TensorFlow Variable Shape assign - tensorflow

Question

I am trying to create a variable and then trying to assign it with the value of my convolution layer.
However it is refusing because it is saying shapes are not equal even though I have passed validate_shape=False while creating the variable.
The convolution shape is [32,20,20,3]. How do I pass this into the variable?
the bottom code:
conv = tf.layers.conv2d_transpose(conv, filters=3, kernel_size=3, strides=(2,2), padding='same',activation=tf.nn.relu) # TO ASSIGN LATER
g=tf.Variable(([32,20,20]),dtype=tf.float32,validate_shape=False)#THE VARIABLE
loss = tf.reduce_mean(tf.square(conv))
opt = tf.train.AdamOptimizer().minimize(loss)
saver = tf.train.Saver()
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for i in range(1000):
_, xx,inp,output,target = sess.run([opt, loss,x,conv,y])#
print(xx)
print("subtraction result:",output[0]-target[0])
g=g.assign(conv)
print(g.eval())
I am getting this error:
InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [3] rhs shape= [32,20,20,3]
[[Node: Assign_7 = Assign[T=DT_FLOAT, use_locking=false, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](Variable_9, conv2d_transpose_98/Relu)]]
Can someone please help fix this?

Answer 1

I think you want:
import numpy as np
import tensorflow as tf
g = tf.Variable(initial_value=np.zeros((32,20,20,3)), expected_shape=(32,20,20,3), dtype=tf.float32)
If you print g you get the correct shape now:
<tf.Variable 'Variable_3:0' shape=(32, 20, 20, 3) dtype=float32_ref>
What you did was this:
g = tf.Variable(initial_value=(32,20,20), dtype=tf.float32, valid_shape=False)
By not stating expected_shape you defaulted to positional arguments, the first argument of tf.Variable is initial_value as per the documentation below:
__init__(
initial_value=None,
trainable=True,
collections=None,
validate_shape=True,
caching_device=None,
name=None,
variable_def=None,
dtype=None,
expected_shape=None,
import_scope=None,
constraint=None
)
That shape of the initial_value you declared would have been a vector of length [3] which is exactly the shape that the assign operation is complaining about.
Moral of the story: it's generally less buggy to declare arguments by name if you can. :)