python-3.x – 在最小化AdamOptimizer时,在op输入和计算输入渐变之间获得不兼容的形状

概述运行tensorflow代码时出现以下错误： Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/tensor_shape.py", line 579, in merge_with new_dims.append(dim.m 运行tensorflow代码时出现以下错误：

Traceback (most recent call last):  file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/tensor_shape.py",line 579,in merge_with    new_dims.append(dim.merge_with(other[i]))  file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/tensor_shape.py",line 138,in merge_with    self.assert_is_compatible_with(other)  file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/tensor_shape.py",line 111,in assert_is_compatible_with    other))ValueError: Dimensions 5 and 4 are not compatibleDuring handling of the above exception,another exception occurred:Traceback (most recent call last):  file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gradIEnts_impl.py",line 602,in gradIEnts    in_grad.set_shape(t_in.get_shape())  file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py",line 407,in set_shape    self._shape = self._shape.merge_with(shape)  file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/tensor_shape.py",line 582,in merge_with    raise ValueError("Shapes %s and %s are not compatible" % (self,other))ValueError: Shapes (?,5,15,1) and (?,4,1) are not compatibleDuring handling of the above exception,another exception occurred:Traceback (most recent call last):  file "experiment.py",line 65,in <module>    batches_per_lot=batches_per_lot,sigma=dp_sigma,dp=dp)  file "/home/srikrishna/Research/RGAN_kinect/RGAN_forecasting/model.py",line 247,in GAN_solvers    G_solver = tf.train.AdamOptimizer().minimize(G_loss_mean_over_batch,var_List=generator_vars)  file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/optimizer.py",line 343,in minimize    grad_loss=grad_loss)  file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/optimizer.py",line 414,in compute_gradIEnts    colocate_gradIEnts_with_ops=colocate_gradIEnts_with_ops)  file "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gradIEnts_impl.py",line 609,in gradIEnts    % (op.name,i,t_in.shape,in_grad.shape))ValueError: Incompatible shapes between op input and calculated input gradIEnt.  Forward operation: generator/conv2d_transpose_1.  input index: 2. Original input shape: (?,1).  Calculated input gradIEnt shape: (?,1)

我试图使用一些卷积和conv2d_transpose.在最小化 *** 作期间,错误来自conv2d_transpose层.不确定它为什么会发生.以下是我构建网络的方法：

deconv1 = tf.nn.Conv2d_transpose(output_3d,tf.get_variable('DW1',shape=[4,1,1],initializer=tf.random_normal_initializer()),strIDes=[1,2,3,output_shape=[-1,1])        de_relu1 = tf.nn.relu(deconv1,'de_relu1')deconv2 = tf.nn.Conv2d_transpose(de_relu1,tf.get_variable('DW2',shape=[5,20,75,1])        de_relu2 = tf.nn.relu(deconv2,'de_relu2')

我正在使用tensorflow 1.4.1

解决方法 好吧,事实证明我是以错误的方式解释错误.问题是我给deconv2的输出形状是不正确的.由于conv2d_transpose在张量流中的实现方式,因此在前向传播步骤中完成了conv2d_transpose的形状验证.

将步幅= [1,1]改为strIDes = [1,1]使其工作正常.

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