CODEWITHSUNDEEP
tensorflowinitialization
Eleanor
Eleanor

Reputation: 2847

Attempting to use uninitialized value. [Tensorflow]

Here is my code:

def conv_pooling(data, sequence_length, filter_size, embedding_size, num_filters):
    filter_shape = [filter_size, embedding_size, 1, num_filters]
    w = tf.Variable(tf.truncated_normal(filter_shape,stddev = 0.1), 
    name = "w")
    b = tf.Variable(tf.constant(0.1, shape=[num_filters]), name = 
    "b")
    conv = tf.nn.conv2d(
        item,
        w,
        strides = [1,1,1,1],
        padding = "VALID",
        name = "conv"
    )
    h = tf.nn.relu(tf.nn.bias_add(conv, b), name = "relu")
    pooled = tf.nn.max_pool(
        h,
        ksize = [1,sequence_length - filter_size + 1, 1, 1],
        strides = [1,1,1,1],
        padding = "VALID",
        name = "pool"
    )

    return pooled

init_op = tf.global_variables_initializer()
pooled_outputs = []
with tf.Session() as sess:

     sess.run(init_op)

     for i, filter_size in enumerate(filter_sizes):

         pooled = sess.run(conv_pooling(data, sequence_length, filter_size, embedding_size, num_filters), feed_dict = {embedded_chars: item})

         pooled_outputs.append(pooled)

This 'data' is a tf.Variable that use the global tf.placeholder 'embedded_chars', so don't worry about if it is working. The error happens because of w and b cannot be initialized.

I tried sess.run(tf.local_variables_initializer()) also, not work and return the same error. Does anyone know a way that I can initialized w and b here? As you see the size of w change in for loop.

Thank you!

Upvotes: 0

Views: 160

Answers (1)

LKS
LKS

Reputation: 673

See the code below. That's why @mikkola means about creating your graph before initialization.

// create your computation graph
pooled = conv_pooling(data, sequence_length, filter_size, embedding_size, num_filters)

// initialize the variables in the graph
init_op = tf.global_variables_initializer()

pooled_outputs = []

with tf.Session() as sess:

     sess.run(init_op)

     for i, filter_size in enumerate(filter_sizes):

         // run the graph to get your output
         output = sess.run([pooled], feed_dict = {embedded_chars: item})

         pooled_outputs.append(output)

Upvotes: 1

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