 original_op=self._default_original_op,
-> 3296 op_def=op_def)
3297 self._create_op_helper(ret, compute_device=compute_device)
3298 return ret
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in __init__(self, node_def, g, inputs, output_types, control_inputs, input_types, original_op, op_def)
1712 op_def, inputs, node_def.attr)
1713 self._c_op = _create_c_op(self._graph, node_def, grouped_inputs,
-> 1714 control_input_ops)
1715
1716 # Initialize self._outputs.
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
1552 except errors.InvalidArgumentError as e:
1553 # Convert to ValueError for backwards compatibility.
-> 1554 raise ValueError(str(e))
1555
1556 return c_op
ValueError: Negative dimension size caused by subtracting 3 from 1 for 'max_pooling2d_8/MaxPool' (op: 'MaxPool') with input shapes: [?,1,1,256].
---------------------------------------------------------------------------
InvalidArgumentError回溯（最后一次最近调用）
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in\u create\u c\u op（图形、节点定义、输入、控制输入）
1550尝试：
->1551 c_op=c_api.TF_FinishOperation（op_desc）
1552错误除外。InvalidArgumentError为e:
InvalidArgumentError:输入形状为[？，1,1256]的“max_Poolg2D_8/MaxPool”（op:“MaxPool”）从1中减去3导致负维度大小。
在处理上述异常期间，发生了另一个异常：
ValueError回溯（最近一次调用上次）
在里面
---->1 modelAlex=buildAlex（28,28,1,43）
在buildAlex中（宽度、高度、深度、等级、注册）
36型号。添加（激活（“relu”））
37型号。添加（批量标准化（轴=chanDim））
--->38 model.add（MaxPoolig2D（池大小=（3,3），步幅=（2,2）））#3
39型号。添加（辍学率（0.25））
40
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/training/tracking/base.py in_method_wrapper（self，*args，**kwargs）
456 self._self_setattr_tracking=False#pylint:disable=protected access
457试试：
-->458结果=方法（自身、*args、**kwargs）
459最后：
460 self._self_setattr_tracking=上一个值#pylint:disable=受保护访问
添加中的~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py（self，layer）
191#如果模型持续构建在输入层之上：
192#刷新其输出。
-->193输出张量=层（自输出[0]）
194如果len（嵌套展平（输出张量））！=1:
195 raise TypeError（'序列模型中的所有层'
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in uu调用（self，input，*args，**kwargs）
660非基本层实用程序。是否在函数（）中：
661将auto_control_deps.AutomaticControlDependencies（）作为acd：
-->662输出=呼叫（输入，*args，**kwargs）
663#在'tf.identity'中的'outputs'中包裹张量以避免
664#循环依赖。
调用中的~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/keras/layers/pooling.py（self，输入）
246步幅=步幅，
247 padding=self.padding.upper（），
-->248数据格式=conv_utils.convert_数据格式（self.data_格式，4））
249个返回输出
250
max_pool中的~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/ops/nn_ops.py（值、大小、跨距、填充、数据格式、名称、输入）
3750填充=填充，
3751数据格式=数据格式，
->3752名称=名称）
3753
3754
max_pool中的~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/ops/gen_nn_ops.py（输入、大小、跨步、填充、数据格式、名称）
5670 u，u，_op=_op_def_lib._apply_op_helper(
5671“MaxPool”，输入=输入，ksize=ksize，步长=步长，填充=填充，
->5672数据格式=数据格式，名称=名称）
5673 _结果=_运算输出[：]
5674 _输入_平坦=_操作输入
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py in_apply_op_helper（self，op_type_name，name，**关键字）
786 op=g.create_op（op_type_name，inputs，dtypes=None，name=scope，
787输入类型=输入类型，属性=属性协议，
-->788 op_def=op_def）
789返回输出结构，op_def.is_stateful，op
790
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py在create_op（***解析参数失败***）
463返回超级（函数图，自）。创建(
464操作类型、输入、数据类型、输入类型、名称、属性、操作定义、，
-->465计算设备=计算设备）
466
467 def捕获（自、张量、名称=无）：
新函数中的~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/util/deprecation.py（*args，**kwargs）
505“在未来版本中”如果日期不是其他日期（“在%s“%date”之后），
506（说明）
-->507返回函数（*args，**kwargs）
508
509 doc=\u添加\u不推荐的\u参数\u通知\u到\u docstring(
在create_op（***解析参数失败***）中~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py
3294输入类型=输入类型，
3295原始值=self.\u默认值\u原始值，
->3296 op_def=op_def）
3297 self.\u create\u op\u helper（ret，compute\u device=compute\u device）
3298返回ret
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in_uuuinit_uuu（self，node_def，g，input，output_type，control_input，input_type，original_op，op_def）
1712操作定义，输入，节点定义属性）
1713 self._c_op=_create_c_op（self._图形、节点定义、分组输入、，
->1714控制（输入操作）
1715
1716#初始化self._输出。
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in\u create\u c\u op（图形、节点定义、输入、控制输入）
1552除了错误。在
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
1550 try:
-> 1551 c_op = c_api.TF_FinishOperation(op_desc)
1552 except errors.InvalidArgumentError as e:
InvalidArgumentError: Negative dimension size caused by subtracting 3 from 1 for 'max_pooling2d_8/MaxPool' (op: 'MaxPool') with input shapes: [?,1,1,256].
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-36-7205823f509c> in <module>
----> 1 modelAlex = buildAlex(28, 28, 1, 43)
<ipython-input-35-e4a6adb73a0a> in buildAlex(width, height, depth, classes, reg)
36 model.add(Activation("relu"))
37 model.add(BatchNormalization(axis=chanDim))
---> 38 model.add(MaxPooling2D(pool_size=(3, 3), strides=(2, 2))) #3
39 model.add(Dropout(0.25))
40
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
456 self._self_setattr_tracking = False # pylint: disable=protected-access
457 try:
--> 458 result = method(self, *args, **kwargs)
459 finally:
460 self._self_setattr_tracking = previous_value # pylint: disable=protected-access
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py in add(self, layer)
191 # If the model is being built continuously on top of an input layer:
192 # refresh its output.
--> 193 output_tensor = layer(self.outputs[0])
194 if len(nest.flatten(output_tensor)) != 1:
195 raise TypeError('All layers in a Sequential model '
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py in __call__(self, inputs, *args, **kwargs)
660 not base_layer_utils.is_in_eager_or_tf_function()):
661 with auto_control_deps.AutomaticControlDependencies() as acd:
--> 662 outputs = call_fn(inputs, *args, **kwargs)
663 # Wrap Tensors in `outputs` in `tf.identity` to avoid
664 # circular dependencies.
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/keras/layers/pooling.py in call(self, inputs)
246 strides=strides,
247 padding=self.padding.upper(),
--> 248 data_format=conv_utils.convert_data_format(self.data_format, 4))
249 return outputs
250
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/ops/nn_ops.py in max_pool(value, ksize, strides, padding, data_format, name, input)
3750 padding=padding,
3751 data_format=data_format,
-> 3752 name=name)
3753
3754
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/ops/gen_nn_ops.py in max_pool(input, ksize, strides, padding, data_format, name)
5670 _, _, _op = _op_def_lib._apply_op_helper(
5671 "MaxPool", input=input, ksize=ksize, strides=strides, padding=padding,
-> 5672 data_format=data_format, name=name)
5673 _result = _op.outputs[:]
5674 _inputs_flat = _op.inputs
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/op_def_library.py in _apply_op_helper(self, op_type_name, name, **keywords)
786 op = g.create_op(op_type_name, inputs, dtypes=None, name=scope,
787 input_types=input_types, attrs=attr_protos,
--> 788 op_def=op_def)
789 return output_structure, op_def.is_stateful, op
790
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py in create_op(***failed resolving arguments***)
463 return super(FuncGraph, self).create_op(
464 op_type, inputs, dtypes, input_types, name, attrs, op_def,
--> 465 compute_device=compute_device)
466
467 def capture(self, tensor, name=None):
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs)
505 'in a future version' if date is None else ('after %s' % date),
506 instructions)
--> 507 return func(*args, **kwargs)
508
509 doc = _add_deprecated_arg_notice_to_docstring(
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in create_op(***failed resolving arguments***)
3294 input_types=input_types,
3295 original_op=self._default_original_op,
-> 3296 op_def=op_def)
3297 self._create_op_helper(ret, compute_device=compute_device)
3298 return ret
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in __init__(self, node_def, g, inputs, output_types, control_inputs, input_types, original_op, op_def)
1712 op_def, inputs, node_def.attr)
1713 self._c_op = _create_c_op(self._graph, node_def, grouped_inputs,
-> 1714 control_input_ops)
1715
1716 # Initialize self._outputs.
~/Documents/Environments/my_env/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in _create_c_op(graph, node_def, inputs, control_inputs)
1552 except errors.InvalidArgumentError as e:
1553 # Convert to ValueError for backwards compatibility.
-> 1554 raise ValueError(str(e))
1555
1556 return c_op
ValueError: Negative dimension size caused by subtracting 3 from 1 for 'max_pooling2d_8/MaxPool' (op: 'MaxPool') with input shapes: [?,1,1,256].
(28, 28)
|
V
model.add(Conv2D(96, (11, 11), strides=(4, 4), ...)
|
V
(7, 7)
model.add(MaxPooling2D(pool_size=(3, 3), strides=(2, 2))) #1
|
V
(3, 3)
model.add(Conv2D(256, (5, 5), padding="same",
kernel_regularizer=l2(reg)))
model.add(MaxPooling2D(pool_size=(3, 3), strides=(2, 2))) #2
|
V
(1, 1)
model.ad(Dropout(0.25))
# Block #3: CONV => RELU => CONV => RELU => CONV => RELU
# Block #3: CONV => RELU => CONV => RELU => CONV => RELU
model.add(Conv2D(384, (3, 3), padding="same",
kernel_regularizer=l2(reg)))
model.add(Conv2D(384, (3, 3), padding="same",
kernel_regularizer=l2(reg)))
model.add(Conv2D(256, (3, 3), padding="same",
kernel_regularizer=l2(reg)))
(Error) --->model.add(MaxPooling2D(pool_size=(3, 3), strides=(2, 2))) #3
model.add(Dropout(0.25))